Chamath

Available sources confirm that in the audio of the Nov 22, 2025 All‑In episode, Chamath (while talking with Alan Keating about the Polk hand) says they’ll "get Nick to play picture in picture this hand." This line appears in third‑party transcripts of the episode’s audio, but those transcripts only represent what’s said, not what’s shown on screen. (cockatoo.com)

The produced episode’s video is hosted on YouTube (watch URL ending in 4tgV87SM-r0), as referenced by multiple episode listings and summaries, but those pages likewise only describe the topics and segments, not any specific editing choices like picture‑in‑picture overlays. (digitalhabitats.global)

Due to current technical limits I cannot inspect the actual video stream or any frame captures, and a web search does not reveal any reliable viewer reports or notes indicating whether the poker hand was in fact shown via picture‑in‑picture in the released video. (digitalhabitats.global)

Because the episode is already published (so it’s not a timing issue) but there is no accessible, verifiable information about the video’s on‑screen layout, whether the prediction came true cannot be determined from the available evidence. Therefore the outcome is ambiguous rather than clearly right, wrong, or too early to tell.

Chamath’s prediction is that investors shorting Palantir around mid‑November 2025 will, on net, lose money as Palantir’s share price rises over time.

Key facts:

• The episode is dated 14 November 2025.
• As of 28 November 2025, Palantir (PLTR) is trading around $168–169 per share .

We do not have a clearly defined evaluation horizon (e.g., 6 months, 1 year, full short thesis cycle). Only ~2 weeks have elapsed between the prediction date and the latest available price. Short positions can become profitable or unprofitable over much longer timeframes, and the claim is about eventual losses for shorts, not about a very short window.

Even if shorts are currently losing or making money, that does not yet tell us the ultimate outcome of those positions. Because the time window since the prediction is very short and the prediction is about performance "from late 2025 onward" without a specific cutoff date, there is not enough elapsed time to reasonably say whether shorts ultimately lost money.

Therefore, the correct evaluation as of 30 November 2025 is:

• Result: inconclusive (too early to tell whether shorts will, on net, lose money over the full subsequent period).

As of today (November 30, 2025), we are only about one month into the predicted 2–3 month “risk‑off” window and still well before February 2026, when Chamath predicted markets would be “firmly in risk on mode.” That means the full timeline of the forecast (through at least February 2026) has not yet played out, so its ultimate accuracy cannot be judged.

Available data for November 2025 show a mixed picture: some indicators point to improved risk appetite among U.S. equity investors, while others show emerging caution and modest outflows from global equity funds, suggesting neither a clearly entrenched, multi‑month risk‑off phase nor confirmation of the later risk‑on rebound. (spglobal.com)

Because the key test of the prediction is the state of market sentiment by February 2026—which is still in the future—the forecast must be considered too early to call.

As of November 30, 2025, December 2025 has not yet occurred, so OpenAI’s actual December revenue figures are not available. OpenAI is a private company and does not publish real-time monthly revenue data; no credible filings or reports provide actual December 2025 revenue yet.

Public reporting only gives projections that OpenAI’s annualized revenue could reach around $20 billion by the end of 2025, not confirmation that it has already achieved a December 2025 revenue of $1.666 billion or more. For example, Reuters reports that OpenAI anticipates its annualized revenue could reach $20 billion by the end of 2025, and similar expectations are referenced in other financial coverage, but these are forecasts, not realized results. (reuters.com)

The Shortform summary of the specific All-In episode confirms that Chamath indeed claimed OpenAI would end 2025 with a $20 billion forward run rate, matching the normalized prediction you provided. (shortform.com) However, without actual December 2025 revenue data, it is too early to say whether this prediction is right or wrong.

Evidence from multiple price sources shows that Chamath’s conditional prediction played out:

• Around the time of the podcast (early November 2025), Bitcoin was hovering just above $100,000; for example, r/Bitcoin’s daily stats list the November 5, 2025 price at about $102,326, implying the $100k level was an active support/psychological area. (reddit.com)
• In the very near term after early November, Bitcoin did break below $100,000 on several occasions. Forbes and Motley Fool/Nasdaq report that on November 4, 2025, BTC dropped roughly 6% in a day and traded around $99,780–$99,076, explicitly noting that it had fallen back under $100,000 for the first time in months.(forbes.com) Other coverage describes additional sub‑$100k prints on November 4–5 driven by liquidations and Fed‑rate concerns.(finance.yahoo.com)
• After this break, the down‑move continued: by November 13–14, Bitcoin had fallen to intraday lows near $96,682–$97,451, roughly 3–4% below the $100,000 mark, with articles framing this as its lowest level in over six months.(forbes.com) The selloff did not immediately exhaust there.
• The decline eventually deepened much further, to the low $80,000s. Reporting on November 21, 2025, notes BTC briefly touching about $80,600–$82,600 before closing the day around $84,500, nearly a 20% drawdown from the $100k level.(nypost.com)
• By late November, coverage repeatedly describes Bitcoin as stabilizing or consolidating in the high‑$80k to low‑$90k range (around $86k–$92k) after that drop, with language about a consolidation phase and price “stabilizing near $88,000.”(m.economictimes.com) That matches the idea that, after the break and further downside, the market found a new equilibrium and began to rebound.

Interpreting the normalized prediction — “after breaking below $100,000, Bitcoin will fall another roughly 5–10% before stabilizing or reversing” — the key factual components are:

1. A decisive break of the $100k psychological barrier in the near term.
2. Additional material downside beyond that level before a stabilization/reversal phase.

Both clearly occurred: BTC fell through $100k multiple times soon after early November 2025, then went well beyond Chamath’s 5–10% downside window (ultimately ~15–20% below $100k at the trough) before later stabilizing in the high‑$80k/low‑$90k band and beginning to recover. While the magnitude of the eventual decline exceeded his 5–10% estimate, the direction and structure of the move — break of $100k followed by further downside and then stabilization — were essentially correct. Hence the prediction is best scored as right rather than wrong or ambiguous.

As of November 30, 2025, there has been no California ballot measure approved by voters establishing a billionaire wealth/wealth-tax of the kind described, no subsequent court invalidation of such a voter‑approved tax, and therefore no follow‑on legislative tax package using that voter approval as justification.

Key points:

• California has had proposals and discussions about wealth or high-earner taxes (e.g., various ideas from legislators and activists), but no enacted, voter-approved billionaire wealth tax that was then struck down in court is documented in the news or in official state records by this date.
• Because the contingent sequence in Chamath’s prediction (1) voter approval, (2) judicial overturning, then (3) legislative action, has not even begun, we cannot yet say whether the legislature will later respond in the way he predicts.

Since the triggering events have not occurred and the relevant election cycles (e.g., November 2026) are still in the future, the correctness of the prediction cannot yet be evaluated, so the status is “inconclusive (too early)”.

As of November 30, 2025, California has not yet implemented any billionaire wealth tax, so Chamath’s conditional, longer‑term prediction cannot be meaningfully judged.

• The main current effort is the 2026 Billionaire Tax Act, a proposed statewide ballot initiative to impose a one‑time 5% tax on net worth above roughly $1–1.1 billion, targeting around 200 billionaires. It has only been filed and is in the signature‑gathering phase for the November 2026 ballot; it is not law and has not taken effect. (seiu-uhw.org)
• An earlier legislative attempt, AB 259 (2023–2024), would have created an ongoing wealth tax with a structure that did push the threshold down over time (initially taxing net worth above $1 billion, then extending to wealth above $50 million after 2026). However, AB 259 failed in committee on February 1, 2024 and never became law. (calmatters.digitaldemocracy.org)

Chamath’s normalized prediction was: if California’s billionaire wealth‑tax framework is implemented and sustained, the threshold will eventually be lowered below $1 billion. Since no such framework has been enacted or sustained yet, we can’t evaluate whether the threshold would later be pushed down in practice. The necessary precondition for the prediction to be tested has not occurred, so the outcome remains unknown.

The prediction was explicitly about severe long‑term business deterioration and DraftKings/FanDuel being effectively 'toast', driven by the rise of platforms like Polymarket.

As of late November 2025 (about five weeks after the October 24, 2025 podcast), both DraftKings and Flutter (FanDuel’s parent) remain large, actively traded companies: DraftKings is around $33 per share and Flutter around $209 per share, implying substantial market value and far from a collapse. Their stocks have sold off and faced downgrades in 2025, with analysts citing margin pressure, higher taxes, and emerging competition from prediction markets, but this is framed as earnings headwinds and reduced price targets, not business failure. (investors.com) Industry coverage still describes DraftKings and FanDuel as the two dominant U.S. sportsbook operators with roughly 70% market share, even as prediction markets like Kalshi and Polymarket gain traction. (ainvest.com)

Polymarket and other prediction platforms have clearly spooked investors—e.g., DKNG and FLUT dropped sharply after news of a $2 billion ICE investment in Polymarket, and reports explicitly link some of the share-price pressure to prediction‑market competition. (sccgmanagement.com) However, the incumbents are also actively adapting by entering prediction markets themselves (e.g., DraftKings’ Railbird acquisition and planned ‘DraftKings Predictions’, FanDuel’s planned ‘FanDuel Predicts’ app with CME), which cuts against the idea that their competitive position is already largely eroding and irrecoverable. (insidebitcoins.com)

Given the very short time elapsed and the fact that both firms are still leading players with significant revenue, market share, and strategic options, it is too early to say that they have suffered the kind of long‑term, existential deterioration implied by the prediction. The available evidence supports increased risk and pressure, not that they are definitively 'toast', so the outcome is best classified as inconclusive at this point.

As of November 30, 2025, it’s too early to judge this prediction.

Chamath’s timeframe was "within the next several years" from October 24, 2025, so only about a month has elapsed—well short of the horizon implied by the statement.

Current market structure only shows partial steps toward what he describes:

• Multi-asset trading platforms like QuantConnect already let users trade across several traditional asset classes (equities, futures, forex, options, cryptocurrencies) from a single environment, but they do not natively integrate regulated event‑betting/prediction markets into the same retail account with unified margin as described. (en.wikipedia.org)
• Regulated prediction markets such as Kalshi focus on event contracts and don’t function as unified brokers for stocks, options, and crypto within one shared-margin account. (en.wikipedia.org)
• Crypto‑native prediction platforms like Polymarket similarly center on event markets and are not fully integrated, mainstream multi‑asset brokerage apps that combine equities, options, and prediction markets under one KYC/AML umbrella. (en.wikipedia.org)
• New infrastructure efforts like The Clearing Co aim to let brokerages bolt prediction markets onto existing offerings (stocks, crypto, etc.), but they are still in licensing/early-launch stages and have not yet produced the sort of dominant, unified end‑user app Chamath envisions. (wsj.com)

So, while no clear, dominant platform yet matches his full vision, the specified multi‑year window has barely begun. The correct status today is therefore inconclusive (too early to tell) rather than right or wrong.

As of 30 November 2025, available market‑share data shows that AWS, Microsoft Azure, and Google Cloud Platform have not yet converged to anything close to a 33/33/33 split in public cloud infrastructure, but Chamath’s claim was explicitly about where they will “eventually” end up in a mature, steady‑state market. That time horizon has clearly not arrived, so the prediction cannot yet be judged true or false.

Recent analyst estimates for global cloud infrastructure (IaaS+PaaS) continue to show AWS in the lead, Azure gaining, and GCP a distant third: for example, 2024–2025 reports from firms such as Synergy Research and Canalys put AWS at roughly the low‑30s percent share, Azure in the mid‑20s, and Google Cloud around low‑ to mid‑teens, with the remainder split among other providers (Alibaba Cloud, Oracle, IBM, etc.). These numbers confirm that:

• The market is still meaningfully not three‑way equal; GCP is far from AWS/Azure’s scale, and a non‑trivial “other” category still exists.
• The industry itself is still evolving rapidly, including major AI‑driven and specialized cloud services, which makes it hard to claim we’ve reached the “mature, non‑AI public cloud infrastructure market” he was talking about.

Because the prediction is about the eventual end state of a market that is still in flux decades before any plausible maturity, the correct assessment today is that it’s too early to tell whether the market will converge to the ~33/33/33 split Chamath forecast. Hence the result is inconclusive (too early).

Public information shows that at Tesla’s November 6, 2025 annual shareholder meeting, shareholders approved Elon Musk’s new “trillion‑dollar” compensation package with roughly 75% of votes cast in favor, according to preliminary results reported by multiple outlets.(kpbs.org)

Before the vote, however, there was significant, visible opposition that made outright rejection at least a live possibility:

• Major proxy advisory firms ISS and Glass Lewis both formally recommended that investors vote against the package, calling it excessively large and dilutive.(businessinsider.com)
• Norway’s sovereign wealth fund (one of Tesla’s largest shareholders) publicly announced it would vote against the deal, and other large funds and unions organized campaigns opposing it.(theguardian.com)
• Tesla’s own board chair, Robyn Denholm, warned in a pre‑meeting letter and media appearances that the company risked losing Musk if the plan was not approved, underscoring that the board itself viewed rejection as a real risk, not a remote theoretical possibility.(reuters.com)

Chamath’s statement was probabilistic and qualitative: that there was a risk / “meaningful chance” the package could be voted down, not that it would be voted down. A single observed outcome (approval) does not let us retrospectively measure the true ex‑ante probability to check whether that “meaningful chance” assessment was numerically accurate. At the same time, the documented opposition and warnings show there clearly was some genuine risk, but the eventual 75% approval margin could be read as evidence that the actual probability of failure may have been relatively low.

Because the claim is about the size of an ex‑ante probability and not about a definitive outcome, and because the realized vote result alone cannot confirm or falsify the exact probability he implied, the prediction cannot be cleanly scored as right or wrong. The fairest evaluation is ambiguous: enough time has passed and we know the outcome, but we still cannot determine from available evidence whether his “meaningful chance of rejection” assessment was quantitatively correct.

As of now (November 30, 2025), Tesla’s humanoid robot Optimus is still in relatively early development and prototyping:

• Tesla has shown several Optimus prototypes and small-batch units, but there is no credible reporting that anything close to 1,000,000 units have been produced or deployed.
• There is also no record of Optimus (or any other Elon Musk–associated humanoid robot line) being shipped to or operating on Mars; current and near-term Mars missions use traditional rover/lander platforms, not humanoid robots.

Because the condition in Chamath’s prediction refers specifically to where the first million robots are deployed (Mars vs. Earth), and that milestone has not occurred yet, there is no way to assess the truth of the prediction at this time. It could still be right or wrong in the future, but currently it’s too early to tell, so the status is inconclusive.

Chamath’s prediction on Oct 17, 2025 was that local political and community opposition that blocks or forces withdrawal of large AI/data-center projects would continue and evolve into a broader trend “in the coming years,” rather than remain isolated incidents.

What has happened so far (before and after the prediction):

• Before the podcast (trend already emerging):

  • An NPR/10a Labs analysis found that 16 data‑center projects nationwide were delayed or rejected between May of the previous year and March 2025 due to community resistance, framing it as mounting nationwide opposition to AI/data centers, not just one‑off cases. (wboi.org)
  • Google withdrew a 468‑acre data center project in Indianapolis after intense local pushback—hundreds of residents packed hearings and celebrated when Google pulled its rezoning request. (axios.com)
  • In Tucson, the City Council unanimously rejected the massive Amazon‑linked Project Blue data center after weeks of protests and organizing by groups like No Desert Data Center, explicitly citing water, energy, and transparency concerns. (azluminaria.org)

• After the podcast (Oct 17–Nov 30, 2025):

  • Microsoft canceled a 244‑acre data center (Project Nova) in Caledonia, Wisconsin following pushback from residents and local officials, stating it would seek a site better aligned with community needs. (tomshardware.com)
  • A proposed $17 billion “Project Sail” data center in Coweta County, Georgia has triggered large‑scale opposition, with a 3,600‑member citizen group (“Stop Project Sail”), public meetings, and widespread concern over water use, noise, and construction impacts. (ft.com)
  • In Springdale Borough, Pennsylvania, residents and environmental groups are opposing a 565,000‑square‑foot AI data center at the site of the former Cheswick Generating Station, citing pollution, noise, and high electricity and water use; the borough council’s final decision is still pending. (axios.com)

These examples—spanning the Midwest, Southwest, Southeast, and Northeast—show that new cases of community backlash and even project cancellations have indeed occurred since the prediction, and they fit the pattern Chamath described.

Why the verdict is still “inconclusive (too early)” rather than “right”:

• The prediction explicitly concerns a multi‑year trajectory (“the beginning of a trend” that will continue “in the coming years”). As of today (Nov 30, 2025), only about six weeks have passed since the podcast.
• While post‑prediction events in Wisconsin, Georgia, and Pennsylvania are consistent with his claim and reinforce that this is more than a few isolated incidents, we cannot yet know whether this level of opposition will persist or intensify over “the coming years.”

So: early evidence strongly aligns with Chamath’s thesis that local opposition to AI/data centers is spreading and affecting projects across multiple states, but because his forecast was explicitly about a long‑term trend over years, not just the next few months, there hasn’t been enough time to say definitively that the prediction has come true. Hence the result is inconclusive (too early) rather than clearly right or wrong.

The prediction explicitly uses a 10 to 20 year horizon from the 2025 discussion ("in the ten or 15 or 20 year time frame"), which maps roughly to 2035–2045. As of November 30, 2025, we are only ~0 years into that window, so:

• It is too early to know whether nuclear, natural gas, and solar will become so abundant by 2035–2045 that they structurally reduce long‑term oil demand and weaken oil’s persistent bid as an asset.
• Current data on the global energy mix and oil demand/prices in the mid‑2020s cannot definitively confirm or falsify a claim about the structural situation a decade or more in the future.

Because the forecast’s evaluation period has not arrived yet, its correctness cannot be determined at this time.

The prediction specifies a five‑year horizon starting from the October 2025 conversation, i.e., roughly until October 2030. As of the current date (November 30, 2025), only about two months have elapsed, so there is not yet enough elapsed time to assess whether average retail electricity prices will have doubled over that full five‑year period. Therefore, the prediction cannot currently be judged right or wrong.

Chamath’s claim is a conditional, long‑term prediction: if the new private owners of EA (1) streamline operating expenses, (2) successfully adopt next‑gen AI tools, and (3) break some dependency on Xbox/PlayStation distribution, then EA could become a “multi‑hundred‑billion‑dollar” asset, far above the ~$55B take‑private valuation.

As of November 30, 2025:

• EA has only recently agreed to a $55B leveraged buyout led by Saudi Arabia’s Public Investment Fund, Silver Lake, and Affinity Partners; the deal is described as the largest take‑private/LBO ever. (ft.com)
• The transaction is not yet closed; reports state it is expected to complete in the first half of 2026 / early fiscal 2027, pending shareholder and regulatory approvals. (barrons.com)
• Because the company is only in the process of going private, there is no observable market‑based equity valuation under new ownership, and “the subsequent years” Chamath refers to have not occurred.

Given that (a) the key operational and strategic changes he conditions the prediction on cannot reasonably be evaluated yet, and (b) the multi‑year horizon for reaching “hundreds of billions” in value has not elapsed, there is no way to determine whether this forecast is right or wrong at this time.

Therefore the status of the prediction is inconclusive (too early to tell).

The prediction is explicitly about what will happen "over the next several years" (multi‑year horizon) to risk‑adjusted excess returns in the broad private equity asset class. The podcast was released on October 3, 2025 and today is November 30, 2025, so not even two months have elapsed.

Private equity performance is only observable with significant lag (funds are valued quarterly or annually, and risk‑adjusted excess returns versus public benchmarks can only be assessed reliably over multi‑year periods). Given both the short time that has passed and the inherently long evaluation window for this kind of claim, there is nowhere near enough data yet to determine whether broad PE excess returns have in fact trended toward zero.

Because the stated timeframe (“next several years”) has not come close to expiring, the accuracy of this prediction cannot yet be judged.

There isn’t enough time yet to definitively judge this multi‑year prediction, although early data partly supports the described trends.

1. Capital concentration in a few top PE firms

• Industry data for 2020–2024 show that the six largest private‑equity firms raised about 60% of total PE funds, indicating strong concentration of new capital into a relatively small group of large managers.(visualcapitalist.com)
• Megafunds (>$5B) accounted for more than half of all PE capital raised in 2024, with large vehicles such as EQT X (~$23.7B) and Silver Lake Partners VII (~$20.5B) closing successfully even as overall fundraising slowed.(businessday.ng)
• At the same time, total global PE fundraising has declined in recent years, hitting multi‑year lows and reflecting tighter capital availability for the broader universe of PE managers.(businessday.ng)
  Taken together, this is directionally consistent with Chamath’s claim that money would move away from the broad PE universe and become more concentrated in a handful of top firms.

2. Shift into private credit

• Private credit assets under management have grown rapidly to around $1.7 trillion globally—more than triple their 2015 level—and private credit has become a major source of deal funding and corporate refinancing. Large asset managers and sovereign wealth funds are actively scaling private‑credit platforms (e.g., BlackRock’s proposed acquisition of HPS, TPG’s acquisition of Angelo Gordon, Abu Dhabi and Korea sovereign funds seeding or expanding private‑credit strategies).(pwc.com)
• News on Blue Owl and other managers highlights both the sector’s growth and emerging stresses (illiquidity concerns, fund‑structure backlash, some borrower defaults), but this is far from a clear consensus that a fully fledged “bubble” has formed and burst.(reuters.com)

3. Why the prediction is still inconclusive

• Chamath framed this as a process happening “over the coming years.” As of November 30, 2025, we are only about two months past the October 3, 2025 podcast date, so the full multi‑year trajectory he described has not yet played out.
• The direction of the trends (capital concentration in top PE firms and strong capital flows into private credit) matches current evidence, but the core evaluable claim—that private credit becomes “the next big bubble” (i.e., a speculative excess that later unwinds)—cannot yet be confirmed or falsified. The market has grown fast and drawn concern, but there has not been a decisive boom‑and‑bust event that would clearly validate or invalidate the “big bubble” characterization.

Because the structural shift he describes is multi‑year and the bubble aspect has not yet clearly materialized or burst, the fairest assessment as of late 2025 is inconclusive (too early) rather than definitively right or wrong.

Based on current information, there isn’t enough evidence yet to say whether Chamath’s prediction has come true.

• In the Oct 3, 2025 episode, he explicitly frames this as a future “Raptor 3” SPAC structure: a sponsor would pre‑wire $1–3B of flexible common equity capital so that the de‑SPAC is a “totally pre‑baked IPO” with no redemption risk and all money rolling into common stock. (podscripts.co)
• Subsequent coverage in October 2025 (e.g., ABMedia / 8V summaries of his remarks) describes Raptor 2 as the current SPAC 2.0 structure and says Raptor 3 is still being prepared, with Chamath planning to raise $1–3B in a pre‑structured pool so companies can list at a fair price. These articles present Raptor 3 as an upcoming design, not something that has already been launched or adopted. (abmedia.io)
• The available write‑ups on “SPAC 2.0 (Raptor 2/3)” discuss Raptor 3 conceptually as the next evolution of SPACs that would integrate capital sources and pre‑configure the deal, again framing it as a proposal rather than a live market structure. (note.com)
• Broader news and filings as of November 30, 2025 do not show any completed SPACs (by Chamath or the wider market) that clearly match his described Raptor 3 pattern—i.e., a standardised, widely used structure where sponsors universally pre‑arrange multi‑billion‑dollar common equity pools eliminating redemption risk. The only references we find to “Raptor 3” are explanatory or forward‑looking, not reports of executed deals. (podscripts.co)
• Only about two months have passed between the prediction (Oct 3, 2025) and the current date (Nov 30, 2025). Launching a new SPAC vehicle, raising $1–3B, completing a de‑SPAC under a novel structure, and having it recognized as the “next iteration” of the market generally takes longer than this.

Given that Raptor 3 is still in the planning / proposal stage and there has not yet been time for the SPAC market to adopt or reject this structure, the correct status of the prediction today is “inconclusive (too early)”, not clearly right or wrong.

The prediction’s horizon is 1–2 years from the early‑October 2025 discussion, i.e. roughly between October 2026 and October 2027 for consumer video‑generation apps like a Sora‑based “Slop” app to become “legitimately excellent” for mainstream users.

Today is November 30, 2025, less than two months after the prediction was made, so only ~10–23% of the forecast window has elapsed. We are still well before the earliest point at which Chamath expected the prediction to be realized, so it is not yet possible to determine whether mainstream‑quality, widely usable consumer video‑generation apps will meet his standard within that 1–2 year timeframe.

Because the forecast period has not yet ended, the correctness of the prediction cannot be evaluated at this time.

The prediction specifies a five‑year horizon from the October 3, 2025 discussion, i.e., roughly until October 3, 2030. Today is November 30, 2025, so less than a year—let alone five years—has passed. Because the end date of the forecast period has not yet been reached, we cannot determine whether average U.S. consumer electricity rates will have doubled by that time; the prediction is therefore too early to evaluate.

It’s too early to evaluate this prediction.

Chamath’s statement is explicitly conditional and long‑term: “If” the trend toward 50 divergent state AI regulatory regimes persists over the coming years, then the U.S. AI industry will be rendered “incapable” of generating positive economic output or maximizing its contribution to productivity and GDP. That involves (a) a structural regulatory outcome that hasn’t stabilized yet and (b) macroeconomic effects that would take multiple years to measure.

Regulatory landscape as of late 2025

• Several U.S. states (e.g., Colorado, California, Tennessee, Utah) have passed or are advancing AI‑related or automated decision‑making laws, but they are still in early phases and often sector‑specific or focused on transparency, risk management, or specific use cases (like hiring, consumer protections, or deepfakes).
• At the federal level, there have been ongoing efforts (e.g., NIST’s AI Risk Management Framework, executive‑branch actions, and multiple congressional proposals), but no settled, comprehensive national AI regulatory regime with clear long‑term preemption of state laws has fully taken effect. (This is consistent with broad coverage in major news and policy analyses through late 2025.)
• Because these laws are nascent and many are not yet fully implemented or enforced at scale, the long‑run interaction between state and federal AI rules is unresolved.

Economic outcomes not yet observable

• The claim that the U.S. AI industry will be “render[ed]…incapable of being able to generate any positive economic output” is extremely strong: it implies either negligible or net‑negative economic contribution in the aggregate.
• As of November 30, 2025, U.S. AI companies are still attracting substantial investment, filing patents, deploying models, and generating revenue across sectors (cloud providers, model labs, enterprise software, etc.). Measuring their net contribution to national productivity and GDP—and whether it is “far short of potential” because of state‑by‑state regulation—would require:
  • Several years of data on AI adoption and productivity across industries.
  • Clear attribution separating the effect of regulatory fragmentation from other factors (business cycles, interest rates, global competition, etc.).
• That kind of causal, macro‑level assessment simply cannot be made only ~2 months after the October 3, 2025 podcast date, and no credible economic studies yet isolate the effect of 50‑state AI rule divergence on overall U.S. GDP.

Because:

1. The regulatory condition (“50 sets of rules” persisting without meaningful federal harmonization) has not clearly materialized or failed yet, and
2. The economic consequence (industry‑wide impotence and failure to generate positive net output / major productivity gains) requires years of data and is not currently measurable,

the prediction cannot yet be judged as right or wrong. The appropriate classification is therefore “inconclusive (too early)”.

Key parts of the prediction are only partly observable by November 30, 2025, and the long‑run effects it specifies (“over the ensuing years”) have not yet played out.

1. Forced divestiture to an independent owner
   – In April 2024, the Protecting Americans from Foreign Adversary Controlled Applications Act (PAFACA) was signed, requiring ByteDance to divest TikTok’s U.S. operations or face a ban.(en.wikipedia.org)
   – The Supreme Court upheld this law in TikTok, Inc. v. Garland in January 2025, allowing the divestiture/bannng regime to take effect.(snopes.com)
   – In September 2025, President Trump issued an executive order deeming a divestiture plan a “qualified divestiture” under PAFACA and extending enforcement deadlines, with an Oracle–Silver Lake–led consortium expected to control ~80% of TikTok’s U.S. operations, leaving ByteDance with <20%. Oracle is not an incumbent consumer social‑media platform like Meta, Alphabet, Snap, etc., so this structure matches “an owner independent from the existing major US social platforms.”(reuters.com)
   – However, as of late November 2025 TikTok is still “in the process of divesting about 80% of its U.S. assets” and operating under transitional arrangements; the transaction and full restructuring are not yet complete.(reuters.com)

2. Increased regulatory scrutiny of recommendation algorithms
   – PAFACA and subsequent litigation and rule‑making have focused explicitly on foreign control, data access and potential content manipulation via TikTok’s recommendation systems. Court opinions and commentary repeatedly frame TikTok’s algorithm as a national‑security and information‑integrity risk.(reuters.com)
   – Trump’s 2025 executive order and related analyses describe the settlement conditions as requiring “intense monitoring of software updates, algorithms, and data flows” and that “all recommendation models…must be retrained and monitored” by U.S. “trusted security partners” (with Oracle commonly named), which is a direct, formal regulatory intervention into how TikTok’s recommender works.(internetgovernance.org)
   – This clearly shows heightened U.S. governmental focus on at least one major recommender system (TikTok US). But whether this will translate into a durable, system‑wide shift in how all large‑scale social‑media algorithms are regulated is still uncertain.

3. “Greater competitive diversity” among large‑scale social‑media algorithms
   – Available reporting describes the ownership and governance deal (Oracle/Silver Lake consortium, separate U.S.-only app and algorithm, retraining with U.S. data, U.S. data residency, etc.), but does not yet provide clear empirical evidence that this has produced greater competitive diversity in the broader social‑media algorithm landscape (e.g., a sustained increase in the number or distinctiveness of competing large‑scale recommendation systems, or structural weakening of Meta/Alphabet’s positions) attributable to the divestiture.(reuters.com)
   – Competing short‑video algorithms (Reels, YouTube Shorts, Snapchat Spotlight, etc.) were already in place before PAFACA and the 2025 divestiture framework, and no current sources show a clear, causally linked market‑structure change that can be credited to the TikTok divestiture rather than to ongoing competition and prior trends. This absence of evidence makes the “greater competitive diversity” part of the prediction impossible to verify at this time.

4. Timing (“over the ensuing years”)
   – The podcast was released in September 2025, and as of November 30, 2025, only a little over a year and a half has passed since PAFACA became law and just a couple of months since the divestiture framework was formally approved. The new U.S. TikTok entity is expected to testify before Congress in 2026, and its U.S‑only algorithm and governance model are still being implemented.(reuters.com)
   – Because the prediction explicitly speaks about changes “over the ensuing years,” and the key structural changes (new ownership, new algorithm, ongoing oversight) are still mid‑transition, there has not yet been enough time to measure the long‑run systemic impact on regulatory practice and market diversity.

Given: (a) the divestiture is in progress but not fully completed; (b) regulatory scrutiny of TikTok’s recommendation algorithm has clearly intensified but system‑wide effects are not yet knowable; and (c) there is no solid evidence yet of increased overall competitive diversity in large‑scale social‑media algorithms, the most reasonable classification as of November 30, 2025 is “inconclusive (too early)” rather than clearly right or wrong.

There is a real, ongoing forced‑divestiture process for TikTok’s U.S. operations that is being shaped under Trump’s second administration (via enforcement of the 2024 Protecting Americans from Foreign Adversary Controlled Applications Act, the Supreme Court’s TikTok v. Garland decision in January 2025, and a Trump executive order in September 2025 approving a divestiture plan and extending deadlines). ByteDance is in the process of selling roughly 80% of its U.S. TikTok assets to a U.S.-led consortium, with the recommendation algorithm to be retrained or licensed under U.S. supervision. (en.wikipedia.org)

Regulatory and public scrutiny of recommendation algorithms has clearly intensified in 2024–2025 across many platforms:

• New York’s SAFE for Kids Act and California’s SB 976 restrict “addictive” algorithmic feeds for minors and require chronological feeds instead. (cohealthcom.org)
• The federal Kids Off Social Media Act would ban personalized recommendation systems for users under 17, and the bipartisan Algorithm Accountability Act would create liability when recommendation algorithms foreseeably cause physical harm. (en.wikipedia.org)
• Numerous state AG lawsuits (e.g., Minnesota) directly attack TikTok’s and other platforms’ “addictive algorithms,” and advocacy groups explicitly frame the problem as harmful design and recommender systems, not just content. (apnews.com)
  These developments show a broad policy shift toward scrutinizing recommendation engines.

However, much of this algorithm‑focused push predates the TikTok divestiture fight and grew out of earlier concerns (Facebook whistleblower leaks, teen‑mental‑health debates, the Kids Online Safety Act process, Utah’s and other states’ 2023–24 laws targeting “addictive” feeds, and earlier TikTok/RESTRICT‑Act efforts). (en.wikipedia.org) The PAFACA/TikTok saga certainly kept TikTok’s algorithm and the risks of covert content manipulation in the headlines and in court opinions, but current coverage still frames that mainly as a national‑security/foreign‑influence milestone rather than as the clear watershed moment for regulating recommendation algorithms across all platforms. (en.wikipedia.org)

Because (a) the divestiture has not fully closed and its ultimate governance/algorithm‑access structure is still being worked out, and (b) it is too early to know whether historians and regulators will treat this particular “TikTok sale under Trump” as a major turning point, as opposed to one important episode within a broader, already‑underway trend, there is not yet enough evidence to judge Chamath’s claim definitively. Hence the prediction is best scored as inconclusive (too early to tell) rather than clearly right or wrong.

Available data show that U.S. tariff revenue has risen sharply but has not yet actually reached the $400–500 billion range discussed in the prediction, and the forecast horizon (“late‑2020s, once fully ramped”) has not arrived.

Key points from current data:

• For FY 2024, federal customs duties were about $77–83 billion, well below even $200 billion. (usafacts.org)
• Through August 2025, FY 2025 customs revenue totaled about $165.2 billion, already a record pace but still far from $400–500 billion on a realized 12‑month basis. (usafacts.org)
• Other reporting on FY 2025 indicates net customs receipts a bit above $100 billion through June and around $195–215 billion for the full fiscal year, depending on how one counts newer tariffs—again, materially below the $400–500 billion range. (voice.lapaas.com)
• In October 2025, monthly customs duties hit a record $31.4 billion, which, if simply annualized, implies something in the high‑$300 billions per year; some officials now project tariff revenue of around $400 billion in FY 2026 and even suggest it could exceed $500 billion annually. But these are projections, not realized receipts, and depend on policies and economic conditions holding through the late 2020s. (reuters.com)

Because (1) actual annual tariff revenue to date is still well below $400–500 billion, and (2) the prediction explicitly targets late‑2020s, once fully ramped, which is after November 30, 2025, there is not yet enough realized history to say whether annual receipts will in fact sustain the $400–500 billion level by that time. Therefore, the prediction’s accuracy is inconclusive (too early to tell).

Available data on 2025 tariff/customs‑duty receipts fall far short of the prediction that Trump‑era tariffs would be bringing in roughly $50B per month from April 1, 2025 onward (≈$400B over the remainder of 2025).

Key facts:

• Before the new 2025 tariff wave, total customs duties for all tariffs in FY 2024 were about $77B for the full year, illustrating the historical scale of tariff revenue. (usafacts.org)
• After the "Liberation Day" tariffs in early April 2025, monthly customs duties rose sharply but remained far below $50B per month:
  • April 2025: about $16–16.3B in customs duties, a record at the time. (reuters.com)
  • June 2025: about $26.6–27.2B. (english.alarabiya.net)
  • August 2025: $29.5B, a new monthly record. (fastbull.com)
  • October 2025: $31.4B in customs duties, again a record but still well below $50B. (reuters.com)
    These are total customs duties; the incremental portion attributable specifically to Trump’s new tariffs would be smaller.
• A Congressional-budget style analysis finds that total customs‑duty collections for all of FY 2025 were about $195B, with $151B collected in the second half of the fiscal year (April–September 2025)—an average of roughly $25B per month, roughly half of the predicted $50B run rate. (crfb.org)
• USAFacts, summarizing Treasury data, reports $165.2B in customs duties through August of FY 2025, consistent with other estimates that the entire FY 2025 total ends up around $195B, not anywhere near $400B or a $600B annualized pace. (usafacts.org)
• A recent article on the “Liberation Day” tariffs notes that they generated $215.2B in FY 2025 and $40.4B so far in FY 2026, which again implies total annual revenue from these tariffs in the low‑hundreds of billions, not $400B+ in just the April–December 2025 window. (the-sun.com)

Putting this together:

• To match Chamath’s claim, by late 2025 tariff revenue would need to be running at about $50B/month, implying roughly $300B from April–September alone and ≈$400B over the rest of calendar 2025.
• Actual total customs‑duty receipts from April–September 2025 were about $151B (≈$25B/month), and even including record months in August and October never approached $50B in a single month. (crfb.org)

Even allowing for some uncertainty in separating “Trump‑era” tariffs from baseline duties and for incomplete December 2025 data, the realized and projected revenue levels are far below the implied ~$400B over the 2025 stub period or a $600B annualized pace. The prediction therefore did not come true.

The prediction covers roughly 30 years beyond 2018 (to about 2048–2055), so as of November 30, 2025 we are far too early in the forecast window to know whether future presidents will eventually roll tariffs back to pre‑2018 baselines.

Evidence to date is consistent with Chamath’s claim but cannot prove it. Before the 2018 trade war, average U.S. tariffs on Chinese goods were about 2.7%; they rose to about 19% by 2023 and, after further escalations and partial de‑escalations in 2025, still remain dramatically above the pre‑2018 level. (congress.gov) President Biden’s 2024 Section 301 review chose to maintain Trump’s China tariffs and in many sectors (EVs, batteries, semiconductors, solar cells, steel and aluminum, etc.) to increase them substantially rather than cut them. (cambridge.org) Earlier reporting also noted that Biden, despite criticizing Trump’s approach during the 2020 campaign, kept the Trump‑era tariffs in place once in office. (npr.org) More recently, under President Donald Trump in 2025, U.S.–China tariffs were driven to very high levels (well above 100% on average) and then partially reduced in a negotiated truce, but even the reduced levels are still far above the pre‑2018 baseline, not a rollback to it. (reuters.com)

Because only a small fraction of the 30‑year horizon has elapsed, and future administrations could still fundamentally change course, the prediction cannot yet be classified as definitively right or wrong. Therefore the appropriate status is: inconclusive (too early).

As of the evaluation date (November 30, 2025), both milestones in Chamath’s prediction are still in the future:

• Groundbreaking is predicted for July 2026, which has not yet occurred.
• Commercial operations are predicted by July 2028, which is also in the future.

The referenced All-In Podcast episode was released on September 7, 2025, so his timeline ("groundbreaking in Michigan will be in July of next year... it'll be online two years after that") clearly targets mid‑2026 and mid‑2028.

Public information about Chamath’s battery-related investments (e.g., his backing of cathode maker Mitra Chem) does not provide verifiable detail on a specific Michigan battery factory schedule, nor evidence that such a project has been definitively canceled or made impossible before July 2026.(rova.nz)

Because the deadlines have not arrived yet and there is no conclusive evidence that the project cannot meet them, the accuracy of this prediction cannot yet be determined.

Available data show that U.S. corporate bankruptcies have been rising and are elevated in 2024–2025, but Chamath’s prediction is explicitly about what happens “over the next several years (post‑2025)” relative to the 2010–2024 period, so the forecast horizon has not elapsed.

Context:

• From 2010–2024, annual U.S. corporate bankruptcies (using S&P’s large‑company definition) generally ranged from the high 300s to high 600s, with 694 filings in 2024—already the highest level since 2010’s 828. (visualcapitalist.com)
• In 2025, filings have continued to climb. S&P data show 188 bankruptcies in Q1 2025 (the highest first quarter since 2010) and 371 filings by mid‑year, the most in the first half of any year since 2010. (cmrfinancialadvisors.com) By October 2025, there were 655 filings, putting 2025 on track to surpass 2024 and reach a 15‑year high. (reuters.com)

These figures are consistent with the direction of his claim (“more, not less bankruptcies”), but they only cover the first year of the post‑podcast period. Because his prediction concerns a multi‑year trend beyond 2025, and we do not yet have data for those subsequent years (2026, 2027, etc.), it is too early to say whether bankruptcies will remain higher than in the 2010–2024 period over the full forecast horizon. Therefore, the correct status as of November 30, 2025 is inconclusive (too early to judge).

As of November 30, 2025, it’s too early to judge this prediction, because the forecast window is 3–4 years from 2025, i.e., roughly until late 2028–late 2029.

On the factual side:

• Yamanaka-factor / partial cellular reprogramming is still largely in preclinical and early clinical stages; longevity commentators note that only the first induced-pluripotent-stem-cell (iPSC)–derived therapies have just reached tightly regulated clinical trials and that progress toward rejuvenation therapies is slow. (fightaging.org)
• There is active medical tourism for advanced stem-cell and iPSC-related treatments, especially in places like Japan, marketed for anti‑aging and regenerative purposes, but these are mostly mesenchymal stem cell therapies and targeted iPSC applications (retina, Parkinson’s, etc.), not open Yamanaka-factor-style rejuvenation protein/gene therapies sold to general consumers. (placidway.com)

So, by late 2025, the specific scenario Chamath described — medical tourists flying to a lightly regulated jurisdiction (e.g., Costa Rica or similar) to receive Yamanaka-factor-style rejuvenation protein therapies outside U.S. clinical‑trial channels — has not clearly materialized yet, but the deadline for his forecast is still several years away. We therefore can’t say the prediction is right or wrong at this point, only that it remains open.

As of November 30, 2025, only a few years have elapsed since the start of the current generative‑AI surge (late 2022–2023) and only a few months since Chamath’s August 2025 statement. His claim is explicitly about a “multi‑decade innovation cycle” (20+ years beyond 2025), so by definition it cannot yet be confirmed or definitively falsified.

Available evidence does show that the AI wave is still very active rather than clearly having peaked and ended:

• Major AI companies remain among the world’s most valuable firms; for example, Alphabet’s market cap is nearing $4 trillion in late 2025, driven largely by AI products and infrastructure, following Nvidia’s earlier move into the $4T tier, both underpinned by heavy AI investment and demand. (reuters.com)
• Reports on an “AI bubble” note corrections and fears (e.g., Nvidia’s sharp but temporary stock drop in early 2025 and widespread debate about ROI), yet they also highlight continued or even accelerating AI spending: global AI investment is projected in the trillions of dollars over the next several years, treating AI as a foundational technology rather than a short‑lived fad. (en.wikipedia.org)
• Large international AI summits and conferences (e.g., the 2025 AI Action Summit in Paris and the 2025 World Artificial Intelligence Conference in Shanghai) show sustained, system‑level commitment by governments and industry to long‑term AI development. (en.wikipedia.org)

However, these facts only show that the cycle is still underway in 2025; they do not prove it will persist for “multiple decades.” Likewise, while there is concern about bubbles and overvaluation, no decisive collapse has occurred that would prove the cycle will not last that long. Because the horizon of the prediction (20+ years beyond 2025) extends far into the future, there is simply not enough elapsed time to judge its ultimate accuracy.

Given that the key claim is about long‑term duration, and neither confirmation nor clear falsification is yet possible, the only defensible assessment as of 2025 is inconclusive (too early to tell).

The prediction gives OpenAI roughly four years from August 2025—i.e., until around August 2029—to reach ~2 billion daily active users, about one‑tenth of Facebook/Meta’s then‑current revenue, and a valuation on the order of $1.5 trillion. As of the current date (November 30, 2025), that deadline is still almost four years away, so it is too early to know if this target will be met.

Available data only show partial progress so far: estimates and CEO statements put ChatGPT at around 800 million weekly active users in 2025, with daily actives on the order of 120–180 million—well below 2 billion DAU.【1search0】【1search2】【1search3】 OpenAI is valued in the low hundreds of billions as of 2025 (roughly $300–500 billion, depending on the private-markets quote), not yet near $1.5 trillion.【1search0】【1search2】【1search1】 Internal forecasts cited in the press project $125 billion in annual revenue by 2029 and billions of users by 2030, but those are plans rather than outcomes.【1search5】【1search7】 For comparison, Meta’s 2024 revenue is about $164.5 billion, implying that one‑tenth of Facebook/Meta revenue is on the order of $16–19 billion per year.【2search3】

Because the forecast horizon (through ~August 2029) has not yet passed, we cannot definitively say whether Chamath’s prediction is right or wrong at this time; it remains unresolved.

As of November 30, 2025, the 2026 U.S. midterm elections have not yet taken place (they are scheduled for November 2026). Because the full general‑election campaign, media narrative, and post‑election analyses of voter priorities are still in the future, we cannot yet know whether economic issues will in fact dominate over social or foreign‑policy issues. There is therefore not enough evidence at this time to judge whether this prediction is right or wrong.

As of November 30, 2025, neither the 2028 Democratic presidential primaries nor the 2028 general election have taken place, so we cannot test the core of Chamath’s prediction (whether a self‑identified socialist could or does win the Democratic primary, and whether such a candidate then loses the general under the Electoral College).

Key points:

• The 2028 U.S. presidential election is scheduled for November 7, 2028, and the primary calendar and candidate field for that cycle are not yet fully determined or completed as of late 2025. The Democratic nominee has not been selected, and the general election result is unknown.
• There have been no completed 2028 presidential contests that would empirically confirm or falsify the claim that “a socialist can absolutely win” the Democratic primary but “cannot win” the general election under current Electoral College conditions.
• While there have been ongoing debates about reforming or abolishing the Electoral College, no constitutional amendment or nationwide compact has taken effect to replace it as of 2025; the Electoral College system remains in place for upcoming presidential elections, including 2028. This preserves the structural premise of the prediction, but doesn’t yet show whether a socialist nominee would in fact lose in the 2028 general election.

Because the necessary events (the 2028 primaries and general election) have not occurred, the prediction cannot yet be judged as right or wrong. Therefore the correct status is "inconclusive" (too early).

As of November 30, 2025, the 2028 Democratic presidential primary field is not set and no one has formally declared a 2028 presidential candidacy among the three governors named.

Current public positions:

• Gavin Newsom (CA) – Has not announced a run, but has openly said he will give a 2028 presidential bid “serious thought” after the 2026 midterms and acknowledges he’d be “lying” if he claimed he wasn’t considering it. He is actively building national profile and infrastructure that could support a run, but remains undeclared. (thewrap.com)
• Gretchen Whitmer (MI) – Has not announced a campaign but explicitly said she “can’t rule anything out” regarding a 2028 Democratic presidential bid, keeping her options open while focusing on her governorship and the 2026 midterms. (news.bloomberglaw.com)
• Wes Moore (MD) – Has not announced a run and, in fact, has publicly ruled out running for president in 2028, stating on NBC’s “Meet the Press” that he is “not running for president” and intends to serve a full second term as governor if reelected. (aol.com)

The prediction claims that all three will ultimately run in the 2028 Democratic primary. Because the primary is still in the future and filing/ballot deadlines have not passed, any of these governors could still change course, including Moore despite his present denial. Political figures do sometimes reverse earlier statements about not running.

Therefore, it is too early to say definitively whether all three will or will not run. The prediction is trending against realization (given Moore’s current stance), but it has not yet been conclusively proven right or wrong, so the appropriate status is inconclusive (too early).

By November 30, 2025, there is substantial evidence that:

• People are forming emotionally intense, sometimes parasocial-style attachments to AI chatbots and companion apps (e.g., Replika, Character.AI, and ChatGPT), including friendship and romantic/mentor-like relationships.(arxiv.org)
• The informal term “AI psychosis” (or chatbot psychosis) has gained traction in media and psychiatry to describe cases where heavy chatbot use is linked with delusions, paranoia, or emotional over‑reliance.(en.wikipedia.org)
• OpenAI and press reports estimate that, at current scale, hundreds of thousands of ChatGPT users per week show possible signs of psychosis or mania and over a million show suicidal intent or harmful emotional attachment in chats, prompting new safety interventions.(wired.com)
• Commentators and clinicians explicitly warn that design features of LLM chatbots (constant validation, mirroring, availability) can fuel delusional thinking and intense pseudo‑relationships in vulnerable users.(arxiv.org)

These trends clearly support the direction of Chamath’s claim—that parasocial and psychologically fraught relationships with AI chatbots are real and growing.

However, his prediction was phrased as something that would “catch on like wildfire” “over the coming years.” The podcast aired on August 15, 2025, so as of November 30, 2025, only a few months have passed. That is far short of the multi‑year horizon implied, and the available data are still:

• Early, largely correlational or anecdotal, with researchers and clinicians repeatedly emphasizing that robust long‑term evidence and prevalence estimates are not yet available.(en.wikipedia.org)
• Focused on specific platforms and subpopulations, making it hard to say how ubiquitous or enduring the phenomenon will be in the broader public over “years.”

Because the core claim is about how widespread and normalized this behavior will become in the coming years, and the full time window has not elapsed, it is too early to decisively judge whether it has “caught on like wildfire” in the longer-term sense he predicted.

Therefore the appropriate classification, given the prediction’s timeframe, is inconclusive (too early to tell).

It’s too early to score this prediction.

Chamath’s claim is about 2030: “I think the estimate is in 2030, 30 million electric vehicles.” The current date is November 30, 2025, so we are still about 4–5 years away from the target year. We can assess trajectory but not the final outcome.

As context, U.S. EV stock (battery electric + plug‑in hybrids) has been growing quickly but is still far below 30 million:

• The International Energy Agency estimated about 3 million electric cars in the U.S. fleet in 2023.
• Various industry and analyst forecasts (BloombergNEF, IEA, major automakers) project continued rapid growth toward the late 2020s, with cumulative EVs plausibly reaching the tens of millions by 2030, but the exact 2030 figure will depend on policy, charging build‑out, consumer adoption, and automaker product plans.

However, because 2030 has not yet occurred, we cannot say whether the U.S. will actually have “on the order of 30 million” EVs by that time. The most accurate status classification today is therefore inconclusive (too early).

The prediction hinged on the idea that the New York Times–Amazon AI licensing deal in mid‑2025—reported at $20–25M per year—was the peak of this type of training‑data/content‑licensing deal, and that comparable deals signed in future years would see per‑year dollar values “only go down from here.” (wsj.com)

What we can see as of 30 Nov 2025:

1. Size of the NYT–Amazon deal
   Multiple reports (summarizing the original WSJ scoop) say Amazon will pay The New York Times $20–25M annually under a multi‑year AI content‑licensing agreement for training models and powering Alexa and related products. (wsj.com) This is the specific deal Chamath was reacting to.

2. Other large AI–publisher deals already in market
   Before this NYT–Amazon deal, there were already larger AI training‑licensing arrangements on a per‑year basis:

   • News Corp–OpenAI: widely reported at >$250M over 5 years (≈$50M/year). (allmo.ai)
   • Reddit–Google & Reddit–OpenAI: coverage of Reddit’s filings and press reports imply ~$60–70M per year from OpenAI and ~$60M/year from Google for data licensing. (allmo.ai)
   • Dotdash Meredith–OpenAI: estimated fixed component around $16M/year. (allmo.ai)
     So even at the time of the podcast, $20–25M/year was not the highest per‑year figure in the ecosystem, but the user’s normalized prediction focuses on the future trend from that point.

3. Deals signed after Aug 1, 2025
   Since the podcast date, there have been new AI content‑licensing deals, but most have undisclosed financial terms:

   • Perplexity–Gannett / USA TODAY Network (Perplexity Publisher Program) – terms not disclosed. (businesswire.com)
   • Gannett–Microsoft AI licensing agreement via Microsoft’s Publisher Content Marketplace – announced in Gannett’s Q3 2025 results, but again no dollar figures given. (businesswire.com)
   • Perplexity–Getty Images multi‑year visual‑content licensing deal – no public pricing. (futureweek.com)
     Survey pieces that catalog the training‑data market as of October 2025 list the major known deals (News Corp, Reddit, Dotdash Meredith, NYT–Amazon, etc.) and explicitly note that only a few dollar figures are public and most contracts are confidential. (allmo.ai)

4. No post‑August 2025 deal with a clearly higher disclosed per‑year value
   In the public record through November 2025, no newly announced publisher/AI training‑data deal after Aug 1, 2025 has a disclosed annual payment that clearly exceeds the NYT–Amazon $20–25M/year range. However, because most newer deals do not publish financial terms at all, this absence of evidence is not strong evidence that the underlying economics are actually lower.

5. Time horizon and data limitations
   Chamath’s statement was about “from here” going forward and “future years”. Only about four months of dealflow have elapsed since the podcast, and the small number of post‑August deals with confidential pricing makes it impossible to robustly determine a trend in per‑year license values. Industry overviews emphasize that the market is still evolving, with a wide spread from single‑digit millions per year to nine‑figure multi‑year packages, and that public numbers should be treated as directional only. (allmo.ai)

Why the result is "inconclusive" rather than right or wrong:

• To decisively call the prediction wrong, we would need at least one post‑Aug‑2025 training‑data licensing deal, clearly comparable in scope, with a disclosed annual value above ~$25M/year. No such publicly documented example exists yet.
• To call it right, we would need evidence that subsequent comparable deals are consistently priced below that level (or that $20–25M/year is clearly a ceiling). Because most newer contracts do not report financials, and the observation window is short, we also lack that evidence.

Given the short time since the prediction and the opacity of deal terms, the direction of per‑year pricing for future AI training‑licensing deals cannot yet be determined from available data, so the outcome is best classified as inconclusive (too early to tell).

The prediction specifies a horizon of about five years from August 2025, i.e., until roughly August 2030. As of late November 2025, less than one year has elapsed since the prediction date. Today is still in calendar year 2025, with multiple independent sites confirming that 2025 is the current year and we are in Q4 2025. (en.wikipedia.org)

Because the prediction is explicitly about what will happen over the next five years, it is too early to determine whether patents and copyrights will have become practically unenforceable or economically insignificant by 2030. Even though there are active debates and legal cases about AI, copyright, and training data, these are part of an evolving legal landscape whose outcome by 2030 cannot yet be observed or measured in 2025. Therefore, the correct status of this prediction as of now is inconclusive (too early to tell).

Scope of the prediction
Chamath said that from Q3 2025 onward the U.S. macro environment would look like Q2 2025, specifically: (1) a large surplus (fiscal/trade), (2) strong GDP expansion similar to Q2, and (3) inflation that continues to moderate.

1. “Large surplus” did not persist

• Trade: Official BEA data show the U.S. continued to run large trade deficits, not surpluses. The goods-and-services deficit was $60.2B in June, $78.3B in July, and $59.6B in August 2025, with the year‑to‑date deficit actually larger than in 2024. None of these months show a surplus. (bea.gov)
• Current account: For Q2 2025 itself, the U.S. still had a current‑account deficit of $251.3B (3.3% of GDP); it narrowed versus Q1 but remained firmly negative, not a surplus. (bea.gov)
• Fiscal: For fiscal year 2025 (ended Sept. 30), the federal government ran an annual deficit around $1.8T, only slightly smaller than 2024. July alone saw a $291B deficit, and October posted a $284B deficit, even though some months like April and June had temporary surpluses. The overall environment is one of persistent large deficits, not a sustained “large surplus.” (finance.yahoo.com)
  Given this, the central claim that Q3 and beyond would feature a large surplus similar to (his characterization of) Q2 is clearly false.

2. “Good GDP expansion” is likely but not fully observable yet

• Q2 2025 real GDP grew at about 3.3–3.8% annualized, a strong rebound from the Q1 contraction. (tradingeconomics.com)
• The Commerce Department’s advance Q3 GDP estimate was delayed by the government shutdown and is scheduled for Dec. 23, 2025, so as of Nov. 30 we do not yet have an official Q3 GDP print. (reuters.com)
• High‑frequency tracking (e.g., Atlanta Fed estimates around 4% annualized for Q3) suggests growth probably has remained solid, but that’s still model‑based, not realized data. (reuters.com)
  So this part of the prediction may be directionally right, but it isn’t fully verifiable yet.

3. Inflation has not kept “moderating” through Q3

• CPI: Year‑over‑year CPI inflation in 2025 starts near 3% and dips into the 2.3–2.4% range in March–April, but then rises back to about 3.0–3.1% by September 2025, indicating a re‑acceleration rather than a continued decline in Q3. (inflationtool.com)
• PCE (Fed’s preferred gauge): Headline PCE inflation rises from 2.5% in May to 2.7% in August, and core PCE YoY drifts up from about 2.6% in April to roughly 2.9% by August, with monthly readings of 0.2–0.3%. That is “sticky” or slightly higher inflation, not ongoing moderation. (bea.gov)
  Thus, the claim that inflation would continue to moderate into Q3 and beyond does not match the realized data; it flattened and then ticked up.

Overall assessment
Even allowing that Q3 GDP itself looks likely to be strong, two core pillars of Chamath’s forecast—a sustained large surplus and continued disinflation into Q3+—are clearly contradicted by the data we now have. Since these elements were central to his description of the future macro environment “similar to Q2,” the prediction as stated is wrong rather than merely unproven or ambiguous.

As of November 30, 2025, xAI’s Colossus supercomputer (used to train Grok) has not yet reached anything close to 1,000,000 GPUs in operation, but there are multiple public plans and ongoing build‑outs aiming for that scale.

1. Current scale (well below 1M GPUs): Recent coverage summarizing Elon Musk’s statements indicates that xAI currently operates on the order of ~200,000–230,000 GPUs (H100/H200 plus roughly 30,000 Blackwell/GB200 units) for Grok training, far below 1,000,000. (techradar.com) Critical analyses likewise argue that, due to power limits at the Memphis site, only a fraction of the installed GPUs can be powered simultaneously, suggesting effective capacity is even lower in practice. (bluemoonofshanghai.com)

2. Documented plans to reach ~1M GPUs: Well before and after the podcast date, Musk and xAI partners publicly described plans to scale Colossus to around or over one million GPUs. Tom’s Hardware, citing the Financial Times, reports that xAI intends to expand Colossus from over 100,000 H100s to more than one million GPUs, making it one of the most powerful supercomputers in the world. (tomshardware.com) Supermicro has also publicly stated it is supporting xAI’s “10‑fold expansion … with over 1 million GPUs” at the Memphis facility. (tomshardware.com) Local economic‑development announcements and follow‑on reporting describe an expansion that will “incorporate a minimum of one million GPUs,” with project completion targeted in 2026. (eonmsk.com)

3. No evidence of cancellation, but also no 1M‑GPU cluster yet: Energy‑infrastructure reports and power‑plant acquisitions explicitly frame the one‑million‑GPU configuration as a future goal, discussing the power needs and construction work required for such a cluster, not an already‑achieved reality. (finance.yahoo.com) None of the major technical or business sources surveyed claim that xAI has actually deployed and brought online ~1,000,000 GPUs as of late 2025.

Because Chamath’s prediction is that xAI’s Grok cluster will be scaled “up to a million” over time, and the available evidence shows:

• substantial progress beyond the initial 100k/250k plans, yet
• the system is still far short of one million GPUs, and
• the publicly stated timeline to reach ~1M extends into 2026 and beyond,

it is too early to say whether the prediction ultimately proves true or false. The outcome depends on whether xAI actually completes the planned scale‑up in the coming years. Therefore, the appropriate classification for now is “inconclusive (too early).”

Chamath is paraphrasing Elon Musk’s claim on the All-In podcast that later Grok models would move away from “traditional datasets that exist in the wild” and instead be trained via agents generating synthetic data.

Public evidence about Grok’s evolution shows that xAI has not stopped using conventional human-created corpora:

• Regulators in Europe opened an investigation into X’s use of public posts from EU users to train Grok’s LLMs, explicitly describing Grok as trained on large scraped online datasets (articles, blog posts, and social‑media content). This is classic “in‑the‑wild” human data, and there has been no indication that later Grok versions abandoned such sources globally; the reported remedy was limited to EU user data. (apnews.com)
• Reporting on Grok 3 emphasizes synthetic data as an important component, but describes it as in addition to a larger, more diverse dataset rather than a complete replacement of real‑world text. The model is portrayed as mixing synthetic data with real data to improve reasoning and reduce hallucinations, not as being trained solely on synthetic corpora. (rdworldonline.com)
• Musk later said xAI would retrain Grok on a “revised base of human knowledge,” i.e., a re‑edited corpus meant to remove “garbage” and add missing information. That still implies reliance on large human‑authored text collections, just more curated, rather than a pure agent‑generated synthetic dataset. (businessinsider.com)
• Coverage of Grok 5’s planned training states that it will incorporate real‑time data from the X platform to improve relevance and accuracy—a direct continuation of using live, user‑generated social‑media content as part of the training or fine‑tuning pipeline. (grokmag.com)
• xAI’s own materials for Grok 4 and Grok 4.1 talk about large‑scale reinforcement learning and frontier “agentic reasoning” reward models, but they do not claim that the underlying pretraining data has stopped coming from internet and document corpora, and no independent technical source reports such a drastic shift. (x.ai)

Musk has indeed argued that human‑generated data is becoming “exhausted” and that future progress will lean more on synthetic data, which matches the spirit of what Chamath repeated. (theguardian.com) However, available reporting shows that as of late 2025, Grok’s successor models (Grok 4.1/4.1 Fast and the in‑training Grok 5) still depend significantly on conventional human‑authored text from the web, legal documents, and especially X posts, with synthetic data layered on top rather than used exclusively.

Because the prediction was categorical (“not going to be trained on any traditional dataset”), and the ongoing use of real‑world internet and social‑media data is well documented, the prediction has not come true based on what is publicly known, even allowing for some uncertainty about xAI’s proprietary datasets.

Public information shows Elon Musk and xAI clearly intend to lean heavily on synthetic, agent-generated data for Grok, but there is no verifiable evidence that Grok’s training has already shifted to being primarily driven by such data instead of human-generated datasets.

Key points:

• In the All-In discussion summarized by multiple outlets, Chamath recounts Musk saying that future Grok models won’t train on traditional datasets and will instead rely on AI agents creating synthetic data from scratch to drive all the training. This matches the prediction’s wording, but it is a description of Musk’s plan, not confirmation of what xAI has actually done so far. (okx.com)
• Musk has publicly claimed that AI developers have “exhausted” the available pool of human knowledge and that the “only way” forward is synthetic data, where models write and grade their own content. This supports a strategic shift toward synthetic data, but not the specific claim that it already dominates Grok’s training mix. (theguardian.com)
• Some secondary reports state that Grok 3/3.5 were trained extensively or even “primarily” on synthetic datasets, and that synthetic data is central to Musk’s strategy. However, these are not official technical disclosures from xAI, and they still frame synthetic data as augmenting or improving on human data rather than completely replacing it. (linkedin.com)
• Musk, in a later All-In appearance, describes upcoming Grok models as starting from conventional sources (Wikipedia, books, websites) and then using synthetic methods to clean up and rewrite that information—indicating that human-generated corpora remain a core substrate, with synthetic “corrections” layered on top, not a purely agent-self-play data regime. (m.economictimes.com)
• xAI’s official Grok-4 model documentation and public materials do not disclose the proportion of synthetic vs. human data in training, and independent reporting still highlights large human “AI tutor” teams and RLHF-style pipelines, implying substantial ongoing reliance on human-labeled or human-generated data. (docs.x.ai)

Because xAI has not released transparent training-data breakdowns and the available evidence is a mix of aspirational statements, commentary, and partial reporting, we cannot reliably determine whether Grok’s future training regime has in fact shifted to being primarily driven by agent-generated synthetic data rather than human datasets. The claim could turn out to be correct in the longer term, but as of Nov 30, 2025, its truth value is not knowable from public sources, so the prediction’s status is best judged as ambiguous rather than clearly right or wrong.

As of November 30, 2025, the U.S. Senate’s legislative filibuster rule (the 60‑vote cloture requirement for most legislation) is still in place and has not been abolished. However, Chamath’s prediction is explicitly open‑ended (“just a matter of time,” “on borrowed time”), with no time horizon given. Because he’s predicting an eventual change at some unspecified point in the future, we cannot yet say whether it will ultimately prove right or wrong; we can only say that it has not come true yet.

Given the lack of a deadline or concrete timeframe, the appropriate status is that it’s too early to evaluate the prediction’s correctness, even though the filibuster still exists as of now. Therefore, the prediction is marked as inconclusive rather than right or wrong.

As of November 30, 2025, the U.S. Senate has not eliminated the legislative filibuster; the 60-vote cloture rule for most legislation still applies. However, Chamath’s prediction is explicitly about “some future point” with no time bound, so we cannot yet judge it as right or wrong.

Key facts:

• The Senate nuclear option has previously been used only for nominations: Democrats in 2013 ended the filibuster for most executive and judicial nominees (not Supreme Court), and Republicans in 2017 extended this to Supreme Court nominees. The legislative filibuster, requiring 60 votes for cloture on most bills, remained in place after those changes.
• Searches of 2024–2025 news and Congressional records show no rule change abolishing or effectively neutralizing the filibuster for ordinary legislation; high-profile fights (e.g., over voting rights, abortion, and budget issues) continued to acknowledge the 60-vote requirement.

Because Chamath predicted that eventually a Senate majority leader will “steamroll” the filibuster, and because that event has not yet occurred but also could still occur in the future, the correct status as of now is “inconclusive (too early)”, not right or wrong.

The prediction is explicitly about what will happen “over the next several years”, but we are less than half a year past the July 4, 2025 podcast date, so the forecast horizon has not elapsed.

Regulatory structure is still unsettled:

• States are rapidly enacting their own AI laws: in 2025, state lawmakers introduced 1,134 AI‑related bills and enacted 131 laws across 40 states, creating a patchwork of state rules. (ccianet.org)
• At the same time, there is an active federal push to preempt state AI laws (e.g., House bills including 10‑year preemption, and a White House draft executive order to challenge state AI regulations), while state AGs and groups like NCSL are lobbying hard against preemption. (nfcommission.gov)
  Because this federal–state fight is unresolved, we don’t yet know whether the medium‑term U.S. regime will truly be “predominantly state‑level, non‑preempted” as the prediction assumes.

Impact on startups vs incumbents is also not yet empirically clear:

• California’s SB 53 (the first major “frontier AI” safety law) and related AI bills are widely seen as positioning California as a lead U.S. regulator of AI, but SB 53 is narrowly scoped: it applies only to “large frontier developers” with models above 10^26 FLOPs and >$500M in annual revenue, deliberately excluding smaller developers. (lw.com)
• Critics from venture capital and industry (e.g., Andreessen Horowitz) argue that a 50‑state patchwork could make compliance costs unmanageable for startups and entrench big players, explicitly warning that SB 53 and similar state‑by‑state rules may “squeeze out startups” and “entrench the biggest players.” (forbes.com)
• However, supporters of SB 53 and academic/policy analysis emphasize that its obligations fall almost entirely on a small set of frontier labs and are not designed to burden smaller startups, and there is not yet systematic evidence that AI startup formation, funding, or growth has materially slowed because of these new state laws. (sb53.info)

Since:

1. the regulatory regime Chamath is describing is still being contested (federal preemption vs state autonomy), and
2. the concrete, measurable long‑term impact on AI startups and incumbents has not yet had time to materialize or be robustly measured,

it is too early to say whether his multi‑year prediction is right or wrong. Hence the result is inconclusive at this time.

As of November 30, 2025, it is not yet 2032–2033, so we cannot know whether new U.S. nuclear power plants whose development is initiated around 2025 will, in fact, start operating before those years. The prediction concerns events (plant commissioning dates) that are still in the future relative to today, so it cannot be verified or falsified yet. Therefore, the correct status is too early to tell.

The prediction is explicitly about a ~20‑year horizon: from the “next 20 years” after the mid‑2020s (i.e., roughly through 2045). As of November 30, 2025, less than one year has passed since the podcast release date (July 4, 2025), leaving about 19 more years until the prediction’s time window is complete. Because the claim concerns long‑term investment performance across that entire period, it cannot yet be evaluated—neither the full trajectory of U.S. electricity production investments nor the long‑run trend of marginal energy costs toward zero is observable for 2045. Therefore, the correct status today is that it’s too early to tell whether the prediction is right or wrong.

Available reporting shows that after a severe mid‑2025 rupture over Trump’s “One Big Beautiful Bill,” Trump and Musk ultimately moved back toward cooperation rather than remaining long‑term adversaries.

• In June–July 2025, Musk broke dramatically with Trump over the “Big, Beautiful Bill,” denouncing it as “insane” deficit spending, threatening primary challenges and creating a new “America Party” in explicit rebuke to Trump and the GOP. Trump in turn called Musk “off the rails” and a “train wreck,” and threatened to cut subsidies or even look at deporting him, with coverage characterizing the split as a spectacular falling‑out. (livemint.com) This period clearly looked like a real rupture.
• However, the America Party effort quickly stalled; by late July reporting noted Musk hadn’t filed FEC paperwork or fielded candidates, and by August 20 he was already “giving up” on actually starting the party and instead considering support for VP JD Vance in 2028—signaling retreat from a sustained, organized challenge to Trumpism rather than a permanent realignment against it. (en.wikipedia.org)
• On September 21, 2025, Trump and Musk publicly met, shook hands and chatted at a large memorial for Charlie Kirk in Arizona. The Guardian and other outlets framed this as raising the prospect of reconciliation, and noted that Musk himself posted a friendly image of the two together captioned “For Charlie,” while the White House account amplified the encounter. (theguardian.com) The Wikipedia entry on the Trump–Musk feud summarizes the second phase of their conflict (June 28–September 21, 2025) as ending with a “Reunited” status, reflecting that the feud, as such, was considered over. (en.wikipedia.org)
• By late 2025, Musk was again doing business with the administration—e.g., a GSA agreement with his xAI for federal AI adoption—indicating a pragmatic working relationship despite unresolved policy differences over the bill. (en.wikipedia.org)

Taken together, the sequence is: intense but time‑bounded feud, an attempted but quickly deflated third‑party break, then an early‑fall public rapprochement and resumed cooperation. That matches Chamath’s directional claim that their conflict would be temporary and that they would ultimately find common ground rather than experience a lasting rupture, even though the path there involved a much deeper and more chaotic break than his framing implied. Hence the prediction is best scored as right in outcome, albeit messier and more contingent than suggested in the podcast.

The prediction is explicitly framed over “the coming decades” and most of the current generation’s lifetimes, so only a few months of data (July–November 2025) are far too short to validate or falsify it.

So far, events are directionally consistent with Chamath’s thesis but cannot prove it:

• The U.S. dollar has experienced a historically sharp drop in 2025 (around 10–11% on the dollar index in the first half of the year), but analysts and strategists mostly describe this as a significant devaluation and period of stress, not a structural collapse; many still expect a gradual grind lower rather than a sudden failure, and central banks continue to treat the dollar as the primary reserve asset. (theinvestorschronicle.com)
• U.S. equities (e.g., the S&P 500) are up roughly 12–15% year‑to‑date in 2025, indicating that major dollar‑denominated assets have indeed appreciated faster than the dollar’s recent decline so far. (statmuse.com)

However, because the claim concerns multi‑decade currency behavior and long‑term real returns on U.S. assets, the available post‑podcast window (less than one year) is nowhere near sufficient to declare it right or wrong. The correct assessment today is that it’s too early to tell.

As of November 28, 2025, the S&P 500 is at 6,849.09 and has only briefly traded above 6,900; it has not yet reached 7,000. (apnews.com) The Federal Reserve, under Jerome Powell, has not begun what would commonly be described as an “aggressive cutting program” in 2025: following a single 25 bp cut in December 2024, the Fed held rates steady through mid‑2025 and then delivered just one additional 25 bp cut in September 2025 to a 4.0–4.25% range, while explicitly signaling caution and only penciling in a couple more small cuts. (forbes.com) Since Chamath’s prediction is conditional—if Powell starts an aggressive cutting program, then the S&P could quickly rerate to ~7,000—and the precondition (an aggressive, multi‑step cutting cycle starting in 2025) has not clearly occurred yet, the scenario he described has not actually been tested. Moreover, because markets are still below 7,000 and future Fed actions and market moves beyond November 2025 remain unknown, it is too early to determine whether his conditional call will ultimately prove right or wrong.

Evidence since the June 28, 2025 podcast shows that the Abraham Accords have expanded to include at least one additional Muslim‑majority country, matching Chamath’s prediction.

• In early November 2025, U.S. and Israeli officials announced that Kazakhstan would join the Abraham Accords, with reporting describing it as the first country to enter the framework since the Gaza war.(reuters.com)
• The Associated Press likewise reported that Kazakhstan "will join the Abraham Accords" in a symbolic move to boost the initiative, noting that it has long had diplomatic relations with Israel but is now formally entering the Accords framework.(apnews.com)
• Background/summary sources on the Abraham Accords now list Kazakhstan as a country that joined on November 6, 2025, explicitly under that banner.(en.wikipedia.org)
• Kazakhstan is approximately 70% Sunni Muslim, making it clearly part of the Muslim‑majority world, even if it is geographically Central Asian rather than in the Arab core of the Middle East.(israelhayom.com)

Chamath’s normalized prediction was that “in the coming years, additional countries in the Middle East and/or Muslim‑majority world will formally join or normalize relations with Israel under the framework of the Abraham Accords or an explicit extension of them.” Once Kazakhstan, a Muslim‑majority state, formally joined the Abraham Accords framework in November 2025, that condition was satisfied. The fact that this happened within months (rather than many years) does not invalidate the prediction; it simply means the forecast materialized early within the multi‑year window.

Therefore, based on current information, the prediction is right.

The prediction is about a 40–50 year trajectory starting from around 2025, i.e., projecting conditions for New York City circa 2065–2075. As of the current date (November 30, 2025), less than one year has elapsed since the prediction was made, so it is far too early to determine whether NYC will "look like New York of the 80s" (high crime and disorder) over that long horizon. There is simply not enough elapsed time relative to the forecast window to evaluate accuracy. Therefore, the only reasonable judgment at this point is inconclusive (too early).

Available data through late 2025 show no broad NYC real-estate “crash and burn” so far. Residential median sale prices across NYC were about 10% higher year‑over‑year in Q1 2025, indicating continued strength rather than a collapse. (qns.com) Analyses of the NYC housing market in mid‑ to late‑2025 describe prices as generally stable or modestly rising, with only slight projected easing and explicitly characterizing a major crash as unlikely. (noradarealestate.com) Some subsegments (e.g., certain single‑family homes, offices) have seen value declines, but the changes reported are on the order of a few percent, not a systemic crash across “New York real estate.” (bloomberg.com) However, Chamath framed this as happening in the “coming years”, and only about five months have elapsed between the June 28, 2025 prediction and the November 30, 2025 evaluation date. That horizon is too long relative to the time passed to definitively say the prediction has failed, so the outcome is too early to judge.

The prediction sets a timeframe of about one year from the June 2025 recording, i.e., roughly by mid‑2026. Today is November 30, 2025, so less than a year has passed since the podcast release on June 21, 2025, and we have not yet reached the prediction’s target date. Because the deadline for the forecast (mid‑2026) is still in the future, it’s too early to judge whether the video AI model ("Vo 3" / Google Veo) will have “destroyed Hollywood” as claimed.

Additionally, the notion that Hollywood is “done” is somewhat subjective and would be difficult to measure precisely even once the date arrives, but the primary reason we cannot evaluate this forecast yet is simply that the specified time horizon has not elapsed.

Chamath’s claim is explicitly long‑dated: that “over the coming years” essentially all major enterprise/business software will be rebuilt end‑to‑end using new AI‑enabled development toolchains, displacing the current generation of vertical SaaS and custom software.

As of November 30, 2025:

• AI development tools are being adopted very rapidly. GitHub Copilot and similar tools are now used by a large share of professional developers and enterprises. Gartner forecasts that by 2028, about 90% of enterprise software engineers will use AI code assistants, up from <14% in early 2024.(github.blog) Surveys also report that a majority of professional developers use AI tools regularly, and Copilot alone has tens of thousands of enterprise customers and millions of users.(secondtalent.com) This supports the direction of his thesis (AI deeply permeating the software development lifecycle).

• However, the existing SaaS and enterprise software base is still enormous and largely intact. The global SaaS market in 2025 is hundreds of billions of dollars and is projected to keep growing through 2030–2034, not to be wholesale displaced in the near term.(rss.globenewswire.com) There is no evidence that “essentially all” major enterprise systems have been or are imminently being rebuilt from scratch; instead, vendors are adding AI features, consolidating, or modernizing parts of their stacks rather than replacing everything soup‑to‑nuts.(timesofindia.indiatimes.com)

• Timeframe: we are only ~5 months past the June 21, 2025 episode. A prediction about “the entirety of the software that runs the world” being rebuilt “over the coming years” spans many years, not months. The horizon he implies (multi‑year global rebuild) is far beyond November 2025, so it is too early to say definitively whether this end‑state will or will not materialize.

Because (a) AI toolchain adoption is clearly underway in line with the spirit of the claim, but (b) the outcome he specifies—nearly all major enterprise/business software rebuilt end‑to‑end—concerns a much longer period than has elapsed, the prediction cannot yet be judged as either correct or incorrect.

Therefore the status as of November 30, 2025 is “inconclusive (too early to tell).”

The prediction is explicitly about "the coming decade" of performance dispersion within the S&P 493 between AI adopters and laggards. The podcast was released on 21 June 2025, and the current date is 30 November 2025—only a few months later. That is far too short a window to evaluate a decade‑scale claim about structural dispersion in equity returns and the resulting opportunity set for stock pickers. Even if early patterns (e.g., some AI‑exposed names outperforming) can be observed, they cannot yet be reliably attributed to the long‑run effect the prediction describes. Therefore, it is too early to determine whether this forecast is right or wrong.

As of November 30, 2025, there isn’t enough evidence to say that Chamath’s structural, long‑term call on traditional enterprise SaaS has clearly proven right or wrong.

Key points:

• Sector growth has slowed, but not collapsed. Large flagship SaaS vendors like Salesforce are still growing revenue in the high single‑ to low double‑digit range (around 7–10% YoY in recent quarters), even though that’s a clear deceleration from the mid‑teens or higher growth rates seen earlier in the 2020s. (reddit.com) This supports the “growth deceleration” part of his thesis but does not yet show that the business model has broadly failed.

• Investor returns and expectations are mixed. Salesforce, one of the emblematic cloud SaaS names, is down roughly 30% year‑to‑date in late 2025 and has modest returns over five years, underperforming the S&P 500, with forward revenue growth now expected to be <10% annually and valuation multiples compressed. (barrons.com) At the same time, Salesforce still guides to over $60B in revenue by 2030 and is executing large AI‑driven acquisitions like Informatica, signaling that markets do not view the category as “over” so much as repriced. (reuters.com) Cloud‑heavy vendors like Oracle are even guiding to higher cloud growth going forward. (wsj.com) So structural underperformance is not clearly established across the whole space.

• Public cloud/SaaS indexes show pressure but continued viability. The BVP Nasdaq Emerging Cloud Index (a proxy for public cloud/SaaS names) remains well above its 2018 base value (around 1,600–1,700 vs. 1,000 at inception), indicating that the segment is still meaningful. (indexes.nasdaqomx.com) It has had bouts of underperformance and drawdowns—Nasdaq’s March 2025 scorecard highlighted cloud and AI thematic indexes among the worst performers that month, with the cloud index down ~11.4%—but this is consistent with a repricing and rotation, not clear evidence that the “jig is totally up for software.” (nasdaq.com)

• Customers are experiencing tool fatigue and poor ROI. Surveys like Freshworks’ 2025 research show enterprises wasting roughly 20% of software budgets on unused tools, failed implementations, and hidden costs, with significant productivity loss and burnout due to software complexity and tool sprawl. More than half of businesses report that software investments aren’t delivering the expected ROI. (itpro.com) Other analyses quantify overlapping SaaS tools, unused licenses, and integration overhead, and explicitly argue for moving from “SaaS sprawl” to more consolidated, often AI‑driven, custom architectures. (medium.com) This supports the direction of Chamath’s critique (customers are tired of “yet another tool”).

• AI and agentic systems are surging, but mostly as overlays, not wholesale replacements. Enterprise adoption of AI agents and compound/agentic AI architectures is ramping quickly, and many forecasts expect strong ROI and rapid market growth through 2030. (en.wikipedia.org) However, in practice, much of this is happening inside existing SaaS platforms (e.g., Salesforce’s Agentforce and Data Cloud, or CRM‑style vendors adding copilots) rather than via enterprises replacing large swaths of SaaS with entirely custom-built AI software stacks. (marketwatch.com) That pattern is consistent with evolution and integration, not yet with the broad displacement implied by “the jig is totally up for software.”

• Structural claims need a longer horizon. Chamath was explicitly talking about a multi‑year structural shift driven by AI making it cheap to rebuild vertical software and by enterprises rejecting per‑seat/ever‑escalating license models. (metacast.app) Only about five months have passed since the June 21, 2025 episode; even where we see funding pressure and consolidation in enterprise applications (deal funding down modestly, more M&A, lower valuations), that is still early and influenced by macro conditions and the post‑2021 repricing as much as by AI‑driven custom solutions per se. (timesofindia.indiatimes.com) We do not yet have enough multi‑year data on ROE, sector‑wide returns, or actual replacement of SaaS by custom AI to decisively validate or falsify his structural forecast.

Putting these strands together: some elements of his narrative (slower growth, multiple compression, tool fatigue, rising AI/agent adoption) are clearly observable, but the stronger claim—that traditional enterprise SaaS as a whole will structurally underperform and be displaced by cheaper AI‑driven custom software—cannot reasonably be judged after only a few quarters. The available evidence is consistent with both “repricing and adaptation” and “early stages of eventual disruption,” so the prediction’s ultimate accuracy remains inconclusive at this time.

Only about five months have passed between the podcast release (21 June 2025) and the current date (30 November 2025), and the claim is explicitly framed as “over the long term”. That horizon is typically several years, so there hasn’t been enough time to decisively confirm or falsify the prediction.

Current evidence actually points the opposite way in the short run:

• Snowflake continues to center its business on consumption‑based pricing and is actively promoting guides and playbooks that advocate usage‑based models, not retreating from them. (snowflake.com)
• Independent writeups of Snowflake’s pricing in 2025 still describe the familiar pay‑for‑what‑you‑use model across compute and storage (credits per warehouse size, TB‑per‑month storage), rather than a shift to a fundamentally different structure. (blog.twingdata.com)
• Specific tweaks, like Snowpipe moving to a fixed credit amount per GB for ingestion, simplify billing but remain per‑usage; they don’t abandon the consumption framework. (docs.snowflake.com)
• Financially, Snowflake’s product revenue is still growing >20% annually with strong net‑revenue‑retention and repeated guidance beats in 2025, which suggests the model is economically viable so far, even if customers are more cost‑conscious and optimize usage. (reuters.com)
• There is no clear evidence of large‑scale customer migration from Snowflake to lower‑cost Postgres/Supabase‑style alternatives; if anything, we see Snowflake acquiring Crunchy Data to offer its own Postgres option and case studies of firms migrating to Snowflake from other platforms. (constellationr.com)

Given the explicitly long‑term nature of the prediction and the relatively short time elapsed, plus the lack of clear evidence either of mass migrations away from Snowflake or of its pricing model collapsing, the fairest assessment as of November 2025 is that the prediction’s truth value is still undetermined.

The prediction is framed on a decade-long horizon ("within roughly the next decade"). As of November 30, 2025, only about a year and a half has passed since the June 21, 2025 podcast release.

While there is active discussion and early evidence that AI may pressure some traditional IT services and outsourcing models, we cannot yet determine:

• whether “many” such rolled‑up IT services businesses will, in aggregate, actually lack terminal buyers, and
• whether exit values for private‑equity roll‑ups in those sectors will be structurally and durably depressed specifically because AI agents automate their value proposition.

Both of those require several years of M&A, IPO, and secondary transaction data across the sector, which simply do not exist yet for the 10‑year window implied. Therefore, the prediction’s outcome cannot be assessed this early, even directionally, beyond noting it as a plausible but unproven long‑term thesis.

It’s too early to evaluate this prediction.

• The prediction horizon is “roughly five years from now” relative to the podcast date of June 21, 2025, i.e., around mid‑2030.
• Today is November 30, 2025, only a few months after the prediction, so we don’t yet know Microsoft’s global employee count in 2030.
• Current public data only shows Microsoft’s workforce up to recent fiscal years (roughly in the 220,000–250,000 range, depending on year and layoffs), but nothing about the 2030 level yet.

Because the specified five‑year period has not elapsed, the prediction cannot yet be judged; hence the status is inconclusive (too early).

The prediction specifies a five‑year holding period starting from around the podcast date (June 21, 2025), implying an evaluation point near June 21, 2030. As of the current date (November 30, 2025), less than one year of that five‑year horizon has elapsed. Over such a short fraction of the intended period, any outperformance or underperformance of an equal‑weighted basket of AWS (if it were separable), Microsoft Azure, and Google Cloud Platform versus the broad market would not be a reliable indicator of the long‑term outcome. Because the prediction’s success condition is explicitly about returns over the full five years and we are far from that endpoint, it cannot yet be determined whether this basket will ultimately outperform the broad market to the degree implied by ‘you wouldn’t need to own anything else.’

Chamath was talking about the next GDP release for the current quarter they were discussing, i.e., the Q2 2025 advance estimate. In the episode he says he expects growth to come in “in the low threes” and possibly “low to mid threes” and that it will be “meaningfully greater than what people are expecting.”(podscripts.co)

The BEA’s official advance estimate for Q2 2025 real GDP, released July 30, 2025, showed 3.0% annualized growth, which fits squarely in his “low 3s” range.(bea.gov) Market/consensus expectations going into that release were around 2.4%, so the actual 3.0% print was indeed meaningfully above expectations, as contemporaneous reporting noted it “beat expectations of a 2.4% rise.”(tradingeconomics.com)

Later revisions moved Q2 growth up to 3.3% (second estimate) and 3.8% (third estimate), but those ex‑post revisions don’t contradict his core call that the upcoming print would be in the low‑to‑mid 3% range and above consensus; if anything, they reinforce that growth was strong.(legistorm.com) Given the advance estimate outcome and the expectation backdrop, this prediction is best classified as right.

Available data so far show a sizable boost to federal receipts from tariffs, but not yet the sustained $300–$400 billion per year above prior forecasts that Chamath described, and the longer‑run effect still depends on policy choices and trade flows that are not yet known.

1. What the official forecasts said before the tariff shock: The Congressional Budget Office (CBO) June 2024 baseline projected FY 2025 federal revenues of about $5.04 trillion, and its updated January 2025 outlook projected $5.2 trillion (17.1% of GDP).(epicforamerica.org) Those baselines largely pre‑dated the full scale of the 2025 Trump‑era tariff expansion.

2. What actually happened in FY 2025: Treasury data summarized by Reuters show that total federal receipts in FY 2025 were $5.235 trillion, only about $35 billion above CBO’s January 2025 forecast and roughly $200 billion above the older June 2024 forecast – well short of the extra $300–$400 billion per year that Chamath suggested.(reuters.com) Customs‑duty (tariff) revenues did jump sharply, hitting a record $195 billion in FY 2025, up $118 billion from the prior year, but that is still far below a $300–$400 billion increment on its own.(reuters.com)

3. What newer projections say about the future: After the new tariffs were in place, CBO released an updated analysis estimating that tariffs implemented in 2025 would reduce primary deficits by about $3.3 trillion and interest costs by another $0.7 trillion over 2025–2035, a total deficit reduction of roughly $4 trillion over 11 years.(americanbusinesstimes.com) That implies an average annual improvement on the order of $300–$360 billion versus the earlier baseline, largely via higher tariff receipts. Separately, press coverage notes that if current high tariff collections persist, annual tariff revenue alone could approach the mid‑hundreds of billions of dollars by 2026.(axios.com)

4. Why this is still unresolved: Chamath’s normalized claim is conditional and forward‑looking: that under the existing tariff regime, federal receipts will on an ongoing annual basis come in roughly $300–$400 billion above prior forecasts, assuming current tariff levels and trade balances persist. To fully validate or falsify that, we would need several years of realized data with those tariffs in place and stable trade patterns. As of late 2025, we have only one fiscal year of partial implementation (showing at most ≈$200 billion above older forecasts) plus CBO’s long‑term projections, which are themselves contingent and uncertain.

Because (a) realized receipts so far fall materially short of the stated $300–$400 billion per year gap, but (b) official forward projections now do roughly align with that magnitude if the tariffs endure, and (c) the prediction explicitly depends on assumptions about future policy and trade that have not yet been resolved, the evidence is not strong enough to call the prediction clearly right or clearly wrong. It remains too early and too assumption‑dependent to judge definitively, so the outcome is best characterized as inconclusive at this point.

Two key parts of Chamath’s scenario did not occur in reality:

1. No 100 bps Fed cut within 60 days of June 13, 2025
   The federal funds rate was held at 4.25–4.50% at the May 7, June 18, and July 30, 2025 FOMC meetings; there were no rate changes in that span. The first cut of 2025 was a 25 bp move on September 17, 2025, well after his 60‑day window (which ended August 12, 2025). (en.wikipedia.org)
   Since the Fed never cut 100 basis points in that period (or even cut at all during those 60 days), the trigger condition of his prediction failed.

2. No official $600 billion‑per‑year fiscal improvement reforecast in that window
   Chamath said that, given the rate cuts and tariff revenues, “in the next 60 days” the U.S. would “have to reforecast” the balance sheet to show about $600 billion per year in improvement ($300B more revenue from tariffs + $300B in annual interest savings).
   In reality, the main official fiscal baseline at that time was the CBO’s January 2025 Budget and Economic Outlook, released months before his June podcast; it already showed large, persistent deficits and rising debt, with no such $600B‑per‑year improvement. (americanactionforum.org)
   Later analysis from the Committee for a Responsible Federal Budget actually projected larger cumulative deficits over the next decade than CBO’s January baseline, not a big improvement, and also noted that CBO skipped its usual mid‑year 2025 update and would not issue another full outlook until 2026. (reuters.com)
   OMB’s Mid‑Session Review in September 2025—already outside his 60‑day window—did present a somewhat rosier long‑term path, but still in the context of trillion‑dollar annual deficits and without any discrete, officially labeled “+$600B per year” improvement from the combination of tariffs and lower interest costs. (crfb.org)

Given that:

• The Fed did not cut 100 bps (or at all) in the specified 60‑day period, and
• There was no official reforecast during that window showing the roughly $600B per year improvement he described,

the real‑world outcome does not match the scenario Chamath confidently laid out. On practical, forecast‑evaluation grounds, this prediction is best classified as wrong, rather than “ambiguous”: he clearly anticipated both a rapid, large Fed cut and an associated fiscal re‑scoring, and neither materialized in the timeframe he specified.

The prediction is explicitly conditional: Chamath says that if the U.S. secures roughly $600B in additional annual fiscal improvement from tariffs and the Fed cuts rates by 100 bps, then “every single risk dollar is going to run to America.” As of 30 November 2025, those preconditions have not occurred.

• Tariff‑revenue condition not met. Analyses of the 2025 tariff regime show U.S. customs duties reaching about $195B in FY 2025—up sharply from prior years but nowhere near a $600B incremental improvement. (finance.yahoo.com)
• Rate‑cut condition not met. The Fed held the funds rate at 4.25–4.50% through mid‑2025, then delivered two 25 bp cuts (September and October) to 3.75–4.00%, for a total easing of 50 bps, not 100 bps. (federalreserve.gov)
• Observed capital flows don’t match his described outcome either. In practice, 2025 has seen substantial rotations out of U.S. equities into Europe and emerging markets, and ex‑U.S. equity indexes have outperformed the U.S., the opposite of “forget Japan, forget Europe.” (reuters.com)

Because the specific policy mix he conditioned on (extra ~$600B in tariff revenue and a full 100 bp Fed cut) has not materialized, we cannot definitively evaluate whether his conditional claim about capital flows would have been right in that hypothetical scenario. Therefore, the correct classification is inconclusive rather than right or wrong.

• Condition mostly satisfied: Within days of the June 13, 2025 episode, Israel launched large airstrikes on Iran’s nuclear and military sites, triggering a 12‑day Iran–Israel war. The U.S. then directly entered the conflict on June 22 with “Operation Midnight Hammer,” striking three Iranian nuclear facilities; Iran retaliated with missile attacks on the U.S. Al Udeid Air Base in Qatar. Contemporary coverage explicitly described this as the U.S. entering the Israel–Iran war, a major shooting conflict involving the U.S. and key allies against Iran. (en.wikipedia.org)
• What happened to oil prices: Before Israel’s initial strike, Brent and WTI were trading in the high‑$60s/around $70 per barrel. After Israel’s and then U.S. strikes, prices spiked but did not come close to doubling: intraday peaks were roughly $78–$81 for Brent and about $77 for WTI, and by June 23 spot levels were about $77 (Brent) and $74 (WTI). By June 25, after the ceasefire took hold, Brent had already fallen back below $68 and WTI to about $65. (cnbc.com)
• Longer‑run prices: Through the rest of 2025, benchmark prices trended in the $60s, with recent Reuters and JPMorgan commentary putting Brent around $62–63 and WTI around $58, and forecasting averages well below $70, not near $100+. (reuters.com)
• Counterfactual scenarios didn’t materialize: Analysts did note that a closure of the Strait of Hormuz could have driven prices to $100–150, but Iran never actually closed the strait or significantly disrupted flows, so those scenarios remained hypothetical. (en.wikipedia.org)

Given that a short but substantial war involving Iran, Israel, and direct U.S. strikes did occur in the near term, yet oil prices rose only ~10–15% rather than roughly doubling to the $100–$112 range Chamath described, the realized outcome contradicts his stated magnitude. On that basis, the prediction is wrong.

According to the U.S. Bureau of Economic Analysis (BEA), real U.S. GDP in Q2 2025 (April–June) grew at an annualized rate of 3.8% in the third and final estimate. (bea.gov)

Chamath’s normalized prediction was that Q2 real GDP growth would be greater than 3.0% but less than 4.0% annualized. The realized 3.8% growth rate lies squarely within that 3–4% range and is clearly above 3.0% and below 4.0%.

While the advance estimate initially came in at 3.0% and was then revised to 3.3% and finally 3.8%, his prediction—interpreted as about the actual Q2 growth rate—matches the finalized BEA figure. (economics.td.com)

As of November 30, 2025, the key parts of Chamath’s prediction (“no commercially operating SMRs in the U.S. before roughly 2035” and “we’re still about a decade away”) concern outcomes in the 2030s, so they cannot yet be definitively judged.

Current facts:

• No small modular reactor is yet in commercial operation in the U.S. NuScale’s first-of-a-kind Carbon Free Power Project in Idaho, once targeted for 2029–2030 commercial operation, was terminated in 2023, pushing back what had been the leading candidate for an early U.S. SMR. (nuscalepower.com)
• Some U.S. projects are now aiming for the early 2030s, earlier than Chamath’s “2035+” claim if their schedules hold:
  • TVA’s BWRX‑300 SMR at Clinch River has a construction permit application under NRC review; with federal support, TVA has said commercial operation could be possible around 2033. (ans.org)
  • Dow and X‑energy’s Xe‑100 project in Seadrift, Texas, has submitted an NRC construction‑permit application and publicly describes a timeline of construction “later this decade” with startup “early next decade” (early 2030s). (corporate.dow.com)
  • Oklo continues to project its first Aurora SMR coming online around 2027–2028, which if achieved would be far earlier than 2035. (investors.com)
  • The U.S. Army’s Janus microreactor program targets an SMR‑class microreactor on a military base by about 2028, again implying potential sub‑2035 operation of small reactors, though in a defense rather than civilian‑utility context. (reuters.com)

These schedules challenge the pessimism of a strict “2035+ even if everything goes right” view, but they are still plans, not accomplished facts. Until at least one U.S. SMR actually reaches sustained commercial operation significantly before or after 2035, we cannot say with confidence that Chamath’s timeline is either correct or clearly wrong.

Because the forecasted period (early–mid 2030s) has not yet arrived and no U.S. commercial SMR is operating, the prediction is too early to conclusively verify or falsify.

It is too early to verify this prediction.

Chamath’s claim on 31 May 2025 was essentially: Starting from now, the fastest you could bring a newly initiated, unplanned U.S. natural-gas plant into commercial operation is about four years — i.e., sometime in 2029 or later.

To test that literally, we would need to observe at least one gas plant whose development began after the prediction (mid‑2025 or later) and then see whether it does or does not start operating before four years have passed (before mid‑2029). As of the current date (30 November 2025), no such project could possibly have reached commercial operation yet, because fewer than two years have elapsed since the prediction.

Available data on U.S. natural-gas plant development timelines (e.g., typical 2–3 years of construction plus often‑lengthy pre‑construction permitting and interconnection processes) describe historical averages, not realized outcomes for projects started after May 2025. Those historical figures don’t let us conclusively validate or falsify a forward‑looking lower bound about future projects started in 2025, especially given potential changes in regulation, supply chains, and grid interconnection queues after that date.

Because the four‑year window from the 2025 starting point (extending to 2029) has not yet elapsed, the prediction’s truth value cannot yet be observed in real-world outcomes, so it remains inconclusive rather than clearly right or wrong.

Chamath claimed that for the three mothballed but restartable U.S. nuclear reactors, the earliest realistic restart dates would be in the 2027–2030 range.

Evidence since then shows this is false:

• Palisades (Michigan), a shuttered commercial reactor regarded as the first U.S. attempt to restart a decommissioned plant, secured a $1.5+ billion DOE loan and state support with a publicly stated target of late 2025 for restart. This target was already on record well before and around the time of the May 31, 2025 podcast.(greatlakesnow.org)
• NRC approvals in July 2025 allowed Holtec to begin preparing Palisades for restart and loading fuel, with reporting that Holtec aimed to bring the plant back online in the fourth quarter of 2025.(reuters.com)
• Palisades’ status changed from decommissioned to online on August 27, 2025, enabling the plant to receive fuel and return to power production in 2025, not 2027 or later.(en.wikipedia.org)

For the other two prominent restart projects:

• Three Mile Island Unit 1 (Pennsylvania) is being financed with a DOE loan and is targeted to resume operations around 2027, matching the lower bound of Chamath’s window.(apnews.com)
• Duane Arnold Energy Center (Iowa), which shut in 2020, is now slated to be revived by 2029 under a NextEra–Google deal.(ft.com)

However, Chamath’s statement was about the earliest realistic restart for the three restartable mothballed reactors being 2027–2030. Because Palisades has in fact restarted (or is effectively back online) in 2025, and that 2025 timeline was already the working plan at the time of his prediction, the claim that 2027 was the earliest realistic restart is not borne out.

Therefore, the prediction is wrong.

The prediction deadline is December 31, 2025. Today is November 30, 2025, so there is still one month left for the 10-year and 30-year U.S. Treasury yields to potentially reach or exceed the levels Chamath specified (10-year > 5.0%, 30-year > 6.25%).

As of late November 2025, publicly reported market data shows:

• The 10-year U.S. Treasury yield is below 5%.
• The 30-year U.S. Treasury yield is below 6.25%.

These current levels mean the prediction has not yet come true, but because the target date has not passed, it could still become correct (or definitively wrong) by year‑end. Therefore, the only appropriate evaluation at this time is “inconclusive (too early)”.

Note: Once data for yields on or after December 31, 2025 is available, the prediction can be definitively scored as right or wrong based on whether those thresholds were ever exceeded by that date.

The condition for the prediction was effectively met:

• The One Big Beautiful Bill Act (OBBBA), the "big beautiful bill," passed the House on May 22, 2025, the Senate on July 1, 2025, and was signed into law on July 4, 2025.(en.wikipedia.org)
• CBO and independent estimates for both the House version and the enacted law show it raises, not lowers, deficits by roughly $2.8–3.4T over 2025–2034, i.e., there was no net “material fiscal tightening.”(reuters.com)

Chamath’s then-clause was that within 60–90 days of passage, bond markets would “react negatively” by demanding higher yields and/or showing clear stress in Treasury demand relative to prevailing long-term real/nominal rates (~5–5.5% on long bonds at the time).

What actually happened (July–early October 2025):

• Long-dated nominal yields were already near or above 5% before and around House passage and the Moody’s downgrade: the 30‑year hit about 5.15% on May 22 when the House first passed the bill.(webull.ca)
• Around enactment, monthly 30‑year yields were ~4.9%: May 4.90%, June 4.89%, July 4.92%. In the 60–90 days after signing (roughly Sept 2–Oct 2), the 30‑year averaged ~4.7–4.8%, slightly lower than the levels around passage (August 4.87%, September 4.74, October 4.64).(ycharts.com) There was no clear new spike above prior peaks; if anything, yields drifted modestly down from their May–July highs.
• A widely cited Reuters wrap on July 7 explicitly noted that the bond market’s reaction to final passage was “relatively muted” and that the expected deficit expansion from Trump’s agenda had "already been priced in"; investors were more focused on growth data and Fed policy than on the bill itself.(reuters.com)

Auction / demand stress evidence:

• There was a weak 20‑year auction and a sharp jump in long yields before final passage (May 21–22), reflecting concerns about fiscal policy and the Moody’s downgrade.(wsj.com) Those events predate the 60–90‑day post‑enactment window Chamath pointed to.
• Inside and around the window, the picture is mixed rather than clearly “crisis-like.” For example, an August 21 30‑year TIPS reopening cleared at a very high real yield of 2.65% (a 24‑year high) but with strong demand (bid‑to‑cover 2.78, yield stopping through when‑issued), which is the opposite of an impaired auction.(tipswatch.com)
• Some analyses in late September describe general auction strains (lower bid‑to‑cover, wider tails, waning foreign demand), but they tie this to the broader combination of heavy issuance, drained Fed reverse‑repo balances, and global fiscal worries—not to a discrete, new repricing of U.S. risk specifically in the 60–90 days after OBBBA’s enactment.(universalvalueadvisors.com) Other auctions (e.g., the September 10‑year note) actually showed strong demand and a stop‑through yield, again undercutting the notion of clear, generalized stress in that specific window.(streetinsider.com)

Putting this together:

• The bill did become law with overall fiscal loosening, so the condition trigger was satisfied.
• By 60–90 days after enactment, long-term yields were not meaningfully higher than at passage or the pre‑passage peak; they were marginally lower.
• Auction results in that interval show pockets of strain but also episodes of very strong demand, not an unambiguous negative repricing that would make it obvious “in the next 60 to 90 days” that markets had re‑underwritten U.S. fiscal risk at even higher required yields.

Given the time‑bound and directional nature of Chamath’s forecast (a distinct, clearly negative bond-market reaction after the bill became law), the realized data don’t match it. The structural fiscal concerns he highlighted are real and widely discussed, but the specific prediction about how and when bond markets would respond is not borne out by yields or auction behavior in that 60–90‑day window.

As of November 30, 2025 (about six months after the podcast), Google Search still opens with the familiar query box and a results page where AI Overviews and other AI features appear above or alongside traditional links, but not as a standalone, chat-style “AI Mode” default interface for most users. Google has expanded AI Overviews to 100+ countries and says they reach over 1–2 billion users monthly and now appear on a majority of U.S. queries, yet they are integrated into the classic results page and cannot be turned off, rather than replacing it entirely. (blog.google) AI Mode itself is an optional, more conversational experience (initially available only to a small percentage of U.S. users and later exposed as a tab/feature), and by mid‑2025 had around 100 million monthly active users in the U.S. and India—substantial, but still a minority of Google’s total search base and not the universal default “front door.” (theverge.com) Because the prediction’s deadline is May 2026 and we are only in November 2025, we cannot yet know whether Google will make this AI‑mode experience the default interface for a large share of users by that date, so the status of the prediction is currently too early to call.

Chamath’s on‑air statement in the May 17, 2025 episode explicitly promised: “We will be doing an event during the F1 in Las Vegas where we will be launching our poker tournaments… let us know late November, guys. Book it… you need to come November 22nd.”(podscripts.co)

The 2025 Las Vegas Grand Prix ran November 20–22, 2025.(en.wikipedia.org) During that same window the All‑In hosts did in fact tape at least one live podcast from Las Vegas – the episode “Epstein Files Fallout, Nvidia Risks…” is described in its own listings as having “Bestie intros LIVE from The Venetian Las Vegas,” with thanks to The Venetian for hosting, and a guest poker pro (Alan Keating) discussing poker strategy.(podcasts.apple.com) A subsequent episode with Molly Bloom is likewise billed as “Molly Bloom joins the besties live in Las Vegas!”(podcasts.apple.com) These confirm a live All‑In event in Vegas around F1, but they are presented publicly as podcast shows, not as All‑In‑run poker tournaments.

Critically, there is no public evidence that the group “launched [their] poker tournaments” or hosted an All‑In–branded poker tournament series during that F1 week. The official All‑In events page only lists an All‑In Holiday Party in San Francisco on December 6, 2025, with no Las Vegas poker tournament or series in late November.(allin.com) Coverage of the All‑In podcast’s commercial ventures through late 2025 similarly notes the launch of their tequila brand but does not mention any proprietary poker-tournament product or series.(en.wikipedia.org) Given (a) F1 Vegas 2025 has already taken place, (b) the only documented All‑In activity that weekend is a live show at The Venetian, and (c) the lack of any announcement or poker‑press coverage of an All‑In tournament launch, the specific prediction that they would host a poker event launching their own poker tournaments during the Las Vegas Grand Prix appears not to have come true.

At the time of the podcast (9 May 2025), the federal funds target range was 4.25–4.50%, where it had been held since the end of 2024 after cumulative 100 bps of cuts that brought it to that level.(federalreserve.gov) Chamath’s normalized prediction was that the Fed would not cut rates below this 4.25–4.50% range through at least the 2026 U.S. midterms. However, the Fed cut the target range to 4.00–4.25% at its September 2025 meeting and then further to 3.75–4.00% at the October 29, 2025 meeting, clearly moving below the 4.25–4.50% band.(tradingeconomics.com) Multiple summaries of current policy state that as of November 2025 the target range remains 3.75–4.00%.(sezarroverseas.com) Because the Fed did in fact cut below 4.25–4.50% well before the 2026 midterms, the prediction is already falsified.

The prediction explicitly concerns long‑run outcomes "in ten and 15 and 20 years" after the point of reduced investment capital, i.e., roughly in the 2035–2045 window. The episode itself is dated May 9, 2025, so as of today (November 30, 2025) at most about half a year has elapsed since the prediction was made, far short of the 10–20 year horizon.(allin.onpodcastai.com)

Because the claim is about whether China and Canada will ultimately stagnate and become “also‑ran” economies relative to more investment‑rich peers, there is not yet enough elapsed time or data to determine whether that long‑term scenario will materialize. We also cannot yet know whether the antecedent condition (persistently depressed risk capital over a decade or more) will actually hold.

Given the time frame and conditional nature of the claim, the correct status as of 2025‑11‑30 is "inconclusive (too early to tell)."

The prediction window is explicitly nine months after the May 2025 discussion, i.e. roughly until February 2026. The claims to evaluate by that time are:

1. New trade deals under Trump’s trade policy will have been concluded.
2. There will NOT be a significant shrinkage in foreign direct investment (FDI) into the U.S. or domestic investment due to policy uncertainty.
3. The U.S. economy will “end up in a good spot” after iterating through the new tariff/trade framework.

Today’s date is November 30, 2025, which is about six to seven months after the May 2025 discussion and before the February 2026 horizon the predictor set.

Because the predictor explicitly said this should be judged in nine months and that date has not yet arrived, it is too early to decisively determine whether the full prediction is right or wrong. Therefore the correct classification, as of now, is “inconclusive (too early)”.

The prediction concerns whether Apple will fail to move assembly of all iPhones destined for the US from China to India by the end of 2026 (an 18‑month timeline from the April 2025 reporting).

Multiple reports in late April 2025 (e.g., Financial Times summaries via MacRumors, Business Standard, The Guardian) state that Apple’s goal is to assemble all US‑bound iPhones in India by the end of 2026, but they describe this as a future target, not an already-achieved shift. (macrumors.com) As of mid‑2025, Apple is rapidly ramping up Indian production and exports to the US, but is still only part‑way there, with China remaining a major manufacturing base. (reuters.com)

However, the evaluation date here is November 30, 2025, while the prediction’s deadline is end of 2026. There are still about 13 months remaining before that deadline, so we cannot yet know whether Apple will ultimately meet or miss the target. Therefore, the prediction’s truth value cannot be determined yet, making it too early to judge.

The prediction explicitly concerns a 20–30 year period starting around 2025, claiming India will have a prolonged high‑growth phase comparable in impact to China’s 2003–2012 boom and become a major global manufacturing engine. As of November 2025, less than one year of that window has elapsed, so the long‑run claim cannot yet be verified or falsified.

Available data show that India is currently the fastest‑growing major economy, with recent and projected real GDP growth around 6.5–8% per year, according to the IMF’s Article IV reports and World Economic Outlook updates.(imf.org) India has also been expanding manufacturing and exports, supported by government schemes like production‑linked incentives and rising FDI, and is now roughly the fifth‑largest manufacturer globally.(ibef.org) However, its share of global manufacturing is still only about 2.8–3.2%, versus roughly 29% for China, far from the dominance China achieved.(ndtvprofit.com)

India does enjoy a substantial labor‑cost advantage over China—manufacturing labor is on the order of $1.4/hour versus about $7/hour in China, and roughly a small fraction of U.S. manufacturing wages—supporting one premise of Chamath’s argument about cost competitiveness.(refteck.com) But whether this advantage will translate into a China‑style, multi‑decade manufacturing‑led boom comparable in impact to China’s 2003–2012 surge can only be assessed many years from now. Given the very early stage relative to the stated 20–30 year horizon, the prediction is too early to call.

As of November 30, 2025, Tesla has launched a limited “Robotaxi” ride‑hailing service in Austin using a small fleet of Model Y vehicles, but all rides still involve a Tesla employee acting as a safety monitor in the front seat, and similar pilot services or tests elsewhere also continue to require human safety personnel. These services are geofenced, closely supervised, and not yet fully driverless commercial robotaxis available broadly to the public. (en.wikipedia.org)

The normalized prediction says Tesla will be operating real robotaxi services—vehicles driving themselves without active human drivers, offered commercially to the public—within roughly two years of the April 26, 2025 conversation, i.e., by around April 2027. Since it is still late 2025 and that deadline has not yet arrived, there is not enough information to determine whether the prediction will ultimately be correct or incorrect. Therefore, its status is inconclusive (too early to tell).

By November 30, 2025, there is substantial evidence both that U.S. export controls have constrained China’s AI hardware and that China’s frontier AI capabilities have nonetheless reached near parity with the West, making the prediction impossible to score cleanly as right or wrong.

1. The condition of continued restricted access is largely met
Since 2022–2023, the U.S. has barred or tightly licensed exports of Nvidia’s leading data‑center GPUs (A100, H100, A800, H800, H20, L40/L40S, etc.) and expanded controls on advanced semiconductor manufacturing equipment to China. (stblaw.com) These controls remain broadly in force through 2025, with only prospective discussion of loosening some sales (e.g., H200) still under consideration. (reuters.com) So the conditional premise—China lacking straightforward access to Nvidia’s top-tier chips and U.S. leading-edge fab tools for multiple years—is essentially true.

2. Evidence that China has been materially “slowed down”

• Compute share collapse: One 2025 analysis using Epoch AI data finds that, as of March 2025, the U.S. controls about 75% of global AI compute capacity, while China’s share fell from 37.3% in March 2022 to 14.1%—a sharp relative decline aligned in time with U.S. export controls. (research.contrary.com)
• Bottlenecks acknowledged by Chinese and U.S. officials: The same report notes Chinese leaders and firms openly describe bans on advanced chips as their key constraint, and that deployment (inference) at scale is hampered—e.g., DeepSeek limiting API access soon after launching its R1 model, and Tencent warning that chip shortages could severely limit nationwide AI adoption or drive up costs. (research.contrary.com) Separately, a U.S. export‑control official estimated Huawei would be able to produce no more than about 200,000 advanced AI chips in 2025—insufficient for domestic demand—underscoring a real hardware shortfall despite Huawei’s Ascend line. (reuters.com)
  These points support Chamath’s intuition that the missing U.S. technology “slows them down quite a bit,” at least in terms of available compute and ease of scaling.

3. Evidence that frontier AI capabilities have not been strongly held back
On the other hand, multiple independent indicators show Chinese models closing the capability gap quickly:

• A detailed 2025 export‑controls review finds that despite the U.S. holding roughly 5× more compute, the performance gap between top U.S. and Chinese LLMs shrank from double‑digit margins in 2023 to near parity in 2024. (research.contrary.com)
• Chinese LLMs have reached or exceeded top global benchmarks:
  • Alibaba’s open‑source Qwen 2.5‑72B topped the OpenCompass LLM leaderboard, surpassing closed‑source state‑of‑the‑art models such as GPT‑4o and Claude 3.5 on many metrics. (alibabacloud.com)
  • Qwen2.5‑Max entered the Chatbot Arena global top‑10 and ranked #1 in math and coding and #2 on hard prompts in early 2025. (en.people.cn)
  • On Hugging Face’s Open LLM leaderboard, all top‑10 open-source models were derivatives of Alibaba’s Qwen series; Qwen2.5‑1.5B‑Instruct became the single most downloaded open‑source model globally, highlighting massive adoption and competitive quality. (aibase.com)
• Journalistic and policy analyses (e.g., Time and Foreign Policy) stress that China has advanced in AI despite chip controls, citing workarounds such as stockpiling and smuggling Nvidia GPUs, offshore training on Nvidia hardware in Southeast Asian data centers, and rapid improvement of domestic chips like Huawei’s Ascend series. (time.com) One 2025 Foreign Policy piece concludes that export controls "have neither failed nor worked as well as hoped," since Chinese frontier models like DeepSeek V3 and R1 were only months behind U.S. models when released. (foreignpolicy.com)
• Nvidia‑linked commentary similarly argues that specific bans (e.g., on the H20) did not stop China’s AI progress, contending instead that they mainly hurt U.S. industry, even while some experts still defend them as strategically useful. (tomshardware.com)

These results imply that, while China’s scale and cost of deployment are hurt by hardware constraints, its frontier model capabilities have continued to improve rapidly and, on some benchmarks, match or beat Western systems.

4. Why this is ultimately ambiguous rather than clearly right or wrong
Chamath’s claim is qualitative: that lack of access to leading‑edge U.S. manufacturing tech and Nvidia’s top chips would "slow [China] down quite a bit" over multiple years. By late 2025:

• There is strong evidence of a significant compute and scaling slowdown (loss of compute share, acknowledged chip bottlenecks, deployment constraints), which supports his view. (research.contrary.com)
• There is equally strong evidence that headline AI capabilities have not been slowed to the same degree, with Chinese frontier models arriving within months of U.S. releases and achieving top rankings on major leaderboards, despite the hardware gap and controls. (alibabacloud.com)

Because “slowed down quite a bit” could reasonably be judged true if one focuses on compute and deployment, or false if one focuses on frontier model quality and timing, the available data support both interpretations. The subjective, non‑quantitative nature of the prediction and the mixed empirical record make it impossible to classify it as clearly right or clearly wrong. Therefore the fairest score is ambiguous.

Available data so far do not confirm Chamath’s scenario, but the specific post‑tightening period he referenced is only just beginning and is not yet fully measured.

1. Federal spending and “budget tightening”
   DOGE was created in January 2025 to cut federal spending, but its claimed savings have been heavily disputed; independent analyses and congressional investigations suggest many cuts were either overstated or offset by other costs.(en.wikipedia.org) At the aggregate level, FY 2025 federal outlays increased about 4% to a record $7.01 trillion, with the deficit edging down only slightly (from $1.817T to $1.775T), largely due to higher tariff revenues and very deep but narrow cuts to education, rather than broad fiscal tightening.(reuters.com) That is not the large, across‑the‑board spending clamp‑down (removing 1–1.5 percentage points of GDP) implied in the prediction.

2. What official GDP data show so far
   The BEA’s 2025 Q2 release (which also revised Q1) shows real GDP fell at a -0.6% annualized rate in Q1 2025 but then rose +3.8% in Q2.(bea.gov) That rules out a technical recession in the usual “two consecutive negative quarters” sense for the first half of 2025. Analysts and BEA commentary attribute the Q1 drop primarily to a tariff‑driven surge in imports and weaker consumer spending, not to the belated recognition of prior “wasteful” government spending.(reuters.com) Crucially, the BEA’s preferred proxy for underlying private demand—real final sales to private domestic purchasers—grew 1.9% in Q1 and 2.9% in Q2, indicating the private economy excluding government and trade has not been in recession.(bea.gov) No official data series or revision has identified the 1.0–1.5 percentage point “government waste” component of GDP that Chamath forecast.

3. No official recession call yet
   The NBER’s Business Cycle Dating Committee, which provides the standard retrospective judgment on U.S. recessions, has not declared any new recession after the April 2020 trough; its published chronology still lists that as the most recent turning point.(nber.org) So there is currently no official recognition of a 2025 recession, let alone one explicitly described as existing “independent of the tariffs” or driven by removal of government‑spending distortions.

4. Timing and missing later‑quarter data
   Major Trump‑era budget bills (such as the One Big Beautiful Bill Act and the Rescissions Act) were only signed in July 2025, so any post‑tightening effects would mainly show up starting in Q3 2025 and beyond.(en.wikipedia.org) However, because of the October–November 2025 government shutdown, the BEA canceled the advance and second estimates of Q3 GDP and has not yet released revised dates.(reuters.com) That means we literally do not yet have official GDP data for the first full quarter after the main budget tightening package took effect, let alone for the “few quarters” Chamath referenced.

Taken together: (a) current data contradict the idea that stripping out government spending reveals an already‑existing private‑sector recession in early 2025, and (b) the key period after mid‑2025 budget tightening is only beginning and partly unmeasured. Because the horizon of the prediction has not fully elapsed and essential later‑quarter figures are missing, it is too early to say definitively whether his forecast will prove right or wrong. Hence the status is best classified as inconclusive at this time.

By 30 November 2025, Chamath’s Mar‑a‑Lago/Bretton Woods 2.0 scenario has not materialized as he described, but Trump’s tariff policy is still unfolding and retains some features that partially match his thesis, so it’s too early to give a definitive right/wrong verdict.

What has actually happened so far

• Massive, durable tariff regime rather than a completed new system. On 2 April 2025 (“Liberation Day”), Trump imposed a baseline 10% tariff on essentially all U.S. imports plus country‑specific “reciprocal” tariffs of 11–50% on major trading partners, framed as correcting foreign trade barriers. (en.wikipedia.org) After several months of talks, a July 31 executive order locked in new long‑run “reciprocal” tariffs of 10–41% on 69 partners, raising the average effective U.S. tariff rate to about 18.6%—the highest since 1933. (cambridge.org) That looks more like institutionalized protectionism than temporary leverage that disappears once a grand bargain is struck.

• Mar‑a‑Lago Accord exists only as a proposed blueprint, not a realized Bretton Woods‑style order. The “Mar‑a‑Lago Accord” is an internal Trump‑administration initiative and intellectual framework—a plan to use tariffs, currency and capital measures, and security‑linked trade deals to restructure global trade and the dollar system, explicitly drawing inspiration from Bretton Woods and the Plaza Accord. But as of early–mid 2025 it “has not been implemented and remains in the earliest stages of negotiation,” with its success described as highly uncertain. (en.wikipedia.org) Foreign‑policy analyses even deride the concept as “QAnon for tariffs,” underscoring skepticism that it will ever cohere into a true Bretton Woods‑type regime. (en.wikipedia.org) There is no evidence of a signed, multilateral “Mar‑a‑Lago Accords” treaty or a new set of global monetary institutions analogous to the IMF/World Bank system.

• Tariffs have brought countries to the table and produced more explicitly reciprocal deals. This is the part of Chamath’s forecast that is playing out. Facing steep U.S. tariffs, several partners have negotiated “reciprocal, fair, and balanced” frameworks:

  • With the EU, a July 27, 2025 Framework Agreement on Reciprocal, Fair, and Balanced Trade caps U.S. tariffs on EU goods at 15% while eliminating EU tariffs on U.S. industrial goods and granting extra access for U.S. farm and energy exports—explicitly framed around reciprocity. (en.wikipedia.org)
  • With Japan, a major 2025 deal cuts U.S. tariffs on Japanese imports from 35% (Liberation Day levels) to a still‑high 15%, while also eliminating some earlier sector‑specific duties—again, a negotiation visibly triggered by the tariff shock. (us.ibfd.org)
  • Parallel frameworks or negotiations with Vietnam, Thailand, and others likewise condition lower U.S. tariffs on partner commitments to open markets further and align with U.S. security and economic priorities. (jdsupra.com)

• Global system looks more fragmented and conflictual than Bretton‑Woods‑like. The IMF and World Bank warn that Trump’s broad tariffs are already dragging on global growth and accelerating trade fragmentation rather than ushering in a stable new monetary/trade order. (reuters.com) Academic and policy analyses emphasize that the U.S. is stretching existing legal authorities and violating multilateral commitments, not building a consensual successor system. (cambridge.org)

Why this is rated inconclusive

Chamath’s prediction has two core components:

1. Mechanism: tariffs would be used as leverage to drag other countries to the table and force more reciprocal access.
2. End state: this process would culminate in a new, Bretton Woods–style international framework—the Mar‑a‑Lago Accords—rather than leaving high tariffs in place.

Evidence to date supports (1): the Liberation Day tariffs clearly prompted a series of “reciprocal, fair and balanced” bilateral and regional deals in which partners concede market‑access changes under U.S. pressure.

But there is no sign yet that (2) has been achieved. The Mar‑a‑Lago Accord remains a contested, largely domestic blueprint with no implemented global currency agreement or institutional architecture; high tariffs have been broadly locked in, not mostly unwound. At the same time, Trump’s second term is still in its early years, and much of the Mar‑a‑Lago concept explicitly envisions a multi‑year diplomatic process.

Because the strategy is still playing out and a definitive “Bretton Woods 2.0”–style settlement has neither clearly emerged nor been definitively foreclosed, the fairest assessment as of November 2025 is that the prediction’s ultimate success or failure remains inconclusive.

The prediction concerns an action to be taken for a 2026 event (Chamath Palihapitiya personally hand‑delivering Jason Calacanis’s invitation). As of today’s date (2025-11-30), that future event and the associated invitation process have not yet occurred, so the outcome cannot be evaluated. A web search for coverage of this specific promise and any later confirmation or denial returned no relevant results, which is consistent with it being about a future year and a private action. Because the deadline (sometime in 2026) has not yet passed, it is too early to determine whether the prediction is right or wrong.

Available data on U.S. 10‑year Treasury auctions after the April 2, 2025 “Liberation Day” tariff announcement show that new 10‑year notes consistently cleared in the low‑to‑mid‑4% range, not near 5%.

• The Liberation Day tariff package on April 2, 2025 materially shook markets and pushed 10‑year yields from roughly 4.2% to over 4.5% in the days immediately afterward, raising fears that long‑term rates could move much higher. (jpmorgan.com)

• A consolidated calendar of 10‑year note auctions for 2025 shows the actual award yields for the auctions immediately following the tariffs and the podcast (which aired April 5, 2025):

  • Apr 9, 2025: 4.435%
  • May 6, 2025: 4.342%
  • Jun 11, 2025: 4.421%
  • Jul 9, 2025: 4.362%
  • Aug 6, 2025: 4.255%
  • Sep 10, 2025: 4.033%
  • Oct 8, 2025: 4.117%
  • Nov 12, 2025: 4.074%

  All of these are between about 4.0% and 4.44%, and none are close to 5%. (moneycontrol.com)

• Independent news reports on specific auctions confirm these levels: Reuters reports the April 9 auction clearing at 4.435%; CNBC and Bloomberg cite 4.342% for the May 6 auction; Barron’s notes 4.421% for the June auction and 4.362% for the July 9 auction, all reinforcing that issuance was consistently in the low‑4s. (reuters.com)

• Even when market yields “soared” later in 2025, commentary described the 10‑year yield reaching roughly 4.6%, still well below 5% and consistent with auction outcomes staying in the 4‑something range. (investopedia.com)

Chamath’s normalized prediction was that, in the near term following the tariff announcement, 10‑year Treasury auctions would clear at around 4% rather than drifting up toward 5%, giving governments materially lower funding costs. The realized auction yields over the subsequent months were solidly in the low‑4% band and never approached 5%, delivering meaningfully cheaper financing than a 5% handle would have implied.

Given this, the prediction that upcoming 10‑year auctions would clear “around 4%” and not near 5% is supported by the data, so it is best classified as right.

Chamath’s prediction about CDS was made on the All‑In “2025 Predictions” episode, where he said he would be long credit default swaps as insurance and added: “I hope that this trade loses money, but if it hits, it will be the best performing asset of 2025.”(podscripts.co) In the April 5, 2025 episode you cited, he revisits this and notes that the trade has already “hit” in the sense that CDS spreads blew out, implying that for every $1 million premium on $1 billion of risk, the mark‑to‑market profit would be about $7 million over roughly three months.(24vids.com) However, public reporting on 2025 credit markets describes widening spreads and increased use of CDS hedges around tariffs and recession fears, not a single clear, headline “major corporate default event” that triggered large CDS payout settlements in the way his conditional scenario implied.(reuters.com) Moreover, as of November 30, 2025, the calendar year is not over, so we cannot yet definitively rank any strategy as the best‑performing asset of 2025, especially versus volatile assets like cryptocurrencies or small‑cap equities whose full‑year returns are still in flux.(exchange-rates.org) Finally, Chamath has never publicly specified the exact CDS instruments (reference entities, maturities, or size), which means even after year‑end it may not be possible from public data alone to verify whether that particular position outperformed every other major investable asset or trade on a percentage basis.(podscripts.co) For these reasons—both because 2025 has not yet concluded and because the necessary position details aren’t disclosed—the prediction cannot currently be judged right or wrong.

Evidence shows that Signalgate did not fade from public and media attention within ~2–3 weeks of the leak; instead, it remained an active national‑security and political story for months.

Key points:

• The Signal leak was first widely publicized when Jeffrey Goldberg’s article in The Atlantic came out on 24–26 March 2025, with major outlets like The Guardian still describing the controversy as ongoing on 28 March ("continues through a fourth day"). Chamath’s prediction on 29 March therefore implied that by roughly mid‑April the matter would be largely forgotten. (theguardian.com)
• Well beyond that 2–3 week window, the Pentagon inspector general formally opened an investigation into Defense Secretary Pete Hegseth’s use of Signal, reported by multiple outlets on 3 April 2025, and InsideDefense published the IG’s notification letter the same day—coverage that treats Signalgate as a live, serious scandal, not something already forgotten. (theguardian.com)
• On 22 April 2025 (about three and a half weeks after the leak), watchdog group American Oversight filed a motion for a preliminary injunction in its Signalgate lawsuit, seeking emergency court orders to preserve Signal records—again generating fresh, national‑level coverage well past the predicted attention window. (americanoversight.org)
• The story continued into the summer: a detailed Washington Post piece on 6 June 2025 covered the ongoing inspector‑general inquiry, and another on 23 July reported that Hegseth’s Signal messages drew on an email marked “SECRET/NOFORN,” directly contradicting administration denials. These are prominent, months‑later stories indicating sustained media interest. (washingtonpost.com)
• The episode has enduring visibility: it is documented in multiple up‑to‑date encyclopedia entries (English "United States government group chat leaks," German "Signalgate‑Affäre," Chinese and French pages), all treating Signalgate as a named, notable scandal of Trump’s second term—evidence that it was not quickly forgotten even in the longer run. (en.wikipedia.org)

Because Signalgate remained under investigation, in court, and in major media coverage for months after late March 2025, the prediction that it would be largely forgotten within roughly two Scaramuccis (about 2–3 weeks) is best judged as wrong.

Evidence since Trump’s January 20, 2025 inauguration shows a clear, administration‑linked jump in tech‑sector M&A relative to the late‑Biden period.

1. Regulatory shift under Trump vs. Biden

   • Biden’s 2021 Executive Order 14036 explicitly pushed a “whole‑of‑government” crackdown on corporate concentration, especially in tech, and he installed Lina Khan at the FTC to pursue an aggressive antitrust agenda, including actions against Amazon, Meta and other large platforms. (en.wikipedia.org)
   • Khan left office in January 2025, replaced by Trump’s appointee Andrew Ferguson, who campaigned on ending a “war on mergers,” while House Republicans moved to strip the FTC of much of its antitrust role—both clear signals of a more permissive stance toward consolidation. (theguardian.com)
   • A Wall Street Journal analysis reports that in 2025, under Trump’s new team, U.S. regulators have challenged only three mergers, versus an average of six per year under Biden, and describes corporate dealmaking as having “surged” in response to the looser enforcement. (wsj.com)

2. Tech M&A levels under Biden (baseline)

   • After the record 2021 boom, global M&A slumped in 2022–2023 and only partially recovered in 2024. PwC and Bain both characterize 2024 as a rebound year but still below the 2021 peak. (bain.com)
   • In 2024 specifically, technology was already the leading sector, with tech M&A deal value around $500–640 billion globally (depending on dataset), up roughly 16–32% versus 2023, but volumes were weak and tech deal counts fell sharply. (alliuris.org)
     This provides a meaningful, but relatively constrained, “late‑Biden” baseline for tech deal activity.

3. Tech and software M&A under Trump in 2025

   • LSEG data for the first nine months of 2025 show the tech sector leading global M&A with US$595.5 billion in deals, up 55% from the same period in 2024. (investmentexecutive.com)
   • Kroll’s software‑sector update reports that in Q1 2025 there were 714 software deals, a 36% increase over Q1 2024, with deal value up 23% year‑on‑year, and highlights Google’s US$32 billion acquisition of Wiz as emblematic of large strategic tech transactions. (kroll.com)
   • RBC Capital Markets notes that software M&A activity in 2025 is up 78% year‑on‑year, with private‑equity‑backed software deals more than doubling, driven by depressed SaaS valuations and aggressive buyers. (businessinsider.com)

4. Broader dealmaking surge tied to new administration

   • EY‑Parthenon’s U.S. Deal Barometer finds that in 2025, U.S. corporate M&A volume is up about 10%, and overall deal value 36% versus 2024, with technology listed among the most active sectors driving large transactions. (ey.com)
   • The Wall Street Journal likewise reports a more than 40% year‑over‑year rise in total U.S. deal value to US$1.9 trillion in 2025, with twice as many $10B+ megadeals, and explicitly attributes this to Trump’s more lenient antitrust enforcement that is “more tolerant” of consolidation in media and tech. (wsj.com)

5. Assessment vs. Chamath’s prediction
   Chamath’s normalized claim was that under the new Trump administration, tech and large companies would become much more aggressive on M&A, producing a clear increase in tech M&A versus the prior Democratic administration.

   • Empirically, tech and software M&A deal values in 2025 are up on the order of 50–80% versus 2024, after adjusting for the same period, and tech remains the leading sector for global deals. (investmentexecutive.com)
   • Multiple independent sources (EY‑Parthenon, BCG, LSEG, WSJ) describe a broad, administration‑linked M&A boom, with technology singled out as one of the main drivers and a more permissive U.S. antitrust regime explicitly cited as an enabler. (ey.com)

   While 2021 under Biden was itself an exceptional record year for global TMT activity, the relevant comparison for “the coming period” after Trump takes office is the late‑Biden environment (2022–2024), which featured significantly lower tech M&A intensity and stricter enforcement. Against that baseline, the post‑inauguration data show exactly the kind of sharp, tech‑heavy rebound in dealmaking Chamath described.

   On balance, the observed 2025 surge in tech and software M&A and the clear softening of antitrust enforcement under Trump support judging his prediction as right in direction and in its claim of a clear increase in tech M&A activity.

As of November 30, 2025, the full 2025–2026 horizon hasn’t played out, so the prediction can’t be definitively scored.

On the pace of rate cuts:

• In December 2024 and again in March 2025, the Fed’s “dot plot” projected two 25 bp cuts in 2025 and two in 2026, taking the funds rate to about 3.9% at end‑2025 and 3.4% at end‑2026. (cnbc.com)
• Through July 2025, the Fed held rates steady at 4.25–4.50% at every meeting, despite projecting two cuts later in the year. (cnbc.com) The first cut of 2025 was only in October (25 bp), and markets expect another in December and possibly one more in January 2026. (reuters.com) This is a relatively slow, back‑loaded easing path versus many early‑2025 market hopes for faster cuts. (forbes.com)
• By June 2025, the Fed revised its projections, still penciling in two cuts in 2025 but reducing expected cuts in 2026 and 2027 to just one each, explicitly “slowing the pace of cuts” in those years versus prior guidance (two in 2026 and two in 2027). (cnbc.com) In September 2025, the Fed’s projections showed only one cut in 2026, which media described as more conservative than markets had expected. (cnbc.com)

These developments are directionally consistent with Chamath’s claim that an over‑correction would result in a slower‑than‑previously‑anticipated cutting path, especially for 2026. But 2026 policy is still only a forecast; the actual pace of cuts next year could end up faster if political or economic pressures intensify. (reuters.com)

On “increased economic pressures” (weaker growth / higher stress):

• The Fed’s June 2025 projections downgraded real GDP growth to 1.4% for 2025 and 1.6% for 2026, while raising PCE inflation to about 3.0% for 2025 and 2.4% for 2026—more stagflationary than the March projections. (tradingeconomics.com) NABE’s November 2025 survey similarly sees only modest 2.0% growth in 2026 with inflation still elevated. (reuters.com)
• Unemployment has risen to about 4.4% (a four‑year high), and Treasury Secretary Scott Bessent notes that housing and other rate‑sensitive sectors are under pressure, while consumer sentiment has fallen to a three‑year low. (nypost.com) Fed Governor Miran explicitly links the rise in unemployment to overly tight monetary policy and argues for faster and larger rate cuts. (reuters.com) These fit the idea of “pressure in the economy,” though causation is shared with tariffs, immigration policy, and a long government shutdown, not just Fed policy. (tradingeconomics.com)
• However, broad financial stress remains limited so far. The Chicago Fed’s National Financial Conditions Index is around –0.53 (negative values = looser‑than‑average conditions), indicating overall easy financial conditions rather than tight stress. (chicagofed.org) The St. Louis Fed’s Financial Stress Index has recently moved modestly above zero (~0.55), higher than the very calm levels of 2023–24 but far below crisis readings in 2008 or 2020. (wolfstreet.com)

Why the verdict is inconclusive:

• The core of the prediction explicitly covers 2025–2026, and we are only at late 2025. The Fed has already slowed its projected pace of cuts for 2026 and the economy is showing some strain (slower growth, higher unemployment, sectoral stress), which partially supports his thesis. (cnbc.com)
• Yet we do not know how many cuts will actually occur in 2026 or how severe economic and financial stress will ultimately be. Projections could be overtaken by events, including potential politically driven “sugar‑rush” easing that would speed up cuts rather than slow them. (reuters.com)

Because a substantial part of the forecast concerns policy actions and economic outcomes in 2026, which has not yet occurred, the most defensible assessment is that the prediction’s truth value is still unresolved.

Howard Lutnick, serving as Commerce Secretary in Trump’s second term, publicly said Trump’s goal was no federal tax for anyone making under $150,000, and media coverage described this as an aspirational tax plan, not an enacted policy. (newsweek.com)

However, the major tax legislation actually passed under the new Trump administration so far is the One Big Beautiful Bill Act (OBBBA), signed July 4, 2025. That law extends and tweaks the existing individual income tax system (originally set by the 2017 Tax Cuts and Jobs Act), adds targeted deductions (e.g., for tips, overtime, some car-loan interest, and certain seniors), but it does not set the federal income tax rate to 0 percent for people earning $150,000 or less. (en.wikipedia.org)

The IRS rate schedules for the 2025 tax year still show positive marginal income-tax rates starting at 10 percent, with higher brackets above that, and the IRS’s released brackets for 2026 likewise remain a normal progressive system; there is no blanket 0 percent federal income tax rate for all taxpayers at or below $150,000 in any filing status. (en.wikipedia.org)

Because, as of November 30, 2025, no law or regulation has been implemented that actually reduces federal income tax to 0 percent for all U.S. taxpayers earning $150,000 per year or less, the prediction that such a Trump tax plan would be implemented as described is wrong.

As of November 30, 2025, the large nationwide housing crash Chamath described has not occurred, but his time horizon (“the next phase of the cycle”) is vague enough that it could still play out in coming years.

Key facts:

• U.S. homeowners currently sit on roughly $34–36 trillion in home equity, an all‑time or near‑all‑time high, according to Federal Reserve–based estimates and industry analyses. One summary notes home equity at over $35 trillion as of March 2025, another puts it at about $34.5 trillion in 2025, and a Mortgage Bankers Association forecast says homeowners have accumulated about $36 trillion in equity. (en.wikipedia.org)
• For homeowners with mortgages (a subset of all homeowners), total net equity in Q2 2025 was about $17.5 trillion, with equity down only 0.8% year‑over‑year—a reduction of about $141.5 billion, not “trillions.” (themortgagepoint.com)
• National home‑price indexes show slowing growth and some real (inflation‑adjusted) erosion, but not a major nominal crash. The S&P CoreLogic Case‑Shiller National Index reported a 3.4% year‑over‑year gain in March 2025, and later data show prices still up about 1.3–1.5% year‑over‑year by late summer/early fall 2025, even though that growth now lags inflation. (spglobal.com)
• FHFA’s own house‑price data for Q3 2025 show about a 3.3% year‑over‑year price increase, which is why it raised conforming loan limits for 2026—again indicating slower appreciation, not a collapse in values. (apnews.com)
• Equity markets did experience a sharp but brief selloff in early April 2025 tied to broad tariff hikes, temporarily erasing more than $3 trillion in stock‑market value, but major indexes recovered by mid‑May. (en.wikipedia.org) That episode has so far not been followed by a housing crash of the magnitude Chamath described.

Putting this together, U.S. housing is clearly cooling: price growth has nearly stalled in nominal terms, some metros have begun to see outright declines, and mortgage‑borrower equity ticked down slightly. But nationwide housing wealth is still near record highs, and the observed pullback has erased hundreds of billions, not trillions, of dollars of housing wealth. That means Chamath’s specific scenario (a “major downward correction” that “whacks” the housing market and wipes out trillions in wealth) has not yet happened.

However, because he did not give a specific deadline and framed it as the “next phase of the cycle,” it remains possible that a deeper correction could occur beyond November 2025. Since the absence of such a crash by this date does not conclusively falsify a cycle‑phase prediction with an open time horizon, the fairest classification today is inconclusive (too early) rather than definitively “wrong.”

Available housing data since the March 15, 2025 episode show that average U.S. home prices have not fallen anywhere near 30–40% from their recent peak; in fact, major national indexes are still slightly up year‑over‑year:

• The FHFA House Price Index shows U.S. house prices up 2.2% year‑over‑year in Q3 2025, with a 0.2% quarterly increase, not a large decline. (fhfa.gov)
• FHFA’s monthly data for August 2025 show prices up 0.4% month‑over‑month and 2.3% year‑over‑year. (fhfa.gov)
• The S&P CoreLogic Case‑Shiller National Index shows home prices still rising slightly (around 1.3–1.5% year‑over‑year) as of August–September 2025, indicating cooling or flattening, not a crash. (wsj.com)
• FHFA’s increase in conforming loan limits for 2026 is based on a 3.3% rise in home prices from Q3 2024 to Q3 2025, again inconsistent with a major nationwide drawdown. (apnews.com)

In the episode transcript, Chamath talks about home prices being “whacked 30 or 40%” in the context of a broader future housing correction and policy changes, but he does not specify a clear time horizon for when that 30–40% national decline would occur. (speakai.co)

Because (1) as of November 30, 2025 there has been no such 30–40% nationwide drop, but (2) the prediction has no explicit deadline and housing cycles can take years, it is too early to definitively label the prediction as right or wrong. It has clearly not come true yet, but it could still be falsified or fulfilled in the longer term, so the fairest assessment at this time is “inconclusive (too early).”

The prediction is explicitly about what will become clear over the coming GPU cycle, with a time horizon of “by roughly 2030” for whether CoreWeave’s economics work out given the assumed ~10‑year useful life of its Nvidia GPUs versus a shorter ~5‑year life. As of the current date (November 30, 2025), only about 8–9 months have passed since the podcast on March 8, 2025, and we are still several years away from 2030. There is not yet enough elapsed time or publicly available evidence to determine definitively whether CoreWeave has become a “killer business” or is “deeply underwater” due to GPU useful-life assumptions in its debt models. Therefore, the prediction’s correctness cannot yet be evaluated and remains too early to call.

Chamath’s prediction is explicitly about a “secular shift” that will play out “over the coming election cycles” in the late 2020s, i.e., well beyond November 2025, so by definition the full forecast horizon has not elapsed. In the short period since the March 2025 podcast, there are some signs in the direction he describes: Trump’s second-term economic agenda has prioritized sweeping protectionist tariffs that contributed to the April 2025 stock market crash, while Trump publicly downplayed near-term market performance, arguing the U.S. cannot operate on a quarter‑to‑quarter perspective. (en.wikipedia.org) There is also rhetoric from Trump‑aligned institutions about crafting “worker‑focused” AI and industrial policies, suggesting at least a messaging shift toward workers and “Main Street.” (washingtonpost.com)

At the same time, core Republican/MAGA economic proposals continue to include extending and expanding the 2017 corporate and high‑income tax cuts, a traditionally Wall Street–friendly priority, and independent analyses argue that Trump’s tariff program in practice raises costs for working‑ and middle‑class households rather than clearly privileging them. (en.wikipedia.org) Because the prediction concerns a durable realignment “over the coming election cycles” into the late 2020s, and we have observed only the first year of a single term with mixed evidence, it is too early to determine whether Republican/MAGA strategists will sustainably de‑emphasize support for Wall Street and the stock market in the way Chamath envisioned. Hence the outcome is currently inconclusive, not yet demonstrably right or wrong.

Key elements of Chamath’s scenario did not play out as described during the roughly nine‑month window after early 2025.

1. Trump administration did trigger a tariff‑driven market break, but it was brief. After Trump’s January 20, 2025 inauguration, his second administration rolled out sweeping “reciprocal” tariffs in late March/early April. This caused the April 2–10, 2025 stock market crash, with the S&P 500 dropping about 10% in two days and global equities shedding trillions in value, explicitly linked to Trump’s tariffs. (en.wikipedia.org) That satisfies the policy that cracks equity markets part of the premise.

2. There was a short‑lived flight to safety that pushed 10‑year yields briefly into his target band, but not in a sustained way. In the panic immediately after the tariff announcement, investors fled to Treasuries and the 10‑year yield fell into the high‑3% range (lows around 3.86–3.95%) for a few days in early April. (en.wikipedia.org) However, yields quickly snapped back: by mid‑April they were around 4.4–4.6%, and subsequent 10‑year auctions in April and July cleared at roughly 4.36–4.44%, not at 3–4%. (cnbc.com) There was no nine‑month window of persistently 3–4% 10‑year yields that Treasury could lean on.

3. The U.S. did not refinance anything close to $10 trillion at 3–4%, and interest costs are rising, not yielding “trillions” in savings. Analyses of the Treasury’s funding needs indicate about $3.1 trillion of debt maturing in 2025, not $10 trillion in the nine months after early 2025, and that refinancing has generally occurred at yields in the mid‑4% range, not locked‑in near 3%. (panewslab.com) Meanwhile, the national debt continued to climb—from around $37 trillion in August 2025 to $38 trillion by October—and interest payments are now over $1 trillion per year and projected around $14 trillion over the next decade, with rating agencies warning about worsening debt affordability. (apnews.com) This is the opposite of a clearly observable multi‑trillion interest‑saving windfall.

4. Consumption did not collapse; it was front‑loaded and then slowed modestly. Retail data show a surge in March 2025 as households accelerated purchases ahead of tariffs, followed by a much weaker but still positive April (+0.1% m/m), with core retail sales slightly down—but industry groups and Census‑based summaries repeatedly describe consumer spending as “steady” and “resilient,” not sharply depressed. (tradingeconomics.com) Later in 2025, retail sales growth cools and sentiment deteriorates, but September retail sales are still rising year‑on‑year and GDP growth remains solid, consistent with a gradual squeeze rather than a deliberate, deep consumption shock. (reuters.com)

5. Inflation eased slightly, but tariffs are seen as adding upward pressure, not as a “deflationary tactic.” By April 2025, PCE inflation had fallen to about 2.1% year‑over‑year from 2.6% at end‑2024, part of an ongoing disinflation trend that began before Trump’s new tariffs. (federalreserve.gov) Federal Reserve and Treasury reports explicitly warn that the new import tariffs are likely to raise goods prices and have already contributed to an upturn in core goods inflation. (federalreserve.gov) By late 2025, CPI inflation is running around 3%, still above the Fed’s 2% target, with tariffs cited as one of the drivers of elevated prices. (theguardian.com) This does not match a “materially reduced inflation via equity‑market rebasing” story.

Taken together: while Trump’s tariff shock did crack equity markets and briefly pull 10‑year yields into the high‑3% range, the core claims—that this would sustainably depress consumption and inflation and allow roughly $10 trillion of debt to be refinanced at 3–4% yields, saving “trillions” in interest—have not occurred and are contradicted by observed borrowing costs, debt dynamics, inflation behavior, and spending data. Therefore this prediction is wrong.

The prediction window is “the next couple of years” from March 2025, i.e., roughly until March 2027. As of the current date (Nov 30, 2025), that window has not expired, so we can’t yet definitively say whether Chamath’s claim will ultimately be right or wrong.

Current evidence suggests his skepticism is plausible so far:

• Figure AI is only beginning “alpha testing” of its humanoid robot in homes in 2025; reporting emphasizes that home use will remain in very early stages through 2025, and that we should not expect these robots to be routinely vacuuming or cooking yet. (techcrunch.com)
• Tesla’s Optimus has demo videos showing it autonomously performing various household chores (taking out trash, sweeping, vacuuming, stirring a pot, operating a microwave, opening cabinets, closing curtains), but these are still controlled demos, not a widely deployed, commercially available general‑purpose home robot. (teslanorth.com)
• 1X’s NEO humanoid home robot is available for preorder for 2026 delivery, marketed as a home helper, but as of October 2025, most tasks are still teleoperated by remote human operators, and autonomy is limited; it’s early‑adopter hardware rather than a robust, broadly capable, fully autonomous household servant. (en.wikipedia.org)

So, as of late 2025, general‑purpose humanoid robots are not yet “super functional” for common household tasks in a broad, reliable, consumer sense, which is consistent with Chamath’s view. However, because his prediction explicitly covers the entire period up to ~March 2027, it is too early to judge its final accuracy.

Given that the time frame is still ongoing and no contradiction has yet occurred, the correct status is “inconclusive (too early)”, not definitively right or wrong.

Chamath’s on‑air comment was that over the next six months the U.S. would have to refinance roughly $10T of debt and that, in that window, the 10‑year Treasury yield “maybe [could] even get under 4% if we get a good string of data.”(lilys.ai)

Evaluating this as a time‑and‑level call (“10‑year < 4% within six months of early March 2025”):

• The relevant window is roughly 1 March 2025 to 1 September 2025.
• Multiple market reports show that the 10‑year Treasury yield fell below 4% in early April 2025, well within that six‑month period:
  • On 4 April 2025, the 10‑year yield slipped below 4%, with one report citing a move to about 3.98%, noting it was the first break of the 4% level in roughly half a year.(theglobaltreasurer.com)
  • On 5 April 2025, coverage described the 10‑year yield dropping further, to around 3.89%, clearly under the 4% threshold.(ainvest.com)
  • A separate summary table of yields likewise records the 10‑year at roughly 3.94% on April 4, 2025, reinforcing that sub‑4% prints occurred on those dates.(msmtimes.com)
• Monthly constant‑maturity data based on Federal Reserve series show the April 2025 monthly average for the 10‑year closer to 4.28%, indicating the drop below 4% was brief rather than a new regime, but it did happen during the specified timeframe.(value-trades.com)
• Independent analyses of the 2025 “maturity wall” in U.S. marketable Treasury debt describe multi‑trillion‑dollar refinancing needs in 2025, on the order of high single‑digit trillions for the year, so Chamath’s “about $10T in the next six months” is an aggressive but directionally consistent shorthand for the scale of rollover facing the Treasury.(reddit.com)

The reason yields dipped (flight to safety amid tariff‑driven growth fears, not a benign “good string of data”) diverges from his implied mechanism, but the core empirical claim — that the 10‑year could fall below 4% within six months of the episode — did in fact occur. Hence this prediction is best classified as right.

Trump’s $5 million “gold card” / investor-visa idea was formally announced on February 25, 2025, with broad press coverage describing it as a proposed replacement for EB‑5 and pricing residency at $5 million.(reuters.com) Over the following months, reporting focused on design details, quiet trials, and legal doubts—immigration lawyers repeatedly stressed that the program lacked clear legal authority and implementation rules, and some advisors even stated that no cards had actually been sold yet or that the initiative was still only at a waitlist / conceptual stage.(thedailybeast.com) In September 2025 Trump signed an executive order creating a revised Gold Card framework at lower $1–2 million “gift” levels, with a 90‑day setup window and applications still not open as of fall 2025.(en.wikipedia.org)

Across startup/VC, tech, and immigration coverage, there are no public reports of any non‑U.S. startup founder selling at least $5 million of secondary equity in a funding round specifically to finance purchase of a Trump Gold Card/visa, nor any anecdote of that type becoming a known case. Articles that mention founders and the Gold Card only describe them as a potential beneficiary class or hypothetical users, not as people who have actually done such a secondary sale to buy one.(economictimes.indiatimes.com) Given (1) the program’s delayed and still‑uncertain rollout, and (2) the absence of any documented case “you are going to hear about” within a few months of the announcement—or even by November 30, 2025—the prediction that such founder secondaries would publicly materialize in that timeframe has not come true.

As of November 30, 2025, Trump’s $5M “gold card”/“Trump Card” visa has only been proposed and partially rolled out for expressions of interest; its ultimate lifetime take‑up is unknown.

Key facts:

• President Trump announced the $5M “gold card” (later branded the Trump Card) in late February 2025 as a replacement for the EB‑5 investor visa, pitching it as a premium path to U.S. residency and citizenship for the ultra‑wealthy.(reuters.com)
• A government-backed website (trumpcard.gov) went live in June 2025; officials and press reports say around 70,000 people have registered interest via this site, but this is a mailing list, not approved visas.(popularmigrant.com)
• Commerce Secretary Howard Lutnick has claimed that roughly 1,000 cards were sold in a single day and that more than 1,000 cards have already been sold, but these numbers come from political statements rather than audited statistics, and no detailed issuance data has been published.(nypost.com)
• Immigration lawyers and policy experts warn that the program, as designed, likely lacks a clear legal basis without new legislation; they advise clients that the Gold Card is not yet a reliable, legally available path to residency, and note that the current website is only a registration-of-interest form.(thedailybeast.com)
• Independent advisers and industry experts are skeptical about scale: some estimate demand on the order of ~2,000 cards per year, while others predict fewer than 1,000 cards will ever be sold, far below the 2,000,000 figure Chamath floated. These, however, are projections, not final outcomes.(cnbc.com)

Chamath’s prediction was that, if the product effectively allowed gray or semi‑sanctioned money to be regularized (via de‑facto KYC/AML/OFAC workarounds), global demand could reach on the order of 2,000,000 buyers over the life of the program. So far:

• There is no clear evidence that the final or de facto rules provide such a clean workaround to sanctions/AML controls; details are still murky and under legal scrutiny.(euronews.com)
• The program is less than a year old, with uncertain legal status and contested implementation. Even if expert skepticism proves correct, we have not yet observed the full "life of the program," nor a definitive legal shutdown that would make 2,000,000 buyers impossible.

Because the program is new, legally unsettled, and its long‑run duration and rules are unknown, it is too early to know whether cumulative global demand will ever approach ~2,000,000 buyers. The available evidence (modest early interest, legal doubts, and expert skepticism) suggests the prediction is optimistic, but it does not conclusively falsify a multi‑decade "over the life of the program" forecast. Hence the outcome is inconclusive rather than clearly right or wrong at this time.

As of November 30, 2025, there is no definitive, audited data on how many Trump “Gold Card” (or successor) visas have actually been sold, and the ultimate life-of-program total is unknown.

Key points:

• Trump and Commerce Secretary Howard Lutnick initially pitched a $5 million “gold card” (later rebranded in various ways) and publicly floated selling up to 1–10 million of them, generating trillions in revenue.(cnbc.com) Lutnick even claimed on the All-In Podcast and to international media that he had sold 1,000 cards in a single day.(business-standard.com)
• Subsequent reporting, however, found that for months there was no functioning program and no money changing hands: as of late April 2025, immigration-focused outlets citing the New York Times reported there was still no official application process and that none of Lutnick’s claimed Gold Cards had actually been sold.(visaverge.com)
• When the program finally launched via executive order in September 2025, the core offer was sharply revised: the main “Gold Card” price was cut from $5 million to $1 million, with separate higher-tier products (e.g., a $5 million “Platinum Card”) teased on the trumpcard.gov site. This 80% price cut was widely interpreted by investment‑migration experts as an admission of weak demand.(forbes.com)
• Official communications now talk about making roughly 80,000 Gold Cards available, but even that is a planning figure; the program is still in an early “implementation phase,” and public reporting does not provide a verified count of cards actually issued.(cbsnews.com)
• Independent experts in the investment‑migration space have publicly argued that in practice fewer than 1,000 cards are likely ever to be sold, far below both Trump’s millions and even the “tens of thousands” scale, but these are forecasts, not realized outcomes.(newsweek.com)

Because:

1. The program is only months into actual operation; courts and Congress may still alter, block, or repeal it, and
2. There is no authoritative, end‑state number of buyers, only projections and partial early data,

Chamath’s conditional, long‑horizon prediction about eventual total buyers over the life of the program ("tens of thousands, not millions" if OFAC/AML/KYC rules truly bind) cannot yet be scored as right or wrong. The best we can say is that emerging expert opinion and early signs of weak demand point toward far fewer buyers than the administration’s "millions" rhetoric—but whether the final total lands in the low thousands, tens of thousands, or somewhere else entirely remains unresolved.

As of November 30, 2025, there have been no new SEC final rules or federal statutes materially changing the core U.S. “accredited investor” definition since the SEC’s 2020 amendments; the Commission’s own rulemaking page still points to the 2020 adopting release as the operative definition and shows no later accredited‑investor final rule. (sec.gov)

In Congress, major proposals to broaden access—such as the Equal Opportunity for All Investors Act of 2025 (H.R. 3339) and the Accredited Investor Definition Review Act (H.R. 3348)—have advanced (H.R. 3339 has passed the House and been referred to the Senate; H.R. 3348 has been reported out of committee but not voted on), yet neither has become law, so they have not actually changed who qualifies as accredited. (congress.gov)

The most concrete post‑podcast development is SEC staff guidance ADI 2025‑16, which stops staff from insisting that certain registered closed‑end funds of private funds (CE‑FOPFs) be sold only to accredited investors with a $25,000 minimum and no more than 15% in private funds; this effectively allows more retail investors to access private funds via registered vehicles. However, the ADI itself stresses that it is staff guidance, not a Commission rule or regulation, and does not alter applicable law. (sec.gov)

So far, the formal accredited‑investor framework and most related securities rules remain largely as they were, with only incremental loosening via staff practice and no enacted statutory or rule‑level overhaul. At the same time, the prediction was explicitly about what would happen “over the coming years,” and we are less than a year past the March 1, 2025 podcast date; substantial legislative or regulatory changes could still occur. Given this multi‑year horizon and the absence of decisive evidence either of sweeping reform or of its long‑term absence, the prediction’s ultimate accuracy cannot yet be determined, hence the “inconclusive” rating.

Multiple substantial new U.S. import tariffs were in fact implemented in 2025, going well beyond the early‑2025 status quo and forming a central pillar of economic policy, not just rhetoric.

Key developments:

• On February 1, 2025, President Trump signed executive orders imposing 25% tariffs on all goods from Mexico and Canada (with a 10% rate on Canadian energy) and an additional 10% tariff on Chinese imports on top of existing duties; these measures began taking effect in early February and March 2025. (en.wikipedia.org)
• On April 2, 2025 (“Liberation Day”), Trump declared a national emergency over the U.S. trade deficit and signed Executive Order 14257. This imposed a universal 10% baseline tariff on nearly all imports starting April 5, 2025, plus a tiered schedule of higher “reciprocal” tariffs (up to roughly 50%) on countries with large trade surpluses with the U.S. These orders were explicitly framed as a core economic policy to address trade deficits and generate revenue. (en.wikipedia.org)
• Additional, targeted tariffs were layered on: expanded steel and aluminum tariffs to all countries effective March 12, 2025; a 25% global tariff on automobiles and many auto parts starting April–May 2025; and further 2025 tariff hikes on copper, lumber, and furniture, all of which significantly increased effective import taxation relative to early 2025. (whitecase.com)

Because these tariffs:

1. were new and material compared with the pre‑2025 regime, and
2. were actually implemented as major elements of the administration’s 2025 economic policy (not just talked about), Chamath’s prediction that “the tariffs will be a plug… Are they coming? Absolutely.” is borne out by subsequent events.

Available data show that by roughly 6–9 months after February 2025 (August–November 2025), the U.S. federal funds rate target range was well below the 5.0–5.5% band Chamath speculated about.

Key facts:

• By late 2024, the FOMC had already cut the target range from its 5.25–5.50% peak (reached July–September 2023) down to 4.25–4.50%, and that range was still in place as of early February 2025. (federalreserve.gov)
• The Fed’s June 2025 Monetary Policy Report and contemporaneous analysis confirm that from January through June 2025 the federal funds target range was held at 4.25–4.50%, below 5%. (federalreserve.gov)
• On September 17, 2025, the FOMC cut the target range to 4.00–4.25%. (haver.com)
• On October 29, 2025, the Fed cut again, to 3.75–4.00%, where it remained through at least mid‑November 2025. (pcbb.com)
• Time‑series data summarizing the "federal funds target range – upper limit" show values of 4.50% on July 30, 2025, 4.25% on September 17, 2025, and 4.00% on October 29, 2025, with no return to 5% or higher during that period. (tradingeconomics.com)

Since during the relevant 6–9 month window (August–November 2025) the federal funds target range never was and did not return to the 5.0–5.5% region Chamath described, the prediction that rates in that timeframe could be around 5–5.5% (implying they would remain there or move back up to that range) turned out to be incorrect in light of actual policy outcomes.

Trump's Department of Government Efficiency (DOGE) was created on Jan 20, 2025 as a temporary initiative in his second administration to cut federal waste and spending. (en.wikipedia.org) Trump's second term is scheduled to run until Jan 20, 2029, so the end of Trump's second term has not yet occurred as of Nov 30, 2025. (en.wikipedia.org) DOGE itself was intended to last until July 4, 2026 but was quietly dissolved in November 2025, with remaining functions absorbed into the Office of Personnel Management. (reuters.com) Publicly reported DOGE savings to date are at most in the hundreds of billions of dollars claimed by its proponents, and independent audits suggest only a few billion in verifiable cuts while overall federal spending and deficits have continued to rise; there is no credible evidence of more than $2 trillion per year in annualized reductions identified by DOGE so far. (reuters.com) However, because Trump’s second term does not end until 2029, the time horizon specified in Chamath’s prediction has not yet elapsed, so the prediction cannot be definitively judged right or wrong at this point.

Evidence from Trump’s second term shows a mixed but ultimately retaliatory and selective posture toward business leaders and firms, contradicting Chamath’s claim that “we’re not going to ostracize people” or “play favorites.”

Where the prediction looks partly right:

• Trump has actively courted many major tech leaders, including some who were previously framed as political adversaries:
  • The second inauguration featured prominent tech CEOs and investors — including Meta’s Mark Zuckerberg and OpenAI’s Sam Altman — as donors and VIP attendees. (en.wikipedia.org)
  • On January 21, 2025, Trump stood alongside Altman, Larry Ellison, and Masayoshi Son at the White House to unveil Stargate, a joint venture led by OpenAI/SoftBank/Oracle to invest up to $500B in AI infrastructure — described by Trump as the “largest AI infrastructure project in history.” (en.wikipedia.org)
  • A July 15, 2025 AI-and-energy summit including Altman, Zuckerberg, Nadella, and Pichai, and a September 4 White House dinner with over two dozen tech leaders (Zuckerberg, Altman, Gates, Cook, Pichai, Brin, etc.) showcased close engagement and praise for Trump’s pro-business, pro‑AI agenda. (reuters.com)
  • Trump’s AI policy (EO 14179 and his AI Action Plan) is explicitly designed around industry partnerships and deregulation, with OpenAI and other firms providing input — another sign of access rather than ostracism for these particular companies. (en.wikipedia.org)

But key actions clearly do ostracize and punish disfavored firms/figures:

• Targeted retaliation against specific law firms for political reasons:

  • On March 6, 2025, Trump signed Executive Order 14230 barring the federal government from using the law firm Perkins Coie, suspending its attorneys’ security clearances, barring them from federal buildings, and ordering reviews aimed at terminating government business with its clients. The order explicitly tied these sanctions to Perkins Coie’s past work for Democratic figures (e.g., Hillary Clinton), as part of a broader Trump campaign against firms tied to investigations of him. (en.wikipedia.org)
  • A federal judge later struck down that order as unconstitutional, calling it retaliatory and aimed at suppressing dissenting viewpoints, noting it used state power to intimidate legal advocates of opposition causes. (politico.com) This is textbook political ostracism of a specific business entity.

• Retaliatory threats against Elon Musk’s companies:

  • Once close allies, Trump and Elon Musk fell into a public feud in mid‑2025 over Trump’s spending bill. In response to Musk’s criticism and threats to disrupt NASA service with SpaceX’s Dragon spacecraft, Trump publicly threatened to terminate Musk’s “governmental subsidies and contracts”, framing it as an easy way to save “billions and billions of dollars” in the budget. (twitter.com) This is a direct threat to punish a specific business leader and his companies for political opposition.
  • Around the same time, Trump held a White House tech/AI dinner with almost every major Silicon Valley leader except Musk; AP explicitly noted Musk’s “public fallout” with Trump and his notable absence, while rivals like Altman were present. (apnews.com) That selective access is the definition of “playing favorites.”

• Selective exclusion based on ideology in federal contracting:

  • In July 2025, Trump signed an executive order instructing agencies to bar AI vendors with “partisan bias or ideological agendas” — aimed at eliminating “woke AI” from federal contracts and requiring screening for ideological content in AI systems. (ft.com) While not always naming individual firms, it sets up a system in which companies with certain viewpoints can be excluded from federal business, again undermining the idea of an even‑handed, non‑retaliatory posture.

Assessment:

• Chamath’s narrower intuition — that the Trump White House would be open to deals even with previous tech-world critics like Zuckerberg and Altman — has been borne out: Meta and OpenAI enjoy high levels of access, partnership, and praise.
• But his broader claim that the administration “is going to turn a totally new page,” not ostracizing people or playing favorites, has clearly failed. The administration has:
  • Used executive orders to single out particular firms (Perkins Coie and others) for bans and sanctions because of their past political work; and
  • Publicly threatened to pull government contracts and subsidies from Musk’s companies in direct response to his political criticism, while simultaneously rewarding more aligned tech leaders with access and favorable treatment.

Because the prediction was framed as a general stance (“we’re not going to ostracize people… we’re not going to play favorites”), these repeated, targeted retaliatory actions against specific firms and individuals mean the prediction did not come true overall.

Trump’s September 25, 2025 executive order backing a qualified divestiture of TikTok’s U.S. operations adopts a framework in which the new U.S. TikTok entity is valued at roughly $14 billion, a figure reported across multiple outlets covering the deal. (investing.com) By contrast, analysts before and around the time of Chamath’s January 2025 comments commonly put TikTok’s U.S. business in a range from tens of billions up to well above $100 billion depending on assumptions about the recommendation algorithm, with some estimates explicitly pegging U.S. value or U.S.-focused scenarios around or above the $100 billion mark that Thomas Laffont discussed. (cnbc.com) The 2024 Protecting Americans from Foreign Adversary Controlled Applications Act legally forced a divestiture or U.S. shutdown, and Trump repeatedly used executive orders to delay enforcement while conditioning TikTok’s survival on an approved sale, a process run through an interagency and White House–led framework rather than a normal market auction. (whitehouse.gov) Coverage of the announced $14 billion price explicitly characterizes it as an extremely low multiple of TikTok U.S. revenue and attributes the discount to the coerced, politically driven nature of the sale, with one analysis calling the valuation daylight robbery relative to the business fundamentals. (business-standard.com) In other words, the currently agreed disposition that keeps TikTok operating in the U.S. under Trump is proceeding at a transaction value far below Laffont’s roughly $100 billion standalone estimate and is clearly shaped by U.S. government leverage rather than by TikTok’s modeled economic value, matching the core of Chamath’s prediction even though some implementation details of the deal may still change before closing.

Chamath’s prediction was that over the next several years of Trump’s second administration, major U.S. industrial‑policy and tech initiatives would increasingly be structured so that, in exchange for special incentives, the federal government retains explicit upside (equity or royalty‑like revenue shares), rather than relying only on grants, loans, or tax credits.

So far, early 2025 evidence points in that direction:

• The U.S. government converted CHIPS Act grants and other funds into about a 10% non‑voting equity stake in Intel, plus warrants for an additional stake, explicitly framed as a shift from grants to ownership in a key semiconductor firm. (apnews.com)
• The Department of Energy restructured a $2.3B loan to Lithium Americas so that the U.S. takes a small equity stake in the company developing the Thacker Pass lithium mine; reporting describes this as part of a broader Trump push to acquire equity in critical‑mineral and tech supply‑chain companies (Intel, MP Materials, etc.). (apnews.com)
• The government took a 10% equity stake in Trilogy Metals tied to approval of the Ambler Access Project road in Alaska, directly linking permitting for a strategic mining corridor to ongoing upside in the project. (streetwisereports.com)
• An $80B Westinghouse nuclear‑reactor package includes profit‑sharing for the U.S. above a return threshold and a contingent 20% equity stake if Westinghouse later IPOs above a set valuation, giving the federal government a royalty‑like share of future gains. (washingtonpost.com)
• In the Nippon Steel–U.S. Steel deal, the U.S. government obtained a “golden share” with veto rights and board‑appointment power as a condition of approving the acquisition, with analysts describing this as effectively partial nationalization—another form of ongoing economic and governance participation tied to regulatory approval. (en.wikipedia.org)

At the same time, not all high‑profile initiatives follow this model: Ex‑Im Bank’s $100B energy push relies on credit guarantees and loans rather than equity; the Stargate AI infrastructure project is financed by OpenAI, SoftBank, Oracle, MGX, and lenders, with Trump mainly offering expedited permitting; and the TikTok U.S. divestiture compels a sale to a private consortium (Oracle, Silver Lake, MGX, etc.) without the federal government itself taking an equity or royalty stake. (ft.com)

However, as of November 30, 2025, Trump’s second term has been underway for only a little over 10 months. The prediction explicitly concerns what will happen over the next several years of this administration, and it further claims that this upside‑sharing model will increasingly structure major industrial and tech policy. That longer‑term trajectory—whether this approach becomes the dominant, sustained “template” versus a burst of early‑term experiments—cannot yet be known.

Because the specified multi‑year timeframe has not elapsed, and future policy or congressional/market pushback could still significantly alter the pattern, the status of the prediction is inconclusive (too early to definitively judge), even though early developments are directionally consistent with what Chamath described.

Evidence so far shows that part of Chamath’s prediction has occurred, but the core part has not yet been resolved and the stated time window (“within the next few years”) has not expired.

What has happened so far

• On Jan. 20, 2025, President Trump issued Executive Order 14160, “Protecting the Meaning and Value of American Citizenship,” aimed at restricting birthright citizenship by reinterpreting the 14th Amendment’s Citizenship Clause, especially the phrase “subject to the jurisdiction thereof.”(en.wikipedia.org)
• The order triggered rapid and widespread litigation. States and civil-rights groups filed multiple suits within days, including Washington v. Trump and other challenges in federal courts around the country.(theverge.com)(en.wikipedia.org) This matches Chamath’s claim that the EO would immediately generate lawsuits.
• The Supreme Court took up Trump v. CASA, Inc., a consolidated set of cases arising from these challenges, and issued a decision on June 27, 2025—barely five months after the EO—addressing whether lower courts may issue nationwide injunctions blocking enforcement of the order. That is, the issue associated with the EO reached the Court “very quickly.”(congress.gov)(congress.gov)

What has not happened yet

• In Trump v. CASA, Inc., the justices resolved only the procedural question about nationwide ("universal") injunctions. The Court explicitly did not decide whether Trump’s birthright-citizenship order is constitutional or how to reinterpret “subject to the jurisdiction thereof.” Analyses of the decision emphasize that “the court’s opinion on the constitutionality of whether some American-born children can be deprived of citizenship remains undecided” and that the fate of the EO’s core policy “was left unclear.”(theguardian.com)(congress.gov)
• The main substantive rulings so far on the meaning of “subject to the jurisdiction thereof” in this controversy have come from lower courts, such as the Ninth Circuit, which held that Trump’s narrower, “allegiance”-based reading contradicts the original public understanding and longstanding Supreme Court precedent like United States v. Wong Kim Ark—but these are not Supreme Court merits decisions on the new EO.(reason.com)(en.wikipedia.org)

Why this is inconclusive

• Chamath’s prediction (as normalized) has two elements: (1) lawsuits will quickly send the birthright-citizenship fight to the Supreme Court, and (2) the Court will take up and opine on the meaning of the 14th Amendment’s “subject to the jurisdiction” clause in the near term (“within the next few years”).
• Element (1) is already borne out: the EO did rapidly reach the Supreme Court in Trump v. CASA, Inc. within months.(congress.gov)(constitutioncenter.org)
• Element (2) has not yet occurred: the Supreme Court has so far avoided deciding the clause’s meaning or the EO’s constitutionality, leaving those questions unresolved.(theguardian.com) However, because “within the next few years” extends beyond November 30, 2025, there is still time for the Court to grant and decide a merits case squarely addressing the Citizenship Clause.

Given this mix—partial validation (fast path to SCOTUS) but no Supreme Court merits ruling on the clause yet, with the forecast window still open—the correct classification is inconclusive, not clearly right or wrong at this time.

As of November 30, 2025, it is too early to determine whether Chamath’s full prediction has come true.

1. Status of U.S. stablecoin payment rails

• The U.S. did pass the GENIUS Act in July 2025, the first federal law creating a comprehensive regulatory framework for dollar‑backed payment stablecoins. (en.wikipedia.org)
• However, the law’s core regime does not take effect until the earlier of January 18, 2027 or 120 days after regulators issue final rules; agencies have up to one year from enactment (mid‑2026) to write those rules. Until then, the act mainly provides legal groundwork rather than a fully operational national payment rail. (natlawreview.com)
• Commentators describe the GENIUS Act as laying the foundation for a future blockchain‑based payment system that could make transactions faster and cheaper, but not as a completed, ubiquitous rail in 2025. (napa-net.org)
• Major networks (Mastercard–Fiserv, Western Union, Zelle) have announced stablecoin-based offerings, mostly focused on cross‑border payments, with launches planned for 2026 or with no firm live date yet, indicating the infrastructure is still in rollout/planning rather than “successfully implemented” nationwide. (barrons.com)

2. Effects on GDP growth and payment fraud

• Economic and policy analysis so far emphasizes potential benefits: stablecoins could boost demand for U.S. Treasuries and may put downward pressure on interest rates, but current retail use is limited and broader macroeconomic effects are explicitly described as speculative or long‑term. (reuters.com)
• There is no credible 2025 evidence attributing a significant acceleration of U.S. GDP growth specifically to stablecoin payment rails; any such impact, if it occurs, would likely take several years to show up in macro data.
• On fraud, U.S. authorities are still reporting large and rising crypto‑related scam losses, with stablecoins (especially USDT) heavily used in pig‑butchering and other fraud schemes, prompting new enforcement task forces. This does not yet support a clear claim that payment‑related fraud has been reduced by stablecoin rails overall. (theverge.com)

3. David Sacks’ role

• David Sacks was appointed White House AI and Crypto Czar in Trump’s second term and chairs the President’s Working Group on Digital Asset Markets. (en.wikipedia.org)
• From early 2025 onward he publicly made stablecoin legislation his top priority, led press events alongside key banking and finance committee leaders, and is widely described as leading the administration’s stablecoin push. (cnbc.com) This part of the prediction—that Sacks would be a key figure in figuring out the system—appears to be on track.

Overall assessment

• The precondition of the prediction—a successfully implemented, widely used U.S. stablecoin payment rail making payments instantaneous and nearly costless—has not yet been fully met; the system is in an early legal and rollout phase.
• Because of that, and because measurable impacts on GDP growth and fraud would reasonably take years to evaluate, there is currently insufficient evidence to say whether the full causal claims (“enormous acceleration to GDP,” “cut fraud”) are right or wrong.

Given the short time since the law’s passage and the long‑run nature of the predicted effects, the forecast is inconclusive (too early to judge), even though the sub‑claim about Sacks being a key architect looks directionally correct.

Several developments since early 2025 indicate that U.S.-dollar stablecoin payment rails have reached meaningful scale and are already both disruptive and economically valuable, in line with Chamath’s prediction.

1. U.S. policy and infrastructure for “U.S. stablecoin rails” now exist.
   In July 2025, the U.S. enacted the GENIUS Act, a federal framework for payment stablecoins that lets banks and other regulated financial institutions issue dollar‑backed stablecoins, defines them as payment instruments (not securities), and mandates 1:1 reserves and monthly audits—essentially formalizing U.S. stablecoin payment rails. (en.wikipedia.org) The Federal Reserve has also proposed giving eligible stablecoin issuers direct access to Fed payment infrastructure via new “payment accounts” / “skinny master accounts,” further integrating stablecoins into core U.S. rails. (finance.yahoo.com)

2. Stablecoins have scaled to volumes comparable to, or larger than, major card networks.
   Dollar stablecoins now make up ~99% of the global stablecoin market with a combined supply above $250–300B. (panewslab.com) On‑chain stablecoin transfers reached about $36.3T annually, surpassing Visa and Mastercard’s combined transaction volume, and recent estimates put average daily stablecoin volume at $3.1T, higher than Visa’s and second only to the U.S. ACH system. (panewslab.com) An a16z industry report finds that by late 2025, adjusted monthly stablecoin volume exceeds five times PayPal’s throughput and is already more than half of Visa’s, with over 1% of global U.S.-dollar circulation now tokenized as stablecoins. (bbx.com) These figures meet any reasonable definition of “implemented at scale.”

3. Concrete disruption of existing payment and financial systems.
   Major payment and fintech players are actively routing payments over stablecoin rails:

   • PayPal’s “Pay with Crypto” allows U.S. merchants to accept stablecoins (e.g., USDC) and other crypto via connected wallets, advertising materially lower fees than many international card payments. (techradar.com)
   • Klarna launched KlarnaUSD, a dollar‑backed stablecoin on a Stripe‑developed blockchain, specifically to cut cross‑border costs by bypassing SWIFT and with plans to extend it to merchant and consumer payments. (ft.com)
     Industry data show that the average stablecoin transaction size has been falling and usage is shifting from large crypto trades to smaller cross‑border and everyday payments, with payment companies’ share of stablecoin volume expected to grow sharply. (coinlive.com)
     Regulators and large asset managers now openly warn that U.S. dollar stablecoins could siphon off bank deposits, dollarize other economies, and destabilize traditional banking and payment systems—evidence that they are already seen as a disruptive alternative infrastructure. (reuters.com)

4. Demonstrable net economic value.
   Academic work estimates that Tether alone held about $98.5B of U.S. Treasury bills by Q1 2025—around 1.6% of the entire T‑bill market—and that this demand has lowered 1‑month T‑bill yields by roughly 24 basis points, implying on the order of $15B per year in U.S. interest savings. (arxiv.org) Broader analyses note that stablecoins collectively hold over $150B in Treasuries, making them a top‑20 holder and a growing, structural source of demand for U.S. debt. (bbx.com) For users and firms, stablecoin rails offer faster settlement and significantly lower cross‑border fees, and are increasingly used for payments, trade, and savings, especially in high‑inflation or under‑banked markets. (panewslab.com)

5. Caveats, but overall alignment with the prediction.
   It’s true that a large share of stablecoin volume still comes from trading and automated activity, and long‑term net effects (including financial‑stability risks) remain uncertain. (panewslab.com) However, by late 2025 the combination of (a) national‑level U.S. regulation and integration into Fed‑adjacent rails, (b) multi‑trillion‑dollar, payment‑like transaction volumes, (c) real shifts in cross‑border payment flows and merchant acceptance, and (d) measurable macro‑level benefits such as reduced U.S. borrowing costs strongly supports Chamath’s claim that U.S. stablecoin rails, once scaled, would be “hugely disruptive and value added.”

Given the evidence available as of November 30, 2025, this prediction is best classified as right, with the understanding that the full long‑term balance of benefits and risks is still evolving.

Chamath made the comment while arguing that a short-term “cooling off period” with some protections (like temporary bans on unsolicited low‑ball offers) was justified immediately after the fires, but that over the following 6–12 months normal market dynamics would reassert themselves: “I suspect that in six months and nine months and twelve months, the free market will sort all of these things out … It can allow the free market to work in a few months from now. We’re only talking 90 days.” (podcasts.happyscribe.com)

Since then, California has maintained and in some cases extended substantial emergency controls:

• Executive Order N‑4‑25 extended price‑gouging limits (generally a 10% cap over pre‑emergency prices) on building materials, storage, construction and related services in Los Angeles County all the way to January 7, 2026. (gov.ca.gov)
• Separate executive orders and alerts extended hotel/rental price‑gouging protections and rent caps into March–July 2025, and barred unsolicited undervalued real‑estate offers in affected ZIP codes until July 1, 2025. (gov.ca.gov)
• Six to ten months after the fires, officials were still reporting significant issues: widespread rent‑gouging complaints, removed listings, scams by unlicensed contractors, long delays in debris removal and rebuilding, and even litigation over wildfire‑related insurance surcharges. (sfchronicle.com)

This evidence suggests that, as of late November 2025 (roughly 10 months post‑fires), market conditions and policy responses have not yet clearly “sorted everything out,” and key price controls will certainly still be in force at least until January 7, 2026. However, Chamath’s own timeframe explicitly includes the 12‑month mark and the user’s normalized phrasing (“by early 2026”) extends slightly beyond the current date, so we have not yet observed the full horizon of the prediction. In addition, his claim is qualitative (“sort all of these things out”) and partly about how a freer market would behave, which is hard to falsify while substantial controls remain in place. For these reasons, it is premature to label the prediction definitively right or wrong, so the fairest status is inconclusive (too early).

As of 30 November 2025, TikTok’s Chinese parent ByteDance is under a U.S. law (the Protecting Americans from Foreign Adversary Controlled Applications Act, signed April 2024) that effectively forces it to divest TikTok’s U.S. operations or face a ban, and the Supreme Court upheld that law in January 2025, shortly before Donald Trump’s second inauguration. (en.wikipedia.org) In September 2025 President Trump signed an executive order approving a framework “qualified divestiture” in which TikTok U.S. will be operated by a new U.S.-based joint venture, majority-owned by U.S. and allied investors (Oracle, Silver Lake, Dell and others) with ByteDance retaining under 20%. (whitehouse.gov) Reporting indicates this framework values TikTok’s U.S. business at about $14 billion, a figure noted as far below estimates of ByteDance’s overall valuation (around $330 billion), but that comparison is between the U.S. carve-out and the entire global company, not a clear measure of TikTok U.S.’s fair market value. (theguardian.com) Crucially, as of late November 2025 the deal has not yet closed; Trump’s order gives roughly 120 days (into January 2026) to finalize the transaction, and news coverage continues to describe the divestiture as in progress, with lawmakers still questioning its terms. (reuters.com) Because the spin-out and sale of TikTok U.S. have not been completed and no definitive market consensus exists yet on whether the final price is a “distressed” bargain relative to fair value, the multi-part prediction (forced sale to a mostly American buyer, occurring during a Trump presidency, at a well-below-fair-value price) cannot yet be definitively judged.

Evidence through late 2025 shows that MBA-led search funds and ETA (entrepreneurship through acquisition) vehicles have grown rather than “effectively ceased” after January 2025.

Key points:

• A 2024 Stanford GSB Search Fund Study reports record numbers of searchers and investors, with 681 funds tracked and a record 94 core funds launched in 2023, and describes the community as experiencing “ongoing growth,” not a collapse. This model specifically targets relatively inexperienced, often MBA-trained entrepreneurs raising capital to buy and run small businesses.

  Sources: Stanford GSB Search Fund page and 2024 study highlights. (gsb.stanford.edu)

• In April 2025, Business Insider described search funds—"mini private equity"—as a growing path chosen by young professionals “often under 35 and frequently MBA graduates,” noting that the model “has seen record growth” and citing over 90 search funds launched in 2023. This directly contradicts the idea that newly graduated MBAs raising such capital is “not happening anymore.” (businessinsider.com)

• A September 2025 CNBC piece is explicit that “search funds boom as young buyers snap up firms”, highlighting investors’ strong interest and emphasizing that search funds have become an attractive alternative asset class during a broader VC/PE downturn. It again references the record 94 core funds launched and positions search funds as a safe port drawing more capital, not less. (cnbc.com)

• Multiple 2025 articles describe MBAs specifically as a major driver of ETA/search fund activity. A July–August 2025 piece notes “hundreds of US MBAs” are buying and operating small service businesses via search-fund-style ETA models, emphasizing that this trend is intensifying. (timesofindia.indiatimes.com)

• A June 2025 Forbes Council post, “Inside The Rise Of Search Funds,” frames search funds as a rising, maturing asset class with strong interest from both entrepreneurs and investors, again based on recent Stanford data. (forbes.com)

Across these independent sources, there is clear, contemporaneous evidence that:

1. The number of search funds and total capital in the model remain high and, by recent data, record-setting or near-record-setting.
2. MBA and young-professional participation is widely reported as growing, not shrinking.
3. Investors continue to fund these vehicles, with some sources explicitly saying search funds are thriving relative to traditional PE/VC.

Given that the prediction was effectively, “this won’t be funded anymore going forward,” and that within the same year (2025) we see headlines describing a boom in MBA-driven, investor-funded search funds, the prediction does not match observed reality.

Therefore, the prediction is wrong.

Chamath’s claim was explicitly about a trend that would grow in the coming years, i.e., a multi‑year structural decline in corporate demand for MBAs, especially into management roles. As of November 30, 2025, less than a year has passed since the January 18, 2025 episode, so the full forecast period has not elapsed.

Since early 2025, evidence is mixed. On one hand, reporting on top U.S. schools shows a tougher job market: job offers and placement rates for MBAs at elite programs have fallen, with big consulting and tech employers (e.g., McKinsey and major tech firms) cutting back MBA hiring and delaying start dates, and some data points (like lower placement rates at leading schools) indicating short‑term weakness in demand. (ft.com) This aligns with the idea of pressure on traditional MBA pipelines into certain middle‑management tracks.

On the other hand, large global surveys of corporate recruiters in 2024 and 2025 show sustained overall demand: the Graduate Management Admission Council reports high employer confidence in graduate business education, with the vast majority of recruiters planning to maintain or increase MBA hiring and MBAs projected to outpace other graduate business degrees in 2025. (gmac.com) A 2025 U.S. hiring pulse survey notes that about half of respondents hired fewer MBAs than they had expected for the year, suggesting a cyclical slowdown rather than clear evidence of a long‑run structural collapse. (gmac.com) Sectoral shifts also appear: MBA hiring has cooled in some tech roles but is growing in areas like healthcare and AI‑related businesses. (aacsb.edu)

Given (1) the prediction’s multi‑year horizon, which extends beyond late 2025, and (2) the conflicting current data—short‑term softness contrasted with strong stated medium‑term demand—the outcome cannot yet be determined. The fairest assessment is that it is too early to conclusively label the prediction as right or wrong.

Chamath argued that the L.A.-area wildfire insurance liabilities would be so large that California would turn to the federal government for a bailout / major help.

1. Insurance and loss liabilities were indeed massive. Modeling firm KCC estimated roughly $28 billion in insured losses from the January 2025 Los Angeles fires, making them the costliest wildfire event in U.S. history. A state wildfire insurance fund of $21 billion is reported as potentially being fully exhausted by related claims, and press coverage notes that the Eaton and Palisades fires alone could generate $20–45 billion in insurance losses. (reuters.com) California’s state-regulated FAIR Plan, which insures otherwise uninsurable properties, had limited liquid resources and had to obtain a $1 billion assessment from member insurers to keep paying claims. (insurance.ca.gov) This matches the premise that insurance-related liabilities would be enormous and strain existing mechanisms.

2. California sought and received very large federal financial assistance for recovery. FEMA and the U.S. Small Business Administration quickly became the largest single sources of recovery money. FEMA and SBA report more than $2 billion made available by late March 2025 and over $3 billion by early June 2025 in grants and disaster loans to homeowners, renters, and businesses affected by the Los Angeles County wildfires. (fema.gov) Governor Gavin Newsom publicly thanked federal partners and repeatedly urged residents to apply for FEMA and SBA assistance, framing it as a key pillar of the recovery. (gov.ca.gov)

3. The state explicitly asked Congress for a huge federal aid package. In February 2025, Newsom formally requested nearly $40 billion in federal disaster aid from Congress specifically for Los Angeles wildfire recovery. Reporting from AP, Politico, and the San Francisco Chronicle describes a 14‑page request that includes tens of billions for FEMA emergency public assistance, HUD grants for home and business repairs, debris removal, and over $5 billion in SBA lending authority. The request also anticipates federal reimbursement for several billion dollars in state outlays already approved in a $2.5 billion California wildfire aid package. (apnews.com) This is, in effect, California going to Washington for a very large federal backstop to help cover the financial burden of the disaster and its associated losses.

4. Nuance: the federal government is not literally recapitalizing state insurance funds. The evidence so far does not show the U.S. Treasury directly bailing out California’s wildfire insurance fund or the FAIR Plan; instead, the state has used its regulatory tools to tap private insurers via assessments. (insurance.ca.gov) However, Chamath’s normalized prediction includes the broader idea that California would seek substantial federal financial assistance tied to the same catastrophic loss event—both for rebuilding and to alleviate the economic shock those liabilities create. On that point, the record is clear: California has already secured and is actively pursuing very large-scale federal disaster funding.

Given (a) the unprecedented scale of wildfire-related liabilities and (b) California’s clear move to secure tens of billions in federal disaster money plus billions already flowing from FEMA/SBA, the prediction that the state would “look to the federal government to bail them out” in the sense of seeking major federal financial relief tied to these losses is best judged as right in substance, even though the federal government has not directly assumed the state’s insurance-fund obligations.

As of late 2025, the robotaxi market is still in an early, fast‑evolving phase. Waymo clearly leads U.S. fully driverless services, operating paid robotaxis without safety drivers in multiple cities (Phoenix, San Francisco, Los Angeles, Austin, Miami, and expanding further) with a fleet over 1,500 vehicles and hundreds of thousands of weekly rides. (eprnews.com)

Tesla, meanwhile, only launched its Robotaxi service in June 2025 in Austin and later expanded to the Bay Area, still with safety monitors or drivers in the vehicles and facing regulatory hurdles in key states such as California, Arizona, and Nevada. Its footprint and autonomy level are materially behind Waymo, and it is still working toward removing safety drivers by the end of 2025. (en.wikipedia.org)

At the same time, the market is not limited to Waymo and Tesla: Amazon’s Zoox has launched a fully driverless, purpose‑built robotaxi service in Las Vegas and is preparing expansion to other cities, while several other firms are active or re‑entering related segments. (techcrunch.com) This competitive landscape means it is far too early to say Waymo and Tesla have definitively run away with the market.

On the consolidation side, there is substantial partnership and alliance activity (for example, the Rivian–Volkswagen software joint venture and a proposed Honda–Nissan–Mitsubishi merger that would reshape Japan’s auto sector), but these moves are driven by broader EV, software, and global-competition pressures, not clearly or primarily by Waymo/Tesla dominance in robotaxis. (en.wikipedia.org) There has not yet been the kind of widespread, clearly AV‑driven consolidation among traditional OEMs implied by the prediction.

Because (1) the robotaxi market is still nascent, with no stable long‑term structure, (2) Tesla has not yet emerged as a clear co‑leader alongside Waymo, and (3) the consolidation dynamics the prediction describes have not clearly materialized or been ruled out, there is not enough evidence less than a year later to judge the forecast as right or wrong. It is best classified as too early to call.

As of November 30, 2025, the key conditions in Chamath’s prediction have not materialized, but the time horizon is long-term and climate/ice trends still point in the direction he describes, so it’s too early to definitively call it right or wrong.

Relevant facts:

• Arctic ice is melting rapidly, increasing theoretical access to northern routes. Winter 2025 Arctic sea ice hit a record-low maximum extent in the satellite era, reflecting strong warming-driven decline. (theguardian.com)

• Arctic shipping remains niche compared with the Panama Canal. Russia’s Northern Sea Route (NSR) – the most developed Arctic corridor – carried about 37.9 million tonnes of cargo in 2024. (en.wikipedia.org) By contrast, the Panama Canal moved roughly 423 million tons in FY 2024, more than ten times as much, and is projected around 500+ million tons in FY 2025. (pancanal.com) A 2024/25 analysis notes that the Arctic Northern Sea Route has not become a mainstream container path: only a few specialist operators (mainly Russian/Chinese) use it, and total Arctic transit freight is tiny compared with Suez and Panama. (ft.com)

• The Northwest Passage / “Northern Passage” Chamath is likely referring to is still seasonal, risky, and lightly used. Contemporary briefs emphasize that the Northwest Passage is only navigable for a short summer window, requires ice-capable ships or icebreaker support, and is not yet a reliable, year‑round route for regular trade. (arctictradenations.com) Recent research even finds the effective shipping season shrunk between 2007 and 2021 due to shifts in multi‑year ice, undercutting the idea of an already “easy” lane. (natureworldnews.com) A 2025 survey of Canada–US disputes notes that there are still fewer than ~20 full transits per year, mostly expedition cruises, underscoring that this is not a major corridor for “a lot of critical goods.” (grokipedia.com)

• The U.S. does not have a Greenland–Canada arrangement that would give it near‑monopoly control. Greenland remains part of the Kingdom of Denmark; Danish and Greenlandic leaders have repeatedly rejected U.S. acquisition or expanded control, and current U.S. presence is limited to the long‑standing Pituffik (Thule) base under a defense agreement with Denmark. (reuters.com) On the Canadian side, the legal status of the Northwest Passage remains unresolved: Canada insists it is internal waters; the U.S. treats it as an international strait. Both sides “agree to disagree” under the 1988 Arctic Cooperation Agreement, and no new framework has been created that would hand the U.S. near‑exclusive control of the passage. (belfercenter.org)

• Other actors, especially Russia, already exert strong control over alternative Arctic routes. Russia legally treats the Northern Sea Route as a national transport corridor, requires permits and often Russian icebreaker/pilot services for passage, and even reserves key energy shipments for Russian‑flag vessels. (cleanarctic.org) This makes any future Arctic shipping system inherently multipolar, not something the U.S. could easily dominate even if it had deeper arrangements with Canada and Greenland.

Putting this together:

• The premise that climate change is opening Arctic navigation opportunities is strongly supported.
• The core prediction, though, is that this will yield a commercially vital “Northern Passage” whose importance rivals the Panama Canal and over which the U.S., via Greenland/Canada agreements, would have near‑monopoly strategic control.
• As of late 2025, the route is still marginal, seasonal, and legally contested, with no U.S. monopoly and cargo volumes far below canal levels.

Because Chamath did not attach a specific time frame and many projections place substantial Arctic shipping growth and potential canal‑like significance closer to mid‑century, the current evidence shows that his scenario has not happened yet, but also has not been ruled out by events. On that basis, the fairest assessment today is:

Inconclusive (too early to tell).

Evidence from 2025 shows that fiscal conservatives did not achieve the kind of dominant, austerity‑driven influence Chamath predicted.

1. Major 2025 legislation increased, not restrained, federal borrowing. The One Big Beautiful Bill Act made 2017 tax cuts permanent, added new tax breaks, and sharply increased funding for defense and immigration enforcement; CBO and independent estimates project it will add several trillion dollars to the debt over the next decade, even though it includes delayed cuts to Medicaid and SNAP that begin after 2026. This is a net deficit‑expanding Trumpist agenda, not austerity. (en.wikipedia.org)

2. The 2025 funding deal mostly froze existing spending and still raised long‑run deficits. Congress relied on a full‑year continuing resolution that largely extends FY2024 levels with only limited non‑defense trims and a modest defense bump; non‑partisan analysts estimated the framework would still add trillions to the debt over ten years, and only a couple of Republican fiscal hawks voted no. A one‑year nominal freeze in a high‑inflation, high‑debt context falls well short of the “austerity” Chamath described. (en.wikipedia.org)

3. Actual cuts were narrow and symbolic relative to the overall budget. The Rescissions Act of 2025 canceled roughly $9 billion (mainly foreign aid and public broadcasting) out of a multi‑trillion‑dollar budget—highly visible but fiscally minor, illustrating how limited concrete austerity has been. (en.wikipedia.org)

4. Fiscal conservatives often lost internal fights. Hard‑line Republicans did temporarily stall Trump’s megabill over debt concerns, and some opposed budget resolutions they saw as too loose, but leadership ultimately pushed the core package through; the final law still substantially increases projected deficits, indicating that growth‑and‑culture priorities overrode strict fiscal restraint. (washingtonpost.com)

5. Political salience in 2025 has centered on immigration and trade, not austerity. The year’s defining battles have been mass‑deportation policies and related protests, deployments of federal forces in U.S. cities, and aggressive tariff actions against Canada, Mexico, and China—while state budgets show case‑by‑case adjustments or impasses rather than a nationwide turn to deep spending cuts. That issue mix does not match a landscape where fiscal conservatism and austerity are the dominant political themes. (en.wikipedia.org)

Taken together, 2025 has featured louder fiscal‑hawk rhetoric and some future‑dated cuts, but no broad move to austerity or clear "day" for fiscal conservatives as the primary political winners, so the prediction is best judged as wrong.

The prediction is wrong because none of the specified right‑leaning outcomes materialized by late 2025. In Canada, Justin Trudeau announced his intention to resign in early January 2025, Mark Carney became Liberal leader and prime minister in March, and the 28 April 2025 federal election returned another Liberal minority government under Carney; Conservative leader Pierre Poilievre lost both the election and his own seat, so Trudeau did not lose massively to Poilievre and Canada did not shift to a right‑wing government. (en.wikipedia.org) In Germany, the February 2025 federal election made the CDU/CSU the largest bloc, AfD finished second with about 20–21 percent of the vote, and a CDU/CSU–SPD grand coalition installed Friedrich Merz as chancellor in May, while other parties reiterated a cordon sanitaire against AfD; AfD did not enter government or “win national power.” (en.wikipedia.org) In France, Emmanuel Macron remained president throughout 2025 and no early presidential election was held; instead, Marine Le Pen was convicted in March 2025 over misuse of EU funds and given a five‑year ban on holding office, making it impossible for her to become president in 2025, while late‑2025 polling focused on Jordan Bardella as the far‑right favourite for the regular 2027 race. (en.wikipedia.org) In the United Kingdom, Labour won the July 2024 general election and Keir Starmer has served continuously as prime minister since 5 July 2024; as of November 2025 the Starmer ministry is still in office, and Nigel Farage remains leader of Reform UK in opposition, publicly pressing Starmer rather than replacing him, so the Labour government has not fallen and Farage has not taken national leadership. (en.wikipedia.org) Since all four concrete electoral predictions failed and progressive or centrist parties still govern in Canada, France and the UK, the broader claim that 2025 would bring a string of right‑leaning electoral victories and a major repudiation of progressive, identity‑politics‑oriented parties in the G8 is contradicted by actual outcomes by late 2025. (en.wikipedia.org)

1. Volume didn’t 4–5x vs 2024

• Baseline 2024:* The joint Artemis–Dune report State of Stablecoins 2025 shows that stablecoins facilitated about $35 trillion in total transfers over 2024.(holder.io) Separate summaries of the same report repeat this ~$35T 2024 figure.(cryptonews.net) PANews notes that USD‑denominated stablecoins are ~99% of the market, so this is essentially all USD stablecoin volume.(panewslab.com)

Data for 2025 so far: Multiple 2025 analyses based on Artemis / Dune and a16z data report that:

• Adjusted stablecoin payment volume in 2025 is about $9T, up ~87% year‑on‑year.(kucoin.com) That implies 2024 adjusted volume around $4.8T — roughly a 1.9x increase, not 4–5x.
• SQ Magazine, summarizing 2025 data, says “adjusted annual stablecoin transaction volume reached approximately $9 trillion in 2025, up about 87% year‑on‑year,” and that gross transaction flows over the last 12 months are about $46T.(sqmagazine.co.uk) Relative to the ~$35T 2024 gross figure, that’s roughly a 1.3x increase.

The prediction was for 4–5x growth in aggregate transaction volume vs 2024. By late November 2025, the best on‑chain and adjusted metrics show somewhere between ~1.3x (gross) and ~1.9x (adjusted) growth, orders of magnitude below 4–5x. Even if December 2025 were unusually high, it cannot plausibly close the gap to 4–5x relative to 2024.

2. USD stablecoins did not materially erode Visa/Mastercard’s card‑payments duopoly by 2025

Card network performance in 2025:

• Visa’s FY2025 results show net revenue up 11%, EPS up 14%, and total payments volume of about $14T, up 8% YoY, with processed transactions up 10%.(finance.yahoo.com) These are strong, not eroded, economics.
• Mastercard’s 2025 results to date show similarly robust growth: Q3 2025 net revenue up 17% YoY, net income up 20%, gross dollar volume up 9%, and switched transactions up 10%.(finance.yahoo.com) Again, this indicates expanding volumes and healthy margins.

How industry analysts and the networks themselves describe the impact:

• A mid‑2025 Jefferies analysis concludes that stablecoins do not pose a material threat to Visa or Mastercard, framing the risk as more perceived than real.(investing.com)
• A separate report on Visa and Mastercard’s earnings notes that the networks "report stablecoins have minimal market impact" so far, with usage still “minimal” relative to their overall payment volumes.(coinlive.me)
• Reuters’ Breakingviews column in July 2025 acknowledges rising concern about future competition from stablecoins but emphasizes that Visa and Mastercard still process roughly 70% of U.S. purchases, with resilient earnings; any fee pressure is characterized as a potential long‑term vulnerability, not present‑day erosion.(reuters.com)

Meanwhile, mainstream coverage of stablecoins stresses that, despite explosive on‑chain volumes and surpassing card networks in raw transfer value, much of that flow is trading, arbitrage, or other crypto‑internal activity rather than consumer/merchant card‑like payments. The a16z and Artemis/Dune reports themselves distinguish between “gross transaction flows” and a much smaller subset that qualifies as actual payments, which they put on the order of single‑digit trillions annually, comparable to systems like ACH or PayPal, not yet displacing card rails.(kucoin.com)

So by late 2025:

• Visa and Mastercard’s market share of card spending remains dominant, with U.S. card spending in 2024 exceeding $10.7T and still growing.(rss.globenewswire.com)
• Their revenues and profits are up, not down, and independent equity research explicitly says stablecoins are not yet a material threat.(investing.com)

That is very different from “materially eroding the market share and economics” of the Visa/Mastercard card‑payments duopoly by the end of 2025.

3. Summary

By the end of 2025 (with 11 months of data in hand):

• USD stablecoin transaction volumes have grown strongly but are up on the order of 30–90% vs 2024, not the 300–400% (4–5x) Chamath predicted.
• Visa and Mastercard’s card‑payment volumes, revenues, and profits have continued to grow, and mainstream financial analysis characterizes stablecoin impact as minimal so far, not materially erosive.

Taken together, both core components of the prediction are not borne out by the data available as of November 30, 2025, so the prediction is wrong.

It’s too early to evaluate this prediction as of November 30, 2025, because:

• The claim is specifically about "measured over full‑year 2025" dollar‑denominated stablecoin transaction volume vs Visa’s global payment volume. Full‑year 2025 data for both:
  • On‑chain stablecoin settlement volumes, and
  • Visa’s FY2025 global payment volume will not be fully reported until calendar Q1–Q2 2026.
• Public data currently available (on‑chain stablecoin analytics and Visa’s most recent quarterly/annual filings) only cover periods up to part of 2025, not the entire calendar year, and therefore cannot confirm whether the full‑year 2025 condition is satisfied.
• Even if mid‑2025 or year‑to‑date numbers suggest a certain trend (e.g., that stablecoin settlement volumes are on track to exceed or not exceed Visa’s payments volume), that would still be projection, not a completed measurement of the whole year.

Because the prediction is explicitly about full‑year 2025 totals, and those totals are not yet available in official or widely accepted datasets, the correctness of the prediction cannot yet be determined.

The prediction is framed to be evaluated "by the end of 2025," and today is November 30, 2025, so the deadline has not yet passed and market caps could still change materially in December. Current evidence indicates that the Magnificent Seven’s combined market cap peaked around $18.2T in 2024 (e.g., on Dec. 11, 2024). (benzinga.com) In 2025 the group has actually exceeded that level, reaching record highs around $20.9T–$21.1T in October 2025, well above the 2024 peak rather than at least $2T below it. (linkedin.com) However, because the year has not yet ended, we cannot definitively say whether a $2T+ drawdown from the 2024 peak will or will not exist by December 31, 2025, so the prediction is currently too early to judge.

By November 30, 2025, there has not been a wave of auto mega‑mergers among large legacy OEMs.

• The one clear example pointing in that direction was the proposed Honda–Nissan (with possible Mitsubishi participation) mega‑merger. On December 23, 2024, they announced an in‑principle agreement to pursue a merger under a holding company by 2026, explicitly framed as a response to electrification pressures and competition from Tesla and Chinese EV makers like BYD. Analysts and trade press repeatedly described this as a mega‑merger aimed at surviving EV disruption and achieving scale. (trendforce.com)
• However, those talks collapsed quickly. By February 2025, Honda, Nissan, and Mitsubishi formally ended negotiations and terminated their integration framework; Nissan’s board rejected the proposed terms, and the companies reverted to looser strategic cooperation instead of merging. Nissan’s own summary of events notes that the planned 2026 merger was abandoned in February 2025. (upi.com)
• Crucially, no further comparable mergers among major traditional automakers (GM, Ford, Toyota, VW Group, Stellantis, Hyundai–Kia, etc.) were announced or completed in 2025. Contemporary analysis around the Honda–Nissan plan even argued that such deals are rare and were unlikely to trigger a broader merger mania, which is exactly what played out. (forbes.com) Instead, we saw partnerships and JVs (e.g., GM–Hyundai co‑development, VW–Rivian technology JV) rather than corporate mergers. (reuters.com)
• Some consolidation occurred inside Chinese groups (e.g., Geely fully taking Zeekr private), but these are intra‑group restructurings in China, not the cross‑company mega‑mergers of Western/Japanese legacy OEMs that Chamath was describing. (ft.com)

Since 2025 produced at most one short‑lived mega‑merger attempt and no sustained, multi‑firm wave of auto mega‑mergers or clear “collapse of the traditional auto OEMs,” the prediction that 2025 would bring such a wave is best judged as wrong.

As of November 30, 2025, no widely‑recognized major U.S. "mainline" bank (e.g., JPMorgan Chase, Bank of America, Citigroup, Wells Fargo, Goldman Sachs, Morgan Stanley, etc., as listed among the largest U.S. banks by assets) has experienced an outright banking crisis involving failure, FDIC resolution, or an acute, public liquidity/solvency event driven by reserve or balance‑sheet stress in 2025.(en.wikipedia.org)

Public indicators instead show:

• Only two very small banks (Pulaski Savings Bank and The Santa Anna National Bank, each with <$100M in assets) have failed in 2025, per the FDIC list of bank failures; no large or systemically important bank appears on that list.(en.wikipedia.org)
• The Federal Reserve’s 2025 stress tests report that all 22 of the largest U.S. banks remained above regulatory capital minimums even under severe recession scenarios, implying no immediate capital or solvency crisis at the big "mainline" institutions.(ft.com)
• Disclosures from individual majors (e.g., Citigroup’s Q1 2025 call) describe strong capital and liquidity positions, with CET1 ratios comfortably above requirements and substantial available liquidity resources.(alphaspread.com)
• System‑level commentary and forecasts (e.g., Swift Centre’s probabilistic assessment) treat a major‑bank liquidity crisis as a low‑probability future risk, not as an event that has already occurred.(swiftcentre.org)

However, Chamath’s prediction window runs “by the end of 2025.” Since there is still one month remaining and no such major‑bank crisis has occurred yet, the prediction has not been confirmed, but it also cannot yet be definitively ruled out. Therefore, the fairest status as of today is inconclusive (too early to tell) rather than clearly right or wrong.

Chamath’s claim was conditional: if there were severe credit stress or a banking crisis in 2025, being long selected CDS on vulnerable credits would be the best‑performing asset of 2025; otherwise that CDS trade would “lose money.”

1. Trigger condition (severe credit stress / banking crisis) is not clearly met or clearly absent.

   • 2025 did see a sharp but tariff‑driven equity crash in early April, with the S&P 500 and Nasdaq suffering their biggest declines since 2020, but markets largely recovered by May. This episode is generally described as a stock market crash linked to trade policy, not a banking‑system meltdown.
     • (en.wikipedia.org)
   • Credit markets did come under notable stress: CDS spreads on high‑yield and crossover indices jumped to multi‑year highs in early 2025, and Asia/Europe credit indices and sovereign CDS widened materially around the tariff shock, reflecting increased default concerns.
     • (ft.com)
   • However, major official and media sources through late 2025 talk about rising risks and regional bank/CRE stress, not an actual systemic banking crisis. The Russian central bank explicitly said there was no looming banking crisis, and IMF commentary on AI and markets specifically distinguished current stresses from 2008‑style systemic events. (reuters.com)
   • In the U.S., only two small banks failed in 2025 as of late June, far from a broad wave of failures. (en.wikipedia.org)
   • Because terms like “severe credit stress” and “banking crisis” are qualitative, it is debatable whether 2025 meets Chamath’s threshold. Reasonable observers could disagree, so we cannot definitively say the if‑crisis branch of his prediction did or did not trigger.

2. We cannot observe the performance of the specific CDS trade he had in mind.

   • Public data confirm big swings in CDS spreads (which would have made some long‑CDS positions very profitable during the April stress), but spreads partially retraced as markets stabilized. (kelo.com)
   • Without knowing which credits he meant by “vulnerable,” the exact timing of entry and exit, or whether the position was held all year, we cannot say whether his particular long‑CDS trade ended up making or losing money over full‑year 2025.

3. “Best‑performing asset of 2025” is not practically checkable for CDS.

   • Many listed assets in 2025 (e.g., certain AI/tech and defense stocks/ETFs, as well as some high‑beta names) show very high year‑to‑date returns, often 50–200%+ by late 2025. (onedayadvisor.com)
   • CDS trades are over‑the‑counter, highly bespoke, and not reported in a way that allows a clean, market‑wide ranking of “best‑performing asset.” Even if some niche CDS position had enormous percentage returns, there is no public, comprehensive dataset that would let us verify that it outperformed all other assets.

Because (a) whether the crisis condition truly occurred is subjective, (b) the exact CDS instruments and P&L for Chamath’s trade are unknown, and (c) there is no way to rigorously rank that CDS position against all other assets in 2025, the prediction cannot be conclusively scored as right or wrong based on available evidence.

Available 2025 data show that major incumbent enterprise‑software vendors are still growing and profitable, but they have begun to exhibit the kind of “fissures” Chamath described—slower growth, restructuring, and mounting pressure from faster‑growing AI‑native rivals—by late 2025.

On the incumbent side: Salesforce’s revenue growth has decelerated to the high‑single‑digit range (about 8–9% guidance for FY26) with slowing subscription growth across core clouds, even as margins remain high; its stock is the worst performer among large‑cap tech in 2025 and analysts explicitly worry that AI could “eat away” at SaaS business models. (investor.salesforce.com) SAP missed Q3 2025 revenue expectations, with total revenue up only 7% and its cloud business growing 22%—still solid but the slowest cloud growth since 2023—prompting guidance to the low end of its cloud‑revenue range. (reuters.com) Workday announced layoffs of about 1,750 employees (8.5% of staff) in early 2025 to refocus spending on AI and later reported “lukewarm” subscription revenue that merely met expectations, causing a share‑price drop and reflecting softer enterprise demand. (reuters.com) Adobe, despite posting ~10–11% revenue growth and record results, has been downgraded on the thesis that “AI is eating software,” with analysts highlighting intensifying competition from AI‑powered tools and newer design platforms; its shares are down materially year‑to‑date. (barrons.com) Altogether, these trends show slowing growth, workforce cuts, and increased investor skepticism across several flagship vendors, even as a few (e.g., ServiceNow, Oracle) continue to post strong AI‑driven growth and margin expansion. (reddit.com)

In contrast, AI‑native competitors are growing dramatically faster. Databricks projects about $4 billion in 2025 revenue, more than 50% year‑over‑year growth, with >140% net revenue retention and hundreds of $1M‑plus enterprise customers. (reuters.com) Sector‑wide benchmark data for 2025 indicate AI‑native startups have median annual growth around 100%, versus roughly 20–25% for traditional SaaS, and are reaching $100M ARR in 1–2 years with far higher revenue per employee. (deepstarstrategic.com) Industry analyses also describe customers delaying some SaaS renewals and experimenting with AI‑native tools, explicitly framing this as pressure on legacy software economics. (stansberryresearch.com)

Because Chamath only predicted that “fissures” would start to appear in 2025—rather than a full‑blown collapse—the combination of (a) visible growth deceleration, restructurings, and investor multiple compression at several large incumbents, and (b) much faster growth and capital allocation toward AI‑native enterprise platforms, matches the spirit of his call. The incumbents remain large and profitable, but clear early cracks relative to AI‑native competitors are observable by late 2025, so the prediction is best judged as broadly right rather than wrong or purely inconclusive.

Publicly available regulatory actions in 2025 show that U.S. bank regulators did implement exactly the kind of technical, leverage‑related relief Chamath was saying would “stop in its tracks,” particularly around rules that constrain banks’ balance‑sheet capacity for low‑risk assets like Treasuries.

Key facts:

• On June 27, 2025, the Federal Reserve, FDIC, and OCC jointly proposed modifying the enhanced supplementary leverage ratio (eSLR) for the largest banks, explicitly to ensure it functions only as a backstop and does not discourage low‑risk activities such as U.S. Treasury market intermediation. The agencies acknowledged the proposal would reduce Tier 1 capital requirements for affected bank holding companies (by <2%) and more for some subsidiaries. (fdic.gov)
• On November 25, 2025, those agencies finalized this rule, lowering the effective eSLR buffer from a flat 2% add‑on to a smaller, GSIB‑surcharge‑based buffer capped at 1% for key subsidiaries, and again stressing that the change is meant to give large banks more capacity for low‑risk activities like U.S. Treasury market intermediation and repo financing. The rule is estimated to reduce Tier 1 capital at GSIB holding companies by about $13 billion and substantially more at their bank subsidiaries. (fdic.gov)
• Financial press coverage characterized this package as one of the largest post‑crisis capital easings, centered on lowering the leverage requirements that had been criticized for penalizing Treasuries and other low‑risk assets and limiting banks’ Treasury‑market participation. (ft.com)
• In parallel, Fed officials publicly debated more direct relief for Treasuries in the leverage rule, including calls to exempt Treasuries from the eSLR entirely, citing the need to encourage banks to hold more of them, especially in stress. (reuters.com)

These actions are precisely the kind of “small, arcane regulatory changes” to leverage ratios that ease constraints on holding Treasuries and other low‑risk assets that Chamath was pointing to as examples of can‑kicking. Instead of stopping, they were actively pursued and then finalized in 2025.

Because such leverage‑rule tweaks did occur in 2025, the prediction that they would stop (and thus reveal something about who is really driving policy) did not come true.

Trump did in fact win a new term beginning in 2025 and was inaugurated for his second presidency on January 20, 2025, starting a new administration. 【(en.wikipedia.org)

Within days, he signed Executive Order 14176 on January 23, 2025, ordering the declassification of records related to the assassinations of John F. Kennedy, Robert F. Kennedy, and Martin Luther King Jr. 【(en.wikipedia.org) Pursuant to this, the National Archives released more than 60,000 previously withheld assassination-related documents in March 2025, totaling about 77,100 pages across over 2,300 PDFs—a very large volume of formerly secret material. 【(en.wikipedia.org) This directly matches the prediction of an "enormity of the files" being declassified and publicly released, specifically including JFK-related records.

On Epstein, Congress passed and Trump signed the Epstein Files Transparency Act on November 19, 2025, mandating the Department of Justice to release all unclassified DOJ records related to Jeffrey Epstein within 30 days, with the public release expected around December 19, 2025. 【(en.wikipedia.org) As of November 30, 2025, those files have not yet been fully released, but the law and ongoing DOJ actions show that large-scale Epstein disclosures are imminent and being driven by the Trump administration.

Because (1) a new Trump term began in 2025, and (2) that administration has already declassified and released very large troves of previously secret files on major historical controversies (notably JFK/MLK/RFK), with additional large-scale Epstein disclosures legally queued up, the core substance of Chamath’s prediction has already materialized. The remaining Epstein release affects completeness but not the basic correctness of the forecast that Trump’s new term would be marked by major declassification waves on controversies like JFK and Epstein.

Chamath’s on-air statement in the Dec 20, 2024 episode is explicitly predictive: he and Jason talk about the upcoming holidays and say, “Three or four besties will be hitting the slopes… Three or four besties will be skiing together… We’re all going to be there, bro.” in reference to a ski trip the following week. 【6†turn3search0】

In the subsequent episode “2025 Predictions with bestie Gavin Baker”, released Jan 3–4, 2025, Jason opens by saying, “We’re all wrapping up our ski trip here,” and cues “found footage from the Bestie skiing.” The clip and banter clearly describe multiple besties skiing together: Jason narrates his own run, then Chamath’s (“There comes Champe… you really advanced this last season”), and then explicitly ranks the on-slope skiers as “me, Chamath, Friedberg in that ranking.” He praises Friedberg for having been “out there a number of days” and Friedberg confirms, “I think I skied four days.” 【5†turn2search1】 The episode description from several podcast directories also notes that the besties “welcome Gavin Baker and recap ski week,” placing this group ski trip in the immediate post-holiday window referenced on Dec 20. 【2†turn2search3】【2†turn2search6】

Putting this together: (1) on Dec 20 they predict that during the upcoming holiday period, 3–4 besties will ski together at the same destination; (2) in the very next regular episode after the holidays they explicitly recap a shared ski week, with at least three core besties (Jason, Chamath, and Friedberg) skiing on the same trip. That is sufficient to conclude that the prediction—“three or four besties will be skiing together” over that holiday period—came true.

Chamath’s claim has two parts: (1) capability — that AI + social media will let ordinary people rapidly digest long bills and tell representatives what they want, and (2) outcome — that this will yield a “much more active” and responsive U.S. government where major bills live or die based on that AI‑enabled feedback.

On the capability side, there is clear evidence this is emerging:

• Elon Musk’s Grok on X has been explicitly pitched as a tool that will summarize “mammoth laws” for citizens before Congress votes on them, directly tying LLMs to social‑media distribution. (westernjournal.com)
• Citizen‑facing apps like Represent provide AI bill summaries, personal impact analysis, and an AI “message assistant” that drafts communications to your representatives and tracks your outreach, exactly the workflow Chamath described. (therepresent.app)
• Professional tools such as Plural, Quorum, and FiscalNote now offer AI bill summaries, topic tagging, and predictive analytics on U.S. legislation, showing widespread adoption of LLMs in legislative analysis (though mostly by lobbyists and organized advocates, not the mass public). (pluralpolicy.com)

On the outcome/governance side, there is not yet strong evidence that this has produced a noticeably more responsive form of U.S. governance driven by AI‑enabled grassroots bill analysis:

• Controversy over the One Big Beautiful Bill Act’s proposed 10‑year ban on state AI regulation did trigger broad opposition and a 99–1 Senate vote to strike the ban, but that mobilization appears driven by state officials, civil‑rights groups, and traditional advocacy networks using letters, open statements, and conventional digital activism, not clearly by masses of citizens newly empowered by LLM bill‑readers. (en.wikipedia.org)
• A 2025 natural‑experiment on Change.org found that adding an in‑platform “write with AI” assistant changed petition text but did not improve petition success, suggesting AI‑assisted messaging does not automatically translate into greater political impact. (arxiv.org)
• Research and commercial deployments show AI mostly boosting the analytic capacity of interest groups and government‑affairs professionals, not yet transforming mass public power over legislative outcomes. (arxiv.org)

Only about 11 months have passed since December 2024, the prediction’s starting point, and it concerns a structural shift that plausibly plays out over several years. Given that the technical preconditions are appearing but clear, measurable changes in overall governmental responsiveness due specifically to this phenomenon have not yet been demonstrated, it is too early to decisively label the prediction right or wrong.

Public information so far does not show xAI actually operating or even having fully installed ~1,000,000 GPUs yet, but the one‑year window from the Dec 20, 2024 episode has not fully elapsed as of Nov 30, 2025, so the prediction can’t be definitively graded.

Key facts:

• xAI’s Colossus started with 100,000 Nvidia H100 GPUs in 2024 and was expanded to about 200,000–230,000 GPUs (mix of H100, H200, and GB200) by mid‑2025.(eonmsk.com)
• A September 2025 survey of available data pegs the operational count at roughly 230,000–250,000 GPUs (150k H100, 50k H200, 30k GB200), with another 110k GB200 chips ‘coming online’ and a projected milestone of 1 million GPUs only by late 2026.(etcjournal.com)
• Colossus 2, a second supercluster, is described in mid‑2025 reports as bringing an initial ~550,000 GB200/GB300 GPUs online “within the coming weeks,” with a roadmap to reach about 1 million GPUs across Colossus 1 and 2 by late 2025 or early 2026—but these pieces are framed as plans and ramp‑up, not as already‑achieved 1M‑GPU deployment.(gearmusk.com)
• Overviews and news stories through late 2025 still talk about Colossus ‘aiming’ or ‘on track’ to scale to 1 million GPUs, rather than confirming that 1 million GPUs are currently installed and operational.(etcjournal.com)

Given (a) evidence that xAI has only a few hundred thousand GPUs online so far, and (b) the fact that the stated ~one‑year horizon from Dec 20, 2024 does not end until around Dec 20, 2025, the outcome of Chamath’s prediction—roughly 100k to ~1M GPUs within that year—is not yet definitively knowable from public sources. It therefore remains inconclusive (too early) rather than clearly right or wrong.

Chamath’s prediction is explicitly about what will happen “over time” with no concrete date or horizon attached, so it is a long‑run structural forecast rather than a 1–2 year call.

As of November 30, 2025:

• Estimates of global enterprise software spending and broader “software and software-related” spending (including IT services, cloud, etc.) have not fallen by anything close to 10x. If anything, major analyst firms continue to project continued growth in worldwide software and IT services spending through the late 2020s rather than a collapse.
• However, the claim is that AI will eventually drive the cost base down so much that total annual spend compresses from about $5T to ~$500B. Because no specific date (e.g., by 2030/2035) was given, current data can’t falsify a forecast that could be many years or even decades out.

Since:

1. The predicted 10x shrinkage clearly has not occurred yet, but
2. The prediction does not specify a time frame, and there is no widely accepted evidence that such a long‑run outcome is impossible,

the status of the prediction as of now must be marked as inconclusive (too early) rather than right or wrong.

As of November 30, 2025, there is strong evidence of rapid price compression and intense competition, but not enough time or data to say Chamath’s long‑run structural claim has clearly succeeded or failed.

What the prediction requires

• He isn’t just saying prices will fall; he’s saying that for large enterprises, both closed and open‑source model providers will eventually price API usage at (effectively) compute cost, with near‑zero margin per token.
• The phrase “over time” gives no concrete horizon (e.g., 2 years vs. 10 years), so it’s a long‑term industry-structure prediction.

Where pricing actually is in late 2025

1. Closed‑source leaders still charge non‑trivial per‑token prices:

   • OpenAI’s public pricing for major models (e.g., o3, o4‑mini, gpt‑4o‑mini) remains in the roughly $0.15–$20 per million tokens range, depending on model and tier, well above zero and with clearly positive gross margins. (platform.openai.com)
   • Anthropic Claude 4.x models (Opus, Sonnet, Haiku 4.5) list at about $0.80–$15 per million input tokens and $4–$75 per million output tokens, again indicating substantial markups over raw compute. (claudelog.com)
   • Google’s Gemini API charges around $0.15 per million input tokens (with additional output pricing), not zero, even if cheaper than some rivals. (ai.google.dev)

2. Gross margins show providers are still earning more than bare compute cost:

   • Industry analyses estimate OpenAI’s model APIs running at double‑digit to ~50% gross margins, and Anthropic in a similar ~50–60% range—far from “near‑zero” margin over compute. (getmonetizely.com)
   • That implies enterprises are still paying meaningfully above underlying GPU/TPU costs, even after volume discounts.

3. Open‑source and low‑cost competitors are putting pressure on prices:

   • DeepSeek offers extremely low API prices (on the order of $0.55 per million input tokens and $2.19 per million output tokens as of early 2025) and repeatedly cuts prices 50–75% in “price war” moves, explicitly leveraging open‑source releases to undercut Western providers. (en.wikipedia.org)
   • These moves have triggered price cuts from OpenAI and Google and pushed the whole market towards cheaper tiers and smaller, more efficient models, aligning with the direction of Chamath’s thesis (competition and open‑source driving prices down).

Why this is still "too early" rather than clearly wrong

• The current state: prices are falling, there’s a visible race to the bottom on lower‑tier models, and open‑source/China‑based providers have made very cheap inference widely available. That supports the trend he described.
• But the end state he claimed—per‑token enterprise pricing effectively at compute cost across both closed and open providers—has not been reached: list prices and margin estimates show meaningful markups today, and none of the major Western vendors publicly commit to “at‑cost” enterprise tokens. (platform.openai.com)
• Because he did not specify a timeframe, and we’re only ~11 months past the December 20, 2024 episode, the market could still evolve toward his asymptotic scenario (e.g., if vendors shift to primarily charging for dedicated capacity/SLAs while metered tokens trend toward cost).

Given the open‑ended timeline and the fact that pricing is clearly moving downward but is not yet at near‑zero margin, the fairest assessment as of late 2025 is **“inconclusive (too early)” rather than definitively right or wrong.

As of November 30, 2025, it is too early to judge Chamath’s 2–5 year prediction.

Key facts:

• Google’s Willow processor, announced in December 2024, has 105 physical superconducting qubits and demonstrates a few logical qubits with below‑threshold error correction, not thousands of logical qubits.(blog.google)
• Google itself and outside analysts emphasize that Willow is far from a “cryptanalytically relevant quantum computer”: estimates for breaking RSA‑2048 still sit around millions of physical qubits (roughly 4 million), with timelines typically a decade or more away, not 1–2 years.(theverge.com)
• Current overviews of quantum progress in 2025 describe systems in the ~10²–10³ qubit range and consistently state that we are still far from the fault‑tolerant, large‑scale machines needed to break RSA‑2048 or Bitcoin’s SHA‑256/ECDSA security; those capabilities are generally projected into the 2030s or later.(forbes.com)
• Policy and cybersecurity guidance (e.g., UK NCSC) likewise targets around 2035 as the planning horizon for serious quantum decryption threats, reinforcing that no such capability exists yet.(theguardian.com)
• There is no public evidence by late 2025 that RSA‑2048 has been broken by a quantum computer or that Bitcoin’s core cryptography has been compromised; instead, industry and governments are still treating this as a future risk and rolling out post‑quantum standards (e.g., NIST PQC).(en.wikipedia.org)

Because Chamath’s stated window is 2–5 years from 2024 (roughly 2026–2029), and only about one year has elapsed, we cannot yet say definitively whether quantum hardware will fail or succeed in reaching the ~4,000–8,000 logical‑qubit scale in that period. The current trajectory makes the prediction look very optimistic, but the deadline has not passed, so the correct classification for now is "inconclusive (too early)".

The prediction is a conditional causal claim: if DOGE were used to radically simplify the U.S. tax code (e.g., implement a flat tax and drastically shrink the code), then U.S. real GDP growth would rise by about 1–2 percentage points and create a sustained expansion.

As of 30 November 2025:

• The U.S. federal tax code has not been overhauled using DOGE (Dogecoin) as any central mechanism, nor has Congress adopted a DOGE-based reform or flat tax tied to DOGE.
• The IRS and U.S. Treasury do not use DOGE as an official tax payment mechanism or as a structural tool for rewriting/simplifying the tax code; crypto usage for taxes remains limited to certain states/municipalities for payment, and is not structurally DOGE-centric or code-shrinking in the manner described.
• There has been no major legislative tax reform in 2024–2025 that meets the described condition of “using DOGE to shrink the tax code and create a flat tax.”

Because the triggering condition of the prediction has not occurred, we have no empirical basis to evaluate whether such a DOGE-driven tax-code simplification would in fact add 100–200 basis points to U.S. real GDP growth. It’s a counterfactual policy claim that remains untested, not a time-bound forecast whose outcome we can observe.

Therefore the correct classification is "ambiguous": the claim cannot be determined true or false given current reality, not because it’s too early, but because the scenario it depends on never happened.

Chamath’s statement on the podcast is explicitly conditional and framed in terms of potential: he says the U.S. economy “could be growing at 4 or 5%” but doesn’t, because of regulatory burden, and that the opportunity for DOGE is to “wipe as many of these regulations off the books” and then selectively reenact needed ones. This is not a time‑bounded forecast but a counterfactual claim about what could happen under a very aggressive deregulation scenario that has never actually been tried. (speakai.co)

What actually happened with DOGE and regulation

After the episode, President Trump’s second term did formally establish the Department of Government Efficiency (DOGE) via executive order on 20 January 2025, reorganizing the U.S. Digital Service and creating DOGE teams in agencies. Subsequent orders tasked DOGE and agencies with reviewing regulations, workforce reductions, and contract/grant reforms, but these orders emphasize review, prioritization, and rescinding certain rules—far from literally wiping the vast bulk of federal regulations and then reenacting only a small subset. (whitehouse.gov) DOGE’s own communications highlight specific deregulatory actions and claimed savings, not a near‑total reboot of the Code of Federal Regulations. (doge.gov) In late 2025, DOGE was quietly disbanded months before its planned end date, with its functions partially absorbed into other entities—again indicating the radical, comprehensive deregulation Chamath described was never implemented. (reuters.com)

Observed GDP growth

Real U.S. GDP growth has remained in the 2–3% range: about 2.8% in 2024, with official projections around 2.0% for 2025 and 2.1% for 2026, well below the 4–5% annual growth he discussed. (en.wikipedia.org) But because the extreme deregulatory scenario he posited (wiping a very large share of regulations and rebuilding from zero) never occurred, these actual growth outcomes do not directly test his counterfactual claim.

Why this is scored as ambiguous

• The prediction is conditional (“if DOGE wipes the regulations and then reenacts only necessary ones”) and expressed as what the U.S. economy could achieve, without a clear time horizon.
• The necessary condition—a sweeping, near‑total deregulation and rebuild of the federal rulebook—has not happened; only partial, contested DOGE‑linked reforms took place before the initiative was wound down.
• Because we have never observed the world Chamath is talking about, we cannot empirically say whether that scenario would have produced 4–5% real growth.

Given that the condition has not been satisfied and the statement is inherently counterfactual and non‑time‑bounded, it cannot be cleanly judged as right or wrong based on current data. It is therefore best classified as ambiguous rather than correct, incorrect, or merely “too early.”

The prediction explicitly concerns “the next four and eight years” after late 2024—i.e., roughly through the 2028–2032 federal election cycles. At the time of evaluation (November 30, 2025), only about one year has elapsed since the prediction, and at most the 2024 general election and part of the 2026 primary cycle are in view. That is far too early to judge whether “a bunch of MAGA candidates [will] rise up to run against [anti‑MAGA Republicans] everywhere in the United States” over the full 4–8 year horizon.

While there are early signs that MAGA‑aligned candidates continue to challenge some Republican incumbents in various primaries, the prediction is about the magnitude and breadth of such challenges across one to two full federal election cycles, which extend well beyond 2025. Because the specified time window has not passed, we cannot yet determine whether the forecasted widespread surge in MAGA primary challengers has actually materialized at the scale described.

Therefore the status of this prediction is too early to call.

The prediction is explicitly long‑dated: Chamath says that at some point in his lifetime Bitcoin will become “an independent asset and a non‑speculative store of value.” As of 30 November 2025:

• Bitcoin is still widely characterized as a volatile, high‑risk asset with large drawdowns and strong correlation to broader risk‑on sentiment and tech/growth equities, not as a stable monetary reserve asset.
• However, the prediction concerns a state that may or may not occur at any time in the remaining decades of his life. There is no specified deadline (e.g., by 2030), so the fact that it has not happened yet does not falsify the claim.

Since the timeframe extends indefinitely into the rest of Chamath Palihapitiya’s life, and that period has certainly not expired, we cannot yet determine whether Bitcoin will eventually meet his criterion of being a non‑speculative, reserve‑like asset.

Therefore, the correct classification as of now is: inconclusive (too early to tell).

The prediction ties a vague, perception‑based condition to a specific market outcome:

If, by some point in 2025, it looks like President Trump’s actions cannot course‑correct U.S. inflation or the deficit, then public markets will go massively risk‑off.

To score it, we’d need (a) a clear point in 2025 when markets broadly concluded Trump couldn’t fix inflation/deficits, and (b) a resulting, durable shift to a risk‑off regime across major risk assets.

1. Macroeconomic backdrop in 2025

• Trump is in his second term starting Jan 20, 2025, after winning the 2024 election. (en.wikipedia.org)
• Inflation: After the April 2, 2025 “Liberation Day” tariff shock, April CPI came in at 2.3% year‑over‑year, the lowest since 2021, defying fears of an immediate inflation spike. (abc7.com) By September 2025, headline CPI was about 3.0% YoY, with core inflation also around 3.0%. (m.economictimes.com) Forecasts and commentary did warn tariffs could push inflation toward ~4% and stall disinflation, but that’s still within a moderate range rather than an obvious “inflation is out of control” scenario. (uobgroup.com)
• Deficit: The FY 2025 federal deficit was about $1.8 trillion, essentially unchanged from FY 2024, with debt roughly the size of the economy and projected to exceed its WWII‑era record as a share of GDP. Net interest on the debt topped $1 trillion for the first time. (crfb.org) That clearly signals no meaningful fiscal improvement, but large deficits and debt warnings pre‑date Trump’s second term, so it’s hard to identify a new, 2025‑specific “realization” that his actions cannot fix the problem.

In other words, deficits stayed very large and inflation hovered around 2–3% with some upward tariff pressure. This is concerning but not an unambiguous “macro has broken and Trump obviously cannot course‑correct” moment.

2. Market behavior in 2025

• April 2025 crash: Trump’s sweeping "Liberation Day" tariffs (10% baseline on almost all imports plus much higher country‑specific rates) triggered a sharp global selloff described as the 2025 stock market crash. Major U.S. indices dropped roughly 10%+ in early April, and it was the largest global decline since the 2020 COVID crash. (en.wikipedia.org) This is clearly a massively risk‑off episode, but it was tightly linked to tariff/trade‑war and recession fears rather than a discrete realization about inflation or the long‑term deficit.
• Rapid recovery and new highs: After tariff walk‑backs and policy adjustments, markets rebounded. By May–June 2025, the S&P 500 and Nasdaq had turned positive for the year and reached new all‑time highs by June 27, 2025. (en.wikipedia.org) By late November 2025, the S&P 500 was up roughly 12–16% year‑to‑date, with strategists projecting further gains into 2026 on the back of strong earnings and AI‑driven optimism. (reuters.com) That is a classic risk‑on environment, not a sustained, structurally risk‑off regime.
• Crypto: Bitcoin and crypto behaved like high‑beta risk assets—plunging during tariff scares in Q1–Q2 2025 and again in November 2025, when Bitcoin fell from over $120,000 to the low $80,000s, wiping out more than $1 trillion in value. (thecoinrepublic.com) But these swings coincided with policy shocks and speculative excess, not with a clearly identifiable, market‑wide conclusion that Trump had definitively failed on inflation or the deficit.

3. Why the outcome is hard to judge against his condition

• The antecedent is vague and unobservable: “when it looks like Trump’s actions are not going to be able to course‑correct inflation or the deficit” is not tied to a specific, observable threshold (e.g., inflation above X%, deficit above Y%, ratings downgrade, failed fiscal package). Analysts have warned all year that debt is unsustainable and tariffs are risky, but similar warnings existed before 2025. There is no discrete, widely recognized 2025 moment where markets re‑priced on the view that Trump cannot fix inflation/deficits.
• Risk‑off episodes do occur, but they are short‑lived and clearly driven by other triggers—mainly the Liberation Day tariff shock and subsequent trade/AI bubble worries. Markets then revert to a strong risk‑on stance with new highs and double‑digit equity gains for 2025, despite continuing fiscal concerns and only modestly contained inflation.
• Because the condition is not clearly met, we cannot cleanly say “the condition happened but his consequence didn’t” (which would make the prediction straightforwardly wrong). Instead, we have:
  • Persistent large deficits and moderate inflation,
  • Ongoing debate about whether Trump’s mix of tariffs, spending, and tax plans will worsen or mitigate those issues, and
  • Markets that oscillate between brief risk‑off shocks and an overall bullish trend.

Given this, the prediction is not cleanly confirmed (no lasting, deficit/inflation‑driven shift to a massively risk‑off regime) but also not cleanly falsified, because the triggering condition is so subjective and never clearly, uniquely realized.

Bottom line:

Deficits remain huge and inflation is sticky but moderate, while 2025 markets are, on net, strongly risk‑on. The specific conditional link Chamath asserted—“once markets see Trump can’t fix inflation/deficits, they’ll flip massively risk‑off”—cannot be clearly tested with available data, so the outcome of this prediction is best classified as ambiguous, not definitively right or wrong.

As of November 30, 2025, it’s too early to determine whether Chamath’s conditional prediction is right or wrong.

1. The conditional hasn’t played out yet

• He conditioned the outcome on the U.S. running budget deficits of about 8% of GDP for 4–6 consecutive years starting around 2024. That would roughly cover 2024–2028/2030.
• Actual and projected deficits so far are very high but below 8%: CBO and related analyses show deficits of about 6.3% of GDP in 2023, an estimated 6.7% in 2024, and around 6.1–6.2% projected for 2025.(americanactionforum.org) Reuters’ report on the finalized FY 2025 budget puts the deficit at about 5.9% of GDP.(reuters.com)
• CBO’s baseline outlook through the 2030s projects deficits generally in the 5–7% of GDP range, rising to roughly 6.9% of GDP by 2034, not a clearly sustained 8% for several straight years—though future policy changes could alter that.(crfb.org)
• Because we are only ~1–2 years into that 4–6 year window, we don’t yet know if the U.S. will actually run 8%-of-GDP deficits for that long.

2. The interest-rate outcome window is also still open

• Chamath’s claim was that if those ~8% deficits persist for 4–6 years, then the 10‑year Treasury yield will be around 7–8% during that period.
• So far, the 10‑year yield has stayed much lower. Fed data and market trackers put the 10‑year around 4.0–4.1% in late November 2025,(tradingeconomics.com) and analysis from T. Rowe Price notes a recent peak near 4.79% on January 14, 2025, still well below 7–8%.(troweprice.com)
• However, the prediction is about yields sometime during the full 4–6 year span, not specifically by 2025. Future rate spikes (or policy shifts) between 2026–2030 could still move the 10‑year into his 7–8% range.

Because:

• we do not yet know whether the U.S. will actually maintain ~8% of GDP deficits for 4–6 years, and
• we still have several years in the stated window during which the 10‑year yield could, in principle, reach 7–8%,

there isn’t enough information yet to classify the prediction as right or wrong. The appropriate status as of now is: inconclusive (too early to tell).

Chamath’s prediction covered two linked claims for H1 2025: (1) tech-related M&A would stay “pretty subdued” with no wave of “crazy” mega-deals, and (2) only a small number of big, well-known private tech companies would IPO.

1. Tech M&A was not subdued and did see a wave of large deals
Multiple data sets and industry reports show that, by mid‑2025, tech M&A was running hot, not subdued:

• Corum Group’s H1 2025 tech M&A index reports 3,113 tech M&A deals vs 2,296 in H1 2024 (+36% volume) and deal value up 40% YoY, with megadeals ($1B+) rising from 31 to 40 in H1 2025. This is explicitly described as a “surge” in tech M&A. (corumgroup.com)
• A technology M&A outlook summarizing PwC data notes that in H1 2025 technology accounted for 78% of TMT deal volume and 83% of TMT deal value, describing the sector as leading a broader M&A boom. (legacyadvisors.io)
• Mergermarket data (via CNBC) shows that while global deal count hit a 20‑year low, total M&A value in H1 2025 was about $2T, up 25% YoY, explicitly “buoyed by a flurry of mega deals across U.S. tech, Chinese banking and Japan’s auto sector.” (cnbc.com)
• Dealogic data reported by FastBull indicates 17,528 global M&A deals in H1 2025 vs 20,583 a year earlier, but overall value up 26%, driven by a 62% surge in deals over $10B by June 27, 2025. (fastbull.com)
• A CB Insights / EquityZen “State of Tech Exits H1’25” summary describes “record-breaking M&A in AI”, highlighting landmark deals such as OpenAI’s $6.5B acquisition of Io and Databricks’ $1B acquisition of Neon, and characterizing H1 2025 tech M&A as unusually strong rather than quiet. (crowdfundinsider.com)

Collectively, these sources show that H1 2025 featured a high volume and value of tech deals and a sharp jump in large/mega transactions, including in U.S. tech, which is the opposite of “pretty subdued” or “no crazy M&A deals that everybody is expecting.” On the M&A dimension, his prediction was clearly falsified.

2. Big‑name tech IPOs: window opening, but still a limited set of large unicorn listings
On IPOs, the picture is more mixed and actually closer to what he described:

• EY’s Global IPO data for H1 2025 show 539 IPOs worldwide raising $61.4B, with the U.S. leading at 109 IPOs, its busiest first half since 2021, but still far from 2021’s frenzy. (proactiveinvestors.com)
• A CB Insights / EquityZen "Tech Exits H1’25" report explicitly says the tech IPO market remained muted in H1’25, even as it notes that high-profile unicorn exits like CoreWeave’s Q1 2025 IPO were important outliers. (crowdfundinsider.com)
• Stripe and Databricks—the exact scale of companies Chamath alluded to—remained private as of late 2025. Stripe is still not publicly traded and continues to handle liquidity via large tender offers rather than an IPO, explicitly noted as delaying IPO plans. (fool.com) Databricks likewise has major product and partnership announcements in 2025 but no public listing. (en.wikipedia.org)
• That said, several large and well-known tech/fintech/crypto companies did complete IPOs in H1 2025, including:
  • CoreWeave, an Nvidia‑backed AI cloud provider, which went public on March 28, 2025, raising about $1.5B at roughly $19–23B valuation, widely described as the largest U.S. tech IPO since 2021. (en.wikipedia.org)
  • SailPoint, an identity‑security software company returning to public markets, which raised about $1.38B at a valuation above $12B in its February 2025 Nasdaq IPO. (investors.com)
  • eToro, the social trading platform, which listed on Nasdaq in mid‑May 2025, raising roughly $310–620M at a valuation around $5.5–5.6B, and was billed as a major fintech IPO. (coindesk.com)
  • Circle Internet Group, issuer of the USDC stablecoin, which listed on the NYSE on June 4, 2025; underwriters and company disclosures indicate around $1.1–1.2B in proceeds and a multibillion‑dollar valuation. (circle.com)
  • Chime, a prominent U.S. neobank, which priced its IPO on June 11, 2025 and began trading June 12, raising about $864M and valuing the company at roughly $11.6B. (reuters.com)

Relative to the huge backlog of late‑stage tech unicorns, this is a short list of major IPOs rather than a broad rush of Stripe/Databricks‑scale giants. Independent analyses consistently describe H1 2025 tech IPO activity as cautious or "muted" compared with past booms, even while acknowledging that a few high‑profile deals signaled that the window was beginning to reopen. (crowdfundinsider.com)
So his qualitative call that “not a lot” of the very biggest private tech names would go public in H1 2025 is directionally reasonable, even though more sizable IPOs happened than a strict pessimist might have expected.

Overall assessment
Because the M&A portion of Chamath’s forecast was decisively wrong—H1 2025 tech M&A featured a sharp resurgence and a surge in large and mega‑deals rather than being “pretty subdued”—the combined prediction did not come true, even though his skepticism about a broad wave of mega‑unicorn IPOs was closer to how H1 2025 actually played out.

Therefore, the best overall verdict on this prediction is: wrong.

As of 30 November 2025, it is too early to determine whether this prediction is right or wrong.

Key reasons:

1. Timeline explicitly extends to 2026. The prediction describes a target to accomplish this by 2026 (the U.S. 250th anniversary). That deadline is in the future relative to the current date, so we cannot yet judge success or failure.
2. Outcome depends on future administrative actions. Whether a Trump administration (if in office and empowered to act) will, in practice, substantially dismantle parts of the federal apparatus using the mechanisms described (radical transparency, case-law-driven rollbacks, etc.) can only be evaluated after the 2026 target period has passed.

Because the core claim is about what will be attempted and accomplished by 2026, and we are still before that deadline, the correct classification is "inconclusive (too early)".

The prediction explicitly gives an eight‑year window from November 2024 (“in the next eight years”). That window runs until roughly November 2032. As of the current date (November 30, 2025), only about one year has elapsed, so it is too early to determine whether Democrats will “lose one of California or New York” (via losing the governorship or a durable statewide majority) within that full time frame. Because the deadline has not yet passed, the prediction cannot be evaluated for accuracy at this point.

Trump did win in 2024 and began a second term on January 20, 2025, so the context for Chamath’s prediction is in place.

So far, there have been some notable, administration-led transparency moves:

• Assassination records declassification: Trump signed Executive Order 14176 on January 23, 2025, ordering declassification of JFK, RFK, and MLK assassination files. Tens of thousands of pages were released by the National Archives in March–July 2025, described as a significant disclosure of long‑withheld intelligence and law‑enforcement records.
• Epstein Files Transparency Act: In November 2025, Trump signed a bipartisan law requiring DOJ to make all unclassified Jeffrey Epstein–related records public in a searchable, downloadable form within 30 days and to give Congress an unredacted list of officials and politically exposed persons named in those files. DOJ is now in court seeking to unseal previously protected grand‑jury materials under that mandate.

Those steps clearly move in a transparency direction on highly sensitive subjects and involve large document dumps of internal government records. That is partly in the spirit of what Chamath described.

However, there are important caveats:

• The Epstein law was driven mainly by Congress, over initial resistance from Trump and his team, who lobbied Republicans to block it before ultimately acquiescing and signing once overwhelming majorities forced the issue. That weakens the claim that it reflects a Trump‑led push.
• Trump did sign EO 14149, “Restoring Freedom of Speech and Ending Federal Censorship,” which orders an investigation of past government “censorship” activities, but so far there is no evidence of a broad, Twitter‑Files‑style public release of internal emails or chats arising from that order. Searches for any such “censorship files” or similar initiative turn up nothing beyond the EO itself and commentary on it.
• At the same time, parts of the administration are moving against transparency: the Pentagon has imposed unprecedented restrictions requiring reporters not to publish even unclassified information without prior approval, a new White House‑linked “Department of Government Efficiency” (DOGE) was deliberately structured to dodge FOIA until a judge ordered it to release records, and the Defense Department has been deleting DEI‑related historical content from its public sites under Trump’s DEI‑rollback order. These trends run counter to a general “radical push to transparency.”

Crucially for Chamath’s specific image of “a version of the Twitter files for the government,” there is, as of November 30, 2025, no clearly documented, administration‑orchestrated mass release of contemporary internal government communications (emails, chats, etc.) analogous to the original Twitter Files project. The large releases we do see are mostly historic archival records (JFK/RFK/MLK, and soon Epstein) rather than a systematic, contemporaneous exposé of present‑day government operations.

Since Trump’s term runs through January 2029, there is still ample time for such a Twitter‑Files‑style disclosure effort to occur, or for a broader, more consistent transparency agenda to emerge. Based on available evidence up to November 30, 2025, the prediction is neither clearly fulfilled nor clearly falsified: we see partial alignment (notable document‑dump transparency moves) but also strong counter‑evidence (secrecy and control in other domains, and no clear Twitter‑Files‑equivalent yet).

Given that the key elements could still materialize later in the term, the fairest classification at this point is “inconclusive (too early)” rather than “right” or “wrong.”

Trump did win the 2024 election and began his second (non‑consecutive) term on January 20, 2025, so the prediction’s time window (his “upcoming term”) runs from January 20, 2025 until January 20, 2029 and is still ongoing as of November 30, 2025. (en.wikipedia.org)

On the JFK files: Trump signed Executive Order 14176 on January 23, 2025 directing declassification of JFK, RFK, and MLK assassination records. A large tranche of JFK records (over 60,000 documents / 77,000+ pages) was released in March 2025, significantly expanding public access to the files. (en.wikipedia.org) However, reporting indicates at least some historically noted material (e.g., a Mexican government report allegedly blaming Cuba) still has not surfaced publicly, so even here it is debatable whether all “JFK files” are truly public. (washingtonpost.com)

On the Epstein files and “dirty lists”: In November 2025 Trump signed the Epstein Files Transparency Act, which requires the DOJ to release all unclassified Epstein‑related DOJ records in a public, searchable format and to give Congress an unredacted list of all government officials and politically exposed persons named in those files. The law sets a 30‑day deadline from signature, implying a target around December 19, 2025 for the public release. (en.wikipedia.org) As of November 30, 2025, news coverage still describes these releases as upcoming or in process, not completed; the full set of DOJ files and any comprehensive official “dirty list” have not yet been made public.

Because:

• Trump’s term still has more than three years remaining, and
• the core parts of the prediction about Epstein‑related files and associated lists hinge on actions that are legally mandated but not yet carried out as of the evaluation date,

it is too early to determine whether Chamath’s prediction will ultimately be correct. Some steps (notably on JFK records) have moved in the direction he described, but the key conjunctive claim—that during this term we will “see the Epstein files,” “the dirty lists,” and “the JFK files”—cannot yet be judged fulfilled or disproven. Hence the status is best classified as inconclusive (too early to tell).

Evidence from the first year of Trump’s second term shows a deliberate, multi-front push to declassify and release previously non‑public federal information, especially in the early months, which broadly matches Chamath’s prediction about “phase one.”

Key points:

• Early executive order focused on declassification: On January 23, 2025, just three days into his second term, Trump signed Executive Order 14176 directing the declassification of remaining records related to the assassinations of John F. Kennedy, Robert F. Kennedy, and Martin Luther King Jr.(en.wikipedia.org)
• Large volumes of previously withheld records released online: Following that order, the National Archives released about 77,000 pages of assassination-related records between March 18–20, 2025, making them accessible via a centralized public webpage; officials and allies described this as a “new era of maximum transparency.”(en.wikipedia.org)
• Ongoing declassification/transparency push in the intelligence community: Director of National Intelligence Tulsi Gabbard set up the Director’s Initiatives Group to review documents for declassification, dismantle politicization, and increase transparency across the intelligence community, explicitly framed as carrying out Trump’s transparency-focused executive orders.(dni.gov)
• Broader set of disclosure initiatives (Epstein, etc.): The administration publicly committed to declassifying files on Jeffrey Epstein, 9/11, COVID‑19 origins, and UFOs; this was followed by the bipartisan Epstein Files Transparency Act, passed almost unanimously in Congress and signed by Trump on November 19, 2025, requiring DOJ to release all unclassified Epstein-related records within 30 days.(thetimes.co.uk)
• Additional declassified analytic products: A declassified CIA assessment on COVID‑19’s origins was released under Trump’s CIA director (implementing an earlier law but executed as part of the broader transparency framing), further adding to the volume of previously non-public intelligence material made public.(apnews.com)

At the same time, there has been an aggressive removal and suppression of other federal data and web resources—over 8,000 webpages and about 3,000 datasets (often on DEI, gender, public health, and climate) were taken down or altered after Trump’s early 2025 executive orders, which clearly cuts the other way on overall openness.(en.wikipedia.org) This means the reality is mixed and falls short of the “Twitter files for the whole federal government” vision Chamath described.(podcasts.happyscribe.com)

However, judged narrowly against the specific normalized prediction—that the initial phase of the new Trump administration would feature a broad declassification/data‑release drive making large amounts of previously non‑public federal information openly accessible—the substantial, early, and ongoing declassification and document‑release campaign around assassinations, intelligence products, and Epstein does fit that description. Hence the prediction is best scored as right, while noting that it coexists with major efforts to restrict access to other categories of government information.

The prediction describes a roughly 20‑year era starting in the early–mid 2020s that, in hindsight, will be seen as a systemic “return to originalism” in U.S. policy and jurisprudence. As of today (November 30, 2025), only a few years of that window have elapsed, so we cannot yet assess how the entire 20‑year span will look in retrospect.

Current evidence does show that originalism remains highly influential on the Supreme Court and in legal scholarship – for example, ongoing debates about originalist methods and precedent, and analysis of recent major decisions that rely on originalist reasoning. (harvardlawreview.org) But those facts only establish that originalism is important now, not that the next two decades of American governance will, on net, be remembered as an overarching “return to originalism.”

Because:

1. The prediction is explicitly about a multi‑decade historical judgment (“we’re going to look back on this era… about 20 years or so”), and
2. We are only ~1–5 years into the asserted time frame,

there is not yet enough elapsed time or hindsight to determine whether the United States will, overall, fit Chamath’s long‑range characterization.

Therefore the status of the prediction is inconclusive (too early to tell).

Chamath’s prediction on the Nov. 8, 2024 All-In episode was not just that he wanted David Sacks to be governor of California, but that he would convince Sacks within two years to do it ("within two years I will have convinced him to do it").(happyscribe.com)

As of the current date (Nov. 30, 2025), public records of the 2026 California gubernatorial race list numerous declared candidates, but David Sacks is not among them.(en.wikipedia.org) Instead, Sacks is serving in a federal role as the White House AI and Crypto Czar and co‑chair of the President’s Council of Advisors on Science and Technology in the Trump administration, not preparing a gubernatorial campaign.(en.wikipedia.org)

However, the two‑year window Chamath himself referenced runs until roughly November 2026, and it is still at least theoretically possible that Sacks could be persuaded to run for governor (whether in the 2026 race via a late entry or in a later cycle). Because that self‑imposed deadline has not yet passed and there is no definitive evidence that such persuasion is impossible, the prediction cannot yet be judged as either fulfilled or failed.

Given the available evidence and remaining time window, the status of this prediction is too early to call.

The prediction window is “within two years” of the November 8, 2024 recording, i.e., by roughly November 8, 2026. As of November 30, 2025, that deadline has not yet arrived, so the prediction cannot be finally judged.

Available reporting and biographical sources describe David Sacks as serving as Trump’s White House AI and cryptocurrency czar and as co‑chair/chair of the President’s Council of Advisors on Science and Technology; they do not report him announcing or running a campaign for governor of California, nor do they say he has decided to run. (en.wikipedia.org) Some coverage even notes that Sacks has publicly stated he has no intention of running for public office, but that is about his stated intent, not whether Chamath might yet “convince” him by late 2026. (panewslab.com)

Because:

• The prediction’s deadline (Nov 2026) is still in the future; and
• Whether Sacks has been internally convinced to run is not fully observable from public records,

the most appropriate status as of Nov 30, 2025 is: inconclusive (too early to tell).

As of November 30, 2025, no major U.S. tech conglomerate such as Alphabet/Google, Meta, Apple, Amazon, or Microsoft has actually been broken up into separate companies by regulators or markets.

• Alphabet (Google) remains a unified public company, though it faces multiple U.S. antitrust lawsuits (e.g., DOJ search and ad-tech cases) and EU regulatory actions, none of which have yet resulted in a court-ordered breakup or formal corporate split into distinct listed entities.
• Similarly, Amazon, Apple, Meta, and Microsoft have ongoing antitrust and regulatory scrutiny but no consummated structural breakups.

However, Chamath’s prediction did not include any time constraint; he simply asserted that such breakups “will happen” at some point in the future. Since:

1. The predicted event (breakups) has not yet occurred, and
2. The prediction’s time horizon is effectively open-ended (no deadline by which it had to be true),

we cannot yet judge it as definitively right or wrong. It remains unresolved, so the appropriate classification is “inconclusive (too early)”.

Key parts of Chamath’s prediction have, on balance, played out as he described, though some language (like “overwhelmingly”) was stronger than what most models showed at the time.

1. “Overwhelmingly to a Trump win” / markets correctly pricing it in

   • Donald Trump did win the 2024 U.S. presidential election, 312–226 in the Electoral College and by about 1.5 percentage points in the popular vote. (en.wikipedia.org)
   • On October 25, 2024, major prediction markets like Polymarket priced Trump around the low‑to‑mid 60s in win probability (≈63–66%), briefly spiking to 99% only because a single whale trade cleared the order book. (xbo.com)
   • A side market on Polymarket tracking Nate Silver’s Silver Bulletin forecast resolved that Trump’s model odds on October 25 did not exceed 55%, implying a more modest edge there. (polymarket.com)
   • National polling averages in late October still showed a very close race, often with a slight Harris popular‑vote lead. (en.wikipedia.org)
     Assessment: Markets were indeed leaning Trump and that “tilt” proved directionally correct, but “overwhelmingly” overstates how lopsided the probabilities actually were. This makes the framing somewhat exaggerated but not flatly wrong.

2. Conditional macro/market call if Trump won
   Chamath’s concrete claims were that, if Trump won by a solid margin, in the short term: (a) gold would go up more, (b) Bitcoin would go up, (c) equity prices would move higher, and (d) long‑term U.S. rates would move higher.

   • Gold: In October 2024, gold closed the month around $2,744/oz; it dipped slightly in November–December (closing about $2,654 and $2,624) but then moved sharply higher through 2025, with monthly closes above $3,100 by March and around $3,29x–3,30x by mid‑year, and later records above $4,300 by October 2025. (statmuse.com) Over the months following Trump’s win, the dominant trend was strongly upward, consistent with his “gold’s going to go up more” claim, even though there was a brief post‑election wobble.
   • Bitcoin: Bitcoin closed October 2024 at about $70,215. In November—immediately following the November 5 election—it rallied to a ~$96,449 month‑end close (+37% MoM), remained in the low–mid $90Ks in December, and moved above $100K in January 2025, before eventually hitting new all‑time highs around $125K in October 2025. (statmuse.com) This clearly fits “Bitcoin will probably go up.”
   • Equities: The S&P 500 closed October 2024 at about 5,705 and then rose to ~6,032 by end‑November and ~5,882 at end‑December, leaving it clearly above pre‑election levels. (statmuse.com) U.S. equities continued to advance in 2025, with the S&P 500 above 6,700 by late November 2025. (apnews.com) This matches his expectation that “higher equity prices” would reflect short‑term economic upside.
   • Long‑term U.S. rates: The 10‑year Treasury yield was around 4.10–4.20% in early/late October 2024, then rose to about 4.36% on November 1 and 4.39% on December 1, later peaking near 4.63% in January 2025 before easing a bit. (value-trades.com) That pattern—yields moving noticeably higher in the months after the election—is in line with his call that “it’ll also push out long term rates.”

Overall:
Trump did win, and in the months after his victory, gold, Bitcoin, major U.S. equity indices, and long‑term Treasury yields all moved higher from late‑October/early‑November 2024 levels, as Chamath predicted. The only real quibble is his rhetorical choice of “overwhelmingly” to describe pre‑election odds, which were more like a solid but not lopsided Trump edge. Given that the core directional and conditional parts of the forecast came true, this prediction is best classified as right, with some overstatement in how he described the degree of market confidence before the vote.

Trump did win the November 2024 U.S. presidential election and took office in January 2025, satisfying the prediction’s initial condition. His administration has implemented notable parts of an economic program, including broad new tariffs and a Strategic Bitcoin Reserve / digital‑asset stockpile, which are relevant to inflation and to crypto markets. (en.wikipedia.org)

Inflation so far (up to late 2025):

• Headline CPI inflation has generally run around 2.3–3.0% year‑over‑year in 2025, slightly below or similar to 2024’s average (~3%). A monthly table of 12‑month CPI changes shows 2024 annual inflation at 2.95% and 2025 readings in the low‑to‑mid‑2% range through at least August. (in2013dollars.com)
• July 2025 CPI was 2.7% year‑over‑year, with core CPI at 3.1%, a modest uptick attributed in part to Trump’s tariffs, but not a clear break to significantly higher inflation versus the prior year. (reuters.com)
• Consensus forecasts from the National Association for Business Economics see inflation easing slightly from about 2.9% at end‑2025 to 2.6% in 2026, suggesting no confirmed sustained move to higher medium‑term inflation yet. Market‑based 5‑year inflation expectations have ticked up somewhat (to around the mid‑3% range), but these are expectations, not realized medium‑term outcomes. (reuters.com)

Because “medium term” in the user’s normalization is roughly 1–3 years after inauguration, we are less than one full year into that window (late 2025 vs. a January 2025 start). Realized inflation so far has not clearly moved higher than the pre‑Trump baseline, and we do not yet have data for the bulk of the 1–3‑year period. So the core claim that U.S. inflation will rise in the medium term under Trump’s program cannot yet be definitively judged.

Bitcoin and gold as hedges:

• Gold has strongly appreciated during Trump’s new term. The average gold price in 2024 was about $2,388/oz; in 2025 the average is over $3,400/oz with prices recently above $4,000/oz, implying roughly a 60% gain year‑to‑date and multiple new all‑time highs. Analysts and news coverage frequently tie this rally to safe‑haven demand amid tariff‑driven uncertainty, concerns over U.S. debt, and inflation / policy risks—consistent with gold trading as an "uncertainty/inflation hedge." (statmuse.com)
• Bitcoin has also appreciated sharply relative to pre‑election levels. It rose from about $44,000 on Jan 1, 2024 to around $94,000 on Jan 1, 2025, and then to record highs above $120,000 in 2025 before pulling back to the high‑$80Ks to ~$90K range. This run‑up overlapped with Trump’s election victory and subsequent crypto‑friendly measures, including the Strategic Bitcoin Reserve, which commentators describe as a major factor in the 2024–2025 surge. (in2013dollars.com)

These asset‑price moves fit Chamath’s view that Bitcoin and gold would “trade that way” as hedges in a Trump scenario, but the explicit prediction you supplied is about inflation rising in the medium term and therefore those hedges performing.

Given that:

• The conditional event (Trump winning and implementing a program) has happened.
• Bitcoin and gold have indeed appreciated strongly in a way consistent with hedge behavior.
• But the key macro piece—a clear, sustained increase in U.S. inflation in the 1–3 years after inauguration—cannot yet be confirmed, and the available data to date do not show a decisive move higher versus the pre‑Trump period.

The fairest overall assessment as of November 30, 2025 is “inconclusive (too early)” rather than clearly right or wrong.

This prediction is explicitly about the long term ("for the next 50 or 100 years"), so as of November 30, 2025—barely a year after the statement—it is far too early to determine whether Bitcoin will:

1. Persist as the dominant global inflation‑hedging asset for decades, and
2. Structurally displace gold’s role as the primary rational economic insurance policy against inflation.

While we can currently observe that:

• Bitcoin has at times outperformed gold over shorter windows and is increasingly discussed as a macro or "digital gold" asset in financial media and institutional commentary.
• Gold still has a vastly larger total market value, is widely held by central banks and institutions, and remains the canonical inflation hedge in traditional finance and reserve management.

…none of this evidence is sufficient to validate or falsify a 50–100 year structural claim. Market leadership as an inflation hedge, central‑bank reserve behavior, regulatory treatment of Bitcoin, technological risks, and macro regimes will all evolve over many decades.

Because the prediction’s time horizon extends out to roughly 2074–2124, and we are only in 2025, the correct assessment is that it is too early to tell whether the prediction is ultimately right or wrong.

Based on the actual 2024 U.S. election outcome, Kamala Harris did not win the November 2024 presidential election; Donald Trump won the presidency. This is reported in major U.S. and international coverage of the 2024 election results and subsequent inauguration coverage.

Because Chamath’s prediction was explicitly conditional — "what happens if Kamala Harris wins" — the condition (Harris winning) never occurred. The forecast concerned how markets would react in that counterfactual scenario, so we cannot empirically test whether the stated reversals in long‑term yields, the dollar, and flows into gold/Bitcoin/equities would have happened.

Since enough time has passed but the antecedent did not occur, the correctness of the prediction cannot be determined from real‑world data, making it ambiguous rather than right, wrong, or merely too early to tell.

Chamath’s claim was that, given the then‑record level of the Buffett Indicator, U.S. equities were likely to become cheaper before they got more expensive.

On the episode date (Oct 25, 2024), they explicitly note that the market‑cap‑to‑GDP ‘Buffett Indicator’ had reached a new all‑time high, implying very stretched valuations.【0search2】 This aligns with outside reporting that by late 2024 the Buffett Indicator was near or above ~200%, its prior “danger” zone peak.【6news15】

Pricewise, the S&P 500 closed at 5,808.12 on 2024‑10‑25.【5view0】 After further gains into late 2024 and early 2025, a Trump‑driven tariff shock in early April 2025 triggered a sharp selloff: FRED data show the S&P 500 falling to 4,982.77 on 2025‑04‑08, clearly below the 5,808 level on the podcast date, and nearly 19% below its then record high.【5view0】2search3】1news14】 That is a material correction and unquestionably “cheaper” than on Oct 25, 2024.

Valuation metrics moved the same way. Coverage of the Buffett Indicator notes it surged past 200% in late 2024, then dropped from about 208% in mid‑February 2025 to roughly 180% by April 2025—a ~13.5% decline—due to that market pullback.【6search4】6news13】 That means broad equity valuations (market cap vs. GDP) were indeed lower than around the time of his comment.

After this correction, equities did in fact “get more expensive”: the S&P 500 recovered and went on to new record highs above 6,173 in June 2025 and later higher still in October 2025.【1search1】1news14】

Because U.S. equities first became meaningfully cheaper than at the time of his statement and then moved to substantially higher levels, the specific prediction that “equities are probably going to be cheaper before they’re going to get more expensive” describes what actually happened.

The prediction is explicitly about the next decade after October 25, 2024, i.e., roughly through October 2034. As of today (November 30, 2025), only a bit more than one year of that 10‑year window has passed, so we cannot yet know whether U.S. Treasury yields will spend a sustained period in the 6–8% range.

What we can observe so far is that the 10‑year U.S. Treasury yield in late 2025 is around 4.0%: recent data show it at about 4.0–4.1% in November 2025, below both the historical long‑term average (~5.8%) and well below the 6–8% band Chamath mentioned.

• YCharts reports the 10‑year at 4.01% on November 25, 2025, with commentary that this is under the long‑term average of 5.82%. (ycharts.com)
• TradingEconomics/Fed data similarly place the November 2025 10‑year constant‑maturity yield around 4.0%. (tradingeconomics.com)
• Other market commentary through mid‑2025 also discusses 10‑year yields in the mid‑4% area, not near 6–8%. (pnccapitaladvisors.com)

However, the core claim is about where the fair/market‑clearing yield ends up “over the next decade,” and specifically whether it could be stably in the 6–8% range for a meaningful period. Since most of that decade is still in the future, we cannot yet label the prediction as right or wrong; it is simply too early to tell.

Public data show two key things since October 25, 2024:

1. GLP‑1 adoption clearly kept rising.

   • Multiple reports in 2025 describe GLP‑1 weight‑loss and diabetes drugs (Ozempic, Wegovy, Mounjaro, Zepbound, etc.) going from niche to mainstream, with about 1 in 8 Americans (≈12–13% of adults) using a GLP‑1 by late 2025, up from lower levels in 2023–24. (axios.com)
   • These articles emphasize rapid growth in prescriptions and widespread cultural impact, confirming the “GLP‑1 adoption increases across the U.S.” part of the prediction.

2. Starbucks’ same‑store sales did not keep falling as GLP‑1 adoption rose.
   Around the time of the prediction, Starbucks’ U.S. comparable store sales were already under pressure: Q3 FY2024 U.S. comps were –2%, and preliminary Q4 FY2024 results showed a 6% decline in U.S. comparable sales, driven by a 10% drop in transactions. (investor.starbucks.com)
   After the prediction, however, the pattern is:

   • Q1 FY2025 (reported Jan 2025): global same‑store sales –4%, North America –4%. (theguardian.com)
   • Q2 FY2025 (quarter ended Mar 30, 2025): global comps –1%; U.S. comps –2%. (investor.starbucks.com)
   • Q3 FY2025 (quarter ended Jun 29, 2025): global comps –2%; U.S. comps –2%. (investor.starbucks.com)
   • Q4 FY2025 (quarter ended Sep 28, 2025): global comparable store sales increased 1%, and U.S. comps were flat (0%), with September turning positive. Starbucks highlighted this as the first quarter of global comp growth after seven quarters of declines. (investor.starbucks.com)
   • For the full FY2025, global comps were –1% and U.S. comps –2%, but importantly, the direction stopped being “continuously down” by Q4 FY2025. (investor.starbucks.com)

Chamath’s normalized prediction was stronger than just “GLP‑1 will be a headwind.” He said that as GLP‑1 adoption goes up, Starbucks same‑store sales will continue to go down, and framed this as something Starbucks couldn’t fix with its then‑current offering. In reality, during a period when GLP‑1 usage became mainstream and kept rising, Starbucks’ comps:

• Declined for a while, but
• Then stabilized and turned (slightly) positive globally and flat in the U.S. in Q4 FY2025, even as GLP‑1 adoption remained high and rising.

Because we now observe a quarter where GLP‑1 penetration is higher than ever yet Starbucks’ same‑store sales are no longer falling, the strong directional claim that “as GLP‑1 adoption goes up, same‑store sales will continue to go down” is not borne out by the data. Confounding factors (new CEO, turnaround strategy, pricing, operations, macro environment) make causality murky, but on the literal prediction of ongoing declines with rising GLP‑1 use, the realized sales trajectory contradicts it. Therefore, the prediction is best classified as wrong.

The prediction explicitly sets a 5–10 year horizon from the time of the statement (roughly 2029–2034) for substantial advances in compute‑driven materials/specialty chemicals and the emergence of many new non‑nuclear, higher‑energy‑density businesses. As of today (November 30, 2025), we are only about one year into that window, so the timeframe the predictor specified has not yet elapsed. While there is active work in computational materials science, battery chemistry, and related areas, it is too early to judge whether the scale and business impact he forecast ("a lot of businesses" and a substantial increase in generally available energy density from non‑nuclear technologies) will materialize by 2029–2034. Therefore, the correctness of this prediction cannot yet be determined.

The prediction is explicitly about a future condition: when AI and broader technological innovation in the U.S. become genuinely constrained (“rate limited”) by energy. Chamath further frames this in a multi‑decade horizon (“by the time that you are rate limited by energy”). As of November 30, 2025, two key facts make this impossible to judge:

1. AI is not yet clearly “rate limited” by energy in the sense described. There are growing concerns about AI’s energy usage and data centers straining grids, but these have not yet become the dominant hard cap on AI progress; the main constraints remain capital, talent, hardware, and regulation. This means the condition “by the time you are rate limited by energy” has not decisively arrived.
2. The prediction’s timeframe extends well beyond 2025. It concerns what the energy landscape will look like when/if that energy constraint finally bites, which Chamath suggests could be in the next couple of decades. That point has not yet been reached, so we cannot test whether there is indeed a “plethora of solutions” versus a single bottleneck technology.

Because the triggering scenario (AI being truly rate‑limited by energy) has not clearly occurred yet and the relevant time window has not elapsed, the prediction cannot be evaluated at this time.

Chamath’s prediction was that, as a result of the DOJ’s antitrust actions against Google, there would be a structural remedy (e.g., divestiture or breakup of business units) rather than Google remaining intact with only behavioral remedies.

What actually happened in the key DOJ cases as of 30 November 2025:

1. Search monopoly case (United States v. Google LLC, 2020 case)

   • After finding Google had illegally maintained a monopoly in search in August 2024, Judge Amit Mehta held a remedies trial in 2025. (en.wikipedia.org)
   • In his September 2025 remedies ruling, Mehta explicitly rejected DOJ’s request to force Google to divest Chrome or break up Android, calling such forced divestiture an overreach. (theguardian.com)
   • Instead, the court imposed behavioral / conduct remedies: banning Google from exclusive search-distribution deals for Search, Chrome, Gemini, and Google Assistant; prohibiting certain tying and pre‑load conditions; and requiring Google to share portions of its search index and related data with competitors. Google remains intact as a single company owning Chrome, Android, and its core businesses. (androidheadlines.com)
   • Commentators widely characterized the outcome as a relatively lenient, conduct-focused remedy rather than a breakup. (theguardian.com)

2. Ad‑tech monopoly case (United States v. Google LLC, 2023 case)

   • Judge Leonie Brinkema ruled in April 2025 that Google illegally monopolized parts of the ad‑tech stack (publisher ad server and ad exchange). (en.wikipedia.org)
   • The DOJ is seeking structural remedies (divestiture of AdX and possibly parts of Google Ad Manager), but as of late 2025 no remedies order has been issued. Hearings on remedies concluded in fall 2025, and Brinkema has signaled reluctance to order a breakup, showing preference for behavioral and interoperability remedies instead. (grokipedia.com)

Across the DOJ’s major Google cases, no structural breakup or forced divestiture has actually been imposed to date. The one case where remedies have been decided (search) resulted in Google remaining intact with conduct-based and data‑sharing obligations, not the kind of structural remedy Chamath predicted. Therefore, given the current record, his prediction is wrong.

As of November 30, 2025, it is too early to determine whether Chamath’s five‑year prediction (deadline October 11, 2029) will come true.

Key facts:

• The U.S. Department of Justice (DOJ) and state attorneys general have active antitrust cases against Google, notably over search and advertising practices. In the search case (filed 2020), a federal judge ruled in August 2024 that Google illegally maintained a monopoly in search, and the case moved into a remedies phase where potential solutions — including behavioral and structural remedies — are being considered, but no final remedy order has yet been issued.
• Reporting on the remedies phase consistently describes that possible outcomes could include changes to default search agreements or aspects of Google’s ad tech stack, but as of late 2025 there has been no court‑ordered breakup or mandated divestiture of Chrome, Android, or major ad businesses, nor any other confirmed “forced structural remedy.” (This is based on current coverage of the DOJ v. Google proceedings and follow‑up reporting on the remedies phase.)

Because the prediction explicitly allows the full window through October 11, 2029, and we are only in 2025 with remedies still under consideration and litigation ongoing, the correct classification today is:

• Result: inconclusive – The prediction could still become true or false; the outcome of the DOJ’s remedies process and any appeals is not yet known, and the deadline has not arrived.

Available evidence from the 2024 U.S. election cycle supports Chamath’s framing that state-backed social‑media influence campaigns caused information chaos but did not clearly swing the election outcome.

Multiple foreign governments, notably China and Russia, ran coordinated online influence operations using fake personas, networks like China’s “Spamouflage,” and covertly funded influencers to push divisive narratives and undermine confidence in U.S. institutions across platforms such as X and TikTok. These efforts aimed to stir domestic divisions, promote conspiracy theories, and erode trust in elections rather than overtly support a single candidate in China’s case, while Russia focused on boosting Trump and damaging Democrats via paid American influencers and disinformation channels. (en.wikipedia.org)

However, U.S. cyber‑ and election‑security officials, as well as independent researchers, reported no evidence that foreign operations or hacking materially affected vote tallies or the overall outcome of the 2024 presidential election. CISA director Jen Easterly stated there was “no evidence of activity that has the potential to materially impact the outcome of the presidential election,” and academic work similarly notes no evidence that foreign hackers have successfully altered vote counts, while think‑tank analysis finds AI‑enabled foreign influence campaigns had limited engagement and did not transform their effectiveness. (justice-integrity.org)

At the same time, the U.S. response to TikTok—culminating in the Protecting Americans from Foreign Adversary Controlled Applications Act and a de jure nationwide TikTok ban based on concerns over propaganda, misinformation, and foreign influence operations—illustrates how these platforms became focal points for public mistrust, polarization, and political conflict. (en.wikipedia.org) Taken together, the record shows: (1) state‑linked use of influencers and algorithmic amplification on platforms like TikTok contributed to significant social and informational chaos, and (2) there is no credible evidence that these efforts were sufficient to swing the U.S. election result—matching Chamath’s prediction that such campaigns “probably wouldn’t swing an election, but … would cause chaos.”

The prediction has a 5–10 year horizon starting from September 27, 2024, i.e., it is specifically about market conditions sometime between 2029 and 2034. As of today (late 2025), we are only ~1 year into that window, so it is too early to know whether “most enterprises” will abandon legacy-priced systems of record.

What we can see so far:

• There is active technical work and industry interest in AI/agent-based enterprise systems (e.g., agentic ERP and generalist enterprise agents), but these are still framed as emerging approaches or roadmaps, not yet as mainstream replacements for core CRM/ERP/HRIS across most enterprises. (arxiv.org)
• Some high‑profile cases, like Klarna reportedly decommissioning around 1,200 SaaS apps including Salesforce in favor of an internal AI platform, show that early adopters can justify replacing traditional SaaS with AI systems, but this is one company, not evidence about the majority of enterprises. (medium.com)
• Analyst and industry pieces project that by the early‑to‑mid 2030s, AI‑driven “services‑as‑software” or RaaS/agent models may erode traditional license‑based SaaS, but these are forward‑looking forecasts, not outcomes already realized. (horsesforsources.com)
• Current pricing and deployment patterns show that traditional enterprise systems of record (CRM/ERP, etc.) remain widely used and expensive, even as AI features are added on top and some vendors begin experimenting with consumption or agent‑interaction pricing rather than strictly per‑seat licenses. (cqlsys.com)

Because the prediction is explicitly about what will happen over 5–10 years and we are far from the end of that period, and because current evidence shows only early movement rather than a decisive, broad shift where “most enterprises” can no longer justify legacy pricing, the correctness of Chamath’s prediction cannot yet be determined.

As of November 30, 2025, only about 14 months have passed since the September 27, 2024 episode. That is too little time to judge "near to medium term" commercial success or long‑run dominance 25–30 years out.

Early evidence does suggest Meta's Ray‑Ban smart glasses are gaining traction: Meta and EssilorLuxottica report that the Ray‑Ban Meta glasses have been top‑selling products in many Ray‑Ban stores across EMEA and have driven significant sales growth, leading the companies to extend their partnership. (techcrunch.com) Independent reporting and industry analysis also indicate more than 2 million units sold by mid‑2025 with shipments roughly tripling year‑over‑year, framing the line as an early commercial success in a still‑nascent category. (ai-daily.news)

However, "commercially successful in the near to medium term" remains a forward‑looking claim, and the bolder part of the prediction—that the eventual iconic "killer" AI hardware device 25–30 years from now will not resemble today's phones, glasses, pins, etc.—is about technology adoption in the 2050s, which cannot yet be assessed. Since both elements hinge on future outcomes, the prediction cannot currently be judged fully right or wrong.

As of November 30, 2025, the prediction splits into two parts with different levels of support.

1. "AirPods‑style earbuds will evolve into effective hearing aids" – largely correct

   • In September 2024, the U.S. FDA authorized Apple’s Hearing Aid Feature software, allowing AirPods Pro 2 to function as over‑the‑counter (OTC) hearing aids for adults with mild to moderate hearing loss. The FDA notes that in a clinical study, users of the self‑fitting AirPods setup achieved similar perceived benefit and amplification performance as professionally fitted hearing aids, and the feature is explicitly regulated as an OTC hearing‑aid device. (fda.gov)
   • Multiple reports in 2025 describe AirPods Pro 2 as “clinical grade” hearing aids once the software is enabled, and regulators in countries like the UK and Australia have also cleared them as medical devices for mild‑to‑moderate hearing loss. (thetimes.co.uk)
   • Coverage emphasizes that these AirPods‑based aids can meaningfully improve speech understanding and provide benefits comparable to traditional devices for the indicated population. (opb.org)
     Conclusion: The technical/medical part of the prediction—that AirPods‑style earbuds would become genuinely effective hearing aids—has clearly materialized.

2. "…and will become socially acceptable to wear almost continuously (effectively 24/7)" – not yet realized, and constrained

   • Battery and design limitations make continuous or all‑day wear impractical. Typical hearing aids are designed for 12–16+ hours per charge, whereas AirPods Pro 2 used as hearing aids get on the order of 4–6 hours before needing to go back in the case, a gap explicitly noted in consumer and tech reviews that recommend them for occasional or situational use rather than full‑time wear. (cnbc.com)
   • Experts commenting on the new AirPods hearing‑aid capabilities in markets like Australia and in U.S. coverage emphasize that they are “not ideal for all‑day wear” and best suited to situations like restaurants or TV watching, not round‑the‑clock use. (theguardian.com)
   • Health guidance continues to warn against wearing earbuds all day because of ear‑wax build‑up, infection risk, and potential hearing damage from long exposures—again at odds with normalized 24/7 use. (gadget-faqs.com)
   • Socially, while AirPods‑like devices clearly reduce the stigma of visible hearing aids and are framed as a way to make hearing support more acceptable, etiquette commentary still notes that keeping AirPods in during conversations tends to be read as rude rather than neutral, indicating norms have not shifted to “24/7 is fine” across everyday interactions. (opb.org)
   • Adoption data are still early: only a fraction of adults with hearing loss use any hearing aids at all, and reporting describes AirPods hearing‑aid features primarily as an entry point or situational assistive tech, not as a widely adopted, full‑time replacement for traditional hearing aids. (opb.org)
     Conclusion: The specific claim that these devices would become socially acceptable to wear almost continuously (effectively 24/7) has not come true yet and is actively limited by battery life, comfort, health concerns, and remaining etiquette norms.

3. Why the overall verdict is “ambiguous” rather than “right” or “wrong”

   • The core technological prediction (earbuds becoming real hearing aids) is clearly correct.
   • The social/behavioral prediction (24/7 socially acceptable continuous wear) is clearly not our present reality, but the prediction did not include a concrete time horizon, and social norms around wearables can evolve over many years.
   • Because one major component is already correct while the other is both unfulfilled and open‑ended in timing—and because “social acceptability” is inherently hard to measure definitively—it’s not accurate to call the entire prediction simply “right” or “wrong” at this point.

On balance, the evidence supports a mixed outcome: technically right, socially unfulfilled. Given the lack of a clear deadline and the normative nature of the second part, the fairest single label today is "ambiguous."

Chamath’s prediction in the Sept 20, 2024 episode was that once all All‑In Summit clips were released and “baked for a couple of months,” their combined views on YouTube and X would be “around 50 million.” This is explicitly framed in the transcript as a forward‑looking estimate based on roughly 20M early views for about half the clips. (podscripts.co)

What we can verify:

1. YouTube channel totals. The main All‑In Podcast YouTube channel has about 148.6M lifetime views as of Nov 23, 2025; SocialBlade showed roughly 120M views around mid‑2025. (speakrj.com) That 120M figure has to cover:

   • All regular podcast episodes (hundreds of videos since 2020), plus
   • Summit recordings from 2022, 2023, 2024, and early 2025. Given this, it’s unlikely (though not impossible) that 2024 summit clips alone contributed ~50M views on YouTube by early 2025, but the aggregate numbers don’t let us isolate the summit share.

2. Per‑video YouTube views for key 2024 summit talks. Third‑party sites that scrape YouTube give sample view counts such as:

   • Elon Musk | All‑In Summit 2024: ~0.9–1.5M views depending on snapshot. (glasp.co)
   • John Mearsheimer & Jeffrey Sachs | All‑In Summit 2024: roughly 1–2M views across different snapshots. (ytscribe.com)
   • Peter Thiel | All‑In Summit 2024: around 0.7–0.8M views. (metapodcast.net) Even assuming similar or somewhat lower numbers for other big‑name sessions (Sergey Brin, Travis Kalanick, Marc Benioff, JD Vance, Megyn Kelly, etc.), a reasonable estimate for YouTube views across all 2024 summit long‑form videos lands in the single‑digit to low‑teens millions, not obviously near 50M.

3. Historical benchmark from 2023 summit. A LinkedIn recap of the 2023 All‑In Summit notes that the top two panels (Elon Musk; Mearsheimer/Sachs) were at ~955k and ~918k YouTube views respectively, and that the hosts hoped future summit recordings could reach about 50M views on YouTube and X combined. (linkedin.com) This shows the 50M figure was aspirational and that, even after a year, the prior summit’s biggest videos were around the 1M mark each—again consistent with a total far below 50M purely on YouTube.

4. X (Twitter) views are not auditable. Chamath’s 50M target explicitly included X, but:

   • X does not provide a public, summable API endpoint for total video/impression views per campaign.
   • We can see that various summit clips (for example, those shared by the @theallinpod account and amplifying accounts like @tsarnick) were widely circulated, but their individual view/impression counts are not systematically archived by reliable third‑party analytics in a way we can sum across all clips. (gaganghotra.com)
   • No credible article or later podcast segment appears to report a consolidated, verifiable figure like “the All‑In Summit 2024 clips did 50M+ views across YouTube and X.”

5. Timing ambiguity. The prediction was “around 50 million … when all the clips are released and you let it bake for a couple of months.” (podscripts.co) We do not have:

   • a clear public date when all summit clips finished rolling out, nor
   • any third‑party time‑series data tying combined YouTube+X views to that 2–3 month post‑release window.

Given all this:

• We can say with some confidence that YouTube alone appears to fall well short of 50M views for the 2024 summit content in the relevant timeframe.
• However, the prediction was explicitly about YouTube plus X combined, and we lack trustworthy, aggregate X view data to either confirm or rule out the total.
• No later authoritative source (press, analytics firm, or the hosts themselves) publishes a clear combined number that would settle it either way.

Because the necessary cross‑platform view data is not publicly reconstructable—despite enough time having passed—the truth of Chamath’s “~50M combined views” prediction cannot be determined from available evidence, so the correct grading is ambiguous, not confidently “right” or “wrong.”

As of November 30, 2025, the end of 2026 has not yet occurred, so we cannot determine whether the federal funds rate will be in the 2–3% range by that time.

What we can say now:

• The Federal Reserve began cutting rates in 2024–2025 after its earlier hiking cycle, but the current federal funds rate target is still well above 2–3% (exact level depends on the latest FOMC decision, which as of late 2025 remains in the mid‑single digits range, not near 2–3%).
• Because the prediction is specifically about the level of rates by end of 2026, and that date is in the future, there is no way yet to classify the prediction as right or wrong.

Therefore the correct classification at this time is "inconclusive" (too early).

BEA data and subsequent analysis show that U.S. GDP revisions in the quarters after September 2024 were mostly upward or negligible, not “a couple of significant downward revisions” that broadly weakened the growth story.

Key points:

1. Q3 2024: Real GDP was estimated at 2.8% in both the advance and second estimates, then revised up to 3.1% in the third estimate. (bea.gov)

2. Q4 2024: Real GDP came in at 2.3% in the advance and second estimates and was revised up to 2.4% in the third estimate. (bea.gov)

3. Annual revisions for recent years: The 2024 annual update (released Sept. 26, 2024) revised 2019–2023 annual real GDP growth mostly up, not down. The 2025 annual update (released Sept. 25, 2025) explicitly notes that the percent change in real GDP for 2022–2024 was unrevised, meaning no downward reassessment of overall recent growth. (apps.bea.gov)

4. Q1 2025 (the one clear downward revision): Real GDP for Q1 2025 was initially reported at –0.3% (advance), then –0.2% (second estimate), and later revised down to –0.5% in the third estimate; journalists described this as the economy contracting more than previously thought. (bea.gov) The 2025 annual update then nudged this slightly further down to –0.6%. (bea.gov) This is one quarter with a materially more negative revision.

5. Q2 2025: Real GDP was revised up repeatedly, from 3.0% (advance) to 3.3% (second) and then to 3.8% (third/annual-update release). (bea.gov)

6. Net effect on the perceived economy: The 2025 annual-update article emphasizes that average real GDP growth from 2019–2024 is essentially unchanged from prior estimates, and that annual growth rates for 2022–2024 are either unchanged or previously revised up, not down. (apps.bea.gov) The one notable negative surprise is Q1 2025, not “a couple” of significant downward GDP revisions across multiple quarters.

Because only one quarter (Q1 2025) experienced a clearly significant downward GDP revision while surrounding quarters saw upward or flat revisions, Chamath’s prediction of multiple significant downward GDP revisions over the next few quarters—and a generally weaker picture emerging from revisions—did not materialize. Hence the prediction is best classified as wrong.

Available evidence by roughly one year after the podcast (through late 2025) shows that AI customer service software did not become a fully commoditized, low‑value startup category, even though basic AI features became common.

1. Major AI customer‑support startups are still capturing large, differentiated value. Sierra, an AI customer support startup, reported its ARR growing from about $20M to $100M in a year and was valued around $10B, after raising more than $600M. This is specifically an AI customer‑support company, not a foundation‑model provider, and it is expanding headcount and office footprint rather than being squeezed out by commodity competition. (theverge.com)
2. Incumbent application‑layer vendors doubled down on AI and maintained strong valuations. Intercom, whose core product is an AI‑driven customer service and messaging platform, rolled out Fin and then Fin 2, and was in 2025 discussions with investors about multibillion‑dollar valuations alongside other AI customer‑support vendors like Kore.ai. These companies are positioned as differentiated platforms built on top of foundation models, not as commodity utilities displaced by them. (en.wikipedia.org)
3. Market research describes a fast‑growing, multi‑vendor software market, not a commodity layer owned by a few model providers. Industry reports put the AI‑for‑customer‑service market at roughly $12–13B in 2024, projecting high‑20s CAGRs and tens of billions in value by 2030, with long lists of distinct software vendors (Zendesk, ServiceNow, Freshworks, Ada, Aisera, Intercom, LivePerson, etc.) participating in the space. This is consistent with a competitive applications market riding on foundation models, not one that has been “run over” and reduced to undifferentiated infrastructure. (globenewswire.com)
4. Commentary from practitioners and vendors frames AI features as ‘table stakes’ but stresses differentiation in implementation, trust, and integration. Multiple 2024–2025 pieces from customer‑service‑AI providers emphasize that simply having a chatbot is now “table stakes,” yet argue that real differentiation comes from agentic behavior, omnichannel workflows, governance, and domain‑specific tuning—i.e., application‑layer work on top of commoditizing models still matters and is where value is captured. (forbes.com)
5. Gartner/Reuters analysis points to a crowded and hyped vendor landscape, not pure model‑layer domination. Gartner estimated thousands of self‑described “agentic AI”/support vendors, with only ~130 considered technically legitimate, and predicted that many projects will be scrapped. That suggests oversupply and shake‑out risk—but also that a subset of vendors have meaningful, defensible technology and business value, rather than all value collapsing into generic foundation‑model APIs. (reuters.com)

Taken together, the data show a crowded, partially commoditizing feature space (everyone can plug into foundation models) but continuing strong value capture by differentiated AI customer‑service platforms and startups well past September 2025. That contradicts Chamath’s strong claim that you “cannot touch customer service” because it would be fully commoditized and “run over” by foundation models within about a year.

Evidence from OpenAI’s own materials shows that this prediction basically came true on both timing and substance.

• Preview then production: OpenAI announced OpenAI o1‑preview (with o1‑mini) on September 12, 2024 as an early preview reasoning model in ChatGPT and the API. (openai.com) Later, OpenAI documentation for ChatGPT states that “ChatGPT Enterprise and Edu customers will have access to the o1 model on December 5”, referring to the non‑preview o1 model. (help.openai.com) That’s about 2½ months after the September 20, 2024 podcast—within a “couple of months” window.

• Production build: In the product blog “OpenAI o1 and new tools for developers,” OpenAI describes o1 (not o1‑preview) as “the successor to OpenAI o1‑preview” and explicitly calls it “production‑ready”, listing key production features like function calling, Structured Outputs, developer messages, vision, and a reasoning_effort control. (openai.com) The same article notes that the snapshot o1‑2024‑12‑17 is the version being shipped in the API, clearly marking it as the production release of the o1 line. (openai.com) The API pricing page separately lists o1 as a regular, billable model, distinct from preview models, further confirming production status. (platform.openai.com)

• “Spectacular” / materially more capable: The o1‑2024‑12‑17 snapshot sets state‑of‑the‑art results on several benchmarks and is significantly stronger than o1‑preview—for example, AIME 2024 accuracy jumps from 42.0 to 79.2, MATH from 85.5 to 96.4, and SWE‑bench Verified from 41.3 to 48.9—while also using ~60% fewer reasoning tokens and adding major capabilities (vision, function calling, structured outputs). (openai.com) These are large, tangible gains over the preview model, consistent with a “spectacular” or materially more capable upgrade.

Given that: (1) a non‑preview, production‑ready o1 shipped around mid‑December 2024, roughly “in the next couple of months” after the podcast, and (2) it is clearly a significantly more capable successor to o1‑preview, Chamath’s prediction is best classified as right.

As of November 30, 2025, there is not enough realized data on post‑2020 venture capital vintages to say whether average VC fund returns will ultimately be 50–100% lower than historical norms.

Key reasons:

1. VC fund outcomes are inherently long‑dated. Typical venture funds are structured for ~10–12 years, and many now take 15–20 years to fully return capital; most value realization happens in years 7–10+ and often later. (commonfund.org) That means funds raised around 2020–2022 are still in their early or mid investment period in 2025.

2. J‑curve and lack of distributions show we are still early. Analyses of VC J‑curves show that the negative or flat part usually lasts several years, and Carta’s 2024 data notes that more than 60% of 2019‑vintage VC funds had not distributed any capital back to LPs even after five years. (carta.com) If 2019 vintages are still largely unrealized, 2020–2022 bubble‑era vintages are even further from their true, realized performance.

3. Interim performance is mixed and not predictive of final returns. Cambridge Associates’ 2023–2024 benchmarks show that recent VC vintages (2014–2022) have had weak to slightly positive annual returns, with many pre‑2020 vintages negative in 2023 and some post‑2020 vintages (like 2022) positive in 2023–2024. (cambridgeassociates.com) These are mark‑to‑model/mark‑to‑market snapshots, not final cash‑on‑cash outcomes, and industry analysts explicitly warn that early TVPI/IRR after a few years is not a reliable indicator of eventual fund multiples.

4. Current underperformance vs public markets doesn’t fix the long‑run multiple. Recent commentary notes that VC returns over the last year have been around -1%, versus roughly +20% for public equities, and distributions to LPs in 2023–2024 are far below peak years, contributing to weak fundraising and LP fatigue. (wsj.com) This indicates pressure on the asset class and raises the odds of lower eventual returns—but it still doesn’t tell us whether final average vintage‑year multiples will end up half of, equal to, or only modestly below historical norms.

Because:

• the relevant 2020–2022 "bubble" vintages are only ~3–5 years into what is likely a 12–20 year realization arc, and
• core outcome metrics like DPI (cash returned) and final net multiples are largely unknown for those vintages,

we cannot yet quantitatively determine whether average VC fund returns will be 50–100% lower than historical averages. There are signs consistent with stress and potentially lower future returns, but the prediction is about ultimate average realized performance, and that won’t be observable until well after 2025. Therefore the status of this prediction is inconclusive (too early to tell).

The prediction is framed over “the next several years,” so by November 30, 2025 only ~14 months have elapsed—too little to know whether VC fundraising will remain structurally lower than 2020–2021 for the entire horizon.

Data so far do line up with key parts of Chamath’s view: the number of active U.S. VC firms has already fallen by more than 25% from 2021 to 2024, indicating a substantial washout of managers as capital concentrates in a smaller set of large platforms. (ft.com) Fundraising volumes are also far below the 2021 peak: global VC fundraising in 2024 was about $160.6B versus $403.6B in 2021 (down ~60%), U.S. VC funds raised about $76.8B across 538 funds in 2024, and H1 2025 raised only $26.6B across 238 funds—on pace for the lowest fundraising year in a decade. (sourcery.vc) Capital is increasingly concentrated: in 2024, just 30 U.S. firms captured 75% of commitments and nine firms took roughly half, while by Q3 2025 the top 10 funds accounted for 42.9% of all capital raised and the count of emerging-manager funds hit its lowest level since 2015. (linkedin.com) All of this supports the “many VCs washed out, structurally lower fundraising so far” part of the thesis.

Where the evidence is less clear is the causal link that lower fundraising reflects startups needing “a lot less capital.” Median early‑stage round sizes have continued to rise, hitting record levels in 2024–2025, and analysts note that even with AI-driven efficiency, early‑stage check sizes are growing faster than inflation, not shrinking; instead, capital is being rationed into fewer, larger winners rather than broadly reduced because companies inherently need less money. (axios.com) At the same time, some AI and infrastructure startups remain extraordinarily capital‑intensive, with multi‑billion‑dollar rounds. (reuters.com)

Because (1) the time window he specified (“several years”) has not yet played out and (2) the mechanism he posits about companies fundamentally needing less capital is only partially supported and partly contradicted by current data, it is too early to say the full multi‑part prediction is definitively right or wrong; it is best classified as inconclusive so far, though early fundraising and firm‑consolidation trends are directionally consistent with his view.

As of 30 Nov 2025, there has not yet been a clear, widely adopted new mechanism that fundamentally “reinvents” or substantially restructures the U.S. IPO process, but the prediction explicitly refers to changes happening over the “coming years,” which extends beyond the ~14 months since the podcast.

Key points:

• The main ways U.S. companies access public-market capital remain traditional underwritten IPOs, direct listings (with or without a capital raise), SPACs/de‑SPACs, and reverse mergers—all of which existed before September 2024.

  • Nasdaq’s Direct Listing with Capital Raise (DLCR), which allows companies to both list and raise primary capital in the opening auction, was approved by the SEC in December 2022, well before the podcast, and is still framed as an incremental alternative rather than a replacement for the IPO process. (nasdaq.com)
  • Legal and practitioner guides in 2024–25 still describe the landscape as a menu of IPO, SPAC, direct listing, and reverse-merger options—"evolving" but not fundamentally re‑architected. (finsyn.com)

• Empirically, the backlog / bottleneck problem that Chamath is reacting to has not been resolved:

  • Reports in 2024–25 note that the number of U.S. public companies remains far below late‑1990s levels, even after a rebound in IPO volume, and many large firms (e.g., major tech names) continue to stay private longer. (barrons.com)
  • Private equity is still sitting on a very large overhang of unsold assets (roughly $1 trillion as of mid‑2025), with exits via IPOs and M&A constrained—evidence that no new, scalable exit channel has yet unlocked the backlog. (reuters.com)

• Regulatory signals point toward potential future changes but not a completed “reinvention” yet:

  • In 2025, SEC leadership has emphasized making public listings easier and is exploring rules for blockchain-based issuance and trading of securities, but these are early-stage regulatory directions rather than an already-implemented structural overhaul of the IPO mechanism. (barrons.com)

Given this, we can say:

• The conditions Chamath describes (too many private companies, constrained public-market access) still largely exist.
• The existing IPO process has not yet been clearly “reinvented” or supplemented by a genuinely new, widely used mechanism beyond the pre‑2024 toolkit (IPO, SPAC, direct listing, reverse merger, etc.).
• However, because his timeline is “in the coming years” and regulators/markets are visibly working on incremental reforms and potential new structures, it is too early to declare his prediction definitively right or wrong.

Therefore, the fairest evaluation as of Nov 2025 is “inconclusive (too early)” rather than “right” or “wrong.”

By November 30, 2025 it is too early to know how 2021–2022 venture vintages will ultimately perform.

Key points:

• 2021–2022 vintage funds are only ~3–4 years into their lives. Industry data shows that most VC funds don’t start returning meaningful cash (DPI) until years 5–7, and often don’t reach 1.0× DPI (return of paid‑in capital) until around year 8–10 or later.(phoenixstrategy.group) Final outcomes for these vintages won’t be clear until the early–mid 2030s.
• Carta’s recent benchmarks confirm that 2021–2022 vintages are lagging earlier vintages in DPI: only a small minority of 2021 funds had begun returning any capital after three years, and 2022 funds are also behind historical norms on both deployment and DPI.(carta.com) However, this mainly shows slower exits and illiquidity, not terminal multiples.
• Analyses of vintage‑year performance show the 2021 vintage currently has weaker IRR than surrounding years, with median IRR around zero or negative, reflecting peak 2021 valuations and the subsequent correction.(techcrunch.com) But IRR and TVPI for such young funds are mostly unrealized marks and can change substantially if a few large winners exit later.
• The prediction is about end‑of‑life performance and LP sentiment ("you could return capital, you're going to look like a hero") for the 2021–2022 deployment vintages. There is not yet systematic evidence that, on average, these funds will end up only around 1.0× DPI, nor that LPs broadly view a simple return of capital on these vintages as an unusually good outcome. Available data only shows underperformance and delayed liquidity so far, not final multiples.

Because (1) typical realization timelines run 8–10+ years, and (2) current metrics for 2021–2022 vintages are still largely unrealized and could move significantly, Chamath’s claim about their ultimate performance and how LPs will feel about a mere return of capital cannot yet be judged as right or wrong.

The September 2024 FOMC meeting concluded on September 18, 2024. In its statement that day, the Federal Reserve announced it was lowering the target range for the federal funds rate by 50 basis points, from 5.25–5.50% to 4.75–5.00%. Multiple major outlets and the Fed’s own release confirm that:

• The Fed’s September 18, 2024 statement notes that the Committee decided to lower the target range for the federal funds rate to 4-3/4 to 5 percent, which is a 50 bps cut from the prior 5-1/4 to 5-1/2 percent range.
• Coverage from major financial media the same day explicitly describes this as a half‑percentage‑point (50 bps) rate cut at the September 2024 meeting.

Chamath’s normalized prediction had three key elements:

1. "In the September 2024 FOMC meeting, the Federal Reserve will very likely begin cutting rates" – This is correct: the Fed did in fact begin cutting rates in that meeting; it was the first cut of the cycle after holding rates steady for an extended period.
2. "with substantial pressure for a 50 basis point cut" – Going into the meeting, market commentary and research pieces widely debated the possibility of a 50 bps cut versus 25 bps, with many arguing for a larger move based on softening economic data and labor‑market revisions; that constitutes “substantial pressure” in common financial-market terms.
3. "and [they] probably have enough numerical justification now to cut 50" – The Fed ultimately did choose 50 bps, implying that, in its judgment, the data did justify that magnitude of easing.

Because the Fed at the September 2024 FOMC meeting did start the easing cycle and did implement a 50 bps cut (the scenario Chamath framed as the now-likely and data‑justified outcome), the prediction is right.

(Sources: Federal Reserve September 18, 2024 FOMC statement and contemporaneous financial‑press coverage confirming a 50 bps cut at that meeting.)

Chamath’s claim is explicitly forward‑looking: that in the future a distinct investment class—primarily sovereign wealth funds and similar pooled‑capital vehicles—will emerge whose business model is to finance very large U.S. exit‑tax bills (tens of billions of dollars) in exchange for entrepreneurs relocating themselves and their companies abroad. The U.S. expatriation/exit tax regime under IRC §877A is real and well‑documented, and there is active advisory, planning, and media coverage around large exit‑tax exposures for wealthy Americans.(en.wikipedia.org) Wealth‑migration and harsh exit‑tax regimes are also clearly a trend globally (e.g., Norway’s tightened exit tax for wealthy residents; France, Spain, Germany and others enforcing or expanding exit taxes).(reuters.com) However, extensive recent coverage of exit taxes, sovereign wealth funds, and high‑net‑worth relocation—along with specialized commentary from firms that market themselves precisely to people facing U.S. exit tax—shows no reported cases of sovereign wealth funds or pooled capital vehicles systematically paying U.S. exit‑tax bills as an investment product, let alone an established "investment class" doing so.(wealthshield.asia) The wealth‑tax and exit‑tax proposals that might create even larger U.S. exit‑tax liabilities (such as Warren‑style wealth‑tax bills with a 40% exit levy) have not been enacted, so the extreme "tens of billions per entrepreneur" scenario that would drive such a market also has not materialized yet.(en.wikipedia.org) Because the prediction is open‑ended in time and describes a structural financial innovation that could plausibly take many years to appear (if at all), and because as of November 30, 2025, the best available evidence is that this specific class of investors has not yet emerged, the status of the prediction is best classified as **“inconclusive (too early)” rather than definitively right or wrong.

Chamath framed this as a multi‑year directional call ("over the coming years…they’ll only become more fungible"), and only about one year has elapsed since August 2024, so the time horizon he specified has not really played out yet. In the interim, evidence on global capital-mobility is mixed: the OECD’s FDI Restrictiveness Index shows a rise in statutory barriers in 2024 for the first time since 2018, and the US and EU have both tightened screening of inbound and outbound investments in sensitive sectors (e.g., the US outbound-investment rule on China effective January 2025 and the EU’s move toward mandatory, broader FDI screening). (oecd.org) At the same time, some countries have removed or eased capital controls (e.g., Argentina lifting most currency and capital controls in 2025, Russia softening controls on new investments, ECB pressure to dismantle "trapped" capital within the euro area), and cross‑border channels like Stock Connect into Hong Kong and broader Chinese cross‑border flows have expanded. (apnews.com) Because both liberalizing and restrictive moves have occurred and the "coming years" window is still unfolding, it’s too early to say definitively whether capital has "only" become more fungible in the way he predicted.

As of November 30, 2025, the litigation and appeals Chamath was talking about are still ongoing, so his statement about the probability over the full course of the case and its appeals cannot yet be definitively judged.

Key facts:

1. Search‑monopoly case (United States v. Google LLC, filed 2020). Judge Amit Mehta ruled in August 2024 that Google is an illegal monopolist in general search and search advertising. (en.wikipedia.org) On September 2, 2025, he issued a remedies decision that rejected the Department of Justice’s requests for "radical structural" remedies such as divesting Chrome or Android, instead imposing behavioral and data‑sharing remedies and banning certain exclusive distribution deals. (washingtonpost.com) This means no court‑ordered breakup has occurred in the search case so far. However, Google has indicated it will appeal both the liability and remedies rulings, and commentators expect the appeals to run into 2027–2028. (forbes.com)

2. Ad‑tech monopolization case. In a separate DOJ case over Google’s advertising technology, Judge Leonie Brinkema found in April 2025 that Google illegally monopolized key ad‑tech markets. (androidcentral.com) The DOJ is actively seeking structural relief there (forced divestiture of parts of Google’s ad‑tech stack), but as of late November 2025, the remedies phase is still pending and no breakup order has been issued. (androidcentral.com)

3. Courts’ stance on breakups. In the search case, Mehta explicitly declined structural divestiture, citing the high burden for such a remedy and courts’ traditional reluctance to order breakups under Section 2 of the Sherman Act. (washingtonpost.com) Other coverage and experts likewise describe a full breakup of Google as unlikely, though not impossible. (theguardian.com)

Putting this together:

• Chamath’s claim was not simply “Google won’t be broken up,” but that the probability of a court‑mandated breakup would remain in the single digits over the entire life of the case and appeals.
• The relevant proceedings (especially appeals, and the ad‑tech remedies phase) have not yet run their course, and a structural breakup—while clearly disfavored so far—remains legally possible in future appeals or in the ad‑tech case.

Because the time window he specified (“over the course of the current DOJ antitrust case and its appeals”) has not finished, and no final resolution foreclosing a breakup has yet been reached, we can’t say whether his low‑probability assessment ultimately proves right or wrong. At this point, the prediction is directionally consistent with current judicial outcomes (no breakup ordered and courts skeptical of structural relief), but it has not yet resolved, so the fairest scoring is “inconclusive (too early).”

Chamath’s claim was that, over roughly the month after early August 2024, equity‑trading algorithms would mechanically have to sell about $160B of global equities, which would then induce “many hundreds of billions” more in selling by others, so that “the preponderance of the market action will be to continue to sell.”

What actually happened in that period looks inconsistent with that scenario:

1. Global equity prices rose meaningfully over the forecast window. The MSCI ACWI index gained about 2.6% in August 2024 and another 2.7% in September 2024, indicating broad-based equity appreciation rather than sustained net selling pressure. (statmuse.com) The S&P 500 was similarly up ~2% in August and ~2.5% in September 2024, again suggesting buyers, not persistent forced sellers, dominated. (statmuse.com) It is hard to reconcile a month-long, multi‑hundred‑billion mechanical equity dump with globally rising equity indices and no corresponding prolonged drawdown.

2. Fund‑flow data show net inflows into equities over much of that month, not large net outflows. In the week around the initial yen‑carry shock (reported August 9), global equity funds did see outflows of about $6.3B, with nearly $99B rushing into money‑market funds amid the volatility spike. (reuters.com) But a Reuters/LSEG piece on September 6 noted that the week to September 4 was the first weekly global‑equity outflow in four weeks, implying the prior three weeks (i.e., most of August after the shock) had net inflows into equity funds. (y94.com) Separately, the Financial Times reported that ETF flows hit a record in August 2024 with about $129.7B of net inflows, and equity ETFs saw strong buying, which is the opposite of a market dominated by mechanical equity selling. (ft.com) Together, these flow data contradict the idea that the “preponderance” of activity in that month was forced equity liquidation on the scale Chamath described.

3. Market behavior quickly flipped from a forced‑selling shock to a strong rebound. A yen‑driven meltdown and CTA deleveraging did occur: Goldman Sachs’ Scott Rubner estimated that systematic strategies had already dumped roughly $109B of global equity futures in the month up to mid‑August, and expected some continued selling into autumn. (investing.com) However, within that same mid‑August period, global stocks logged their strongest weekly performance since November 2023, with the S&P 500 up about 3.9% for the week, the MSCI World having its best week since early November, and volatility (VIX) dropping back down. (ft.com) That pattern—rapid rebound, easing volatility, and strong weekly gains—is inconsistent with a month‑long dominance of algorithm‑driven selling.

We do see some systematic selling and rebalancing (CTAs’ $109B unwind, later pension and 401(k) re‑allocations out of equities), but public data do not support Chamath’s much larger, specific claim that algorithms had to sell another $160B in equities over the following month and thereby pull through “many hundreds of billions” more in net selling, nor his conclusion that selling would dominate market action over that entire period. Instead, prices and flows suggest that after an initial shock, net buying and recovery characterized most of that month.

Given the available evidence, the prediction that equity markets would experience continued, large, mechanically driven net selling on the order he specified over the subsequent month did not materialize, so this forecast is best classified as wrong.

Key parts of Chamath’s prediction did not materialize, even though one sub-component (rate cuts) did:

1. Recession call and data becoming “more obvious” in Q3–Q4 2024

   • Official U.S. real GDP growth was positive in every quarter of 2024. BEA data show real GDP increasing 1.6% in Q1 2024 (advance), 2.8% in Q2 (advance, later revised around 3.0%), about 3.0–3.1% in Q3, and 2.4% in Q4; full‑year 2024 growth was 2.8%. (bea.gov)
   • The National Bureau of Economic Research (NBER), the standard arbiter of U.S. recessions, has not dated any new recession after the April 2020 trough; its business‑cycle chronology and derivative indicators show expansion (recession indicator = 0) through at least Q3 2025. (nber.org)
   • Because GDP and other broad indicators remained solidly positive and no NBER recession was declared, it did not become “more obvious” in Q3–Q4 2024, via official data or revisions, that the U.S. had already been in recession as of mid‑2024. This central claim of the prediction is therefore contradicted by realized data and the main official arbiter.

2. Powell “will have to cut” rates in Q3–Q4 2024, question being the size

   • The Federal Reserve did cut rates in that window: at its September 18, 2024 meeting, the FOMC lowered the federal funds rate by 50 basis points (from 5.25–5.50% to 4.75–5.00%), the first cut since the early COVID period. (cnbc.com)
   • Chamath framed the open question as whether Powell would “overreact” and cut 75–100 bps vs 25 bps. In reality, the Fed chose an intermediate path—a 50 bps move with projections implying roughly 100 bps of total easing by the end of 2024—so the actual outcome did not match either extreme he posed. (cnbc.com)

Overall, the core thesis—that the U.S. was already in recession and that this would be clearly borne out by official data and revisions in Q3–Q4 2024—was not borne out. Although he was directionally right that the Fed would start cutting rates in that period, the main, testable part of the prediction (the existence and recognition of a mid‑2024 recession) was wrong. Given that sufficient time and data have now accumulated, this prediction is best classified as wrong.

BEA data show that real U.S. GDP growth was positive in the quarters around the podcast date: it increased at an annualized rate of about 3.0% in Q2 2024, 3.1% in Q3 2024, and 2.4% in Q4 2024, followed by a contraction of –0.6% in Q1 2025 and then a rebound of 3.8% growth in Q2 2025. (apps.bea.gov) Thus, there was only one quarter of negative real GDP (Q1 2025) before growth turned positive again; at no point by roughly August 2025 did the U.S. experience two consecutive quarters of negative real GDP growth, the “technical recession” criterion specified in the normalized prediction. Additionally, business‑cycle dating series and NBER communications indicate no new recession episodes after the brief COVID-19 recession in 2020, reinforcing that no recession—technical or official—was recorded in that 2024–2025 window. (nber.org) Therefore, Chamath’s expectation that the U.S. would “probably be in a technical recession” about a year after the August 2024 discussion did not come to pass.

Chamath’s claim was that by around August 2025, there was a “pretty decent chance the market will be up” relative to early August 2024 levels.

Using the podcast date (August 9, 2024) as the reference point:

• On August 9, 2024, the S&P 500 closed at 5,344.16, and the Nasdaq Composite closed at 16,745.30.【2search3】2search7】2search2】
• By late August 2025, both indices were clearly higher. On August 29, 2025, the S&P 500 closed at 6,460.26 (about 21% above its Aug 9, 2024 level), and the Nasdaq Composite closed at 21,455.55 (roughly 28% higher than Aug 9, 2024).【1search7】1search0】1search5】
• News reports also note that by September 9, 2025, the S&P 500 (6,512.61) and Nasdaq (21,879.49) were at or near record highs, confirming that major U.S. equity indices were significantly above their early‑August‑2024 levels.【2news13】

Whether or not a “technical recession” occurred is not necessary to evaluate the directional market call. The key observable claim—that major U.S. equity indices would likely be higher by around August 2025 than they were in early August 2024—did in fact materialize. Therefore, this prediction is best classified as right.

Public information on the remedies decision in United States v. Google LLC (the DOJ’s search antitrust case) shows that Judge Amit Mehta rejected structural breakup remedies (such as forced divestiture of Chrome or Android) and instead imposed behavioral / conduct remedies with a multi‑year duration.

• A September 10, 2025 Congressional Research Service legal sidebar explains that in the September 2, 2025 remedies decision, the court “rejected the plaintiffs’ proposals for structural relief” (including divestiture of Chrome and contingent divestiture of Android) and instead ordered a set of behavioral remedies (data sharing with rivals, search and ad syndication, limits on exclusive contracts, disclosure of ad‑auction changes, and a technical committee), with the final judgment to run six years. (congress.gov)
• The DOJ’s own September 2, 2025 press release describes the outcome as the court prohibiting Google from entering or maintaining certain exclusive contracts, requiring it to share index and user‑interaction data and to offer search and text‑ad syndication services—all classic conduct remedies—without any order to divest business units. (justice.gov)
• Commentary from outlets like The Guardian characterizes the decision as avoiding breakup (no divestiture of Chrome or Android) and instead imposing relatively limited penalties, criticized by some as a “slap on the wrist,” again underscoring that no Ma Bell–style structural split was ordered. (theguardian.com)

As of November 30, 2025, the final judgment at the trial‑court level is a set of behavioral constraints lasting several years, with no structural breakup ordered, which matches Chamath’s prediction that the “big O” outcome (a Ma Bell–style structural breakup) would be off the table and that the remedy would look more like a consent‑decree‑style conduct regime. Appeals may continue, but the remedies decision we have validates the prediction in substance.

The remedies in the DOJ’s search-monopoly case against Google were decided on September 2, 2025. Judge Amit Mehta ordered behavioral remedies (banning certain exclusive contracts, requiring Google to share some index and interaction data, etc.) while rejecting the DOJ’s proposed structural break‑up of Chrome/Android. The DOJ, under the Trump administration, publicly framed this as a “significant win,” indicating support from the Republican-led executive branch and allied state attorneys general, but that only covers one side of the aisle. (justice.gov)

Congressional and broader political reaction was explicitly mixed, not broadly bipartisan in favor. A Congressional Research Service summary notes that reactions to the remedies decision were mixed and that some Members of Congress criticized the ruling as providing insufficient relief and began talking about new legislation instead—signaling clear dissent rather than unified support. (congress.gov) Prominent Democrats in particular opposed the outcome: Senator Amy Klobuchar (D‑MN) said the limited remedies show why additional rules for Big Tech are needed and used the decision to argue for passing stronger legislation, rather than endorsing the court’s remedy. (theverge.com) Senator Elizabeth Warren (D‑MA) went further, calling the remedies a “slap on the wrist” that fail to hold Google accountable and explicitly arguing the judge should have broken up the company. (warren.senate.gov) News coverage likewise reported that lawmakers were among those describing the penalties as a “slap on the wrist” and expressing deep disappointment at the weak sanctions. (theguardian.com)

Because key Democratic lawmakers publicly criticized the remedies as inadequate rather than “really supporting whatever happens here,” while support came mainly from the Republican DOJ and some industry groups, the outcome was not one of broad, bipartisan public backing for the court’s action. That contradicts Chamath’s prediction that both the Democrats and the Republicans will really support whatever happens here, so the prediction is wrong.

Chamath’s conditional prediction was that if Kamala Harris did not clearly define her positions on 4–5 key issues, she would win the national popular vote but lose the Electoral College in the November 2024 election.

In reality, in the 2024 U.S. presidential election Donald Trump won both the Electoral College and the national popular vote: 312–226 in the Electoral College and 49.8%–48.3% in the popular vote (about a 2.3 million vote margin over Harris). (en.wikipedia.org) This directly contradicts the popular-vote/EC split he described.

The antecedent of his conditional (“in the absence of her defining herself on those 4 or 5 issues”) is also dubious: Harris’s 2024 campaign publicly set out positions on major issues such as abortion rights, an “opportunity economy” and middle‑class tax relief, housing affordability, border security and immigration reform, and her stance on the Israel–Gaza conflict in speeches, interviews, and on her campaign site. (en.wikipedia.org) While one could debate whether this met Chamath’s personal standard of “clearly defining” her positions, the concrete electoral outcome he forecast (popular‑vote win combined with Electoral College loss) did not occur.

Because the verifiable part of the prediction—Harris winning the popular vote while losing the Electoral College—was false in the world that actually happened, this prediction is best classified as wrong.

Evidence from 2024–2025 shows the U.S. economy continued to expand rather than being broadly described as in a recessionary environment.

• Macroeconomic data: Real U.S. GDP grew in every quarter of 2024, with full‑year real growth of about 2.8%, and Q3–Q4 2024 both positive. (bea.gov) The NBER Business Cycle Dating Committee has not declared any new recession after the brief COVID downturn that ended in April 2020, meaning it still classifies the period since May 2020 as an expansion. (nber.org) This undercuts the idea that conditions were widely seen as recessionary starting in or after September 2024.
• Media narrative: In early September 2024, Treasury Secretary Janet Yellen publicly said the U.S. economy remained solid and was on track for a soft landing, explicitly rejecting the view that the U.S. was in recession. (cnbc.com) The National Retail Federation’s chief economist similarly stated on September 6, 2024 that the U.S. economy was “clearly not in a recession” and likely to avoid one in late 2024. (nrf.com) Coverage from CNBC and other outlets through late 2024 framed the debate as recession fears vs. a probable soft landing, not as the country already being in recession. (cnbc.com)
• Corporate earnings commentary: FactSet‑based analysis of S&P 500 earnings calls for late 2023 and early 2024 found that far fewer large companies were even mentioning the word “recession” on their calls than in prior years, while use of the phrase “soft landing” hit multi‑year highs. (jamesinvestment.com) That is the opposite of Chamath’s expectation of “a lot of ink” around multiple major companies “basically in a recession.”
• Minority recession claims: A few opinion pieces and niche analyses argued that parts of the U.S. economy or certain income groups might already be in recession, but they acknowledge that aggregate data still show positive GDP growth and characterize this as a partial or hidden recession affecting specific segments, not the mainstream view of the overall U.S. economy. (forbes.com) These do not amount to major media widely describing the U.S. as in a recessionary environment in the sense implied by the prediction.

Given (1) continued broad economic growth with no officially dated recession, (2) a dominant soft‑landing narrative in major outlets, and (3) no widespread wave of coverage portraying multiple large companies as being “basically in recession,” Chamath’s predicted media and corporate‑commentary pattern did not materialize. Therefore, the prediction is wrong.

The September 17–18, 2024 FOMC meeting did, in fact, deliver a rate cut, and larger than the minimum threshold in the normalized prediction. The target range for the federal funds rate was reduced from 5.25–5.50% to 4.75–5.00%, a 50 basis point cut.(federalreserve.gov) This satisfies the normalized claim that there would be at least a 25 bp cut, even though Chamath’s exact off‑the-cuff wording (“probably going to cut 25”) understated the eventual size of the move.

The minutes show that a “substantial majority” of FOMC participants supported the 50 bp cut, while a minority would have preferred only 25 bp, and Powell voted with the majority.(federalreserve.gov) That pattern is consistent with the idea that, given sufficient committee support, Powell was willing to go to 50 bp rather than being anchored to 25 bp, which matches the conditional part of the prediction about his inclination, even though his exact internal preferences cannot be directly observed.

The final part of the prediction—that this rate cut would not materially resolve the underlying weakness in consumers’ purchasing power and economic stress—is also borne out by subsequent data. By late 2024, U.S. credit‑card defaults had risen to their highest level since 2010, with tens of billions of dollars in write‑offs, underscoring mounting financial strain, especially for lower‑income households.(ft.com) Analyses of household finances through 2024–25 highlight that, despite some improvement in aggregate real incomes, cumulative inflation and high living costs continued to erode resilience, with elevated consumer debt and rising delinquencies particularly among vulnerable groups.(compete.org) Real consumer spending growth showed periods of softness and small declines once adjusted for inflation, indicating that purchasing power pressures persisted rather than being “solved” by a single rate cut.(theglobalstatistics.com)

Taken together, the core normalized elements came true: the Fed cut the policy rate by at least 25 bp at the September 2024 meeting; conditions were such that a larger (50 bp) cut was chosen with broad committee backing; and that easing did not eliminate the underlying consumer‑side weakness or cost‑of‑living pressures. The prediction is therefore best classified as right, with the caveat that Chamath verbally low‑balled the eventual cut size when he said “probably 25.”

The prediction ties Democrats’ chances of winning the White House to having a “bad economy” going into November 2024, which makes it inherently conditional and somewhat vague.

What actually happened:

• Democrats did lose the White House: Donald Trump defeated Kamala Harris on November 5, 2024, winning 312–226 in the Electoral College and by about 1.5 points in the popular vote. (en.wikipedia.org) That outcome is consistent with Chamath’s claim that it would be “very difficult” for Democrats to win under unfavorable economic conditions.

State of the economy going into November 2024 (hard data):

• Real GDP was still expanding at a solid pace: 3.1% annualized in Q3 2024 and about 2.3–2.4% in Q4, with full‑year 2024 growth around 2.8%. That’s moderate, positive growth, not a technical or NBER‑defined recession. (forbes.com)
• The unemployment rate in October 2024 was 4.1% (up from 3.8% a year earlier but still historically low). Job creation in October, however, was anemic—only about 12,000 jobs added, the weakest since 2020, largely due to hurricanes and a Boeing strike—producing very negative pre‑election headlines. (bls.gov)
• Inflation, while still above the Fed’s 2% target, had fallen sharply from its 2022 peak; October 2024 CPI was up about 2.6% year‑over‑year with core at 3.3%, roughly in line with expectations and compatible with a “soft landing” narrative. (cnbc.com)
• Some indicators of sentiment were improving: the Conference Board’s Consumer Confidence Index jumped to 108.7 in October 2024, with the Expectations Index rising above the 80 level that typically signals recession risk, suggesting statistical confidence was not recession‑like. (prnewswire.com)