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.