Across 2023–2025, available data and surveys indicate that most companies have so far used AI coding tools to augment software engineers rather than to justify mass elimination of developer roles, which matches Sacks’s short‑term prediction.

Employment and layoffs picture

• U.S. Bureau of Labor Statistics projections continue to show software developers as a high‑growth occupation, with employment expected to rise ~18% from 2023–2033, versus a 9–10% decline for more automatable computer programmer roles. This indicates ongoing demand for developers even as more routine programming shrinks. (bls.gov)
• Reporting on U.S. jobs shows that about a quarter of traditional “computer programming” jobs vanished over the past two years, but the same analysis notes that software developer roles remained comparatively stable and are broader, more strategic, and less routine than the programmer category that was hit hardest. (washingtonpost.com)
• Tech has seen large layoffs—400,000+ tech workers globally from 2022–2024 and more in 2025—but analyses attribute this mainly to pandemic over‑hiring, higher interest rates, and restructuring, with AI productivity a contributing factor but not the dominant, explicit reason for most cuts. (medium.com) A synthesis of McKinsey and Yale research summarized in 2025 notes that only about 1% of firms explicitly cite AI as the reason for layoffs. (cengizhan.com)

What companies say they plan to do with AI

• A 2024 ManpowerGroup survey of global employers found 55% expect AI to increase headcount, 24% expect no impact, and only 18% expect AI and ML to reduce staffing—evidence that most firms do not see AI primarily as a headcount‑cutting tool. (investor.manpowergroup.com)
• McKinsey’s 2025 State of AI data, broken down by function, indicates that software engineering/IT/product development functions are among those where companies most often expect headcount to increase, even as they adopt AI; only a minority foresee net reductions. (enterpriseaiexecutive.ai)

How AI coding tools are actually being used

• GitHub Copilot and similar tools have been adopted at scale (1.3M paid users across 50,000+ organizations by early 2023), with studies showing up to 55% faster completion on some coding tasks; these reports frame AI as a “pair‑programmer” that still requires human oversight, not as a replacement for entire dev teams. (wired.com)
• Inside Microsoft, engineering leaders report AI coding assistants contributing substantial portions of code and saving developers from “minutes to weeks” of work, yet they describe this as reducing “developer toil” and improving efficiency, not as a program of eliminating most developers. (theverge.com)
• The 2024 and 2025 Stack Overflow developer surveys show that around 76–84% of developers use or plan to use AI tools, and productivity/learning are the top cited benefits, while a large majority do not view AI as an immediate threat to their jobs; AI is seen primarily as a productivity booster. (linkedin.com)

Nuances and caveats

• There is growing evidence that entry‑level and routine coding roles are being squeezed: industry analyses note sharp drops in junior tech postings and a shift toward hiring more senior engineers who then use AI tools, plus significant declines in traditional “programmer” roles. (washingtonpost.com) Some commentators and case studies argue that leaders believe 5 AI‑augmented engineers can replace 10 traditional ones and have used this logic in certain reorganizations. (medium.com)
• However, these effects are uneven and concentrated in specific segments (junior roles, highly routine work, and certain big‑tech restructurings), not a universal pattern of companies “cutting all their developers because one or two can do ten times the work.” The majority of survey and labor‑market evidence still points to augmentation with relatively stable or growing developer demand, at least so far in the 2023–2025 window.

Given this mix, Sacks’s short‑term claim—that over the next few years, most firms would keep substantial developer headcount and use AI mainly to boost productivity and accelerate roadmaps rather than immediately slashing software teams en masse—aligns well with the best available evidence as of late 2025. The prediction is therefore right for the period we can currently observe, even though longer‑term impacts remain uncertain.