Futureism- Sam Altman Thanks Programmers for Their Effort, Says Their Time Is Over

[CentralMass]

19. An AI response to a related question.

Current data from 2026 shows that AI is not replacing coders in large numbers, but it is restructuring the profession. While the U.S. Bureau of Labor Statistics still projects 17% growth in developer jobs through 2033, entry-level hiring has dropped by as much as 73% in the past year as AI automates routine junior-level tasks.
​Code Quality and Rework
​AI-generated code currently suffers from a "quality crisis" characterized by a significant verification tax.
​Issue Frequency: AI-generated pull requests contain 1.7 times more bugs and logic errors than human-written code.
​Security Risks: Vulnerabilities in AI code are 1.57 times more common, often due to missing "defensive" coding like null checks and error handling.
​Trust Gap: Approximately 96% of developers do not fully trust AI-generated code to be functionally correct without manual review.
​Rework: Only about 30% of AI-suggested code is accepted without modification. Senior developers often report a 19% slowdown because debugging AI output takes longer than writing it from scratch.
​Is it Improving?
​Yes, but the nature of the improvement is shifting.
​Efficiency: Developers are becoming 20-55% faster at shipping code, even if that code requires more initial fixing.
​Learning Curve: Studies show that after an initial "slowdown" period, developers who master AI prompting and validation eventually see an 18% speedup in overall task completion.
​Technical Debt: Despite improvements in speed, Gartner predicts a "technical debt reckoning" by 2027, as AI-generated code often lacks long-term architectural judgment and fails to "age well."

However, in my opinion, with a competent group of coders with the expertise and knowledge on the application I think that AI generated code will continue to improve, and continue to eliminate jobs. In the job that I left, or that left me, (I'm old) we had an AI layer that would check code submissions from various teams. It would check for errors and in many cases provide an automated fix to those errors. These fixes were pretty much always correct. All passing code submissions would be tested with a "bot" and all passing code would submitted for the release. The "bot" eliminated 20 teams from having to perform their own individual testing that included securing time and setup on the systems required to validate it. It is as good as the people who are programming the model for the application. If that team is this very good, it can be be very good. It can learn preferences of a particular programmer and improve with their input.