Developer warns AI 'verification' is unreliable after flawed code copy goes undetected
A developer building a second app attempted to replicate a working podcast production pipeline by asking an AI assistant to copy it, then used a separate AI session to verify the result. The fresh session had no context of the original pipeline and confirmed the code looked correct, despite significant production flaws in timing, music fading, and voice settings. The errors only surfaced when the developer ran a real transcript through the new pipeline. The author argues the problem is not blind trust in AI, but mistaking proxy signals — like passing tests or an agent's 'done' — for genuine verification of quality. The experience forms the basis of a new book the developer is writing on how to properly validate work produced by AI coding agents.
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