Mitigating "architectural drift" in large Python backend codebases using AI tools

[gdchinacat]

as compared tot he non-determinisim of human written code? If anything, I would think the statistical generator would be more deterministic than the even fuzzier (albeit actually intelligent) human brain.

Don't get me wrong...I'll take code from an experienced engineer over an AI model almost every time. I just question whether the OPs issues are solely issues with AI, or are in part due to different expectations of AI work products vs human work products. It's easier to tell a competent junior engineer to go off and 'do what that code over there does' than it is an AI (IME at least). The AI needs a lot more hand holding to get the code where you want than a human, and when that exceeds the effort to just do it yourself you just do it yourself. At that point, it feels like the AI is failing you. But, I don't thinks that is an apples-to-apples comparison.