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Comment on Why AI code fails differently: What I learned talking to 200 engineering teams

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The observation is very accurate, but the conclusion is incomplete. The "unwritten rules" problem is, first and foremost, a symptom of a weak engineering culture and a lack of documentation. If a rule is critical to system stability (like the async analytics), it shouldn't be "living in engineers' heads"

Instead of layering on another AI for validation, maybe code generation should be used as a catalyst to finally formalize these rules. Turn them into custom linting rules, architectural tests (like with ArchUnit), or just well-written documentation that a model can be fine-tuned on. Using AI as a crutch for bad processes is a dangerous path

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