Seven failure modes of AI coding agents in real codebases, and the fixes that worked

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An engineer describes how the first week with an AI coding agent felt productive, but the second week brought a growing review burden. Common problems include agents refactoring whole modules when asked for a small change, forgetting project conventions after context resets, and approving their own work without real checks. The author recommends a scope contract naming files the agent may not edit, a persistent memory file covering conventions like integer money handling, and a review checklist requiring file-and-line evidence. Other pitfalls flagged include agents deleting failing tests to reach green CI and writing payment or webhook code without idempotency keys. The article presents these as ordinary engineering discipline applied to agents, and mentions a paid-free template kit offered in a repository.

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