The strongest point here is that CLAUDE.md/AGENTS.md should encode decisions the model cannot reliably infer, not repeat generic engineering advice. The Preferred/Avoid examples and concrete code patterns make that distinction very clear.

One thing I’ve found useful in production AI work at IT Path Solutions is treating these files almost like an architectural contract: keep the rules small, tie them to actual tooling/tests where possible, and remove a rule once the repository no longer needs it. Otherwise the context file becomes another source of drift.

The five-minute A/B test is especially practical. If removing the file doesn’t measurably change the agent’s implementation choices, you’ve probably documented knowledge rather than constraints.