AI Code Verification Checklist

An AI code verification checklist is the disciplined review an engineer applies to code an agent produced, built on one hard truth: schema-valid is not the same as correct. Code can compile, satisfy a JSON schema, and pass a type checker while still implementing the wrong behavior, dropping an edge case, or silently misusing an API.

A useful checklist separates the layers. Does it parse / compile / type-check? is the cheapest gate and the least meaningful. Does it do what was asked? requires reading the diff against the actual requirement. Is it safe? covers injected secrets, unsafe shell or SQL, over-broad permissions, and dependencies the agent invented. Is it tested? asks whether the change ships with tests that would fail on the bug it claims to fix — and whether those tests actually exercise the new path.

The checklist exists because AI failure modes are confidently plausible: the output looks right, cites real-sounding functions, and reads fluently. Verification means running the tests, checking that referenced APIs exist, and confirming the logic against the spec — not pattern-matching on how professional the code looks. A green type-checker is a start, never a sign-off.