Question
Your team wants ~80% unit-test coverage added to a stable, well-typed Python utility module (pure functions, no I/O). One engineer sets up an autonomous agent to 'add tests until coverage hits 80%, running pytest in a loop.' Another just one-shots the whole test file from the module source. Given the module's nature, which fits — and what's the actual risk you're managing?
Treat the AI’s output as a draft to verify, not an answer to trust. Name the specific flaw and the input that triggers it, say how you’d catch it — tests, edge cases, reading critically — and how you’d re-prompt or decompose to get it right.
Vibe coding: describe the solution in plain language (or narrate it) and the coach grades your approach. Generating runnable code from your description is coming next.