Batch audit versus autonomous loop
You need to know which of 3,000 JSON config files in a repo are missing a newly-required `region` key, just once, for a migration ticket. A teammate is drafting a careful multi-paragraph spec for an AI agent to 'audit the configs and produce a report.' Is an AI loop the right reach here? What would you do?
Implement
find_files_missing_key(config_files: list[list[str]], required_key: str) → list[str]Examples
in
[[["config/a.json","name","region"],["config/b.json","name"],["config/c.json","region"]],"region"]out["config/b.json"]in
[[["config/a.json"],["config/b.json","Region"]],"region"]out["config/a.json","config/b.json"]in
[[["config/x.json","region","region"]],"region"]out[]What a strong answer looks like
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.
0:00 of about 12 min
Vibe & agentic: describe the solution in plain language (or narrate it) and the coach grades your approach.
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.