Query result sanity check
You asked an AI assistant for a SQL query: "count how many users signed up in each of the last 7 days." It gave you a query that runs and returns rows. Before you put it in a dashboard, how do you sanity-check that the numbers are actually right — not just that the query executed?
Implement
daily_signup_counts(timestamps: list[str], end_day: str) → list[int]Examples
in
[["2026-06-20 09:00:00","2026-06-20T23:59:59","2026-06-18 12:00:00"],"2026-06-20"]out[0,0,0,0,1,0,2]in
[[],"2026-06-20"]out[0,0,0,0,0,0,0]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.