Question
You ask an AI to write a Postgres query for 'monthly active users' and it returns a clean `COUNT(DISTINCT user_id) ... GROUP BY date_trunc('month', event_time)`. The numbers look right in a quick check, so you ship it — then finance flags that March is double-counting versus their dashboard. You re-prompt 'fix the double counting' and it adds `DISTINCT` in three more places, changing nothing. What assumption did the model bake in, and how do you re-steer to actually fix it?
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.