Question
You asked an agent to optimize a slow data-processing job. Twice it returned a 'faster' version that's actually wrong — once it changed an aggregation that altered results, once it parallelized a step that has an order dependency. Each time it produces a confident speedup that fails correctness. How do you diagnose why it keeps trading correctness for speed, re-steer it, and decide what to keep doing yourself?
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.