Question
An AI agent wrote you a Python Spark job that joins clickstream events to a user-dimension table. Before you put it up for review, you want to be able to explain it cold. The agent used a broadcast join hint and partitioned the output by date. In your pre-review read, what specifically must you understand and be ready to justify so you're not blindsided in review — and what's the difference between 'I can explain it' and 'I tested 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.