Question
An AI agent generated a tidy Go implementation of a rope data structure for your closed-source SaaS editor. It compiles, passes tests, and ships. Months later a license-scanning audit flags that the implementation is near-identical to a GPL-3.0 library on GitHub, down to variable names and comment phrasing. Walk through how you'd respond, and what you'd change in your AI-coding process so this doesn't recur.
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.