Question
You're directing an AI agent to write a Go function that computes a running average and standard deviation over a stream of millions of float64 sensor readings, for an analytics pipeline. Write the prompt/spec that makes it numerically robust at scale. What algorithm and precision constraints do you mandate, and what acceptance criteria catch the failure? Then state what a naive prompt ('compute mean and stddev of the stream') produces that's wrong on real data.
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.