A Three-Stage Process for AI Evals
amaarora · x · 2026-07-19
The author outlines a practical three-stage process for evals:
- Start with a "vibe check" in the loop, tweaking the output until it looks right;
- Next, hand-write 10–20 of the most critical scenarios and define how to quantify performance on them;
- After deployment, collect production traces, organize them into datasets, and feed them back into the eval system.
The core takeaway is to quickly establish an evaluation baseline using a few high-value scenarios, and then solidify the eval system with real-world production data.
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