Hamel Husain advises against ready-to-use AI evaluation metrics

AIHamel Husain compresses the key concepts of his Applied AI Evals course into a 13-card pocket guide, available at hamel.dev. The cards cover error analysis, when to write evals, rejecting generic metrics, and three types of automated evaluation: code assertions, LLM judges, and guardrails. The guide also recommends binary pass/fail scoring over Likert scales and deployment across CI/CD, online monitoring, and guardrails.

AIHamel Husain answers "No" to whether teams should use ready-to-use evaluation metrics, calling them a bad idea in most situations. He points to a linked blog post for his reasoning.