Final step of the AI agent playbook: run error analysis first, let eval metrics emerge naturally
PawelHuryn · x · 2026-09-09
Closing post of Paweł Huryn's AI agent-building series: don't start from standard metrics like hallucination or helpfulness — run error analysis, let metrics emerge from real failures, then build evals and guardrails around them.
Includes two free resources: 'Mastering AI Evals for PMs' (co-written with Hamel Husain, distilling practices from 30+ companies) and the evals-skills GitHub repo with ready-to-use templates.
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