10 evaluation patterns AI engineers use to catch agent regressions
blaizedsouza · x · 2026-07-22
- A concise checklist of 10 agent evaluation patterns for AI engineers, with guidance on when to use each one.
- It covers golden sets, LLM-as-judge, rubric scoring, trajectory evals, tool unit tests, and regression suites.
- The core message: instead of only judging final outputs, teams should evaluate the path, tools, and failure modes of agents so regressions are caught before they ship.
Related event: Top 10 AI Agent Evaluation Methods for Developers(3 posts)→
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