AI Evals. Citation-grounded tutorials, playbooks, and tools for evaluating LLM systems in production.

The reference for AI evals: error analysis, LLM-as-judge, RAG evaluation, agentic evals, 20 task-type playbooks. Every claim cited.

AI Evals

If you ship LLM features, evals are how you keep them working past the demo. This site collects the techniques, tools, and worked examples that practitioners actually use ^[1]. Start with Foundations or pick a persona track on the Start page.

AI Evals

The most useful, opinionated reference for AI evals.

AI Evals is a curated technical reference for evaluating large language model systems in production. The site covers error analysis, LLM-as-judge calibration, RAG evaluation, agentic eval, statistical rigor, and twenty task-specific eval playbooks. Every claim is cited.

Why evals matter
Your first eval in 30 minutes
LLM-as-Judge introduction
RAG eval in two layers
Trajectory eval for agents
Glossary
Papers