Demystifying evals for AI agents
The clearest official explanation of what an agent eval actually is.
Open anthropic.com →You test agents with evals: a set of real tasks plus grading logic, run repeatedly because the same input can produce different outputs. Start embarrassingly simple: read 50 transcripts of your agent working, label every failure, turn the recurring ones into automated checks (code checks where possible, an LLM judge validated against your own labels where judgment is needed). Trust is earned per task: track pass rates over many runs, not one good demo.
A quick orientation. The real value is below: resources worth your time, from people who've actually done it.
The clearest official explanation of what an agent eval actually is.
Open anthropic.com →Every question you will have about evals, answered by the field's top teacher.
Open hamel.dev →The philosophy behind the top-grossing evals course, free to read.
Open hamelhusain.substack.com →The course that trained 2,000+ people, including teams at OpenAI and Anthropic.
Open maven.com →A live walkthrough of building an eval from real product data.
Watch on YouTube youtube.com →The same masterclass in podcast form for the commute.
Listen on Spotify open.spotify.com →The 60-second version of why evals became the must-have skill.
Open x.com →Written notes of the full workflow: error analysis to automated judges.
Open aakashg.com →Explains pass@k and why you must run agent tests many times.
Open cameronrwolfe.substack.com →The honest failure modes of eval culture, so you avoid cargo-culting it.
Open vanishinggradients.fireside.fm →Field lessons from teams that moved agents from demo to production.
Open infoq.com →A single-sitting starter recipe for your first agent eval.
Open zenvanriel.com →Covers the metrics that matter: task success, step count, faithfulness.
Open turingcollege.com →Connects evals to shipping cadence rather than treating them as QA theatre.
Open lennysnewsletter.com →A worked example you can copy line by line for your own product.
Open arize.com →A second full session using messy real data instead of toy examples.
Open news.aakashg.com →Surveys the tooling landscape so you do not build eval infrastructure from scratch.
Open medium.com →A checklist to run before you let an agent near customers.
Open getmaxim.ai →