Demystifying Evals for AI Agents: A Refresher on Anthropic's Guide

A refresher on evaluating AI agents, based on the Anthropic Engineering post "Demystifying evals for AI agents." Watch it after reading the article to lock the concepts in, or use it as a quick review. What's covered: • What an eval is, and why agent evals are harder than single-turn tests • The vocabulary: task, trial, grader, assertion, transcript, outcome, eval harness, agent harness, suite • Transcript vs outcome • Why teams build evals, and how their value compounds • The three grader types: code-based, model-based, human • Capability evals vs regression evals • How coding, conversational, research, and computer use agents are evaluated, with the benchmarks to know: SWE-bench Verified, Terminal-Bench, τ-bench, BrowseComp, WebArena, OSWorld • Non-determinism: pass@k vs pass^k • Anthropic's roadmap from zero evals to evals you can trust • How evals fit with production monitoring, A/B testing, user feedback, transcript review, and human studies • Eval frameworks: Harbor, Braintrust, LangSmith, Langfuse, Arize Phoenix Source: Demystifying evals for AI agents, Anthropic Engineering https://www.anthropic.com/engineering/demy... All credit for the ideas goes to Anthropic. This video is a study aid and is not affiliated with Anthropic. #AIAgents #Anthropic #LLMEvals #AIEvaluation #AgentEvals #AIEngineering