Top Resources to Learn AI Agent Evaluation
A curated set of essential learning materials for anyone interested in evaluating AI agents—from foundational tutorials to advanced tools and performance metrics.
1. Top Resources to Learn AI Agent Evaluation
Evaluating AI agents isn’t just a nice-to-have—it’s critical for deploying robust, production-ready systems. This list brings together some of the best resources across courses, eBooks, and blogs to help you master evaluation techniques:
Evaluating AI Agents – A short course by DeepLearning.AI + Arize AI: Learn how to build agents, observe decision steps, and evaluate tool use, router logic, and full-agent behavior in both dev and prod.
Mastering AI Agents – eBook by Pratik Bhavsar (Galileo): Deep insights into agentic frameworks, choosing the right one, identifying failure modes, and deploying scalable agent systems.
LLM Agent Evaluation – Blog post by Confident AI: Dives into evaluation frameworks like DeepEval, covering multi-step reasoning, tool usage, and pipeline-level metrics.
A Field Guide to Rapidly Improving AI Products – by Hamel Husain: Practical tips on error analysis, observability, and iteration strategies to improve agents fast.
Whether you’re just getting started or improving production systems, these resources are a must. Have other favorites? Add them to the questions section and help grow the list!