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📚 AI Agent Evaluation Series - Part 3 of 5

1. Observability & Evals: Why They Matter ←
2. Human-in-the-Loop Evaluation ←
3. Implementing Automated Evals ← You are here
4. Debugging AI Agents →
5. Human Review Training Guide →

From Theory to Practice: Automated Evals for AI Agents with Langfuse

We covered why observability and evals matter for AI agents in Part 1 of this series. Now let's get practical: how do you actually implement automated evaluations that run continuously, catch regressions before users do, and give you the confidence to ship faster?

This guide walks through setting up automated evals with Langfuse—from basic quality checks to sophisticated LLM-as-a-judge evaluations. And if you're using Answer Agent, you're already halfway there: Langfuse tracing is built-in, so you can skip the instrumentation headache and jump straight to measuring quality.