Evaluation for Production Agents
AGAI 401 · Module 1
Production AI systems require evaluation strategies that go beyond traditional unit tests. This module teaches how to build eval datasets, judge model behavior, compare agent trajectories, and use modern evaluation frameworks to keep agent quality measurable over time.
Lessons in this module
Why AI Evaluation Is Different
Learn why production AI systems require probabilistic, behavioral, and trajectory-based evaluation rather than only deterministic pass/fail tests.
Building Eval Datasets
Learn how to create representative evaluation datasets, define expected behavior, include edge cases, and turn production failures into regression tests.
LLM-as-Judge and Human Evaluation
Learn when to use model-based judging, how to write evaluator rubrics, where human review remains necessary, and how tools like Braintrust, LangSmith, and Weights & Biases support evaluation workflows.
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