AI agent evaluation: How to test, debug, and improve agents in production

AI agents require specialized testing and debugging approaches that differ from traditional software due to their non-deterministic behavior and complex decision-making processes. This entry likely covers methodologies for evaluating agent performance in production environments, including strategies for identifying failure modes, monitoring outputs, and iteratively improving agent behavior. It addresses best practices for ensuring reliability and safety of AI agents when deployed in real-world applications.

Source: Arize AI | 2026-05-05