Observability for AI Agents

Observability for AI agents extends traditional software observability (logs, metrics, traces) to cover the unique aspects of agent behaviour: what the agent reasoned, which tools it called and why, how much context it consumed, where it deviated from expected behaviour, and how its outputs compared to human baselines. Without observability, production agents are black boxes — when they fail (and they will), you have no way to diagnose why or prevent recurrence.