Your AI agent did weird things. You don’t know why.

It charged a customer twice. It said “email sent” when no email left the building. It burned $40 of API credits looping on the same task at 3am. You opened the logs — a wall of JSON. You closed the logs.

AI agent observability is the dashboard you wish came in the box. It’s a recording of everything your agent thought, said, and did — searchable, replayable, and readable by a human in under ten seconds.

Here’s what the jargon actually means:

• Trace stitchingA black-box flight recorder for a 12-step agent run. When step 9 went sideways, you see exactly what step 8 fed it.
• Hallucination detectionCatch the agent claiming it sent the email when it never called the email tool.
• Token & cost trackingSee the $40 loop the moment it starts, not on next month’s invoice.
• Tool-call timelineEvery external action the agent took — which file, which API, which customer record — laid out like a bank statement.
• Approvals & guardrailsA pause button for risky moves (refunds, deletes, sends) before the agent does them, not after.
• Drift & anomaly alertsA nudge when “normal” behavior changes — the agent suddenly answering 3× slower, or calling a tool it’s never touched before.

Without it, every agent failure is a forensic investigation. With it, every failure is a 30-second replay.

← Back to ClawMetry