AI agent observability: what should you actually log?

AI agent observability is the ability to reconstruct what a system received, decided, attempted and verified. Useful logs connect a business task to its sources, tool calls and outcome. Logging every payload is not the goal, especially when it exposes private customer data or credentials.

Follow one task with one identifier

Imagine a report that contains the wrong total. A task ID should connect the incoming request, retrieved source versions, calculation step and saved artifact. Without that chain, the team may blame the model when the source query actually omitted a page of results.

Keep operational evidence rather than relying on hidden model reasoning. Inputs, actions, structured results and destination checks are the practical material for investigation.

Record what helps a decision

• Task identity, owner and workflow version.
• Source IDs, observation times and relevant version references.
• Tool name, sanitized parameters and result status.
• Approval decision and the action it covered.
• Completion evidence, duration and recoverable error state.

Apply access controls and retention rules to logs themselves. A debugging system can become a second uncontrolled customer database if it stores everything indefinitely.

Separate technical and business signals

A model request can succeed while the business task fails. Track both. For example, the text generation may return normally, but saving the draft may be rejected by the destination. The user-facing status should follow the task outcome, not the first successful component.

Also record partial coverage. A report based on two of three sources should not look identical to a complete report.

Make alerts actionable

An alert should identify the affected task, consequence and next recovery step. Avoid notifying the team for every harmless retry or unchanged pending state. The purpose of observability is to help someone make a better decision quickly, including deciding that no intervention is needed.

Be Human editorial guidance. Examples are illustrative unless explicitly attributed. Sources provide background; implementation choices depend on your workflow.