Why AI agents need decision records
Most teams that deploy AI agents keep logs: prompts, outputs, tool calls. Logs are useful for debugging, but they're a poor answer to the question a manager, customer or auditor will eventually ask: why was this done?
What a decision record holds
- The decision, in one plain sentence.
- The evidence it relied on, with sources and versions.
- The approver: a named person, or the written policy that allowed it.
- The time and the context: which task, which agent, which tools.
- What changed afterward, as new linked entries, never edits.
Why logs aren't enough
Logs are written for machines and engineers. They are large, noisy and often rotated away after weeks. A decision record is small, written for people, and meant to be kept.
Append-only, on purpose
If a record can be quietly rewritten, it can't be trusted. Corrections should be new entries that reference the original. Then the history shows both the mistake and the fix, which is exactly what reviewers need.
Start small
You don't need a platform to begin. Pick the three actions your agents take that matter most, and write one record each time they happen. The habit matters more than the tooling.