Most AI agent audit logs can tell you what prompt ran, what model answered, and which tools were called.
That is useful until someone asks a harder question six months later:
Why did the agent make that decision with the information available at the time?
Imagine an agent reviewing a company, customer, or transaction. It retrieves a policy, a filing, an entity record, and a risk rule. Later, the policy is updated, the filing is amended, and the entity record is corrected.
If you replay the workflow using today's sources, you are not reproducing the original decision. You are running a new decision against a different world.
