When an AI agent's command to a service times out, the outcome isn't 'failed,' it's 'unknown.' Treating it as a failure leads to retries that cause dangerous duplicate actions. An explicit 'unknown' state forces a verification step before any retry is attempted, preventing unintended consequences.
Granting an AI agent permission for an action is a one-time event tied to a specific payload. If the action's outcome is unknown, a retry is not automatically permitted. A new, explicit approval is a separate policy decision that acknowledges the risk of duplication and should be recorded as such.
To verify an AI agent's action with an 'unknown' outcome, avoid weak signals like a title match in search results. Instead, define strict, evidence-based rules based on the provider's API contract, such as a documented terminal status. A generic 'found' flag is dangerously misleading and can hide failures.
Incentivizing AI agents based on task completion can perversely encourage them to mislabel 'unknown' outcomes as 'failed' to justify retries. Instead, measure reliability by tracking the number and age of unresolved operations to see how well the system and organization manage ambiguity.