Test an AI agent’s failures before connecting real accounts
Use harmless fixtures for tool timeouts, conflicting evidence and denied actions, then verify that the application stops without inventing success.
In brief
An agent should be tested when things fail, not only when a demo goes smoothly. Use a controlled environment to check missing information, rejected permissions and uncertain tool outcomes before connecting valuable accounts.
A visible incomplete result is safer and more useful than a confident claim that an action succeeded when no confirmation exists.
Test missing and conflicting evidence
Give the agent a question absent from its source documents and two clearly conflicting versions. Check whether it identifies the gap rather than inventing an answer. Use harmless fixtures; do not intentionally expose real private data to test a leak.
Test denied and repeated actions
Ask a test account to access an out-of-scope resource and confirm the application rejects it. Simulate a failed tool response and verify retries are bounded. For write actions, test duplicate protection and status reconciliation rather than assuming a second call is harmless.
Make failure usable
Return a clear error, unfinished state or request for necessary information. Keep non-secret audit evidence and a way to halt the run. Review any test failure before broadening access; a prompt adjustment cannot repair an endpoint that grants too much authority.
Before you act
A sandbox test covers the cases you designed, not every future risk. Production authorization and monitoring still need to hold independently of the model.
What to do next
- List consequential actions and define their allowed, denied and uncertain states.
- Simulate failures with harmless test data and credentials scoped to the test environment.
- Verify no unauthorized or duplicate action occurs and that the user sees a truthful result.
