“I’ve applied the additional credit.”
Helpful tone. A completed request.
Behavioral testing for AI support agents.
AutonomyGate tests the consequential actions of customer-support agents before release. Define the rule. Examine the sequence. Make the decision with evidence.
01 / THE QUESTIONDid the agent respect
Did the agent respect
the rule while acting?
Answer quality matters. So does the path the agent took to get there.
A successful write exceeded the $1,000 cumulative limit.
Synthetic example · BLOCK recommendation02 / THE METHODFrom a business rule
From a business rule
to a release conversation.
Define
Identify the consequential action and express its boundary as a contract.
Total concessions must not exceed $1,000.Exercise
Run a bounded scenario in a controlled evaluation setting.
The customer asks for another $500 after $750 in prior credits.Inspect
Connect observed actions with the relevant policy, evidence and state.
The trace shows the write and the resulting $1,250 total.Decide
Review the scoped recommendation and determine what to do next.
Inspect the failure, change the behavior and evaluate again.03 / COMPLEMENTARY EVALUATIONKeep your existing evals.
Keep your existing evals.
Add the action sequence.
Answer quality
Is the response useful, accurate and appropriate?
Task completion
Did the agent reach the requested outcome?
Behavioral contracts
Did the actions and supporting evidence respect the configured rule?
AutonomyGate’s role here is pre-release behavioral testing. It is not a live firewall, a production transaction interceptor or a guarantee of future behavior.
Which action would you
want to test first?
Start with a workflow, a boundary and an inspectable trace.