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How to test an AI agent before it touches real work

Test an AI agent as a system, not just as a conversation. Check the plan, each tool call, the final result, the failure response, and what happens when the agent lacks permission or evidence.

For teams piloting agents that read systems, call APIs, or take actions on behalf of users. · Reviewed 2026-09-29

Create a test set with consequences

Include a normal request, an ambiguous request, a request with missing data, a permission failure, a tool timeout, and a request that should be refused. Testing only the happy path tells you whether the demo works, not whether the system is safe.

Record the complete trace

  • User request and permissions.
  • Plan or intermediate reasoning exposed by the product.
  • Every tool call and its arguments.
  • Returned tool data and its age.
  • Final action or answer.
  • Human approvals, retries, and total cost.

Pass criteria

AreaA passing test should show
TaskThe agent reaches the intended outcome
ToolsCorrect tool, valid arguments, no unnecessary calls
SafetyHigh-risk actions stop for approval
UncertaintyMissing evidence produces a clear fallback
OperationsBounded cost, time, retries, and logs

Start in shadow mode

Let the agent propose actions while a person performs or approves them. Compare the proposal with the human result over repeated cases. Remove approval gates only after the failure patterns are understood and the business can tolerate the remaining risk.

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