How to test an AI agent before your team depends on it

Define what good looks like

Describe the task in terms a person can judge. A support draft might need to answer the question, use current source material, avoid unsupported claims, and ask for help when information is missing. “Sounds good” is not an acceptance rule.

Test the business result, not just the model output. A correct answer on the wrong customer record is a failure. A good draft that never reaches the reviewer did not complete the task.

Use more than the easy examples

Build a small test set from real work: normal cases, rare but valid cases, missing fields, conflicting records, duplicates, and requests outside scope. Use approved or de-identified material.

Keep some cases apart from the ones used during building, or you will tune to a familiar set and mistake it for reliability. Record the input, the expected behavior, the actual result, and the reason for each failure.

What a disagreement between models showed us

In a support-classification review, one model labeled full issue text and a second reviewed the same material independently. Their disagreements exposed ambiguous rules and missing categories. A request about buying a service, for example, had to be separated from a question about how an existing feature worked.

We corrected the instructions and repeated the reviewed cases. The models then agreed, including on leaving some cases unclassified. We recorded that as a development regression check. Because the same cases were reused, it was not a blind accuracy test or proof that support staff would agree.

The prototype stayed out of live routing. A good test report names the inputs, who judged them, what changed, and what it cannot yet prove.

Test boundaries and failure as actions

Write down what the agent may do. Then try to make it do more. A document or message can contain text that looks like an instruction. It must not change the agent’s permissions or its task.

• Can it reach only the data it needs?
• Do sensitive actions stop for approval?
• Is a repeated request safe to process again?
• Can a reviewer see the source of an important claim?

Then test failure: unavailable tools, incomplete records, failed updates. The interface must never say done when only a draft exists. Prepared, approved, sent, and recorded are different states.

Release small, then keep testing

Start with the smallest useful scope and the people who can give informed feedback. Review real outputs and the effort needed to check them. Name a person who owns the response when it fails, and a way to pause it.

Re-run the relevant tests when the model, prompt, tools, source material, or business rules change. A passed test is evidence about that version only. Track correct completion, corrections, review time, exceptions, and cost per completed task.