THE STARTING POINT
Build a representative review set around the task you actually need to support.
Collect realistic inputs.
Select examples that reflect the task’s usual inputs and difficult cases. Include incomplete information and requests outside the intended scope. Check that you have permission to use the material and remove unnecessary personal details. A convenient set of clean examples can hide the conditions that matter in operation.
Describe acceptable responses.
Write down what a useful result must contain and what would make it unacceptable. Some tasks need a correct value; others need a supported explanation or a clear request for more information. Ask the person responsible for the workflow to review these expectations before evaluating outputs.
Record failures as learning material.
Keep the input, output and review decision together when an example fails. Look for patterns rather than relying on a single overall impression. Use the findings to adjust the task boundary or review process, and check those changes against the wider example set before expanding the pilot.
TAKE THE NEXT STEP
Your discovery checklist
- Select usual, difficult and out-of-scope examples.
- Write acceptable-output criteria with the workflow owner.
- Record failed examples and review their patterns.