What does your AI demo need to prove next?
A fluent answer is a start. The next question is whether the result helps a real person finish a specific task, including the awkward cases that a polished demo can skip.
Ask the person doing the work to try the result on a representative case. Look at the information they still have to find, the corrections they make and whether the handoff gives the next person enough context.
The task is too broad
A broad goal such as “improve operations” leaves the first result unclear. Choose the exact request, document or decision to improve.
The reviewer arrives too late
The team responsible for access and important decisions needs to help shape the test from the beginning.
Changes skip the test
Keep the test cases and expected outcomes. Run them again when prompts, models, information or tools change.
What closes the gap
- One workflow with one owner and a documented exception map
- Baseline metrics that quantify current delay, cost, and error patterns
- Approval gates tied to material risk points instead of broad fear
- An evaluation harness that turns launch and change decisions into evidence-backed calls