AI features need evaluation that is specific to the user task. Generic demos are not enough to tell whether the feature is ready.

Checklist

• Collect realistic examples from actual workflows.
• Define pass/fail criteria before tuning prompts.
• Include edge cases, malformed inputs, and common user mistakes.
• Track changes across prompt, model, and retrieval updates.

Why this helps

The goal is not to make evaluation heavy. The goal is to make quality visible enough that the team can improve it deliberately.