Evaluate an AI feature against representative tasks and known failure modes before relying on live users to discover its limits. A compelling demonstration is useful for exploration, but it is not evidence of dependable performance across real conditions.
Build a representative test set
Include common tasks, edge cases, missing information and inputs the system should decline or escalate. Use appropriately handled data and avoid unnecessary personal information. Keep a held-out set so repeated development does not simply tune to familiar examples.
Document how the examples were selected. A test set composed only of easy successful interactions creates a misleading picture.
Score the dimensions that matter
Assess factual correctness, task completion, appropriate use of sources, latency and the consequences of failure. Add domain-specific criteria when relevant. Do not let polished language outweigh a wrong answer.
For a review-response assistant, an unsupported refund promise may be more serious than an awkward sentence. The evaluation should reflect that difference.
Compare changes deliberately
Run the same evaluation when changing prompts, models, retrieval logic or source material. Record the version and configuration so a result can be reproduced. Investigate regressions rather than assuming a newer component is always better.
Use human judgment where an automated score does not capture the actual customer consequence. Automated checks can support review, but their own limitations need examination.
Prepare for production learning
Define monitoring and an escalation path for failures that escape testing. Make it possible to disable or narrow the feature without disrupting unrelated functionality. Review real-world cases to improve the evaluation set while respecting data handling requirements.
Evaluation is not a one-time gate. It is an ongoing description of what the feature is expected to do and the evidence that it still does it. That makes infrastructure choices accountable to product value rather than novelty.