When do you consider an AI system ready for users?
Answer out loud or in your head first, then compare.
Answer
First I establish which results and risks are acceptable. I check quality on representative tasks, security, time, cost and how failures are handled. A few successful demos aren't enough, nor is the absence of HTTP errors.
I start with a limited group and scope, e.g. only suggestions without independent writes. I have a way to switch the feature off and a safe alternative for the user. I watch the corrections and the real effects. I don't require a perfect sentence in every answer, but errors must not exceed the agreed limit of harm. Someone has to own maintenance and incident response after the first rollout too.
Why it matters: The role includes getting a product working and maintaining it.
Possible follow-ups: What is an absolute reason to halt a rollout?
How did it go? Be honest — “Not yet” puts the question on your review list.
Start with
- J-P01 · What is evaluating an AI system, i.e. an eval? — Evaluation, quality and production AI
- J-P02 · How does an eval differ from an ordinary code test? — Evaluation, quality and production AI
Further reading
- Microsoft Foundry: Observability in generative AI(opens in a new tab)Docs; accessed 22.10.2026. Evaluation, monitoring and tracing across the solution's lifecycle.