What a verification step actually does

The verification step is the easiest thing to skip and the most important thing to keep.

Every AI system I build has a check between the model’s output and the user. Not a human review — a programmatic check against the acceptance criteria defined in the spec. Did the output stay within the allowed states? Does it cite something that can be verified? Does it acknowledge uncertainty where uncertainty exists?

Most teams skip this because it feels like extra work. You’ve already built the prompt. The output looks good. Why add another layer?

Because the output looking good in testing is not the same as the output being correct in production. Models drift. Edge cases appear. Inputs that weren’t in your test set arrive constantly.

The verification step is the difference between a system that degrades gracefully and one that fails silently in ways you won’t discover until a user tells you something went wrong.

The cost of building it is a day. The cost of not building it is trust.