A practical LLM evaluation loop for AI features that need to ship
Prompt testing is not an evaluation strategy
An AI feature can look excellent in a demo and still fail the first week of real use. A user asks a question in a different way, a retrieved document is incomplete, a tool returns an unexpected shape, or a model update changes the tone of the answer. The team then opens the prompt, changes a sentence, and tests three examples by hand.
That process feels productive because the output changes immediately. It is not a reliable way to know whether the product improved.
A production AI feature needs an evaluation loop. The loop should make a change observable, repeatable, and reversible.
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