Putting guardrails around AI in production systems
A demo is judged on its best output
Production is judged on its worst. The interesting question is never how good the model is on a typical case — it is what happens on the malformed invoice, the email in a second language, or the document that is technically a photograph of a document.
Structure the output, then validate it
Free text is difficult to check automatically. Ask for a defined schema, validate every field against your own business rules, and treat a validation failure as a routing decision rather than an error. Failed cases go to a person; they do not go through with a shrug.
Gate by consequence, not by comfort
Not everything needs a human check. Classify actions by what happens if they are wrong. Filing a document in the wrong folder is recoverable. Sending a customer an incorrect invoice is not. Put the approval gate where the consequence is, and leave the rest to run.
Log the input beside the decision
When someone asks in three months why a record looks the way it does, you need the input, the model version, the prompt version and the output stored together. Without that, you cannot debug it and you certainly cannot defend it.
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