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My eval suite passed on launch day, and nothing warned me before users started noticing the answers slipping weeks later.
What you'll have at the end
A scheduled job that scores a sample of live answers against a golden set and alerts when the score drops
You need
You already have a golden test set with a working LLM-as-a-judge script that scores it pass or fail, and a place your production question-answer pairs get logged that you can pull a random sample from.
Not covered
This does not fix a confirmed drop, whether that means rolling back a prompt, retraining, or switching providers: it only proves a drop is real and gets it in front of someone fast.
Leans on
Write your first LLM-as-a-judge grading script
If you don't have a working judge script yet, build the grader before you point it at production traffic.
Roll back a prompt change that broke your output
Once this recipe's alert confirms a real drop, that's the recipe for undoing whatever caused it.
Canary a prompt change before it reaches every user
Checking a change before it reaches everyone is a different problem from watching an already-shipped system for drift weeks later; reach for that one when you're about to ship, not once you're already live.
Checked 18 Aug 2026
Part of the LLMOps cookbook