Originally published on AI Tech Connect.
What you need to know Here is the failure this guide exists to prevent. Your evals passed in March. You shipped, the numbers looked good, and you stopped watching. In June, support tickets start mentioning that the assistant has become oddly terse, or that it refuses a category of request it used to handle. Every call returned 200. The model field says exactly what it said in March. Nothing in your deployment history explains it, and by the time someone suggests the model changed underneath you, there is no way to prove it either way, because nobody measured the baseline. The root cause is a category error: treating the identifier a provider returns as though it were a measurement. It is a label attached by the party whose behaviour you are trying to verify — accurate about which alias…
Top comments (0)