Evaluating and testing AI safely

​A new model comes out, cheaper and faster, and the vendor swears it performs just as well. A prompt gets tuned. Any one of these can silently break a production workflow — and the first sign of trouble is often an angry customer, not a dashboard.

​"Deploys cleanly" and "actually works" are different questions — staging answers the first, evaluation answers the second.

​We will share our experience and take questions from the audience.

​What you'll learn:

• ​Why staging and evaluation are different questions — and why you need both

• ​How to build a gold benchmark: monetization-critical queries, real user history, edge cases

• ​Three key metrics — semantic similarity, faithfulness, groundedness — and what each catches

• ​The cost tradeoff of LLM-judging-LLM evaluation

• ​A live look at pass-rate breakdowns, staging vs. production, inside the Ejento platform