Your model hits 90% on MMLU. How do you decide whether...

MMLU is a quiz-style benchmark that confirms a model can retrieve factual knowledge under standardized prompts. However, it does not predict how a model will perform on actual customer tasks. Before deploying, you should conduct an ask-style evaluation using a representative sample of real-world customer sessions. This evaluation should specifically measure metrics like helpfulness, groundedness, and refusal behavior. You should define a specific evaluation method, such as human-judged samples of 100 realistic sessions, and establish a clear pass threshold for deployment.