Evaluation before model upgrades

A larger model is only an improvement when it performs better on the specific conversations the product needs to handle.

Model upgrades are tempting because benchmark numbers offer a simple story. Product quality is harder: the system must answer grounded questions, select the right evidence, respect boundaries, and recognize when a human conversation is useful.

A focused evaluation set turns those requirements into repeatable tests. It should include successful cases, ambiguous requests, unsupported services, privacy questions, and adversarial prompts.

Once that baseline exists, a new model can be judged by real outcomes, latency, and cost. An upgrade becomes an engineering decision rather than an assumption.

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