The dashboard is green. The incident is real. The model endpoint is available. P95 latency is inside the objective. Token consumption is stable. HTTP error rate has not moved. Yet users are correcting more answers, an agent is opening the wrong records, and a workflow that used to finish in two tool calls now needs […]
The easiest evaluation to pass is the one that cannot stop a release. Many AI teams have evaluation notebooks, scorecards and dashboards. Far fewer have an explicit answer to a harder question: what evidence is required before a new model, prompt, retrieval index or tool definition is allowed to receive production traffic? Without that decision […]
A successful deployment proves that an AI system can run under one configuration, with one set of dependencies, at one point in time. It does not prove that the system can be supported through provider throttling, prompt releases, stale retrieval indexes, tool failures, cost spikes or partial business transactions. That distinction is the boundary between […]
