The industry has converged on a definition of "operator-ready" that is measurable, deployable, and wrong.
The most cited frameworks, Anthropic's "Building Effective Agents" (December 2024), Hamel Husain's "Your AI product needs evals" (2024), the LangChain eval documentation, NIST AI RMF (2023), Google's responsible AI practices, OpenAI's model specification (May 2024), share a common structure. They define reliability as pass-rate on a test set. They define readiness as a threshold on that pass-rate.
This is a reasonable definition for production-readiness. It is not a correct definition for operator-readiness.
The distinction is not semantic. It has direct consequences for how you test, what you ship, and what breaks after handoff.
What the existing frameworks get right
