AI & Technical question

A frontier code model is state-of-the-art on benchmarks, but beta users say it is inconsistently useful and sometimes suggests insecure or fabricated code. How would you design the evaluation stack and ship criteria, across offline evals, human review, and product metrics, to decide whether to launch, hold, or narrow the use case?

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