Separate the model from the product promise
A model response is an input to a product workflow. The workflow still needs validation, permissions, context boundaries, user feedback, safe failure behavior, and an owner when results are uncertain.
Build an evaluation set early
Collect representative tasks, difficult edge cases, unacceptable failures, and expected evidence. Run the same set when prompts, retrieval, or model providers change.
Design the data lifecycle
Document what is sent, where it is processed, how long inputs and outputs persist, who can retrieve them, and how deletion propagates through files, queues, analytics, and backups.
Track value and cost together
Measure accepted outcomes, correction rates, latency, model cost, fallback rate, and user abandonment. A cheaper call is not a win if it creates expensive review work.
Apply this to your product
Our estimator turns the constraints behind this guide into a private planning brief.
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