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Production AI / 1 min read

An AI workflow needs a definition of completion.

Clear completion and stop conditions make outcomes and operating cost easier to assess.

Define the observable finish

A generated draft, a reviewed result, and a verified external update are different outcomes. A production workflow should report the one its business owner actually requested. Without a clear finish, additional attempts can consume resources while leaving the operational task unresolved.

A practical first step is to describe the evidence that establishes completion for one workflow. The team also defines when the workflow stops for missing input, exhausted attempts, denied access, or an unresolved external action. Useful progress and the next required decision should remain available.

Use completion to assess value

A Production AI Lighthouse can evaluate completed tasks, appropriate escalations, unresolved outcomes, and total operating effort. That gives the sponsor a clearer basis for deciding whether to scale, revise, or stop than an activity count alone.

A relevant next step

Production AI Lighthouse

Tera Earlywine helps a business owner and data sponsor bring one defined AI workflow into production. Scope includes evaluation, permitted actions, human escalation, monitoring, and operational handoff, with acceptance criteria for quality, latency, cost, and successful outcomes.

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