A repeatable workflow is not defined by the model. It is defined by the operating pattern around the model.
The minimum structure
Inputs, context, transformation, review, handoff. If one of those pieces is vague, the system becomes fragile.
Why repeatability matters
Repeatability is what turns AI from an interesting capability into a practical business asset. Teams need to know what goes in, what comes out, and how to trust the result enough to keep using it.
What to avoid
Overbuilt architecture before the first proof. Giant scope. Undefined ownership. And the fantasy that one prompt can stand in for an operational system.
What to build first
Build the smallest workflow that produces visible value and can survive real usage. Then tighten it until it stops feeling experimental.
