Start with the workflow, then choose the AI

The first question in an AI project should be about the work. What happens today? Where does someone wait, repeat a task, or make a decision with incomplete information?

A model is one possible tool inside that process. Understanding the process comes first.

Map one complete task

Choose a real task with a clear beginning and end. Record the inputs, the people involved, the systems they use, and the output someone actually needs. “Prepare a product brief for review” is a more useful starting point than “add AI to marketing.”

Look for the handoffs. A fast generation step creates little value if the result still needs to be copied through three disconnected tools.

Decide where judgment belongs

Separate repeatable operations from decisions that need context. Formatting a record, assembling known inputs, or producing a first draft may be suitable for automation. Approving a promise to a customer deserves a different level of control.

Write down what the system can do by itself, what needs review, and what should happen when the input is incomplete. These boundaries are part of the product.

Build a small, observable loop

Start with a single workflow and a representative set of examples. Keep the original inputs, the generated output, and the reviewer’s decision together so problems can be investigated.

• Define what a useful output looks like before choosing a model.
• Keep a manual fallback for interrupted or uncertain steps.
• Make failures visible and give people a way to retry safely.
• Evaluate the whole task, including review and correction time.

The outcome is a practical decision: expand the workflow, change the approach, or keep that step manual. All three can be good engineering choices.

Connect the useful pieces

Once the small loop works, integrate it with the systems people already use. Queues, validation, clear status, and predictable recovery often matter as much as generation quality.

Kovo Pipeline is one example of thinking through connected stages, from a brief to a reviewed video output.