Table of contents

The first AI workflow is a product decision

Yander Editorial

Design & engineering

2 min read

A translucent glass head against a teal background

Choose a narrow, observable task before choosing a model. A useful pilot begins with a clear definition of a finished job.

This field note works through the decisions between an idea and a usable product. It starts with a concrete task and follows the choices that shape the experience, the delivery, and the next iteration.

Choose work with a clear finish line

Start with a recurring task whose inputs and outputs you can inspect. A draft that a person reviews is often easier to evaluate than an open-ended promise to automate a department.

Write down what a useful result looks like and what would make it unacceptable. Include the person who currently owns the work in that conversation.

Inspect the whole handoff

Map where the input comes from, who has access to it, and what happens after the output is produced. A model call is only one step in that sequence.

Keep exception handling visible. If a document is missing or a source is out of date, the workflow should help the operator resolve the problem.

Run a bounded pilot

Use a limited set of tasks and a named group of operators. Review outputs against the original task and record correction effort alongside completion.

Decide in advance what evidence would justify continuing, changing direction, or stopping the pilot. Keep the result of that decision in the delivery notes.

AI & digital transformationBack to top

Found this useful? Share it forward

Frequently asked questions

Common questions about this topic

Where should a team start?

Choose one real task and name the decision you need to make. Start with a recurring task whose inputs and outputs you can inspect. A draft that a person reviews is often easier to evaluate than an open-ended promise to automate a department.

How much should the first version cover?

Keep the scope narrow enough to cover one complete task and its essential recovery paths. Use feedback from that slice to decide what to expand next.

How can we tell whether a change helped?

Compare the experience on the same task before and after the change. Observe completion, correction effort, and recovery, and keep the evidence behind the decision.

Keep reading

Related articles you might find useful

Designing an AI product around a real job

Yander EditorialDesign & engineering
A green-toned sculptural figure

AI UX research for AI products people adopt

Yander EditorialDesign & engineering
A blue-toned abstract image of tools at work

Generative interfaces that make the next step clear

Yander EditorialDesign & engineering
A green flower rendered as an abstract digital form
All articles