Create a product with AI by finishing one useful workflow

In this guide

1. The useful starting point
2. Define the smallest useful outcome
3. 1. Write a one-workflow product brief
4. 2. Prototype the uncertain decision
5. 3. Build a complete working slice
6. 4. Review AI output as product behavior
7. 5. Decide whether to expand
8. Sources and further reading

The useful starting point

Choose one user job, validate the need, and make one complete workflow work with real state and recovery before expanding the feature list.

Define the smallest useful outcome

Imagine a freelance designer who needs to collect a project brief and turn it into a review checklist. The useful outcome is not an “AI workspace.” It is a saved brief that can be reopened, corrected, and used to guide the next conversation. Start there.

Write down what happens today, where it fails, and what evidence suggests the problem matters. If the only evidence is your enthusiasm, begin with conversations or a manual service. AI makes it easier to generate software; it does not establish demand.

1. Write a one-workflow product brief

Help define a small product for [person] doing [job]. Existing evidence: [sources]. Map entry, input, processing, review, save, and return. Identify the riskiest assumption, a manual way to test it, and the smallest useful version. Separate essential behavior from later ideas.

For the fictional brief tool, essential behavior might include creating a brief, editing it, generating a draft checklist, saving both, and reopening the same project. Team permissions, billing, and a template marketplace can wait unless the initial use case truly depends on them.

2. Prototype the uncertain decision

Use a lightweight interactive prototype to explore whether the input questions make sense and whether the output is useful. Label sample outputs. Ask people to complete their task, then explain what they would change before using the checklist.

3. Build a complete working slice

Give your coding assistant explicit acceptance criteria. Ask it to explain the data model and how a person retrieves their work. Distinguish browser-only storage from an account-backed record; the interface should make that difference understandable.

4. Review AI output as product behavior

For a checklist generator, define what makes an output unacceptable: invented requirements, missing source references, or instructions unrelated to the brief. Build a small set of ordinary, incomplete, and conflicting examples. Inspect the result after model or prompt changes. A good demonstration on one example is a starting point, not a reliability claim.

Given this brief, return a draft checklist with each item tied to a supplied requirement. Mark assumptions. If a necessary detail is missing, ask for it rather than inventing it. The user must review the checklist before sharing it.

5. Decide whether to expand

Observe whether people complete the workflow, return to their saved work, and find the output useful enough to act on. Record support issues and corrections. Use those observations to decide whether the next feature removes a real obstacle.

Continue with the existing prototype-to-product handoff guide. If the next step is making one journey testable, review the scope of Ashley’s Prototype Improvement Sprint.

Sources and further reading

• Figma: create a Figma Make file
• Make: create your first AI agent
• W3C: evaluating web accessibility

Sources checked November 4, 2026. Review the linked publisher information for current details.

Put one idea to work

Take the next step with a practical worksheet, a clear research question, and a standard you can use to review the work.

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