# UX Design Coach — AI workflow practice pack

Published 2026-10-16. Original educational prompts and exercises. Use approved, minimized source material. Outputs need human review.

## Use AI to inspect UX microcopy before your next usability test

Find ambiguous labels, incomplete error messages, and misleading promises before testing a flow with real people. Includes a review rubric and two reusable prompts.

### Inspect before rewriting

Review this microcopy for the task [task]. Product facts: [facts]. Screen sequence and exact text: [text]. Do not rewrite yet. Return a table with original phrase, possible misunderstanding, relevant product fact, proposed severity, and question for the team. Check task clarity, consequences, terminology, recovery, and accessibility questions. Label predictions about users as hypotheses. Do not invent behavior or claim that this review establishes accessibility compliance.

### Produce alternatives with explicit tradeoffs

Rewrite only the approved issues below: [issues]. Preserve these verified facts: [facts]. For each item provide two alternatives, explain their tradeoffs, and list any fact still needing confirmation. Keep [terminology] consistent. Then propose three neutral usability tasks that let us observe understanding without repeating the button labels or teaching the expected answer.

### Your exercise

1. Choose a three-screen task and document exactly what each action does.
2. Run the inspection prompt and have a product owner resolve every behavioral unknown.
3. Create two copy alternatives for the highest-impact issue and test understanding with likely users.

### Review checklist

- [ ] Every promise matches verified product behavior.
- [ ] Failure states explain the next useful action.
- [ ] AI predictions remain labeled as hypotheses.
- [ ] Accessibility implementation and user understanding receive separate evaluation.

Your evidence:

Your next decision:

Owner and review date:

## Make AI argue against your favorite design without confusing critique with research

Turn a confident design opinion into testable assumptions, useful alternatives, and a decision record. Includes prompts for balanced critique and research planning.

### Ask for the strongest case on both sides

Evaluate design A and design B for [decision and audience]. Evidence: [dated sources]. Constraints: [constraints]. Criteria and priorities: [criteria]. For each design give the strongest supporting case, strongest objection, assumptions, and unanswered questions. Cite the supplied evidence by identifier. Separate observations from inferences. Do not invent users, quotes, research, or numerical probabilities. What evidence would make you reverse your recommendation?

### Convert objections into questions you can investigate

Turn these three design assumptions into a research plan: [assumptions]. For each suggest the smallest useful investigation, suitable participants or evidence source, a neutral task, what to observe, and what finding would change our decision. State limitations. Do not propose leading questions, fabricate findings, or treat synthetic responses as participant data.

### Your exercise

1. Anonymize two design alternatives as A and B and write the evaluation criteria first.
2. Run the balanced critique, then flag every claim without a supporting evidence identifier.
3. Select one assumption to investigate and save a decision record with a review trigger.

### Review checklist

- [ ] Observed evidence, assumptions, and preferences are separate.
- [ ] Both alternatives receive the same evaluation criteria.
- [ ] Research tasks do not reveal the desired answer.
- [ ] The final decision names uncertainty and the evidence that could change it.

Your evidence:

Your next decision:

Owner and review date:

## Keep learning

Free beginner course: https://aiteachers.cc/courses/first-useful-ai-workflow/

Free experienced-user course: https://aiteachers.cc/courses/repeatable-ai-workflows/