1. UX Research Summary
Turning raw interview notes into a polished research readout is one of the most time-consuming parts of UX research — and one of the most important, because stakeholders who can’t read the findings won’t act on them. This prompt structures your notes into key themes with supporting quotes, pain points, and design recommendations, calibrated for a non-designer audience that needs context without jargon.
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Summarize the following raw user interview notes into a structured UX research readout. Include: key themes (3–5 bullet points), direct user quotes that support each theme, pain points identified, and 2–3 design recommendations. Tone: professional but accessible for a non-designer stakeholder audience. Notes: [paste your interview notes]
Paste your notes in one go — transcripts, bullet points, or rough observations all work. The more raw material you give the AI, the more specific and credible the themes it surfaces. Run the output past your research lead before sharing with stakeholders; the AI will correctly identify patterns but may miss nuance you caught in the room.
2. Design Brief Generator
A well-written design brief aligns the whole team before anyone opens Figma — it defines who you’re designing for, what success looks like, and what constraints are non-negotiable. Without one, designers and PMs often discover they’ve been solving different problems two weeks into the project. This prompt generates a complete brief from a short description, including user persona, success metrics, constraints, and open questions to surface early.
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Write a design brief for the following project. Include: project background and goals, target user persona (demographics, goals, pain points), success metrics, key constraints (timeline, platform, accessibility), and open questions to resolve. Project description: [describe the project]
The “open questions to resolve” section is where this prompt earns its keep — the AI will surface assumptions you haven’t challenged yet. Treat those questions as a kickoff agenda item rather than things to paper over. Resolving them before design starts is worth far more than resolving them during user testing.
3. Developer Handoff Note
Handoff notes are often the weakest link between design and engineering — designers leave too much to interpretation and developers build the happy path without knowing what the error state looks like. This prompt writes a handoff note that covers every interaction state, spacing in both px and rem, accessibility requirements, and flags the edge cases that typically get missed until QA.
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Write a clear developer handoff note for the following design component. Include: component purpose, interaction states (default, hover, active, disabled, error), spacing and sizing specifications in the format 'X px / Y rem', accessibility requirements (ARIA labels, keyboard navigation), and any open design decisions or edge cases to watch for. Component: [describe the component]
Describe the component in enough detail to generate real specifications — name the component, its context in the product, and any states you know are complex. The AI will draft the structure; you fill in the actual px values from your design system. This works especially well for interactive components like dropdowns, form fields, and modals where state coverage is easy to miss.
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4. Usability Test Script
Writing a usability test script from scratch takes longer than it should — you need a warm-up that puts participants at ease, scenario tasks that are realistic without being leading, probing questions that reveal reasoning rather than just behavior, and a debrief that closes cleanly. This prompt generates a full moderated script for any feature, ready to use in a research session or customize for your specific flow.
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Write a moderated usability test script for the following feature. Include: a warm-up introduction (2–3 questions to understand the participant's background), 3 scenario-based tasks with clear prompts, follow-up probing questions after each task, and a debrief section. Keep the tone conversational and neutral — avoid leading questions. Feature: [describe the feature being tested]
The “avoid leading questions” instruction is critical — the AI will phrase tasks as scenarios (“Imagine you’ve just received a new order and you need to…”) rather than instructions (“Click the order button”). Review the script with a colleague before running sessions; fresh eyes catch leading language that familiarity hides.
5. Stakeholder Presentation Narrative
Presenting design decisions to stakeholders is a skill that requires a different muscle than designing — you’re not showing work, you’re making a case. The most effective design presentations follow a clear narrative arc: here’s the problem, here’s what we considered, here’s what we chose and why, here’s the evidence, and here’s what’s next. This prompt writes that narrative for any design decision, timed for a five-minute verbal delivery.
Copy-paste prompt
Write the narrative script for a stakeholder presentation revealing the following design decision. Structure it as: (1) the problem we were solving, (2) the design options we considered, (3) the solution we chose and why, (4) how we validated it, (5) next steps. Keep it under 5 minutes when spoken aloud. Decision: [describe the design decision]
Give the AI the full context of the decision — what you considered and ruled out, what the validation looked like, and what the next steps actually are. The more specific you are in the “decision” field, the less the output reads like a generic design-thinking framework and the more it sounds like something a real designer said in a real meeting.