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Check your user flow for barriers.
"Analyze this user flow from an accessibility perspective. Identify potential barriers for users with: visual impairments, motor disabilities, cognitive differences, and situational limitations (one-handed use, bright sunlight, noisy environment)."
Identify unnecessary friction in your experience.
"Review this checkout/onboarding/signup flow: [describe flow]. Identify every point of friction. For each, classify as: necessary friction (security, legal), reducible friction (can be simplified), or unnecessary friction (should be eliminated)."
How might we reduce checkout abandonment for elderly customers? Use AI to understand the specific barriers elderly users face, then generate 5 solutions that would work for them WITHOUT making the experience worse for younger users.
"What specific UX barriers do elderly users (70+) face in digital checkout processes? Consider: vision, motor skills, cognitive load, trust, technology familiarity. For each barrier, suggest a solution that benefits ALL users."
Map the emotional landscape of your service.
"For this service journey: [describe service], map the emotional experience at each touchpoint. Where does anxiety peak? Where is there an opportunity for delight? Where do customers feel lost or abandoned? Suggest interventions for the 3 worst emotional moments."
How might we make mortgage applications feel less intimidating? Use AI to understand the psychology of financial anxiety, then design 3 service interventions that reduce fear without oversimplifying the process.
"What psychological factors make mortgage applications intimidating? Consider: complexity, jargon, financial risk, time pressure, power imbalance. For each factor, suggest a service design intervention."
Design the invisible parts of the service.
"For this customer-facing service: [describe service], what happens backstage that the customer never sees? Map the internal processes, handoffs, and potential failure points. Where could backstage improvements dramatically improve the frontstage experience?"
Communicate trust through visual design.
"How can we visually communicate trust and security for [product/feature]? Analyze what visual elements (color, typography, spacing, imagery, iconography) signal trustworthiness. Provide 3 distinct visual approaches with specific design recommendations."
Explore unexpected visual directions.
"Generate 3 different mood board concepts for this brand/product: [describe]. Each must be inspired by a different source: one from nature, one from architecture, and one from a historical art movement. Describe the colors, textures, typography, and imagery for each."
How might we communicate trust in our new security features? Use AI to explore how different visual languages convey safety, then create a visual design brief that balances security with approachability.
Make complex information accessible.
"Rewrite this technical explanation for a 5th-grade reading level: [paste text]. Use an analogy to explain the core concept. Then provide 3 alternative versions: one formal, one conversational, and one that uses a story format."
How might we explain data privacy to non-technical users? Use AI to find the right metaphors and language that make privacy feel understandable without being patronizing.
"Explain data privacy to a non-technical user using 3 different approaches: a metaphor, a story, and a Q&A format. Each should cover: what data we collect, why, how it's protected, and what control the user has. Avoid jargon entirely."
Find the right voice for the moment.
"For this user scenario: [describe scenario], write the same message in 5 different tones: reassuring, direct, playful, empathetic, and authoritative. Which tone best serves the user's emotional state at this moment? Why?"
Discover what you don't know you don't know.
"For this research question: [describe question], what are we NOT asking that we should be? What adjacent fields or disciplines might have relevant insights? What methodologies from other domains could we borrow?"
What don't we know about why customers leave? Use AI to generate hypotheses about customer churn that go beyond the obvious. Then design a research plan to test the top 3 most surprising hypotheses.
"Generate 15 hypotheses for why customers might leave [product/service], ranging from obvious to highly unconventional. For the 5 most unconventional, suggest a research method to test each hypothesis."
Audit your research for hidden biases.
"Review this research plan: [describe plan]. Identify potential biases in: participant selection, question framing, data interpretation, and researcher assumptions. For each bias, suggest a specific mitigation strategy."