Design Better User Experiences with AI

I need to create a UX persona for [product]. Here is my user research data: [Paste research findings — interview quotes, survey results, behavioral data, demographics] Build a research-backed persona that includes: (1) a realistic name, photo description, and demographic summary, (2) a one-sentence persona statement: "[Name] is a [role] who needs [need] because [motivation]", (3) goals — 3 primary goals (functional) and 2 emotional/social goals, (4) frustrations — 4-5 pain points supported by direct research quotes, (5) behaviors — typical workflow, tools used, frequency of use, (6) a "day in the life" scenario showing where [product] fits, (7) technology comfort level and preferred devices, and (8) decision-making factors — what influences their product choices. Do not invent characteristics. Everything must trace back to the research data I provided.

Map the end-to-end customer journey for [persona/user type] using [product/service]. The journey starts at [awareness trigger] and ends at [loyalty/advocacy stage]. For each stage of the journey: (1) define the stage name and what triggers the transition to the next stage, (2) list the user's actions and touchpoints (every interaction with your brand), (3) capture their thoughts and questions at this stage, (4) describe their emotional state (frustrated, excited, confused, confident) with a sentiment score, (5) identify pain points and friction, (6) list opportunities for improvement, and (7) note which team owns this touchpoint (marketing, product, support, sales). Create a visual-ready format with stages as columns and the dimensions above as rows. Highlight the top 3 "moments of truth" where the experience makes or breaks the relationship.

Create an empathy map for [user type/persona] in the context of [task or scenario they are trying to accomplish]. Based on this research: [Paste relevant interview quotes, observations, survey responses] Fill in all four quadrants: (1) Says — direct quotes from users during interviews or support tickets, (2) Thinks — thoughts they might not say out loud, inferred from behavior and hesitations, (3) Does — observable actions and behaviors, (4) Feels — emotional responses inferred from tone, body language, and word choice. Then add: (5) Pain points — the biggest frustrations revealed across all four quadrants, (6) Gains — what success looks like for this user, and (7) a design implication for each pain point — one sentence starting with "The product should..." Use only data from the provided research. Flag any quadrant where you are making inferences rather than using direct evidence.

I need to document the key scenarios and use cases for [feature/product]. The primary users are: [list user types]. Create: (1) 5 primary scenarios covering the most common use cases, each written as a narrative: "[User] is in [context]. They want to [goal]. They [actions]. The system [response]. The outcome is [result]." (2) 3 edge case scenarios covering unusual but important situations, (3) 1 error scenario where something goes wrong and the user needs to recover, (4) for each scenario, specify the preconditions (what must be true before the scenario starts), the trigger (what initiates the scenario), and the postconditions (what is true after successful completion), (5) map each scenario to a specific user type/persona, and (6) prioritize scenarios by frequency and business impact for development sequencing.

I need to define anti-personas for [product] — user types we are explicitly NOT designing for. This helps prevent scope creep and feature bloat. Based on our product positioning and target audience: Target audience: [describe ideal users] Product focus: [describe core value proposition] Common feature requests we say no to: [list] Create 3 anti-personas: for each one provide (1) a name and brief description, (2) why they are attracted to the product (what brings them in), (3) why the product is not right for them (the fundamental mismatch), (4) the features they would request that would dilute the product if we built them, (5) the cost of trying to serve them (engineering resources, support burden, UX complexity), and (6) where to redirect them instead (competitor or alternative solution that fits their needs). Include a one-sentence test: "If a feature request primarily serves [anti-persona name], we should say no."

I ran a [open/closed/hybrid] card sort with [number] participants. The cards represented: [list content items or features]. Here are the grouping results: [Paste results — how participants grouped the cards, what they named the groups] Analyze the results: (1) identify the strongest clusters — items that were grouped together by 70%+ of participants, (2) identify "homeless" items that participants placed inconsistently, (3) calculate a similarity matrix showing which items are most often paired, (4) suggest an optimal navigation structure based on the clustering, (5) recommend labels for each category based on participant-generated names (look for the most common and clearest labels), (6) flag any items that should appear in multiple categories (consider cross-links), and (7) compare the results to the current navigation and highlight discrepancies.

Design the information architecture for [product/website]. The content includes: [list all major content types, features, and pages]. The primary user tasks are: [list top 5 user goals]. Create: (1) a hierarchical site map showing all pages organized into no more than 7 top-level categories (Miller's Law), (2) for each category, list the sub-pages up to 3 levels deep, (3) define the primary navigation (always visible), secondary navigation (contextual), and utility navigation (account, settings, help), (4) specify which pages link to which other pages (cross-links), (5) design the breadcrumb structure, (6) recommend a search strategy — what should be searchable, what filters to offer, and (7) test the architecture against the top 5 user tasks — can each task be completed in 3 clicks or fewer?

I need to audit the content on [product/site]. Here is the current structure: [Paste sitemap, page list, or navigation structure] Conduct a content audit: (1) catalog every page or content item with its purpose, audience, and current placement, (2) label each item as: keep as-is, update, merge, archive, or delete with reasoning, (3) identify content gaps — topics or tasks that users expect but that do not exist, (4) flag redundant content — pages or sections that overlap and should be consolidated, (5) check content against the top user tasks — is there a clear content path for each task, (6) assess findability — are items labeled clearly enough that users would look for them where they are placed, and (7) prioritize actions into a 30-60-90 day content improvement plan.

Design the search experience for [product/site]. The searchable content includes: [describe content types — products, articles, users, settings, etc.]. Total items: [approximate number]. Common search queries: [list example searches]. Create a complete search UX specification: (1) search input design — placement, placeholder text, auto-suggestions behavior, (2) search results page layout — result card design for each content type, sort options, filters, (3) define the ranking logic — what signals determine result order (relevance, recency, popularity), (4) empty state — what happens when no results are found (suggestions, did-you-mean, popular searches), (5) type-ahead behavior — what appears as the user types and when, (6) filter and facet design — which filters to show, single vs multi-select, and (7) search analytics — what to track to improve search quality over time.

I need to create a taxonomy for [product/content type — e.g., product categories, help articles, course topics, recipe tags]. The items to categorize: [list or describe the content]. The users are: [describe]. Create: (1) a hierarchical taxonomy with 2-3 levels of categories, (2) clear naming conventions — explain the labeling rules (noun vs verb, singular vs plural, user language vs internal jargon), (3) definitions for each category that eliminate ambiguity about where items belong, (4) cross-reference rules — when should an item appear in multiple categories, (5) governance rules — how to decide where new items go, who approves new categories, (6) a controlled vocabulary of approved terms to prevent synonym proliferation, and (7) a testing method — 5 sample items with the rationale for their placement to train other team members.

Audit the following interface for WCAG 2.2 Level AA compliance: [Describe the interface — page type, key elements, interactive components, forms, media, navigation] For each WCAG principle (Perceivable, Operable, Understandable, Robust), check: (1) list every applicable success criterion, (2) evaluate pass, partial, or fail for each, (3) for failures, describe the specific violation and which users it affects, (4) provide the exact fix with code or design changes, (5) rate the fix effort (quick, medium, major), and (6) prioritize fixes by impact on users with disabilities. Pay special attention to: color contrast ratios, keyboard navigation order, screen reader announcements, form label associations, error identification, and focus management. Include any Level AAA criteria that are easy wins.

I need to design an accessible form for [purpose — registration, checkout, application, contact]. The form fields are: [list all fields with types]. Design an accessible form specification: (1) proper label placement and association (visible labels, not just placeholders), (2) helper text and instruction placement for each complex field, (3) required field indication that does not rely on color alone, (4) error message design — inline vs summary, timing (real-time vs on submit), and screen reader announcement strategy using aria-live, (5) focus management — tab order, focus trapping in modals, focus return after dismissals, (6) keyboard shortcuts for common actions, (7) touch target sizes for mobile (minimum 44x44px), and (8) auto-fill support using correct autocomplete attributes. Include the HTML structure with ARIA attributes for one complex field as an example.

I need to optimize the screen reader experience for [page/feature]. The interface contains: [list all interactive elements, content sections, dynamic content areas]. Write a complete screen reader optimization plan: (1) define the heading hierarchy (h1-h6) and landmark regions (nav, main, aside, footer), (2) specify ARIA roles, labels, and descriptions for each interactive component, (3) define the reading order and whether it matches the visual order, (4) handle dynamic content updates — which use aria-live polite vs assertive and which use focus management, (5) write alt text for all images (decorative images get alt=""), (6) specify how expandable/collapsible sections announce their state, (7) define skip links and how they work, and (8) test the complete flow by writing out what a screen reader would announce step by step as a user navigates from top to bottom.

Review the following design for inclusivity across a range of user needs: [Describe the interface design — layout, colors, typography, interactions, content] Assess against these dimensions: (1) visual accessibility — contrast ratios, text sizes, color dependence, dark mode support, (2) motor accessibility — target sizes, spacing between interactive elements, drag-and-drop alternatives, single-hand usability, (3) cognitive accessibility — reading level, information density, cognitive load, clear error recovery, progress indication, (4) situational limitations — bright sunlight, noisy environment, one-handed use, slow connection, (5) language and cultural inclusivity — jargon, idioms, date/time formats, name field flexibility, (6) age inclusivity — patterns that challenge older or very young users. For each dimension, rate the current design (good, needs work, poor) and provide specific improvements.

I need to create an accessible color system for [product/brand]. Current brand colors: [list hex codes and their uses — primary, secondary, accent, background, text]. Generate an accessible color system: (1) test all color combinations against WCAG AA (4.5:1 for normal text, 3:1 for large text) and AAA standards, (2) for any failing combinations, suggest adjusted colors that maintain brand feel while meeting contrast requirements, (3) create a color usage matrix showing which colors can be safely paired, (4) design a semantic color system (success, warning, error, info) that is accessible, (5) ensure every color-coded element also has a non-color indicator (icon, pattern, text), (6) provide dark mode equivalents that maintain the same contrast ratios, and (7) test the system for the three main types of color blindness (protanopia, deuteranopia, tritanopia) and flag any problematic combinations.