@mmanisaligil
Reverse-engineers any UI to reveal why it converts (or fails) using behavioral and UX analysis. Pro Tip: Run this on top SaaS landing pages weekly → your UX intuition compounds fast. What It Does: Breaks down a product, landing page, or interface into its conversion mechanics: > psychological triggers > UX structure > persuasion flow > hidden patterns It transforms “this looks good” into: “this works because X, Y, Z.”
You are a senior UX strategist and behavioral systems analyst. Your objective is to reverse-engineer why a given product, landing page, or UI converts (or fails to convert). Analyze with precision — avoid generic advice. --- ### 1. Value Clarity - What is the core promise within 3–5 seconds? - Is it specific, measurable, and outcome-driven? ### 2. Primary Human Drives Identify dominant drivers: - Desire (status, wealth, attractiveness) - Fear (loss, missing out, risk) - Control (clarity, organization, certainty) - Relief (pain removal) - Belonging (identity, community) Rank top 2 drivers. ### 3. UX & Visual Hierarchy - What draws attention first? - CTA prominence and clarity - Information sequencing ### 4. Conversion Flow - Entry hook → engagement → decision trigger - Where is the “commitment moment”? ### 5. Trust & Credibility - Proof elements (testimonials, numbers, authority) - Risk reduction (guarantees, clarity) ### 6. Hidden Conversion Mechanics - Subtle persuasion patterns - Emotional triggers not explicitly stated ### 7. Friction & Drop-Off Risks - Confusion points - Overload / missing info --- ### Output Format: **Summary (3–4 lines)** **Top Conversion Drivers** **UX Breakdown** **Hidden Mechanics** **Friction Points** **Actionable Improvements (prioritized)**
This prompt transforms a UI concept into a fully structured, implementation-ready design handoff optimized for both frontend developers and AI coding agents. It bridges the traditional gap between design and development by converting visual or conceptual input into a system-level specification that includes component architecture, layout systems, design tokens, interaction logic, and state handling.
You are a senior product designer and frontend architect. Generate a complete, implementation-ready design handoff optimized for AI coding agents and frontend developers. Be structured, precise, and system-oriented. --- ### 1. System Overview - Purpose of UI - Core user flow ### 2. Component Architecture - Full component tree - Parent-child relationships - Reusable components ### 3. Layout System - Grid (columns, spacing scale) - Responsive behavior (mobile → desktop) ### 4. Design Tokens - Color system (semantic roles) - Typography scale - Spacing system - Radius / elevation ### 5. Interaction Design - Hover / active states - Transitions (timing, easing) - Micro-interactions ### 6. State Logic - Loading - Empty - Error - Edge states ### 7. Accessibility - Contrast - Keyboard navigation - ARIA (if applicable) ### 8. Frontend Mapping - Suggested React/Tailwind structure - Component naming - Props and variants --- ### Output Format: **Overview** **Component Tree** **Design Tokens** **Interaction Rules** **State Handling** **Accessibility Notes** **Frontend Mapping** **Implementation Notes**
This prompt detects inconsistencies and design debt to stabilize and scale UI systems. ⚡ Pro Tip: Run this before scaling frontend team → prevents exponential chaos. Performs a forensic audit of UI: inconsistencies, broken patterns, visual drift, system violations.
You are a design systems engineer performing a forensic UI audit. Your objective is to detect inconsistencies, fragmentation, and hidden design debt. Be specific. Avoid generic feedback. --- ### 1. Typography System - Font scale consistency - Heading hierarchy clarity ### 2. Spacing & Layout - Margin/padding consistency - Layout rhythm vs randomness ### 3. Color System - Semantic consistency - Redundant or conflicting colors ### 4. Component Consistency - Buttons (variants, states) - Inputs (uniform patterns) - Cards, modals, navigation ### 5. Interaction Consistency - Hover / active states - Behavioral uniformity ### 6. Design Debt Signals - One-off styles - Inline overrides - Visual drift across pages --- ### Output Format: **Consistency Score (1–10)** **Critical Inconsistencies** **System Violations** **Design Debt Indicators** **Standardization Plan** **Priority Fix Roadmap**
Transforms any idea into a clean, premium, Apple-inspired UI system with real design discipline and production-ready structure. It avoids “AI-vibe coded” outputs by enforcing disciplined layout systems, intentional spacing, refined typography, and minimal but meaningful interactions. The output focuses on system-level thinking rather than surface visuals, producing structured UI architectures that are both visually premium and implementation-ready.
You are a senior product designer operating at Apple-level design standards (2026). Your task is to transform a given idea into a clean, professional, production-grade UI system. Avoid generic, AI-generated aesthetics. Prioritize clarity, restraint, hierarchy, and precision. --- ### Design Principles (Strictly Enforce) - Clarity over decoration - Generous whitespace and visual breathing room - Minimal color usage (functional, not expressive) - Strong typography hierarchy (clear scale, no randomness) - Subtle, purposeful interactions (no gimmicks) - Pixel-level alignment and consistency - Every element must have a reason to exist --- ### 1. Product Context - What is the product? - Who is the user? - What is the primary action? --- ### 2. Layout Architecture - Page structure (top → bottom) - Grid system (columns, spacing rhythm) - Section hierarchy --- ### 3. Typography System - Font style (e.g. neutral sans-serif) - Size scale (H1 → body → caption) - Weight usage --- ### 4. Color System - Base palette (neutral-first) - Accent usage (limited and intentional) - Functional color roles (success, error, etc.) --- ### 5. Component System Define core components: - Buttons (primary, secondary) - Inputs - Cards / containers - Navigation Ensure consistency and reusability. --- ### 6. Interaction Design - Hover / active states (subtle) - Transitions (fast, smooth, minimal) - Feedback patterns (loading, success, error) --- ### 7. Spacing & Rhythm - Consistent spacing scale - Alignment rules - Visual balance --- ### 8. Output Structure Provide: - UI Overview (1–2 paragraphs) - Layout Breakdown - Typography System - Color System - Component Definitions - Interaction Notes - Design Philosophy (why it works)
Users submit photos, work samples, or journal entries and receive personalized, emotionally resonant feedback that makes them feel seen and capable. The AI is tuned to validate effort, not just output — triggering the "I'm on the right path" dopamine hit on demand. Unlike generic affirmations, the specificity of the response is what creates the emotional response.
Build a web app called "Mirror" — an AI-powered personal coaching tool that gives users emotionally intelligent, personalized feedback. Core features: - Onboarding: user selects their domain (career, fitness, creative work, relationships) and sets a "validation style" (tough love / warm encouragement / analytical) - Daily check-in: a short form where users submit what they did today, how they felt, and one thing they're proud of - AI response: calls the [LLM API] (claude-sonnet-4-20250514) with a system prompt instructing Claude to respond as a perceptive coach — acknowledge effort, name specific strengths, end with one forward-looking insight. Never use generic phrases like "great job" or "well done" - Wins Archive: all past check-ins and AI responses, sortable by date, searchable - Streak tracker: consecutive daily check-ins shown as a simple counter — no gamification badges UI: clean, warm, serif typography, cream (#F5F0E8) background. Should feel like a private journal, not an app. No notifications except a gentle daily reminder at a user-set time. Stack: React frontend, localStorage for data persistence, [LLM API] for AI responses. Single-page app, no backend required.
People are terrified their profile isn't working and they can't see what others see. An AI that rewrites their bio, analyzes their photo selection, and generates personalized openers removes that uncertainty and sells the hope of a better outcome.
Build a web app called "First Impression" — a dating profile audit and optimization tool. Core features: - Photo audit: user describes their photos (up to 6) — AI scores each on energy, approachability, social proof, and uniqueness. Returns a ranked order recommendation with one-line reasoning per photo - Bio rewriter: user pastes current bio, clicks "Optimize", receives 3 rewritten versions in distinct tones (playful / authentic / direct). Each version includes a word count and a predicted "swipe right rate" label (Low / Medium / High) - Icebreaker generator: user describes a match's profile in a few sentences — AI generates 5 personalized openers ranked by predicted response rate, each with a one-line explanation of why it works - Profile score dashboard: a 0–100 composite score across bio quality, photo strength, and opener effectiveness — updates live - Export: formatted PDF of all assets titled "My Profile Package" Stack: React, [LLM API] for all AI calls, jsPDF for export. Mobile-first UI with a card-based layout — warm colors, modern dating app feel.
People want a version of themselves that looks how they feel on the inside — idealized, stylized, professional, or "cooler." Profile pictures are identity signals on every platform they use. Paying for a better signal is rational.
Build a web app called "Alter" — a personalized digital avatar creation tool. Core features: - Style selector: 8 avatar styles presented as visual cards (professional headshot, anime, pixel art, oil painting, cyberpunk, minimalist line art, illustrated character, watercolor) - Input panel: text description of desired look and vibe (mood, colors, personality) — no photo upload required in MVP - Generation: calls fal.ai FLUX API with a structured prompt built from the style selection and description — generates 4 variants per request - Customization: background color picker overlay, optional username/tagline text added via Canvas API - Download: PNG at 400px, 800px, and 1500px square - History: last 12 generated packs saved in localStorage — click any to view and re-download UI: bright, expressive, fun. Large visual cards for style selection. Results shown in a 2x2 grid. Mobile-responsive. Stack: React, fal.ai API for image generation, HTML Canvas for text overlays, localStorage for history.
Group coaches and educators repeatedly rebuild the same infrastructure — scheduling, homework submission, peer feedback, progress tracking — for every cohort they run. Selling the operating system for running a high-quality group program is a B2B belonging play where the coach's students are the end beneficiaries. Coaches stop using it if it adds friction to their existing workflow. Must replace existing tools (Notion + email + Zoom links), not add to them.
Build a group coaching and cohort management platform called "Cohort OS" — the operating system for running structured group programs. Core features: - Program builder: coach sets program name, session count, cadence (weekly/bi-weekly), max participants, price, and start date. Each session has a title, a pre-work assignment, and a post-session reflection prompt - Participant portal: each enrolled participant sees their program timeline, upcoming sessions, submitted assignments, and peer reflections in one dashboard - Assignment submission: participants submit written or link-based assignments before each session. Coach sees all submissions in one view, can leave written feedback per submission - Peer feedback rounds: after each session, participants are prompted to give one piece of structured feedback to one other participant (rotates automatically so everyone gives and receives equally) - Progress tracker: coach dashboard showing assignment completion rate per participant, attendance, and a simple engagement score - Certificate generation: at program completion, auto-generates a PDF certificate with participant name, program name, coach name, and completion date Stack: React, Supabase, Stripe Connect for coach payouts, Resend for session reminders and feedback prompts. Clean, professional design — coach-first UX.
People want to practice before risking real money. The simulation sells the hope of being competent enough to invest eventually — and the journal analysis layer sells the hope of becoming the kind of person whose judgment improves over time. If simulation doesn't reflect real market mechanics, it feels like a toy and loses credibility. Slippage, transaction costs, and realistic price impact must be simulated.
Build a paper trading simulation platform called "Paper" — a realistic, risk-free environment for learning to trade and invest. Core features: - Portfolio setup: user starts with $100,000 in virtual cash. Real-time stock and ETF prices via Yahoo Finance or Alpha Vantage API - Trade execution: market and limit orders supported. Simulate 0.1% slippage on market orders. Commission of $1 per trade (realistic friction without being punitive) - Performance dashboard: P&L chart (daily), total return, annualized return, win rate, average gain and loss, Sharpe ratio, and current sector exposure — all updated with each trade. Built with recharts - Trade journal: required field on every position close — "What was my thesis entering this trade? What happened? What will I do differently?" Three fields, each max 200 characters. Cannot close a position without completing the journal - Behavioral analysis: [LLM API] analyzes the last 20 trade journal entries and identifies recurring behavioral patterns — "You consistently exit winning positions early when they approach round-number price levels" — surfaced monthly - Leaderboard: optional, weekly-resetting leaderboard among friend groups — ranked by risk-adjusted return, not raw P&L Stack: React, Yahoo Finance or Alpha Vantage for market data, [LLM API] for behavioral analysis, recharts. Terminal-inspired design — data dense, no decorative elements.
Note-taking is commoditized. Meaning-making is not. A tool that connects notes into a personal narrative — that shows you the throughline of your thinking across months and years — sells identity and continuity, not storage. If search and sync don't work flawlessly, users abandon immediately regardless of the narrative features. Reliability is table stakes; everything else is the differentiator.
Build a personal knowledge and narrative tool called "Thread" — a second brain that connects notes into a living story. Core features: - Note capture: fast input with title, body, tags, date, and an optional "life chapter" label (user-defined periods like "Building the company" or "Year in Berlin") — chapter labels create narrative structure - Connection engine: [LLM API] periodically analyzes all notes and suggests thematic connections between entries. User sees a "Suggested connections" panel — accepts or rejects each. Accepted connections create bidirectional links - Narrative timeline: a D3.js timeline showing notes grouped by chapter. Zoom out to decade view, zoom in to week view. Click any note to read it in context of its surrounding entries - Weekly synthesis: every Sunday, AI generates a "week in review" paragraph from that week's notes — stored as a special entry in the timeline. Accumulates into a readable life chronicle - Pattern report: monthly — AI identifies recurring themes (concepts mentioned 5+ times), most-linked ideas (high connection density), and "dormant" ideas (not referenced in 60+ days, surfaced as "worth revisiting") - Chapter export: select any chapter by date range and export as a formatted PDF narrative document Stack: React, [LLM API] for connection suggestions, synthesis, and pattern reports, D3.js for timeline visualization, localStorage with JSON export/import for backup. Literary design — serif fonts, generous whitespace.
The gap between "idea" and "first paying customer" is where most solo founders fail — not from lack of effort but from lack of a structured, day-by-day system. A tool that compresses that gap from months to 14 days with templates already customized to their specific idea removes the activation barrier that kills most ventures before they start. The market evolves faster than any fixed playbook. The prompts and templates that worked in 2024 may not work in 2026.
Build a solo-founder launch system called "Zero to One" — a structured 14-day system for going from idea to first paying customer.
Core features:
- Idea intake: user inputs their idea, target customer, and intended price point. [LLM API] validates the inputs by asking 3 clarifying questions — forces specificity before any templates are generated
- Personalized playbook: 14-day calendar where each day has a specific task, a customized template, and a success metric. All templates are generated by [LLM API] using the user's specific idea and customer — not generic. Day 1: problem validation script. Day 3: landing page copy. Day 5: outreach email. Day 7: customer interview guide. Day 10: sales conversation framework. Day 14: post-mortem template
- Daily execution log: each day the user marks the task complete and answers: "What happened?" and "What's the specific blocker if incomplete?" — two fields, 150 chars each
- Decision tree: if-then guidance for the 8 most common sticking points ("No one responded to my outreach → here are 3 likely reasons and the fix for each"). Structured as interactive branching, not a wall of text
- Launch readiness score: composite of daily completions, outreach sent, and conversations held — shown as a 0–100 score that updates daily
- Post-mortem: on day 14, guided reflection template — what worked, what failed, what the next 14 days should focus on. AI generates a one-page summary
Stack: React, [LLM API] for all template generation and decision tree content, localStorage. High-energy design — daily progress always front and center.Freelancers and small operators know they should have better contracts and clearer agreements but find legal complexity paralysing. A tool that generates a good-enough contract in under 5 minutes removes that paralysis and sells a tangible reduction in a very specific anxiety.
Build a legal risk reduction tool for freelancers called "Shield" — a contract generator and reviewer that reduces common legal exposure. IMPORTANT: every page of this app must display a clear disclaimer: "This tool provides templates and general information only. It is not legal advice. Review all documents with a qualified attorney before use." Core features: - Contract generator: user inputs project type (web development / copywriting / design / consulting / photography / other), client type (individual / small business / enterprise), payment terms (fixed / milestone / retainer), approximate project value, and 3 custom deliverables in plain language. [LLM API] generates a complete contract covering scope, IP ownership, payment schedule, revision policy, late payment penalties, confidentiality, and termination — formatted as a clean DOCX - Contract reviewer: user pastes an incoming contract. AI highlights the 5 most important clauses (ranked by risk), flags anything unusual or asymmetric, and for each flagged clause suggests a specific alternative wording - Risk radar: user describes their freelance business in 3 sentences — AI identifies their top 5 legal exposure areas with a one-paragraph explanation of each risk and a mitigation step - Template library: 10 pre-built contract types, all downloadable as DOCX and editable in any word processor - NDA generator: inputs both party names, confidentiality scope, and duration — generates a mutual NDA in under 30 seconds Stack: React, [LLM API] for generation and review, docx-js for DOCX export. Professional, trustworthy design — this handles serious matters.
Major life and business decisions — changing careers, raising a round, ending a relationship, relocating — paralyze people not because they lack information but because the stakes are high enough that being wrong feels catastrophic. Structured analysis that forces clarity on trade-offs makes the decision-making process feel competent even when the outcome is uncertain.
Build a high-stakes decision support system called "Pivot" — a structured thinking tool for major life and business decisions. This is distinct from a simple pros/cons list. The value is in the structured analytical process, not the output document. Core features: - Decision intake: user describes the decision (what they're choosing between), their constraints (time, money, relationships, obligations), their stated values (top 3), their current leaning, and their deadline - Mandatory clarifying questions: [LLM API] generates 5 questions designed to surface hidden assumptions and unstated trade-offs in the user's specific decision. User must answer all 5 before proceeding. The quality of these questions is the quality of the product - Six analytical frames (each run as a separate API call, shown in tabs): (1) Expected value — probability-weighted outcomes under each option (2) Regret minimization — which option you're least likely to regret at age 80 (3) Values coherence — which option is most consistent with stated values, with specific evidence (4) Reversibility index — how easily each option can be undone if it's wrong (5) Second-order effects — what follows from each option in 6 months and 3 years (6) Advice to a friend — if a trusted friend described this exact situation, what would you tell them? - Devil's advocate brief: a separate analysis arguing as strongly as possible against the user's current leaning — shown after the 6 frames - Decision record: stored with all analysis and the final decision made. User updates with actual outcome at 90 days and 1 year Stack: React, [LLM API] with one carefully crafted prompt per analytical frame, localStorage. Focused, serious design — no gamification, no encouragement. This handles real decisions.
This prompt generates a comprehensive, consulting-grade business blueprint by structuring a raw idea into a validated, decision-ready plan. It applies top-tier consulting logic by breaking down the business into market context, value proposition, revenue model, operating structure, and risk factors. Rather than producing generic startup advice, it emphasizes clarity of assumptions, strategic positioning, and scalability potential.
You are a senior strategy consultant (McKinsey-style, hypothesis-driven). Your task is to convert a raw business idea into a decision-ready business blueprint. Work top-down. Be structured, concise, and analytical. Avoid generic advice. --- ### 0. Initial Hypothesis State 1–2 core hypotheses explaining why this business will succeed. --- ### 1. Problem & Customer - Define the core problem (specific, not abstract) - Identify primary customer segment (who feels it most) - Current alternatives and their gaps --- ### 2. Value Proposition - Core value delivered (quantified if possible) - Why this solution is superior (cost, speed, experience, outcome) --- ### 3. Market Sizing (structured logic) - TAM, SAM, SOM (state assumptions clearly) - Growth drivers and constraints --- ### 4. Business Model - Revenue streams (primary vs secondary) - Pricing logic (value-based, cost-plus, etc.) - Cost structure (fixed vs variable drivers) --- ### 5. Competitive Positioning - Key competitors (direct + indirect) - Differentiation axis (price, UX, tech, distribution, brand) - Defensibility potential (moat) --- ### 6. Go-To-Market - Target entry segment - Acquisition channels (ranked by expected efficiency) - Distribution logic --- ### 7. Operating Model - Key activities - Critical resources (people, tech, partners) --- ### 8. Risks & Assumptions - Top 5 assumptions (explicit) - Key failure points --- ### Output Format: **Executive Summary (5 lines max)** **Core Hypotheses** **Structured Analysis (sections above)** **Critical Assumptions** **Top 3 Strategic Decisions Required**
Designs a quantified, risk-aware market entry strategy with clear entry logic and sequencing.
You are a senior market entry consultant (Big 4 + strategy firm mindset). Your task is to design a market entry strategy that is realistic, structured, and decision-oriented. --- ### 0. Entry Hypothesis - Why this market? Why now? --- ### 1. Market Attractiveness - Demand drivers - Market growth rate - Profitability potential --- ### 2. Customer Segmentation - Segment breakdown - Segment attractiveness (size, willingness to pay, accessibility) - Priority segment (justify selection) --- ### 3. Competitive Landscape - Key incumbents - Market saturation vs fragmentation - White space opportunities --- ### 4. Entry Strategy Options Evaluate: - Direct entry - Partnerships - Distribution channels Compare pros/cons. --- ### 5. Go-To-Market Plan - Channel strategy (rank by ROI potential) - Pricing entry strategy (penetration vs premium) - Initial traction strategy --- ### 6. Barriers & Constraints - Regulatory - Operational - Capital requirements --- ### 7. Risk Analysis - Market risks - Execution risks --- ### Output: **Market Entry Recommendation (clear choice)** **Target Segment Justification** **Entry Strategy (why this path)** **Execution Plan (first 90 days)** **Top Risks & Mitigation**
Diagnoses whether a business model is financially viable, scalable, and defensible.
You are a strategy consultant focused on financial logic and unit economics. Your task is to evaluate how the business makes money and whether it scales. --- ### 0. Economic Hypothesis - Why should this business be profitable at scale? --- ### 1. Revenue Streams - Primary revenue drivers - Secondary/optional streams --- ### 2. Pricing Logic - Pricing model (subscription, usage, one-time) - Alignment with customer value --- ### 3. Cost Structure - Fixed costs - Variable costs - Key cost drivers --- ### 4. Unit Economics Estimate: - Revenue per customer/unit - Cost per customer/unit - Contribution margin --- ### 5. Scalability Analysis - Economies of scale potential - Bottlenecks (ops, supply, CAC) --- ### 6. Sensitivity Analysis - What variables impact profitability most? --- ### Output: **Unit Economics Summary** **Profitability Assessment (viable / weak / risky)** **Key Drivers of Margin** **Break-even Insight (logic)** **Top 3 Optimization Levers**
Creates a precise, execution-ready GTM plan with measurable steps and KPIs.
You are a go-to-market strategist focused on execution, not theory. Your task is to convert strategy into a concrete GTM plan. --- ### 0. GTM Hypothesis - Why will customers adopt this product? --- ### 1. Target Customer - Ideal customer profile - Pain intensity and urgency --- ### 2. Positioning - Core message (1 sentence) - Key differentiator --- ### 3. Channel Strategy - Acquisition channels (ranked by expected ROI) - Channel rationale --- ### 4. Funnel Design - Awareness → consideration → conversion → retention - Key conversion points --- ### 5. Execution Plan - First 30 / 60 / 90 day actions - Resource allocation --- ### 6. Metrics & KPIs - CAC, conversion rates, retention - Success thresholds --- ### Output: **Targeting & Positioning** **Channel Strategy (ranked)** **Execution Roadmap (30/60/90 days)** **KPIs & Targets** **Top 3 Execution Risks**
Stress-tests a business under multiple scenarios and defines actionable mitigation strategies.
You are a risk and strategy consultant. Your task is to stress-test a business model across multiple scenarios and identify critical risks. --- ### 0. Core Assumptions List the most important assumptions the business depends on. --- ### 1. Best Case Scenario - Growth drivers - Upside potential --- ### 2. Base Case Scenario - Most likely outcome --- ### 3. Worst Case Scenario - Failure triggers - Downside impact --- ### 4. Risk Categories - Market - Financial - Operational - Strategic --- ### 5. Sensitivity Analysis - Which variables most impact outcomes? --- ### 6. Mitigation Strategies - Preventive actions - Contingency plans --- ### Output: **Scenario Summary Table** **Critical Risks (ranked)** **Impact vs Likelihood Matrix (described)** **Mitigation Plan** **Key Decision Points**