Use this prompt with Claude, ChatGPT, or any AI assistant to generate a working prototype of Pallymarket.

The Prompt

`Build me a React prototype for "Pallymarket" - a private prediction market platform for friend groups.

Core concept: Friends can create custom betting markets on anything, stake money or bragging rights, and settle bets fairly.

Key screens to include:

1. Home/Dashboard

   • List of active markets the user is participating in
   • Quick stats (win rate, total staked, leaderboard position)
   • "Create Market" CTA button

2. Create Market Flow

   • Question input ("Will [X] happen by [date]?")
   • Resolution criteria (how will we know who won?)
   • Stakes options: bragging rights only, or real money ($1-$100 range)
   • Invite friends (email or link)
   • Resolution method: auto-resolve (verifiable events) or group vote

3. Market Detail View

   • The question and resolution criteria
   • Current predictions (who bet what)
   • Countdown to resolution date
   • Chat/comments section
   • "Make Your Prediction" button

4. Leaderboard

   • Friend group rankings by prediction accuracy
   • Filters: all-time, this month, by category
   • Bragging badges (longest streak, biggest upset win, etc.)

Design notes:

• Modern, clean UI with a playful vibe
• Dark mode by default
• Use emojis liberally
• Mobile-first responsive design
• Color palette: deep purple primary, electric green for wins, warm red for losses

Technical requirements:

• React with Tailwind CSS
• Use useState for local state management
• Include sample data to demonstrate functionality
• Make it feel like a real app with smooth transitions

Focus on making it feel fun and social - this is about friendly competition, not serious gambling.`

What You'll Get

A functional React prototype with:

• Interactive market creation
• Sample markets with mock data
• Leaderboard with friend rankings
• Mobile-responsive design

Perfect for validating the concept, showing to potential users, or building out into a full product.

Tips for Best Results

1. Be specific about your use case - Add examples like "betting on who will get promoted first" or "whether the startup will hit their Q2 target"
2. Request iterations - Ask the AI to refine specific screens or add features
3. Export and extend - Copy the code to a local environment and build from there