An intelligent tech stack recommendation system that uses information theory to find your perfect development stack in 3-4 questions

Unlike traditional decision trees that ask generic questions, WTSSIU uses Akinator-style binary search to intelligently narrow down tech stacks:

• 🧠 Smart Question Selection: Uses information theory to ask the most discriminating questions first
• ⚡ 3-4 Questions Max: Gets to your perfect stack faster than any other tool
• 🎯 50/50 Split Strategy: Each question eliminates ~50% of remaining options
• 📊 Real-time Progress: See exactly how many stacks remain after each answer
• 🔄 Dynamic Algorithm: Questions adapt based on your previous answers

// 1. Calculate information gain for each possible question function calculateInformationGain(question, remainingStacks) { // Group stacks by their likely answers const groups = groupStacksByAnswer(question, remainingStacks); // Calculate entropy to find questions that split 50/50 return entropy_before - entropy_after; } // 2. Always ask the question with highest information gain const bestQuestion = questions.reduce((best, current) => calculateInformationGain(current, stacks) > calculateInformationGain(best, stacks) ? current : best ); // 3. Filter remaining stacks based on answer remainingStacks = filterStacksByAnswer(stacks, question, answer);

Instead of asking "Frontend, Backend, or Full-stack?" first, WTSSIU might ask:

1. "Is this primarily a frontend/UI project?" → Eliminates 50% immediately
2. "Do you prefer the JavaScript ecosystem?" → Down to 25% of stacks
3. "Working solo or with a small team?" → Down to 12% of stacks
4. "Do you need database integration?" → Final recommendation!

Result: Your perfect tech stack in 4 questions instead of 8+ 🎯

• Framework: Next.js 15.3.3 with App Router
• Language: TypeScript 5.0
• Styling: Tailwind CSS + Radix UI components
• State: React Hook Form + Zod validation
• Animation: Framer Motion
• Charts: Recharts for analytics
• Icons: Lucide React

# Clone the repository git clone https://github.com/GustyCube/what-tech-stack-should-i-use.git cd what-tech-stack-should-i-use # Install dependencies npm install # Start development server npm run dev

Visit http://localhost:9002 to start finding your perfect tech stack!

• SmartTreeWalker: Information-theoretic question selection
• BinaryTreeDecider: Main UI component with progress tracking
• Question Database: Smart questions designed to maximize information gain
• Stack Filtering: Real-time filtering based on user answers

src/ ├── components/ │ └── binary-tree-decider.tsx # Main decision UI ├── lib/ │ ├── smart-tree-walker.ts # NEW: Smart algorithm │ ├── tree-walker.ts # Legacy tree traversal │ ├── tree.json # Decision tree data │ └── tree-types.ts # TypeScript definitions 

• Frontend: React, Vue, Angular, Svelte, Next.js, Nuxt, Vite
• Backend: Node.js, Python (Django/Flask), PHP (Laravel), Ruby (Rails)
• Full-stack: T3 Stack, MEAN, MERN, Django + React, Rails + React
• Mobile: React Native, Flutter, Ionic
• Database: PostgreSQL, MongoDB, MySQL, Supabase, Firebase
• Deployment: Vercel, Netlify, AWS, GCP, Docker

# Type checking npm run typecheck # Linting npm run lint # Build for production npm run build # Start production server npm start

We love contributions! Here's how you can help:

1. Add New Tech Stacks: Update tree.json with new recommendations
2. Improve Questions: Add smarter discriminating questions to smart-tree-walker.ts
3. Better Scoring: Enhance the scoringFn for existing questions
4. UI/UX: Improve the user experience and visual design

// Add to smart-tree-walker.ts { id: 'new_question', text: 'Your discriminating question?', type: 'boolean', options: ['Yes', 'No'], scoringFn: (stack) => { // Return 1 if stack matches this criteria, 0 if not return stack.tags.includes('your-criteria') ? 1 : 0; } }

WTSSIU tracks (anonymously):

• Question effectiveness and information gain
• User completion rates and drop-off points
• Most popular tech stack recommendations
• Algorithm performance metrics

Traditional decision trees follow predetermined paths. WTSSIU uses Claude Shannon's information theory to:

• Maximize Information Gain: Each question eliminates the maximum number of possibilities
• Minimize Decision Time: Reach conclusions in log₂(n) questions where n = number of stacks
• Adapt Dynamically: Questions change based on remaining possibilities
• Optimize User Experience: Reduce cognitive load and decision fatigue

MIT License - feel free to use this for your own projects!

• Inspired by Akinator and its brilliant question selection algorithm
• Built with amazing tools from the React/Next.js ecosystem
• Thanks to all the developers who maintain the tech stacks we recommend!

Made with ❤️ by developers, for developers

Find your perfect tech stack in under 2 minutes 🚀