Comprehensive Technical Documentation for Full Stack Engineering, AI Development, and Agent Architectures
A complete knowledge base covering CS fundamentals, AI/LLM technologies, engineering best practices, and real-world project case studies.
- Node.js 18.x or higher
- npm or yarn or pnpm
# Clone the repository
git clone https://github.com/YiWang24/AiDIY.git
cd AiDIY
# Install dependencies
npm install# Start the development server
npm start
# Build the site
npm run build
# Serve the built site
npm run serveThe documentation site will be available at http://localhost:3001
Foundational computer science knowledge essential for software engineering:
-
Algorithms & Data Structures
- Time and space complexity analysis
- Common algorithms (sorting, searching, graph algorithms)
- Data structures (arrays, trees, graphs, hash tables)
-
System Design
- Scalability patterns
- Load balancing
- Caching strategies
- Database design principles
-
Database Internals
- Storage engines (B-tree, LSM, etc.)
- Transaction management (ACID)
- Query optimization
- Distributed databases
-
Network & Operating Systems
- TCP/IP networking
- HTTP/HTTPS protocols
- Process management
- Memory management
Modern AI development with focus on practical applications:
-
RAG (Retrieval-Augmented Generation)
- Data processing and chunking strategies
- Vector indexing and storage
- Retrieval strategies and optimization
- Generation and post-processing
- Evaluation metrics
-
Agent Architectures
- Multi-agent systems
- Tool use and function calling
- Context engineering
- State management
- Production deployment
-
LLM Fundamentals
- Transformer architecture
- Fine-tuning strategies
- Prompt engineering techniques
- Token optimization
- Cost management
Practical software engineering knowledge:
-
Backend Development
- API design (REST, GraphQL, gRPC)
- Database integration
- Authentication & authorization
- Performance optimization
-
Frontend Development
- React best practices
- State management
- Component architecture
- Performance tuning
-
DevOps & Cloud
- Docker containers
- CI/CD pipelines
- Cloud deployment (AWS, GCP, Azure)
- Infrastructure as Code
Real-world project examples and refactoring:
- Complete project architectures
- Performance optimization stories
- Debugging complex issues
- Migration strategies
- Documentation Framework: Docusaurus
- Language: MDX (Markdown + JSX)
- Diagrams: Mermaid
- Code Highlighting: Prism.js
- Deployment: Vercel
Contributions are welcome! Please feel free to:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
Yi Wang
- Website: www.yiw.me
- GitHub: @YiWang24
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Note: This documentation serves as a personal knowledge base and reference guide for full stack engineering and AI development. Feel free to explore, learn, and adapt the content to your needs!