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Add version 1.0 documentation snapshot
🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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‎website/versioned_docs/version-1.0/advanced-topics/index.md‎

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sidebar_position: 6
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sidebar_label: 'Advanced Topics'
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---
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# Advanced Topics
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Explore specialized use cases, security considerations, performance optimization, and cutting-edge techniques for AI-assisted development.
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## Module Overview
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This advanced module covers specialized topics, edge cases, and emerging techniques that push the boundaries of AI-assisted development.
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## What You'll Learn
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### Security & Best Practices
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- Security review with AI
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- Identifying vulnerabilities in AI-generated code
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- Secure coding patterns
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- Privacy and data handling
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- License compliance and attribution
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### Performance Optimization
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- Performance profiling with AI
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- Optimization suggestions and validation
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- Algorithm selection and complexity
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- Benchmarking and measurement
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### Specialized Domains
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- Machine learning and data science code
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- Systems programming
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- Mobile development
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- DevOps and infrastructure as code
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- Embedded systems
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### Emerging Techniques
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- Multi-agent collaboration
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- Custom model fine-tuning
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- Retrieval-augmented generation (RAG)
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- Automated testing and QA
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- Code migration and modernization
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### Production Considerations
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- Monitoring AI-generated code in production
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- Debugging and troubleshooting
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- Long-term maintenance
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- Technical debt management
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- Team training and adoption
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## Lessons in This Module
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1. **Security-First Development** - Using AI safely and securely
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2. **Performance Engineering** - Optimization with AI assistance
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3. **Specialized Use Cases** - Domain-specific applications
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4. **Custom Tooling** - Building AI-powered development tools
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5. **Production Readiness** - From prototype to production
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6. **Future of AI Coding** - Emerging trends and techniques
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## Prerequisites
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- Completion of [Architecture & Design](architecture-design) module
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- Production development experience
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- Strong understanding of software engineering principles
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## Time Commitment
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This module takes approximately **6-8 hours** to complete, including advanced exercises and case studies.
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---
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Ready for advanced techniques? Start with **Lesson 1: Security-First Development**.

‎website/versioned_docs/version-1.0/architecture-design/index.md‎

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sidebar_label: 'Architecture & Design'
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---
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# Architecture & Design with AI
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Leverage AI for system design, architectural decisions, and high-level problem-solving. Learn when and how to use AI for design work versus implementation.
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## Module Overview
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AI assistants excel at certain architectural tasks while struggling with others. This module teaches you to use AI effectively for system design, architectural patterns, and technical decision-making.
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## What You'll Learn
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### AI-Assisted Design
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- Using AI for system architecture brainstorming
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- Design pattern selection and application
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- Database schema design
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- API design and specification
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- Microservices vs. monolith decisions
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### Effective Collaboration
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- When to involve AI in design decisions
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- Validating AI architectural suggestions
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- Using AI to explore trade-offs
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- Documenting design decisions with AI
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### Practical Applications
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- Designing scalable systems
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- Security architecture
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- Performance optimization strategies
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- Cloud architecture patterns
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- Legacy system modernization
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### Design Documentation
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- Architecture diagrams with AI
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- Technical specification writing
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- API documentation
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- System design documents
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## Lessons in This Module
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1. **AI's Role in Architecture** - Understanding capabilities and limitations
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2. **System Design Patterns** - Leveraging AI for pattern selection
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3. **Database Design** - Schema design and optimization
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4. **API Design** - RESTful, GraphQL, and gRPC with AI
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5. **Scalability & Performance** - Designing for scale with AI guidance
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6. **Security Architecture** - Security-first design with AI
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7. **Documentation** - Creating and maintaining design docs
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## Prerequisites
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- Completion of [Tools & Workflows](tools-and-workflows) module
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- Experience with system design
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- Understanding of common architectural patterns
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## Time Commitment
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This module takes approximately **6-7 hours** to complete, including case studies and design exercises.
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---
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Ready to design with AI? Start with **Lesson 1: AI's Role in Architecture**.

‎website/versioned_docs/version-1.0/fundamentals/index.md‎

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sidebar_label: 'Fundamentals'
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---
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# AI Coding Fundamentals
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Welcome to the first module of the AI Coding Course. In this module, you'll build a solid foundation for understanding and working with AI coding assistants.
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## Module Overview
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This module covers the essential concepts you need to understand before diving into AI-assisted development:
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- How AI coding assistants work under the hood
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- Understanding capabilities and limitations
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- Mental models for effective AI collaboration
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- When to use (and not use) AI assistance
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- Common pitfalls and how to avoid them
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## What You'll Learn
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### Understanding AI Models
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- Large Language Models (LLMs) and code generation
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- Token limits and context windows
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- Temperature and sampling in code generation
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- Determinism vs. creativity in outputs
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### Effective AI Collaboration
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- The developer-AI partnership model
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- Critical thinking and code verification
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- Understanding AI suggestions
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- Building trust through validation
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### Practical Foundations
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- Setting up your AI development environment
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- First interactions with AI coding tools
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- Reading and evaluating AI-generated code
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- Iterative refinement techniques
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## Lessons in This Module
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1. **Introduction to AI Coding Assistants** - Understanding what AI can and cannot do
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2. **How LLMs Generate Code** - Technical foundations you need to know
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3. **Mental Models for AI Collaboration** - Thinking effectively with AI
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4. **Setting Up Your Environment** - Tools and configuration
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5. **Your First AI-Assisted Project** - Hands-on practice
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## Prerequisites
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Before starting this module, ensure you:
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- Have read the [course introduction](/)
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- Have access to at least one AI coding tool
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- Have a development environment set up
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## Time Commitment
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This module takes approximately **3-4 hours** to complete, including hands-on exercises.
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Ready to begin? Start with **Lesson 1: Introduction to AI Coding Assistants**.

‎website/versioned_docs/version-1.0/intro.md‎

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# Welcome to the AI Coding Course
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Master the art of AI-assisted software engineering. This course is designed for **experienced developers** who want to leverage AI tools effectively in their development workflow.
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## Who This Course Is For
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This course assumes you already have:
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- Strong programming fundamentals
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- Experience with modern development workflows
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- Understanding of software architecture and design patterns
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- Professional development experience
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## What You'll Learn
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### Core Skills
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- Effective prompting techniques for code generation
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- Integrating AI tools into your development workflow
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- Architectural design with AI assistance
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- Code review and refactoring with AI
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- Testing and debugging strategies
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- Security and best practices
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### Course Structure
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The course is organized into **five core modules**:
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1. **[Fundamentals](/docs/fundamentals/)** - Understanding AI coding assistants, their capabilities and limitations
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2. **[Prompting Techniques](/docs/prompting-techniques/)** - Mastering the art of effective communication with AI
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3. **[Tools & Workflows](/docs/tools-and-workflows/)** - Integrating AI into your development environment
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4. **[Architecture & Design](/docs/architecture-design/)** - Using AI for system design and architecture
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5. **[Advanced Topics](/docs/advanced-topics/)** - Security, performance optimization, and specialized use cases
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## How to Use This Course
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- **Sequential Learning**: Start with Fundamentals and progress through each module
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- **Hands-on Practice**: Each lesson includes practical exercises and code examples
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- **Real-world Examples**: Learn from production-ready patterns and use cases
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- **Version Control**: Course content is versioned - you can always reference earlier versions
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## Prerequisites
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Before starting, ensure you have:
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- Node.js 20+ installed
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- A code editor (VS Code recommended)
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- Git for version control
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- Access to AI coding tools (GitHub Copilot, Claude, ChatGPT, or similar)
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Ready to get started? Head to the **[Fundamentals](/docs/fundamentals/)** module.

‎website/versioned_docs/version-1.0/prompting-techniques/index.md‎

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sidebar_label: 'Prompting Techniques'
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# Advanced Prompting Techniques
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Learn to communicate effectively with AI coding assistants to get the results you need. This module focuses on the art and science of prompting for code generation.
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## Module Overview
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Effective prompting is the key skill that separates mediocre from exceptional AI-assisted development. This module teaches you systematic approaches to crafting prompts that generate high-quality, production-ready code.
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## What You'll Learn
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### Prompt Engineering Fundamentals
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- Anatomy of an effective prompt
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- Context, constraints, and specifications
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- Examples and few-shot learning
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- Iterative prompt refinement
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### Advanced Techniques
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- Chain-of-thought prompting for complex logic
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- Decomposing large tasks into smaller prompts
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- Providing codebase context effectively
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- Handling edge cases and error scenarios
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### Domain-Specific Prompting
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- API and integration development
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- Database design and queries
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- Frontend component creation
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- Backend service implementation
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- Testing and test generation
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### Optimization Strategies
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- Minimizing tokens while maintaining clarity
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- Reusing prompt templates
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- Building a personal prompt library
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- Learning from prompt failures
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## Lessons in This Module
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1. **Prompt Engineering Basics** - Structure and components of effective prompts
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2. **Context is King** - Providing the right information at the right time
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3. **Iterative Refinement** - From rough idea to precise specification
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4. **Advanced Patterns** - Chain-of-thought, few-shot, and role-based prompting
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5. **Domain-Specific Techniques** - Tailored approaches for different tasks
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6. **Building Your Prompt Library** - Reusable templates and patterns
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## Prerequisites
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- Completion of the [Fundamentals](fundamentals) module
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- Basic understanding of your chosen AI coding tool
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- Familiarity with software requirements specification
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## Time Commitment
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This module takes approximately **4-5 hours** to complete, including extensive practice exercises.
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Ready to master prompting? Start with **Lesson 1: Prompt Engineering Basics**.

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