A comprehensive guide to working effectively with Claude Code (claude.ai/code) for software development projects, based on real-world experience building production applications.
- Introduction - What is Claude Code and why use it
- Quick Start - Get up and running in 5 minutes
- Setup Guide - Comprehensive setup for your project
- The CLAUDE.md File - Your project's instruction manual for Claude
- Prompt Engineering - Writing effective prompts
- Testing Strategy - E2E-first testing philosophy
- AI-First Workflow - The 10-step systematic development process
- Feature Development Workflow - End-to-end feature development
- Project Planning & Documentation Structure - Organizing project documentation for AI-first development
- Scaling to Large Projects - Multi-phase planning, progress tracking, and project management for complex systems
- Git Workflow - Branch naming, commits, and PR management
- Troubleshooting - Common issues and solutions
- Tips & Tricks - Power user techniques
- Resources - Links and further reading
- CLAUDE.md Template - Production-ready project configuration
- Interactive Tutorial Slides - 40+ slide hands-on workshop
- Workshop Prompts - Copy-paste prompts for exercises (with page references)
- Start with Introduction
- Follow the Quick Start
- Read The CLAUDE.md File
- Review the CLAUDE.md Template
- Review Best Practices
- Study AI-First Workflow
- Explore Testing Strategy
- Learn Tips & Tricks
1. The CLAUDE.md is Essential
- Acts as Claude's "instruction manual" for your project
- Contains architecture, workflow, and conventions
- Updated throughout the project lifecycle
- See the template for a complete example
2. Comprehensive Testing with Coverage
- E2E tests are mandatory (test user journeys end-to-end)
- Unit tests are mandatory (test business logic, utilities, edge cases)
- Component tests are good to have (test containers for microservices)
- Track coverage from all test types (higher coverage = better confidence)
- Test-first approach: Build testing infrastructure before implementation
3. AI Executes 100%, Humans Validate 100%
- AI handles all coding, testing, and documentation
- Humans handle all validation, review, and decision-making
- Clear handoff points between AI and human
- Systematic quality gates at each step
4. Git Workflow Matters
- Use conventional commits
- Never commit directly to main
- Let humans merge PRs, not AI
- Pre-commit checks are mandatory (lint, test, build)
5. Context is King
- Be explicit about your current state
- Provide relevant file paths and code snippets
- Use clear, specific language
- Reference existing patterns in your codebase
6. Iterate and Refine
- Start with working code, then improve
- Run tests frequently
- Commit small, atomic changes
- Progressive refinement over big-bang implementations
- Claude Code - AI pair programmer (claude.ai/code)
- Git - Version control
- GitHub - Code hosting and PR management
- Cypress - E2E testing framework
- Docker - Containerization
- Various languages - Examples for Go, Python, JavaScript/TypeScript, React
Found something unclear or want to add your own learnings?
- Fork this repository
- Create a feature branch (
git checkout -b feature/your-improvement) - Make your changes
- Submit a pull request
This tutorial is MIT licensed. Share freely!
Special thanks to the Claude Code team at Anthropic for creating such a powerful development tool, and to the community of developers sharing their AI-first development experiences.
Questions or feedback? Open an issue or start a discussion!
Last Updated: 2025-11-15