AI Coding Tools Landscape
GitHub Copilot: inline suggestions, chat, multi-file editing. Cursor: full AI-native IDE, terminal, codebase understanding. ChatGPT/Claude: debugging, explanation, architecture. Each tool shines in different scenarios.
Effective AI Pair Programming
Best practices: write descriptive comments before code, use meaningful variable names, provide context about the project, review every AI suggestion, test all generated code.
AI for Debugging and Refactoring
Paste error messages and ask AI to explain and fix. Ask for refactoring suggestions with explanations. Use AI to understand unfamiliar codebases. Prompt: 'Explain this function, identify issues, and suggest improvements.'
AI for Testing and Documentation
Auto-generate unit tests, integration tests, and test cases. Write documentation, README files, API docs, and inline comments. Generate code reviews and security audits.
Building Projects with AI
Full project workflow: describe the project → AI generates architecture → build feature by feature → AI helps debug → add tests → deploy. Real examples of apps built in a weekend.
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