Cursor Masterclass: The AI Code Editor Deep-Dive
A comprehensive deep-dive into Cursor, the AI-powered code editor. Learn advanced features, hidden tips, and workflows that 10x your development speed.
What You'll Learn
- Master Cursor's AI features for faster coding
- Use Projects mode for full codebase context
- Write effective prompts for code generation
- Debug and refactor with AI assistance
- Build your own custom rules and workflows
Cursor has changed how developers write code. But most users barely scratch the surface. This guide covers everything from basics to advanced techniques that will transform your coding workflow.
Why Cursor Over VS Code
Cursor is built on VS Code, so everything you know transfers. But it adds deep AI integration: Cmd+K for inline edits, Cmd+L for chat with context, and automatic codebase understanding. The AI isn't an add-on—it's woven into every interaction.
Essential Keyboard Shortcuts
Cmd+K: Inline edit or generate code at cursor. Cmd+L: Open chat with current file context. Cmd+Shift+L: Add selection to chat. Tab: Accept AI suggestion. These four shortcuts handle 90% of AI interactions.
Using Projects Mode
Projects mode indexes your entire codebase, letting AI understand context across files. Use @ mentions to reference specific files or folders. The AI can then make changes that are consistent with your existing code style and patterns.
Writing Better Code Prompts
Be specific about what you want. Reference existing patterns: 'Create a new API route following the pattern in @routes/users.ts'. Specify constraints: 'Use TypeScript, add error handling, include JSDoc comments'. The more context, the better the output.
Debugging with AI
Paste error messages directly into chat. Select the problematic code and ask 'Why is this failing?'. The AI can trace through logic, identify edge cases, and suggest fixes. It's like having a senior developer pair programming with you.
Custom Rules
Create .cursorrules files to define project-specific instructions. Tell the AI your coding standards, preferred libraries, and architectural patterns. These rules apply to every AI interaction, ensuring consistent output across your project.