AI-first code editor built on VS Code — chat with your entire codebase, generate code from instructions, refactor across multiple files.
Cursor takes the VS Code experience and adds deep AI integration. The killer feature: it understands your entire codebase. Ask "how does authentication work in this project?" and it reads the relevant files and gives you a coherent answer.
Multi-file editing lets you describe a change ("add error handling to all API routes") and Cursor edits multiple files simultaneously.
Professional developers who want AI that understands their project, not just the current file. If you use VS Code, switching to Cursor is seamless.
Codebase-Aware Chat. This is Cursor's standout feature. Unlike GitHub Copilot, which mostly works on the current file, Cursor indexes your entire project and lets you ask questions about it. "How is authentication handled?" "Where is the payment logic?" "What would break if I changed this schema?" — Cursor reads the relevant files and gives context-aware answers. For large codebases, this alone justifies the subscription.
Multi-File Editing. Describe a change in plain English — "add input validation to all API endpoints" or "convert these class components to hooks" — and Cursor proposes edits across multiple files simultaneously. You review each change in a diff view before accepting. This turns what used to be a tedious multi-hour refactoring session into a 10-minute review process.
Inline Completions (Tab-Tab-Tab). As you type, Cursor predicts what you're about to write and offers inline suggestions. These aren't generic snippets — they're context-aware completions that consider your project's patterns, variable names, and coding style. The completions are fast enough that they feel like a natural extension of your typing rather than an interruption.
Cmd+K Inline Editing. Highlight any block of code, press Cmd+K (or Ctrl+K on Windows), and describe what you want changed. "Add error handling" or "optimize this for performance" or "add TypeScript types." Cursor rewrites the selected code in place. It's the fastest way to make targeted improvements without switching to chat.
Terminal Integration. Cursor's AI also works in the integrated terminal. Get help with shell commands, debug error messages, and generate complex CLI one-liners. Ask "how do I find all files larger than 100MB in this directory" and get the exact command without Googling.
Custom AI Rules (.cursorrules). Create a .cursorrules file in your project root to set persistent instructions for the AI. Specify your coding conventions, preferred libraries, architecture patterns, and documentation standards. Every AI interaction then follows your project's rules automatically — no need to repeat yourself.
Onboarding to a New Codebase. Starting at a new job or picking up an unfamiliar open-source project? Instead of spending days reading through files, ask Cursor's chat: "Give me an overview of the project architecture," "How does the data flow from the API to the frontend," or "What design patterns are used here?" It reads the codebase and gives you a guided tour. Developers consistently report cutting onboarding time in half.
Rapid Prototyping. When you need to go from idea to working code fast — hackathons, proof of concepts, MVPs — Cursor lets you describe features in plain English and generates the boilerplate. You focus on the architecture and business logic while Cursor handles the repetitive setup code. Entrepreneurs building MVPs especially benefit from this speed.
Legacy Code Refactoring. Got a codebase with outdated patterns, no types, or inconsistent styles? Cursor's multi-file editing can systematically modernize your code. "Convert all callbacks to async/await," "Add TypeScript types to this module," or "Replace jQuery with vanilla JS" — and review the changes in bulk.
Writing Tests. Tell Cursor "write unit tests for this function" or "generate integration tests for this API endpoint" and it produces test files that understand your existing test framework and patterns. It's not perfect — you'll need to review and adjust — but it removes the blank-page problem and gets you 70-80% of the way there.
Debugging Complex Issues. Paste an error stack trace into chat and ask "what's causing this?" Cursor reads the relevant source files, traces the issue, and suggests specific fixes. It's particularly good at catching issues that span multiple files, where the bug's symptom is far from its cause.
Set up a .cursorrules file immediately. Before writing a single line of code, create a .cursorrules file defining your coding conventions, preferred libraries, and patterns. This dramatically improves the quality of AI suggestions because Cursor stops guessing your style and starts matching it. Include things like "use functional components with hooks," "always handle errors with custom Error classes," or "use Tailwind for styling."
Use @ mentions to point the AI at specific files. In Cursor's chat, type @filename to explicitly include files in the conversation context. Don't rely on the AI to guess which files are relevant — tell it. "Looking at @auth.ts and @middleware.ts, how should I add role-based access control?" gives much better results than a vague question.
Review multi-file edits carefully before accepting. Cursor's multi-file editing is powerful but not infallible. Always review the diff view file by file. Accept changes individually rather than all at once. The AI occasionally makes assumptions about your architecture that don't hold — catching these before they merge is much easier than debugging them later.
Combine Cmd+K with chat for complex changes. Use Cmd+K for quick, surgical edits on a single block of code, and switch to chat when you need to reason about a change that affects multiple files or requires understanding broader context. Knowing when to use each mode makes you significantly more productive.
Don't fight the AI — guide it. If a suggestion is 80% right, accept it and then iterate with another Cmd+K edit rather than rejecting and re-prompting from scratch. It's faster to refine than to regenerate, and each refinement gives the AI more context about what you actually want.
Developers who don't want AI touching their code. If you're philosophically opposed to AI-assisted development, or if your company policy prohibits sending code to external AI services, Cursor isn't for you. Every AI feature involves sending code context to cloud models. There's a privacy mode that limits what's sent, but the core value proposition requires cloud AI processing.
People with low-spec machines. Cursor is built on Electron (like VS Code) and adds AI features on top — which means it's more resource-intensive than a lightweight editor like Vim or Sublime Text. If you're on an older laptop with limited RAM, you may experience sluggishness. 8GB RAM is a practical minimum; 16GB is recommended.
Complete beginners who haven't learned fundamentals. While Cursor can help you write code, blindly accepting AI suggestions without understanding them builds a fragile foundation. If you're brand new to programming, spend time with tutorials and learning resources first, then use Cursor as a companion that explains code rather than just generates it.
Teams needing JetBrains-specific features. If your workflow depends on JetBrains-exclusive features — advanced Java refactoring, database tooling, or framework-specific support — Cursor's VS Code base might feel limiting. Check JetBrains AI instead, which adds AI capabilities to the IDE you already depend on.
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