Cursor Editor Review: Is It Worth Switching from VS Code?

The code editor market has been largely static for years. VS Code dominates, with JetBrains holding its ground among enterprise developers and a handful of smaller editors serving niche audiences. But in 2024-2025, a new player arrived that genuinely disrupted the space: Cursor. Built as a fork of VS Code but re-engineered from the ground up with AI at its core, Cursor promises to change not just how you write code, but how you think about software development.

After using Cursor as our primary editor for six months across multiple projects — including a Next.js web application, a Python data pipeline, and a TypeScript library — we have a thorough understanding of what it does well, where it falls short, and whether it is genuinely worth making the switch. Here is our complete, honest review.

What is Cursor?

Cursor is an AI-native code editor created by Anysphere, a company founded by former engineers from MIT, OpenAI, and Scale AI. Rather than building an editor from scratch, the team made a pragmatic choice: they forked VS Code. This means Cursor inherits the entire VS Code ecosystem — every extension, every theme, every keyboard shortcut, every configuration option — while layering AI capabilities on top.

The result is an editor that feels immediately familiar to any VS Code user but behaves very differently once you start using its AI features. Everything about Cursor is designed around the assumption that you will interact with AI constantly throughout your coding session, not as an occasional assistant, but as a core part of your workflow.

Cursor supports multiple AI models under the hood. You can choose between Claude, GPT-4o, and other models depending on your preference and the task at hand. The editor also includes a local indexing system that builds a semantic understanding of your codebase, enabling the AI to provide suggestions that are contextually aware of your entire project — not just the file you are currently editing.

Installation and Setup

Getting started with Cursor is straightforward. The editor is available for macOS, Windows, and Linux. Here is what the setup process looks like:

Download and Install

Download the installer from the Cursor website. The installation process is identical to VS Code — if you have VS Code installed, Cursor will even detect it and offer to import your existing settings, extensions, and keybindings automatically. This migration feature is one of the smartest decisions the team made, because it means you can start using Cursor with your entire existing development environment intact from day one.

Account and Configuration

After launching Cursor, you need to create an account (email or GitHub login). Once signed in, you will be prompted to configure your AI model preferences. The free tier uses Cursor's own models, while paid plans give you access to premium models like Claude 3.5 Sonnet and GPT-4o.

Codebase Indexing

One of the first things Cursor does after you open a project is index your codebase. This process builds a vector embedding of your code, allowing the AI to understand relationships between files, functions, and modules. For a medium-sized project (say, 50-100K lines of code), indexing typically takes 1-3 minutes. For larger projects, it can take longer, but you can start coding immediately while indexing runs in the background.

Extension Compatibility

Since Cursor is built on VS Code, virtually every VS Code extension works. We tested popular extensions including ESLint, Prettier, GitLens, Thunder Client, Docker, and various language-specific extensions — all worked without any issues. If there is a specific extension you rely on daily, it will almost certainly work in Cursor.

Key Features

Intelligent Code Completion

Cursor's code completion, branded as "Tab completion," goes far beyond what you get from standard VS Code IntelliSense or even GitHub Copilot. The system predicts and suggests multi-line completions that consider:

• Full file context: What you have written in the current file, including imports, variable declarations, and function signatures
• Cross-file context: Related files, type definitions, and implementations across your project
• Codebase-wide patterns: Coding conventions, naming patterns, and architectural choices you have established
• Documentation and comments: Inline comments and docstrings that describe intended behavior

In practice, this means Cursor can suggest an entire function implementation after you write just the function signature. It can generate test cases based on your existing test patterns. It can fill in boilerplate code for new components following the conventions of your project. The completions are not always perfect, but they are accurate enough that you find yourself pressing Tab to accept suggestions far more often than rejecting them.

One practical example: when building a new REST API endpoint in our Next.js project, Cursor suggested the entire handler function — including input validation, error handling, database queries, and the response formatting — after we typed just the route path and function signature. All of it followed the patterns we had already established in other endpoints.

AI Chat (Cmd+L / Ctrl+L)

The AI Chat panel is accessible via a keyboard shortcut and acts as your in-editor AI assistant. What sets Cursor's chat apart from similar features in other editors is its deep awareness of your codebase. You can ask questions like:

• "Where is the user authentication logic handled?"
• "Find all places where we query the database directly instead of using the ORM"
• "Explain how the payment processing flow works in this codebase"
• "What are the potential issues with this approach to caching?"

The chat references specific files and line numbers in its responses. It can read files, search across your project, and provide explanations that are grounded in your actual code. You can also highlight code and ask the chat to explain, refactor, or optimize it.

A particularly useful feature is the ability to "@" files and folders in your chat messages. Typing @src/components tells the AI to consider all files in that directory when responding. This makes it easy to scope conversations to relevant parts of your codebase.

Multi-File Editing

This is arguably Cursor's killer feature. With multi-file editing, you can describe a change that touches multiple files, and Cursor will generate coordinated edits across all of them simultaneously. For example:

• "Add a 'status' field to the User model, update the API endpoints to include it, update the frontend form to allow editing it, and add it to the database migration"

Cursor will propose changes across your model definition, API route handlers, React components, and database migration files — all at once. Each proposed change is shown inline with a diff view, so you can review and accept or reject individual changes before applying them.

This feature shines in scenarios that would normally require you to manually navigate between five or six files, making consistent changes in each. We found it particularly valuable for:

• Adding new features that span the full stack
• Renaming variables or refactoring across a codebase
• Updating type definitions and propagating changes
• Creating new CRUD operations with all the boilerplate

Tab Completion

Beyond the intelligent multi-line completion described above, Cursor offers a rapid-fire Tab completion experience that feels almost like the AI is reading your mind. As you type, ghost text appears suggesting the next several lines or blocks of code. Press Tab to accept, or keep typing to override. The suggestions are contextually relevant and surprisingly accurate, especially for repetitive patterns like creating new components, writing tests, or implementing standard CRUD operations.

Composer (Cmd+I / Ctrl+I)

Composer is Cursor's inline AI assistant that works directly in your editor without opening a side panel. You highlight a block of code or a file, press the shortcut, and describe what you want to change. Composer then generates the replacement code inline, which you can accept or refine. It is perfect for:

• Refactoring a specific function
• Adding error handling to existing code
• Optimizing a database query
• Converting between coding patterns
• Adding comments or documentation

Composer integrates smoothly with the normal editing flow. You do not have to switch context to a chat panel — the AI operates right where you are working.

Codebase-Aware Answers

What truly differentiates Cursor from an AI chatbot with a code editor attached is its deep codebase awareness. Cursor maintains an index of your entire project and uses it to provide answers that are grounded in your actual code. When you ask about how a feature works, it does not give a generic answer — it traces through your specific implementation, references your specific files and functions, and provides guidance that is directly applicable to your project.

Performance Benchmarks

We tested Cursor's performance on several metrics relevant to daily development work.

Editor Responsiveness

Cursor is built on the same Electron foundation as VS Code, so baseline editor performance is nearly identical. Opening files, navigating code, and using standard editor features feel indistinguishable from VS Code. Scrolling, searching, and syntax highlighting are all smooth and responsive.

AI Feature Latency

AI response times depend on your model choice and internet connection. Here are approximate latencies we observed on a stable broadband connection:

| Feature | Average Latency | Notes | |---------|----------------|-------| | Tab Completion | 200-500ms | Near-instant, feels native | | AI Chat Response | 2-5 seconds | Depends on query complexity | | Multi-file Edit | 5-15 seconds | Depends on number of files | | Codebase Indexing | 1-5 minutes | One-time per project, runs in background |

Memory Usage

Cursor uses slightly more RAM than VS Code due to the indexing process. On our test machine (16GB RAM, M2 MacBook Pro), Cursor typically used 400-600MB of RAM compared to VS Code's 300-450MB. The difference is noticeable but not problematic on modern hardware.

CPU Impact

The AI features themselves run on remote servers, so they do not significantly impact local CPU usage. The indexing process can cause brief CPU spikes when a project is first opened or after significant changes, but these settle quickly.

Pros and Cons

Pros

• Seamless VS Code migration: All your extensions, settings, and keyboard shortcuts transfer over. The learning curve is essentially zero for existing VS Code users
• Exceptional code completion: Multi-line, context-aware suggestions that frequently predict what you were about to write
• True multi-file editing: Coordinated changes across multiple files save enormous amounts of time on full-stack development
• Codebase awareness: The AI understands your project structure and conventions, providing relevant and accurate suggestions
• Model flexibility: Choose between Claude, GPT-4o, and other models based on the task
• Active development: The Cursor team ships updates frequently, and the product improves noticeably month over month
• Privacy controls: You can exclude sensitive files and folders from AI indexing

Cons

• Requires internet connection: AI features do not work offline. You get basic editor functionality but lose the core selling point
• Subscription cost: At $20/month, Cursor is more expensive than many alternatives, especially for individual developers
• Occasional hallucinations: The AI sometimes suggests code that looks correct but contains logical errors or uses non-existent APIs. Code review is still essential
• Large project indexing: Very large monorepos (500K+ lines) can take significant time to index and may slow initial project load
• Vendor lock-in concerns: Your workflow becomes heavily dependent on Cursor-specific features that do not exist in standard VS Code
• Resource usage: Slightly higher RAM and CPU usage than plain VS Code due to indexing

Cursor vs VS Code + GitHub Copilot

This is the comparison most developers want to see. Here is how Cursor stacks up against the most popular AI-enhanced VS Code setup.

| Feature | Cursor | VS Code + Copilot | |---------|--------|------------------| | Code Completion | Multi-line, codebase-aware | Single-line or multi-line, limited context | | AI Chat | Deeply integrated, references project files | Available via Copilot Chat, less codebase-aware | | Multi-file Editing | Native, coordinated edits across files | Not available natively | | Extension Ecosystem | Full VS Code compatibility | Full VS Code compatibility | | Setup Complexity | Install and go | Install VS Code + Copilot extension | | Model Choice | Claude, GPT-4o, others | GPT-4o primarily | | Privacy Controls | Granular file/folder exclusions | Basic controls | | Cost | $20/month (Pro) | $10/month (Individual) or $19/month (Business) | | Offline Use | Editor only, no AI | Editor only, no AI |

The key differentiator is depth of integration. Copilot is an add-on to VS Code, while Cursor was designed from the start to be AI-first. This shows in features like multi-file editing and codebase-aware completion, which simply do not exist in the Copilot ecosystem. If you primarily need single-file code suggestions, Copilot is a capable and cheaper option. If you want AI that understands your entire project and can make coordinated changes across files, Cursor is clearly superior.

Pricing

Cursor offers several pricing tiers:

| Plan | Price | AI Features | Best For | |------|-------|-------------|----------| | Free | $0 | Basic completions, limited AI chat | Trying it out | | Pro | $20/month | Full access to all AI features, premium models | Individual developers | | Business | $40/month | Admin controls, centralized billing, SSO | Teams and companies |

The free tier is generous enough to evaluate the product but too limited for daily professional use. The Pro plan at $20/month is the sweet spot for most individual developers. Business pricing at $40/user/month is aimed at teams that need administrative controls and compliance features.

Who Should Switch to Cursor?

Cursor is an excellent choice if you:

• Are a full-stack developer working across frontend and backend code
• Frequently make changes that span multiple files or services
• Want to reduce boilerplate and repetitive coding tasks
• Already use VS Code and want a seamless transition
• Work on medium-sized codebases (1K-500K lines) where codebase awareness provides real value
• Are willing to pay $20/month for AI-assisted development

You might want to stick with VS Code + Copilot if you:

• Are on a tight budget and $10/month matters
• Work primarily on single-file tasks where multi-file editing adds little value
• Have a very large monorepo where indexing is problematic
• Prefer the flexibility of mixing and matching AI tools rather than committing to one
• Need extensive offline development capability

Final Verdict

Rating: 4.8/5

Cursor is the most significant evolution in code editing since VS Code itself launched. It is not just an editor with AI bolted on — it is an editor designed from the ground up for an AI-assisted development workflow. The multi-file editing feature alone can save hours per week for full-stack developers, and the codebase-aware completions reduce the cognitive overhead of context-switching between files.

The VS Code compatibility means there is virtually no risk in trying it — your extensions, settings, and muscle memory transfer over completely. And if you are already paying for GitHub Copilot, the upgrade to Cursor Pro costs only $10 more per month for significantly more capable AI features.

Our recommendation: try Cursor for two weeks. Use it as your primary editor on a real project. If you find yourself reaching for the AI chat, accepting multi-file edits, and relying on codebase-aware completions — and most developers we have spoken to do — you will have a hard time going back to a non-AI-native editor. Cursor represents the direction that all code editors are heading, and it is ahead of the curve today.