Overview
Cursor is currently the editor to beat if you are looking to integrate AI into your daily coding workflow. Unlike GitHub Copilot which functions as an extension living inside VS Code, Cursor is a fork of VS Code itself. This distinction matters because it gives the AI control over the entire environment—the terminal, the file tree, and the diff view—rather than just the text buffer you are currently typing in.
For the user, the switching cost is practically zero. Because it is built on VS Code, you can import your existing extensions, themes, and keybindings in a single click during setup.
The tool targets a wide spectrum of users. On one end, you have "vibe coders" or founders who use it to generate entire MVP stacks by describing high-level logic. On the other, you have senior engineers at large enterprises like Stripe or Shopify who use it to navigate massive codebases and refactor legacy modules without losing context.
Key Features
Composer (Ctrl+I)
This is the feature that usually sells people on the product. Composer is an editing mode that allows you to write a prompt that modifies multiple files simultaneously. You can type "Create a generic modal component in the frontend folder and add a trigger for it in the settings page," and Cursor will plan the edit, create the files, and write the code across both locations. It turns the developer from a typist into an architect who reviews implementation details.
Codebase Indexing
Most chat extensions fail because they only see the file you have open. Cursor scans and indexes your local codebase using embeddings. This creates a "long-term memory" for the AI. You can ask broad questions like "Where do we handle JWT validation?" or "How does the billing logic interact with the user schema?" and it will pull context from relevant files you haven't even opened.
Shadow Workspace & Tab AI
This is a clever technical implementation under the hood. Cursor creates a "Shadow Workspace"—a background instance of your project—where it runs lints and type checks on the code the AI generates before showing it to you. If the AI generates code that breaks the build, the Shadow Workspace catches it and the model self-corrects.
This powers "Tab AI," their version of autocomplete. Instead of just suggesting the next word, it predicts your next edit based on your recent cursor movements. It can suggest multi-line changes that align with the surrounding code style.
Model Context Protocol (MCP)
Cursor supports MCP, an open standard that connects the AI to external data sources. This means you can hook the editor up to your Jira tickets, Google Search, or local databases. The AI can then write code based on the specific requirements found in a ticket or documentation fetched from the web.
Pricing
Cursor offers a tiered model that separates users based on how heavily they rely on premium models like Claude 4.5 Sonnet or GPT-5.2.
- Hobby (Free): Good for testing the waters. You get unlimited basic completions and a 2,000 count limit on lower-tier models. You also get a 2-week trial of the Pro features.
- Pro ($20/month): The standard for most working devs. It includes 500 "fast" premium requests per month and unlimited "slow" requests (which kick in after you hit the cap). You also get 10 uses per day of the high-reasoning "o1" models.
- Business ($40/user/month): Adds centralized billing and an admin dashboard. The critical feature here is strict Privacy Mode enforcement, ensuring code is never stored on Cursor servers or used for training.
- Ultra ($200/month): For power users who hit the 500 fast request limit in a few days. This creates a huge buffer for fast premium requests.
- Add-on: There is also a "Bugbot" agent for PR reviews which usually costs an extra $40/user/month.
Pros & Cons
Pros
- Context Awareness: It genuinely understands your folder structure. The difference between asking ChatGPT to refactor a function and asking Cursor (which knows the dependencies defined in your
package.json) is night and day. - The Flow: The "Composer" window stops you from alt-tabbing to a browser. Keeping the generation and the implementation in the same window keeps you in a flow state.
- Frictionless Switch: Since it is VS Code under the hood, it feels familiar immediately. You don't have to learn a new IDE.
Cons
- Support & Billing: There are valid complaints regarding customer service. Users have reported confusion over usage metrics and slow response times when billing issues arise.
- Hardware Heavy: The local indexing and Shadow Workspace features eat RAM. If you are on an older machine (e.g., 8GB RAM), the editor might feel sluggish compared to stock VS Code.
- Dependency Risk: At its core, Cursor is a UI wrapper around models from OpenAI and Anthropic. If VS Code eventually integrates these features natively at the same depth, Cursor's main value prop evaporates.
- The "Fast" Request Cap: For heavy users, 500 fast requests on the $20 plan go quickly. Once you are throttled to "slow" requests, the lag can break your rhythm.
Verdict
Cursor is currently the best implementation of AI-assisted coding on the market. It moves beyond simple autocomplete and creates a workflow where the AI acts as a junior developer handling the boilerplate while you direct the logic.
If you are a professional developer, the $20/month is easily justified by the time saved on scaffolding and refactoring. If you are a beginner or a founder, it is a massive lever that allows you to punch above your weight class. Just keep an eye on your RAM usage and be prepared to upgrade if you rely heavily on the "fast" responses.