Let's talk about AI coding assistants. They're basically the new hot topic in dev tools, and for good reason. They're designed to help developers write code more efficiently and with fewer errors. They're pretty dang cool.
While there are quite a few players in this space, let's zoom in on two of the major contenders. In one corner, we've got GitHub Copilot, the established player. In the other, Cursor, the new kid on the block shaking things up. Both are trying to make our lives easier as devs.
After spending some time with Copilot and Cursor, I thought it might be useful to break down how they stack up against each other. Whether you're curious about trying them out or just want to know what all the fuss is about, stick around. We're going to dig into some of the key features that matter to us as developers.
Cursor is basically an AI-powered code editor on steroids. It is a fork of Visual Studio Code, bringing advanced AI capabilities to a familiar interface.
GitHub Copilot is an AI coding assistant developed by GitHub in collaboration with OpenAI. It uses machine learning to generate code suggestions and complete tasks directly in your code editor (Visual Studio Code, Visual Studio, Vim/Neovim, JetBrains IDEs).
Both Cursor AI and GitHub Copilot offer a range of features designed to enhance productivity and support developers. Let's dive into the specific features and see how these two compare.
The August 2024 update to VS Code introduced several new features to GitHub Copilot. However, many of these additions are still in the experimental phase and may not always deliver consistent results yet.
You know that feeling when you're typing and the IDE just gets what you're trying to do? That's what we're talking about here.
Cursor's tab completion is pretty wild. It'll suggest multiple lines of code, and it's looking at your whole project to make those suggestions. It even tries to guess where you're going to edit next. Plus, it'll catch and fix mistakes on the fly.
Copilot's more focused on inline suggestions. Tab to accept, and you're off to the races. It often predicts the next logical line of code based on the developer's style, which can significantly speed up coding tasks.
This is where things get interesting. Imagine describing what you want your code to do, and boom — it's there.
Cursor has this thing called Composer that can create entire applications based on your description. It's looking at your whole project when it generates code, so it tries to match your style. You can access it with ⌘ + I for a floating window or ⌘ + SHIFT + I for full-screen mode. For inline generation, boilerplate code and edits, you can use the ⌘ + K feature. Impressively, it can work with multiple programming languages within the same project, adapting its suggestions accordingly.
Copilot's more about those inline suggestions, but Copilot Chat can handle bigger chunks of code if you ask it nicely. The CLI can also generate code if you describe what you want in plain English.
Sometimes you just need to ask a question. But is chatting with an AI actually helpful?
Cursor's chat (⌘ + L) is context-aware, so it knows what you're working on. You can apply code suggestions right from the chat, which is neat. It even supports images for visual context.
GitHub Copilot Chat is similar — you can ask it to explain code or suggest improvements. It's integrated right into VS Code, so it feels pretty seamless. They've been rolling out some new features lately, like better chat history and ways to attach more context. But if you're already using Cursor, you might not find anything groundbreaking here.
Terminal work can be a pain, especially with complex commands.
Cursor extends its AI smarts to the terminal with ⌘ + K. It's pretty handy for translating vague ideas into actual commands.
Copilot's got a CLI that does something similar. It can generate shell commands based on what you're trying to do, which is pretty cool if you can never remember the exact syntax for that one command you use once a year.
This is a big one. Can these tools actually understand your whole project, or are they just looking at the current file?
Cursor's pretty impressive here. It looks at your entire codebase and project structure. You can even use @ symbols to reference specific parts of your project, like @Files, @Folders, @Code, and more.
With the recent update, when using Quick Chat, you can now use the Attach Context action to attach context like files and symbol to your Copilot request.
Support for working across multiple files enables AI assistants to understand and modify complex project structures.
Cursor's Composer can make changes across your entire project, which is pretty powerful. It understands how different files and components relate to each other. Composer can generate files for an entire app at once. I’ve personally used the feature to refactor a single file into more organized files and folders.
Copilot's more limited here. It's mainly focused on the current file, though it can suggest imports from other files.
Composer excels at generating code from descriptions, but specialized tools exist for converting design files to code directly. Visual Copilot, for example, converts Figma designs into code. This can be particularly useful if you have your own design system and want to streamline the process of turning designs into functional code.
We all need a second pair of eyes sometimes. AI-powered code review can provide automated feedback on code quality, potential bugs, and adherence to best practices.
Cursor has an AI Review tool that analyzes your changes. It'll give you feedback on code quality, potential bugs, that sort of thing. You can even customize what it looks for.
Copilot doesn't have a dedicated review feature, but you can use Copilot Chat to explain code and suggest improvements.
Nobody wants to switch between a bunch of tools.
Cursor is its own thing — it's built on top of VS Code, so it'll feel familiar if you're used to that.
Copilot on the other hand integrates with various IDEs — VS Code, IntelliJ, Neovim. The CLI works in any terminal.
One size doesn't fit all in coding. Can you bend these tools to fit your specific needs, or are you stuck with what they give you?
Cursor lets you set custom instructions through settings and .cursorrules files. You can tailor it to your project's specific needs.
A recent experimental setting lets you define a set of instructions that are added to every Copilot request that generates code but seems to be flaky at the moment.
Cursor offers a range of models, including GPT-4, Claude 3.5 Sonnet, and their custom cursor-small model. You can choose based on what you need — speed or capability.
Copilot uses OpenAI's Codex model. They're always updating it, but you don't get to choose which model you're using. The latest model integrated is OpenAI o1-preview.
Let's talk money. How do their pricing models compare?
Cursor has a free Hobby tier with limited features, a Pro tier for $20/month, and a Business tier for $40/user/month.
Copilot is $10/month or $100/year for individuals. They've got enterprise pricing too if you're part of a bigger org.
After diving deep into both Cursor and GitHub Copilot, it's time to pick a champ. And drum roll, please...Cursor takes the crown. Its unique features make it a hard sell to beat in the world of AI-assisted coding.
Now, don't get me wrong, Copilot is a solid tool. It's great for quick suggestions and it plays nice with a bunch of different IDEs. But Cursor? It's just operating on another level.
Here's why Cursor wins out:
- Project-wide smarts: Cursor doesn't just look at your current file, it understands your entire project. That's huge.
- Composer: Being able to generate entire app structures or orchestrate changes across multiple files? That's some next-level stuff.
- Customization: With Cursor, you can tailor the AI to your specific needs. That .cursorrules file is a game-changer.
- AI review: Having an AI that can review your code changes and give you feedback? That's like having a tireless senior dev on your team.
- Model choices: Cursor lets you pick the AI model that fits your needs. Sometimes you need the big guns, sometimes you need speed. Cursor's got you covered either way.
Copilot is still a powerful tool, and if you're looking for something that's easy to integrate into your existing workflow, it might be the way to go. Its code completion capabilities are certainly impressive. But if you want to really push the boundaries of what AI can do for your coding, Cursor is where it's at.
Of course, the best tool is the one that works for you. So give them both a spin if you can. But if you're asking me? Cursor's the one to beat right now.
Introducing Visual Copilot: convert Figma designs to high quality code in a single click.
