What is Cursor AI?

AI has affected every domain of work in the last two years. Software engineering is no exception. The rise of AI tools has redefined how we write code, build apps, and ship new features. Among a dozen of AI tools, Cursor AI shines as a powerful all-in-one solution that combines precise code generation, refactoring, and debugging.

In this article, let’s explore Cursor AI. We’ll see how it works, what features it has to offer, how to use it, and then compare it with other AI tools like GitHub Copilot. And we will finish it off by seeing how you can use Cursor AI as your daily go-to AI assistant.

What is Cursor AI?

Cursor AI is an AI-powered code editor designed to make coding faster, easier, and more efficient. It helps developers write, refactor, and debug code with AI-driven precision. Unlike simpler tools like ChatGPT, Cursor AI understands the nuances of code, offering real-time suggestions that are tailored to your coding style and context.

Powered by Large Language Models (LLMs) like Claude and GPT, Cursor AI has been fine-tuned on vast amounts of code data. It knows how to generate code, review it, and even integrate with existing extensions, making it a natural fit for any developer looking to supercharge their workflow.

How does Cursor AI work?

At its core, Cursor AI relies on natural language processing (NLP) and machine learning techniques to interpret and generate code. It’s trained on massive datasets from platforms like GitHub and StackOverflow, learning patterns, syntax, and best practices across programming languages like JavaScript, Python, TypeScript, Java, and more.

The magic lies in its use of transformer architecture, which allows it to analyze your existing code and offer context-aware suggestions. Whether it’s generating a new function, refactoring a class, or debugging an issue, Cursor AI uses self-supervised learning and reinforcement learning to improve over time, getting better the more you use it.

Key technologies powering Cursor AI include:

• Transformer Architecture: Understands code context and semantics, offering precise suggestions.

• Contextual Learning: Analyzes your codebase to provide relevant and smart recommendations.

• Reinforcement Learning: Improves through feedback, learning from its own code suggestions.

• Self-Supervised Learning: Identifies patterns in large codebases without explicit supervision.

This makes it possible for Cursor AI to handle complex tasks. These include generating full classes or modules, debugging code, and converting pseudocode into executable programs.

How to use Cursor AI

Getting started with Cursor AI is simple. You can download it from its official website and install it on any major operating system. Once installed, you’ll feel right at home if you’re familiar with VS Code, Cursor AI is very identical to VS Code’s interface and even lets you import your existing extensions and settings

After setting your preferences (like keybindings and languages), you’re ready to use Cursor AI. The interface is intuitive, and you can do everything you’d normally do in VS Code—plus much more, thanks to Cursor’s AI features.

From here onward, you are set to use Cursor. Let’s explore some of the major features offered by the AI Code Editor.

Composer

The Composer is an integral feature that enables you to write, edit, and modify code using natural language prompts. Think of it as a ChatGPT prompt but focused on precise code generation. You can open Composer with ctrl + I on Windows or Linux, and ⌘ + I on Mac.

For the purpose of this article, I am focusing on Windows + Linux keybindings. If you’re using Mac, you must replace ctrl with cmd (⌘) key.

You can create a boilerplate of a new project, refactor a file, add a new function or a test case, or improve the accessibility of a UI component by writing a prompt. AI interprets those instructions to make changes or generate new code automatically.

This feature streamlines the coding process by reducing the need to write syntax-heavy code, letting developers focus on logic and architecture instead of repetitive tasks.

Chat Window

The Chat Window is an interactive space where developers can communicate with an AI assistant that has access to the codebase. Think of it as a full-blown ChatGPT session that has access to your entire codebase as well as the outer world.

Chat Window opens the door to many possibilities and enables you to use AI to its fullest. While using Cursor, I find myself using Chat Window more often than any other feature. You can open it by ctrl + shift + L.

Let’s briefly see what you can do with Chat Window.

Write prompts to get work done

You can ask questions, send instructions, and tell it to do stuff for you. The chat has access to the currently opened file and the specific code snippet you selected. You can select a code snippet from the file and add it to the Chat Window by pressing ctrl + shift + L.

Select specific files

If you need to provide multiple files as context, you can do so by clicking the plus (+) icon on the top left of the Chat Window. The selected files are added to the chat, and you can see them beside the Plus icon.

Search entire codebase

In case you want to search through an entire codebase, you can do that as well. To do so, hit ctrl along with enter when you are sending the prompt. It takes the entire codebase into the context and generates code accordingly. It is extremely useful when you are working on a complex feature or an architecture that spans across your codebase.

Search through web

Programming is incomplete without searching the tiniest things online. With Cursor AI, you can search on the web within the IDE itself. In the chat window, mention @web in the prompt and it’ll generate answers after searching it on the web.

Search within documentation

If you are working with a library or a framework, you often need to glance through its documentation to get your work done. With Cursor, you can add links to the documentation in the chat itself. Use @docs and provide the links to the documentation you want to use. The AI will use links to find appropriate responses to your prompts and tailor them to your tech stack.

Image to code

You can include visual examples like as designs, images, wireframes, and mockups in the chat. The AI will use the image as part of the prompt when generating the response. Simply drag and drop or paste an image into the code, and it will be included in the chat.

The Chat Window has a lot to offer. But these are the options you will end up using the most. You can find out more options by adding the @ symbol in the chat. Let’s see some other fears as well.

Learn more about other features available with @ symbol on Cursor’s documentation.

Inline Editing and Suggestions

Another feature that I use often is Inline Editing and Suggestions. With this feature, you can select blocks of code and ask the AI to make changes or provide suggestions directly within the editor. The AI predicts the next steps in your workflow, allowing it to suggest multi-line code completions based on your recent changes.

If you want help with some small task, you can select a piece of code and select Quick questoin to get your answer right away.

This greatly reduces the manual effort required for repetitive coding tasks and helps maintain consistent code quality by preventing errors through predictive code suggestions.

Cursor AI in Terminal

You can use Cursor AI to execute terminal commands as well. Open the terminal in the IDE and press ctrl + k. A small chat window will appear. Now explain what you want to do in natural language. Cursor will convert them into the terminal command you need.

Rules for Cursor AI

Cursor provides a way to provide a brief instruction to the AI model that sets the environment for the AI chat. It is called “Cursor Rules”.

Cursor Rules are custom instructions that guide the AI assistant in Cursor, tailoring its behavior when interpreting code, generating suggestions, and responding to queries.

There are two ways by which you can provide custom rules to AI.

Using Cursor Settings

Open Cursor and navigate to Settings.

1. Look for the "Rules for AI" section.

2. Enter your custom rules directly into the provided text area.

3. Save your changes.

   

These are global rules and are set for all projects you work on. Hence you must consider the types of projects you work on (scope, domain, languages, etc).

Using .cursorrules file

This method is project-specific. You can have one .cursorrules file in each project.

1. Create a new file named .cursorrules in your project's root directory.

2. Open the file in your text editor.

3. Write your custom rules using the appropriate syntax.

4. Save the file.

Cursor AI as Different Developer Personas

Cursor has a lot to offer. Hence you might get overwhelmed by everything it provides. With proper instructions, you can make it work exactly how you want. Let’s look at some examples of how you can integrate Cursor into your everyday developer life.

Cursor AI as an intern

Cursor AI can take care of mundane and boring tasks like creating boilerplates, writing tests, refactoring a codebase, migrating from one library to another, etc.

Cursor AI analyzes your codebase to provide context-aware suggestions based on patterns and best practices. Therefore, you can get rid of repetitive tasks and focus on what matters the most.

Cursor AI as a mentor

If you are someone who’s just getting started with programming, Cursor AI can act as a great tutor. It could help you write syntactically correct code, provide documentation for unfamiliar functions, explain difficult parts of the code, provide feedback on your code, etc.

Learning to code, or a new technology with Cursor AI would help you stay on the right path, and learn from the best resources.

Cursor AI as a peer programmer

If you’re already a seasoned developer, Cursor AI can be your coding buddy who writes code along the way. As it can handle large codebases, understand complex architectures, and identify bottlenecks, it can suggest optimizations, different approaches, and workarounds, for your code.

Cursor AI as a DevOps engineer

Cursor AI is also useful to automate tasks related to infrastructure as code (IaC). It can generate scripts for AWS, Docker configurations, Kubernetes YAML files, and more.

GitHub Copilot vs Cursor AI: Which Is Better?

If you’re wondering how Cursor AI stacks up against other AI tools, the comparison with GitHub Copilot is inevitable. Both tools are excellent, but they serve slightly different purposes.

• GitHub Copilot is ideal for quick code generation and prototyping. It’s lightweight and fast, making it great for developers who need simple code snippets and fast completions.

• Cursor AI, on the other hand, excels at more complex tasks. It can refactor, debug, and understand your entire codebase with deep contextual insights. If you need an all-in-one solution that can handle everything from writing to refactoring and debugging, Cursor AI is the better choice.

Ultimately, the choice between GitHub Copilot vs Cursor AI depends on what you need. For full-featured AI code editing, Cursor AI offers more robust functionality.

Wrapping Up

With the rise of AI code editors, Cursor AI stands out for its versatility and depth. Whether you’re a beginner needing guidance or a seasoned developer looking for a coding buddy, Cursor AI can take your coding workflow to the next level. Its ability to refactor, debug, and offer real-time suggestions makes it an essential tool for any developer’s toolkit.

I hope you found this article helpful. Are you using Cursor in your daily workflow? How productive do you feel with the AI Code Assistant? Or do you use any other tool to enhance your developer productivity? I’d love to know! I’m most active on Peerlist and Twitter if you want to say hi!

If you’re looking for a new job or want to launch a new project, don’t forget to check out Peerlist! It’s the Professional Network to show & tell what you are working on! Showcase your work, launch side projects, find jobs, and connect with the most incredible people.

Until then, happy coding! 👨‍💻