A comparison of capabilities between Cursor and GitHub Copilot. More and more people are switching from GitHub Copilot to Cursor, but why is Cursor becoming so popular? Many authors who recommend Cursor haven't clearly explained what makes Cursor superior to GitHub Copilot. At its core, Cursor's main advantages are reflected in two aspects.

More and more developers are switching from GitHub Copilot to Cursor, but why is Cursor becoming so popular? What capabilities are most important for AI-assisted coding? Many who recommend Cursor haven't clearly explained what makes it superior to GitHub Copilot.

At its core, Cursor's main advantages are reflected in two aspects:

1. Code modification capabilities
2. Context referencing abilities

Code Modification Capabilities: Cursor's Core Advantage

Imagine you're writing an article. "Insertion" is like adding new content at the end, while "modification" involves adjusting and improving parts you've already written. The same applies to programming:

• "Inserting code" is like adding new functionality at the end of a program
• "Modifying code" involves optimizing or correcting existing code

These two operations create vastly different coding experiences. With modification capabilities, it's like having a programming assistant always on standby, ready to help you quickly adjust and refine your code, not just add new content at the end.

This core advantage not only makes Cursor more powerful in functionality but also creates a more fluid and efficient coding experience.

GitHub Copilot's Limitations

GitHub Copilot primarily operates by inserting code based on context. While this is helpful, its functionality is limited to appending new code.

In GitHub Copilot's official examples:

You need to input a function header in a JavaScript file:

function calculateDaysBetweenDates(begin, end) {

Then GitHub Copilot automatically suggests the remainder of the code. This operation only appends a segment of code without modifying the existing code.

Cursor's Comprehensive Editing Capabilities

In contrast, Cursor can not only insert new code but also directly modify existing code.

This capability is reflected in several aspects:

1. Multi-line editing: Cursor can suggest modifications to multiple lines of code based on the current context. All you need to do is press the Tab key to let Cursor make the modifications for you.
   This smooth experience truly makes you feel like someone is coding alongside you.

2. Inline editing: By using the Ctrl/Cmd K shortcut, you can select a code block to edit, then input modification instructions in the prompt bar. Cursor will intelligently modify the selected code based on your instructions.
   If you find Cursor's modified code meets your expectations, simply click Accept. This interaction method is why many find Cursor so intuitive to use (mainly because GitHub Copilot doesn't support modifications, so it can't provide this experience).

3. Intelligent prediction: Cursor can intelligently predict your next coding intention and provide appropriate suggestions.
   In this example, if you changed a variable name from "updates" to "updatesToServer," Cursor would predict that other instances of the "updates" variable should also be updated to "updatesToServer."
   So after you modify code in one place, Cursor will automatically suggest that other places also need synchronous updates, allowing you to simply press Tab repeatedly, which feels incredibly satisfying.

4. Composer functionality: Although still in Beta, Cursor's Composer feature already demonstrates the ability to edit and generate multiple files simultaneously, which is particularly useful in complex projects.

These comprehensive editing capabilities make Cursor's user experience far superior to GitHub Copilot, giving developers a true feeling of "taking off."

Context Referencing Capabilities: More Intuitive, More Powerful

In AI-assisted coding, accurately understanding and utilizing context information is crucial. Cursor also excels in this area, providing more intuitive and powerful context referencing capabilities.

Cursor's @ Symbol References

In Cursor's AI input fields (such as Cmd K, Cmd L, or Terminal Cmd K), you only need to type the @ symbol to see a suggestion list displaying referenceable context information. This list automatically filters based on your input, showing only the most relevant suggestions.

The context options available for reference are clear and straightforward – users can immediately understand what type of context information each option represents. These options basically cover all possible context information that might be needed in daily development.

Among these, @Codebase provides the ability to search global code. Cursor preprocesses your project code by indexing it and stores the related index information locally (while Copilot relies on GitHub's API for remote searching).

GitHub Copilot's Complex Reference Methods

In comparison, GitHub Copilot provides two context reference methods: Chat participants and Chat variables, using the @ and # symbols respectively. This design not only increases usage complexity but also lacks intuitive and clear naming.

Compared to Cursor, the range of context choices GitHub Copilot can provide is also relatively limited, unable to achieve the comprehensive coverage that Cursor offers.

It's worth mentioning that GitHub Copilot only caught up with multi-file context introduction functionality early this year. From GitHub's update logs, it's clear they still have much to learn and borrow from Cursor in this area.

Conclusion

Through its powerful code modification capabilities and intuitive context referencing functionality, Cursor provides developers with a more efficient and intelligent AI coding assistant than GitHub Copilot. If you're looking for a tool that can truly enhance coding efficiency and quality, consider trying Cursor. It might give you an unprecedented feeling of coding "takeoff"!

Have you used Cursor or GitHub Copilot? Feel free to share your experiences and thoughts!