VS Code Is Fighting Back (RIP Cursor?)

What are the new features in VS Code?

Microsoft has upped its game in the AI editor wars by adding a range of new features to VS Code. These enhancements are designed to improve productivity and streamline the coding experience.

• Attaching Extra Context in Quick Chat Users can now add context by attaching files directly in Quick Chat, making interactions with Copilot more accurate and relevant.

• Slash Tests Command Updates With the updated slash tests command, users can now generate tests directly from existing files, simplifying the testing process.

• Custom Code Instructions Developers can configure bespoke code instructions, ensuring Copilot understands and meets specific coding standards and styles.

• Session Summaries in Chat History The new session summaries feature in chat history provides an overview of previous interactions, making it easier to track conversations and decisions.

• Longer Context for Code and Chat The ability to use longer context sections makes the AI more effective, retaining more information from code and chat for better suggestions.

• Check and Infer Commands VS Code can now verify and infer commands and participants, enhancing its ability to understand and act on user inputs.

• Automatic References for Recent Files This feature allows automatic referencing of recently used files, reducing the need to manually locate and reference files repeatedly.

These updates aim to enhance the functionality and usability of VS Code, potentially closing the gap between it and other AI-powered editors like Cursor.

How does Cursor compare to VS Code?

The battle between Cursor and VS Code has become a hot topic in the coding community. Both editors aim to provide an efficient and smooth coding experience but take different approaches.

Speed

Cursor's autocomplete isn't as fast as some alternatives, but it's highly efficient. VS Code, on the other hand, is known for its quick performance and reliable speed.

Features

• Cursor:

  • AI-assisted code completion
  • Command Shift K feature for editing multiple files simultaneously
  • Built-in handling of complex tasks like CORS
  • Unique UI elements that enhance the user experience

• VS Code:

  • Extensive plugin ecosystem
  • Great customization options
  • Strong integration with development tools and workflows

User Experience

Cursor offers a more seamless experience by automating tedious tasks and reducing the need for external documentation lookup. Frequent, contextually aware autocomplete suggestions add to its appeal. On the other hand, VS Code has a broad user base with robust support and extensive documentation, plus a familiar interface for developers across various languages and frameworks.

Drawbacks

• Cursor:

  • Occasional incorrect code suggestions
  • Slower autocomplete compared to specialized tools
  • Challenges in maintaining a forked version of VS Code

• VS Code:

  • Dependency on external plugins for advanced features
  • Sometimes more manual configuration is required for specific tasks

Cursor is pushing boundaries with its AI capabilities and tailored user interface, but VS Code remains a strong competitor with its extensive features and speed. For a deeper dive into Cursor’s performance, check out this Cursor AI editor review.

What is CodeRabbit AI and how does it help?

CodeRabbit AI is revolutionizing code review processes by leveraging advanced AI capabilities to streamline and enhance productivity. Its features are designed to make code review faster and more accurate.

• Cuts Review Times CodeRabbit AI significantly reduces the time spent on code reviews by automating many of the repetitive tasks.

• Bug Detection It can identify many bugs that might be missed by human reviewers, increasing code reliability.

• PR Summarization The tool summarizes pull requests, enabling reviewers to understand changes quickly without sifting through lines of code.

• Diagram Generation CodeRabbit AI can draw diagrams to visualize complex code structures, aiding in better comprehension and documentation.

• One-Click Changes Users can benefit from suggested changes that can be applied with a single click, speeding up the approval process.

Offering these capabilities at no cost for open-source projects makes CodeRabbit AI an attractive choice for many developers. For more in-depth information, you can explore their features on their official website.

Are AI-generated tests reliable?

The reliability of AI-generated tests is a topic of heated debate. While AI tools like GitHub Copilot and Cursor provide convenience, they often fall short in creating robust tests.

"I feel like if the tests aren't written by a human, you're losing a lot of the value from the human," remarked Theo.

Humans bring intuition and understanding to the table, which AI can't replicate. AI can miss nuanced bugs and create tests that are overly verbose or fail to match human expectations.

Additionally, AIs often struggle with context and type safety, leading to tests that may not cover all edge cases or follow best practices. Relying solely on AI for testing could result in a false sense of security.

For now, AI-generated tests should be seen as supplementary, not a replacement for human-written tests. They can save time but should be reviewed meticulously.

What are the limitations of AI editors?

AI editors like VS Code and Cursor offer exciting features but come with limitations that can impact developers.

• Type Safety Issues: Both editors struggle with maintaining type safety, often generating code that has unchecked index access or type errors.

• Context Usage: AI struggles to apply the context consistently. For example, even after adding specific instructions ensuring type-safe responses, both AI systems failed to deliver type-safe code.

• Complex Testing: AI-generated tests tend to be verbose and often miss important edge cases. Theo’s attempt to create and run tests using VS Code's Copilot resulted in errors and unmet expectations.

• Code Comprehension: While Cursor offers advanced features, it still suggests incorrect code at times. In one instance, Cursor duplicated functionality without solving the problem the user needed.

• Limitations in Custom Instructions: Theo explored custom instructions in VS Code, like making the AI always respond with Python code, but found it unreliable.

These are significant drawbacks, making it crucial to thoroughly review and possibly adjust the AI-generated outputs. Despite the advancements, developers should be cautious about over-relying on AI tools. For more on Cursor’s issues and how they deal with maintaining a forked version of VS Code, explore this article.

Is it worth paying for these AI tools?

Evaluating the value of paying for Cursor and VS Code's Copilot requires understanding the specific needs of open-source projects and individual developers. Both offer unique features that might justify their costs depending on the use case.

Benefits of Paid Features

Cursor:

• Custom AI-assisted code completion, tailored to streamline complex tasks.
• Command-Shift-K for editing multiple files simultaneously.
• Enhanced UI elements for better user experience.

VS Code's Copilot:

• Extensive plugin ecosystem which greatly enhances functionality.
• Advanced customization options for developer workflows.
• Integration with numerous development tools and frameworks.

For Open-Source Projects

Cursor is free for open-source projects. Its comprehensive features, like context-aware autocomplete and AI-assisted code review, offer substantial savings in time and effort.

For Individual Developers

For individual developers, the decision hinges on the balance between cost and productivity gains. While Copilot requires a paid subscription, its integrations and extensive plugin support might be worth the investment for those who need a robust setup.

Justifying the Cost

While both AI tools enhance productivity, it's crucial to weigh their specific advantages:

• Enhanced code review and bug detection capabilities.
• Time-saving automations and autocomplete features.
• Improved customization and integrations.

In conclusion, the worth of these AI tools depends significantly on individual or project-specific needs. For more insights into how technology impacts current internet services and economic models, visit this article.