Coding Using AI-Powered Text Editor (Cursor)

nang+
5 Nov 202309:26

TLDRIn this video, the host explores Cursor AI, an AI-powered text editor built on top of VS Code. They discuss its capabilities, such as understanding codebases, offering suggestions, and fixing bugs, comparing it to other AI tools like GitHub Copilot. Despite initial excitement, the host finds Cursor AI lacking in practical functionality, especially in indexing and understanding complex code. They test its ability to generate test files and provide coding assistance, but encounter issues with accuracy and execution. The host concludes with a mixed review, giving it a score of 7 out of 10 for its potential but noting its current limitations.

Takeaways

  • 🧠 The video discusses trying out 'Cursor AI', an AI-powered text editor that integrates with VS Code and is designed to understand codebases and answer questions about them.
  • 💡 Cursor AI has features like chat with your project, bug finding, auto-debugging, and the ability to use your own API key for secure coding.
  • 💸 The company behind Cursor AI has reportedly raised 8 million from the OpenAI fund and is funded by various companies, indicating significant investment in the project.
  • 🔍 The AI editor is capable of providing suggestions and fixes for code, but the effectiveness of these suggestions was not consistently reliable in the demonstration.
  • 🛠️ The video shows the process of using Cursor AI to fix bugs, generate test files, and understand the functionality of the provided code for an ebook application.
  • 🔑 The video mentions the importance of local mode for security, ensuring no code or data is stored externally.
  • 📝 Cursor AI can generate documentation and test files, but the presenter expresses concerns about the complexity and the need to mock external service responses for effective testing.
  • 🤔 The presenter initially gives Cursor AI a rating of 3 out of 10, but later revises it to 7 out of 10, noting its potential despite some issues.
  • 💡 The video also explores the idea of profitability for Cursor AI, suggesting that as a startup, they may be operating at a loss while building their user base.
  • 🔄 The presenter experiences some confusion with the AI's suggestions, highlighting the importance of carefully reviewing AI-generated code before implementation.
  • 🔧 The video concludes with a demonstration of fixing a threading issue in the code, showing that while Cursor AI can provide guidance, it may not always be accurate.

Q & A

  • What is Cursor AI and how does it differ from other AI tools like Chad BT and GitHub Copilot?

    -Cursor AI is a text editor with built-in AI that is designed to understand your entire codebase and answer questions about it. Unlike Chad BT, which allows you to ask questions, and GitHub Copilot, which provides suggestions, Cursor AI is integrated into the text editor and can perform tasks such as pair programming, bug finding, and fixing.

  • How is Cursor AI funded and what companies are involved in its funding?

    -Cursor AI has raised 8 million dollars from the OpenAI fund and is also funded by various companies, although the specific companies are not mentioned in the transcript.

  • What features does Cursor AI offer for code development?

    -Cursor AI offers features such as chat with your project, pair programming chat, edit, generate AI linter, auto-debugging, and dog support. It also allows the use of your own API key and has a secure local mode to ensure no code or data is stored externally.

  • How does Cursor AI handle the security and privacy of the user's code?

    -Cursor AI has a secure mode that allows users to enable local mode, ensuring that no code or data is stored or sent outside the user's environment.

  • What is the process of using Cursor AI to find and fix bugs in the code?

    -To find and fix bugs, you can ask Cursor AI where the bugs are in the code. It will then provide suggestions or write the corrected code for you to implement.

  • What is the user's initial impression of Cursor AI after trying it out?

    -The user initially found Cursor AI to be promising but was disappointed with its performance during the demo, giving it a rating of three out of ten.

  • How does Cursor AI compare to other AI tools like Chad GBT and GitHub Copilot in terms of usefulness?

    -The user found Chad GBT and GitHub Copilot to be more useful than Cursor AI, as Cursor AI had some limitations and did not meet the user's expectations.

  • What is the user's opinion on the profitability and business model of Cursor AI?

    -The user questioned how Cursor AI would make a profit, speculating that as a startup, they might be operating at a loss initially, funded by investors, and planning to charge users once they have a substantial user base.

  • What issues did the user encounter while using Cursor AI to test and fix bugs in their code?

    -The user faced issues where Cursor AI was not able to correctly identify and fix bugs, and at one point, it suggested an incorrect fix that the user had to correct.

  • How does Cursor AI assist in writing test files for the user's code?

    -Cursor AI can write test files for the user's code, but the user noted that they might not use the tests provided by Cursor AI due to the complexity and the need to mock responses from external services.

  • What is the user's final rating for Cursor AI after considering its features and limitations?

    -After considering its features and limitations, the user gave Cursor AI a final rating of seven out of ten, acknowledging that it does what GitHub Copilot does for free and has some useful features.

Outlines

00:00

🤖 Introduction to Cursor AI Text Editor

The video script introduces Cursor AI, a text editor integrated with AI capabilities, which is positioned as an advancement over other AI tools like Chad BT and GitHub Co-pilot. Cursor AI is designed to understand an entire codebase and answer questions related to it, offering features like pair programming with an AI that knows everything about the code. The script mentions that Cursor AI is a fork of Visual Studio Code (VS Code) with added AI functionalities and has received significant funding from the OpenAI fund and other companies. The host expresses excitement about testing Cursor AI's capabilities, such as chatting with the project, bug fixing, and using it as a linter and debugger.

05:01

📚 Cursor AI's Performance and Evaluation

The script continues with the host's experience using Cursor AI, including its ability to generate tests for functions, understand code dependencies, and suggest fixes for bugs. The host discusses the complexities of testing external API calls and the need for mocking responses. Initially, the host rates Cursor AI at a three out of ten, citing limitations and unmet expectations. However, as the host explores more features, such as local mode for security and the ability to generate unique IDs, the rating improves to a seven out of ten. The host notes that while Cursor AI uses Chad GBT, it doesn't require switching tabs, which is a positive aspect. The script concludes with a humorous moment where the host is misled by Cursor AI's suggestion to fix a line of code, leading to a realization of a mistake and a re-evaluation of the tool's effectiveness.

Mindmap

Keywords

💡Cursor AI

Cursor AI is an AI-powered text editor that integrates artificial intelligence to assist in coding. It is built on top of Visual Studio Code (VS Code) and is designed to understand an entire codebase, allowing developers to ask questions and receive suggestions directly within the editor. In the video, Cursor AI is tested for its ability to suggest code improvements, find bugs, and understand the project context, which is central to the video's theme of exploring AI in coding assistance.

💡AI Tools

AI Tools in the context of the video refers to software applications that utilize artificial intelligence to enhance coding productivity. Examples mentioned include Chad BT and GitHub Copilot, which provide question-answering and suggestion features, respectively. These tools are compared with Cursor AI to evaluate its capabilities and effectiveness in aiding developers.

💡Codebase

A codebase is the total collection of source code used to build a software application. In the video, the Cursor AI's ability to understand and interact with the entire codebase is highlighted as a key feature, allowing it to provide more contextual and accurate assistance to the developer.

💡Pair Programming

Pair programming is a software development technique where two programmers work together at one workstation. One, the driver, writes code while the other, the observer or navigator, reviews each line of code as it is written in real-time. In the video, Cursor AI is likened to a 'pure engineer pair programmer' that knows everything about the codebase, emphasizing its potential to work collaboratively with developers.

💡Bug Fixing

Bug fixing is the process of identifying, diagnosing, and resolving issues or faults in a software program. The video demonstrates Cursor AI's capability to spot and fix bugs within the code, showcasing its utility in improving code quality and development efficiency.

💡Open AI Fund

The Open AI Fund is mentioned in the video as one of the funding sources for Cursor AI. It implies that the development of Cursor AI has been supported by an investment from an organization associated with the broader field of artificial intelligence, indicating a level of credibility and potential in the product.

💡Linter

A linter is a tool used in programming that analyzes source code to flag programming errors, bugs, stylistic errors, and suspicious constructs. In the video, Cursor AI's ability to act as an AI linter and provide auto-debugging support is discussed, highlighting its role in code quality assurance.

💡API Key

An API key is a unique identifier used to authenticate a user, developer, or calling program to an API. In the context of the video, Cursor AI allows the use of a custom API key, which suggests that it can be integrated with other services or tools that require API authentication for extended functionality.

💡Local Mode

Local mode refers to the operation of a software application on a user's local machine without reliance on remote servers or cloud services. Cursor AI offers a local mode to ensure that code and data remain on the user's machine, addressing privacy and security concerns highlighted in the video.

💡Ebook Generation

The video script mentions an application that uses AI for generating ebooks, which involves creating titles, outlines, and content for chapters and subsections. This serves as an example of how AI can be applied in content creation, and Cursor AI's understanding of such a project context is tested in the video.

💡Shopify API

The Shopify API is a set of programming tools that allows developers to interact with the Shopify platform, such as adding products to a store. In the video, the script describes a class that uses the Shopify API to add a generated ebook as a product, demonstrating the integration of AI with e-commerce functionalities.

💡GPT-3 and GPT-4

GPT-3 and GPT-4 refer to different iterations of the Generative Pre-trained Transformer, a type of AI language model developed by OpenAI. The video script mentions that the ebook generation process uses GPT-3, while Cursor AI is said to use GPT-4, indicating the progression and capabilities of AI models in content generation.

Highlights

Introduction to Cursor AI, an AI-powered text editor that integrates with the codebase.

Comparison with other AI tools like Chad BT and GitHub Copilot.

Cursor AI's ability to answer questions about the entire codebase.

Funding details, with $8 million raised from OpenAI and other companies.

Cursor AI's chat feature for project interaction and code understanding.

Spotting and fixing bugs within the code.

Reflection on the idea's originality and the learning process.

Using command line with Code or Cursor.

Cursor's security features, including local mode to prevent data storage.

Cursor's auto-debugging and AI linter capabilities.

Initial testing of Cursor AI's bug-finding feature.

Cursor's indexing process and its impact on functionality.

Understanding of the provided code for an AI-generated ebook application.

Request for a test file for all main functions and the response.

Cursor's limitations in testing external API responses.

Initial rating of Cursor AI and comparison with other AI tools.

Discussion on Cursor AI's business model and funding.

Cursor AI's suggestion for fixing a specific line of code.

Realization of a mistake in following Cursor AI's suggestion.

Revised rating of Cursor AI after further testing.

Final thoughts on Cursor AI's performance and potential.