Is Cursor's Copilot++ BETTER than Github Copilot? FAST AI Coding Master Class

IndyDevDan
4 Mar 202414:14

TLDRThe video showcases Cursor's AI coding assistant, Copilot++, which offers advanced auto-completion across multiple lines of code without the cursor needing to be in the exact position. It highlights the assistant's ability to handle multiple prompts simultaneously and integrate reference documents for more context-aware coding. The host demonstrates adding and removing nodes in a graph, updating UI elements, and leveraging the assistant's understanding of context to automate repetitive tasks, emphasizing the efficiency gains in coding with AI assistance.

Takeaways

  • 🚀 Cursor's Copilot++ was recently launched, offering advanced AI coding assistance.
  • 🔍 It provides inline auto-completion, which is aware of more context compared to traditional AI assistants.
  • ✂️ The feature allows for the removal of comments and the addition of elements like buttons with ease.
  • 🔄 Users can run multiple prompts simultaneously, enhancing productivity.
  • 🛠️ Copilot++ auto-completes multiple lines without the cursor needing to be in the exact position.
  • 🔑 It is iteratively controllable, allowing users to correct any mistakes made by the AI.
  • 📚 Reference documents can be added to enhance the AI's understanding and provide specific coding solutions.
  • 🌐 The AI can read and incorporate information from various documentation sources to assist in coding tasks.
  • 🔄 Auto-completion is dynamic, adapting to the user's ongoing coding needs and intentions.
  • 🎨 It supports the customization of elements such as edge styles and node positions within a graph.
  • 🔄 The AI can automatically generate functions and correct errors, streamlining the coding process.

Q & A

  • What is the main topic of the video script?

    -The main topic of the video script is comparing Cursor's Copilot++ to Github Copilot, and demonstrating how to use AI coding assistance for tasks such as creating and manipulating a graph flow in a Vue.js application.

  • What are the unique features of Cursor's Copilot++ mentioned in the script?

    -Cursor's Copilot++ is highlighted for its inline auto-completion that is aware of more context and can auto-complete multiple lines without the cursor necessarily being in the position for the completion.

  • How does the script demonstrate the use of AI coding assistance for creating buttons in a Vue.js application?

    -The script demonstrates using AI coding assistance to generate code for 'add node' and 'remove node' buttons, showing how the AI can provide code snippets and the user can accept and integrate them into the application.

  • What does the script suggest for improving the position of added nodes?

    -The script suggests updating the position of added nodes by calculating the lowest 'y' position of all nodes and adding a certain pixel value to it to ensure the nodes are not positioned in the same spot every time.

  • How does the script utilize the 'useViewFlow' library in Vue.js?

    -The 'useViewFlow' library is utilized to programmatically create and manipulate graph flows in Vue.js, allowing for the dynamic addition and removal of nodes and edges.

  • What is the purpose of the 'fit to view' function mentioned in the script?

    -The 'fit to view' function is intended to automatically resize the view to fit the newly added nodes, ensuring that the graph remains visually organized and the nodes are not out of view.

  • How does the script discuss the iterative control of AI coding assistance?

    -The script emphasizes the importance of being able to correct mistakes made by the AI coding assistant, highlighting the need for iterative control to ensure the accuracy and functionality of the generated code.

  • What is the role of reference documents in enhancing the capabilities of the AI coding assistant?

    -Reference documents, when added to the AI coding assistant, can provide additional context and information that the AI can use to generate more accurate and relevant code snippets.

  • How does the script illustrate the use of auto-completion for labeling elements in the graph?

    -The script shows the AI coding assistant picking up on the pattern of labeling elements as 'llm coder' and auto-completing the labels for the nodes and edges in the graph.

  • What advice does the script give on utilizing AI coding assistants to stay relevant in the engineering field?

    -The script advises focusing less on writing individual lines of code and more on high-level manipulation of the application's logic, using AI coding assistants to generate code automatically and quickly, thus upleveling one's role in the development stack.

Outlines

00:00

🤖 Introduction to AI Coding Assistance with Cursor

The video script introduces Cursor, an advanced AI coding assistant, highlighting its recent feature release, co-pilot Plus+. The assistant demonstrates the ability to run multiple prompts simultaneously, such as creating add and remove buttons for a user interface. It also showcases co-pilot Plus+'s advanced auto-completion capabilities, which can fill in multiple lines of code without the cursor being in the exact position, improving coding efficiency. The script also includes a brief tutorial on using Cursor's features to manipulate UI elements and generate random nodes and edges for a graph.

05:03

🔄 Enhancing Productivity with Cursor's Auto-Completion and Reactive Features

This paragraph delves into Cursor's auto-completion features, emphasizing how it can understand context and auto-complete multiple lines of code. The script describes setting up a view watcher to automatically call the 'fit to view' function when nodes are updated, demonstrating Cursor's reactivity and iterative control. It also explores the use of co-pilot Plus+ for auto-completing labels and edges in a graph, showcasing the AI's ability to pick up on patterns and make intelligent suggestions, thus streamlining the coding process.

10:05

📚 Incorporating Reference Documents and Advanced Auto-Completion in Cursor

The script discusses Cursor's keystone feature of adding reference documents to assist with coding tasks. It illustrates how to integrate documentation about nodes and edges into the coding environment. The assistant then uses these documents to update the graph's edges and nodes with step edges and color changes. It also touches on the limitations of the 'apply diff' functionality and suggests improvements. The video concludes with a focus on using AI coding assistants to enhance engineering capabilities, emphasizing the importance of leveraging technology for productivity and staying relevant in the field.

Mindmap

Keywords

💡Cursor's Copilot++

Cursor's Copilot++ is an advanced AI coding assistant that builds upon the features of traditional code completion tools like Github Copilot. It offers in-line auto-completion that is aware of more context, which allows it to provide code suggestions across multiple lines, not just at the cursor's position. This tool is designed to be more iteratively controllable, enabling users to correct any mistakes it makes, as demonstrated in the video where it auto-completed functions for adding and removing nodes in a graph.

💡Github Copilot

Github Copilot is a widely recognized AI coding assistant developed by GitHub, OpenAI, and Microsoft. It provides code suggestions, auto-completion, and documentation insights, supporting multiple programming languages. Trained on public GitHub repositories, it offers a popular choice for developers, although it may have limitations with newer or niche languages due to fewer public examples. It also offers integration with various IDEs and a chat feature for direct interaction with the AI.

💡AI coding assistance

AI coding assistance refers to the use of artificial intelligence to aid in the coding process by providing suggestions, auto-completions, and even generating code snippets based on the context. This technology helps to accelerate development, reduce errors, and improve code quality. The video demonstrates this by showing how AI can handle multiple prompts simultaneously and create aligned items for a user interface.

💡Auto-completion

Auto-completion in the context of AI coding assistants is a feature that predicts and suggests the next line of code or offers code completions based on the context of what's already written. The video showcases this with Cursor's Copilot++, which is capable of auto-completing multiple lines without the need for the cursor to be in the exact position, unlike traditional auto-completion tools.

💡Code optimization

Code optimization involves improving the efficiency of code, often in terms of performance or memory usage. AI coding assistants like Cursor's Copilot++ can offer suggestions for optimizing code snippets, helping developers to write cleaner and more efficient code. The script mentions this in the context of updating styles and positioning for UI elements.

💡Inline instruction

Inline instruction is a feature that allows developers to give commands directly within the code editor, which the AI coding assistant can then execute. In the video, this is used to quickly generate functions and update code, streamlining the development process.

💡Reference documents

Reference documents are external sources of information that AI coding assistants can use to provide more accurate and context-aware suggestions. In the video, the presenter adds documentation about graph flows and uses it to inform the AI's code generation, enhancing the assistant's ability to provide relevant code snippets.

💡Vue.js

Vue.js is a popular JavaScript framework for building user interfaces and single-page applications. In the context of the video, it is mentioned as the framework used for creating programmatically generated graphs and charts with the help of an AI coding assistant.

💡Graph flows

Graph flows refer to the visual representation of data in a graph structure, where nodes and edges represent elements and their relationships. The video demonstrates the creation and manipulation of graph flows using an AI coding assistant to automate the coding process for adding and removing nodes and edges.

💡Iterative可控性

Iterative可控性 highlights the ability to progressively refine and control the output of AI coding assistants. The script emphasizes the importance of being able to correct any mistakes made by the AI, ensuring that developers maintain control over the final code product.

Highlights

Cursor's Copilot++ is a new AI coding assistant launched to enhance coding efficiency.

AI coding assistance can run multiple prompts simultaneously, improving workflow.

Copilot++ offers inline auto-completion that is aware of more context.

The assistant can auto-complete multiple lines without the cursor being in the exact position.

Cursor's features include adding and removing nodes with auto-alignment.

Auto-completion in Cursor is demonstrated with the creation of 'add node' and 'remove node' functions.

Cursor's auto-completion suggests code changes based on the current context of the application.

The ability to fix node positioning issues on the fly with AI assistance is showcased.

Cursor's UI allows for the addition of reference documents to assist with coding tasks.

The integration of documentation into the coding process is demonstrated with Cursor.

AI coding assistance is used to update edges and nodes in the graph with specific attributes.

Cursor's auto-completion is shown to be effective in renaming elements and adding labels.

The iterative control of AI coding assistants allows for corrections and improvements in real-time.

Cursor's ability to suggest code changes based on reference documents is highlighted.

The video demonstrates how to use AI coding assistants to uplevel one's position in the development stack.

The importance of focusing on high-level logic rather than individual lines of code is emphasized.

The channel's focus on utilizing technology to enhance engineering abilities and stay relevant in the industry.