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

IndyDevDan
4 Mar 202414:14

TLDRThe video explores Cursor's AI coding assistant, Copilot++, comparing it to Github Copilot. It demonstrates the ability to run multiple prompts simultaneously and highlights Cursor's advanced autocomplete features, which complete multiple lines of code contextually. The assistant also shows how to integrate reference documents for coding guidance and updates graph edges with step styles and colors. The video emphasizes the importance of leveraging AI to elevate one's role in the development stack, focusing on high-level logic manipulation and rapid implementation.

Takeaways

  • 🚀 Cursor's Copilot++ is a new AI coding assistant that aims to provide more advanced features compared to Github Copilot.
  • 🔍 It offers in-line auto-completion that is aware of more context and can complete multiple lines without the cursor being in the exact position.
  • ✂️ The assistant can remove comments and add new features like buttons with aligned items through prompts.
  • 🔄 Copilot++ is capable of running multiple prompts simultaneously, allowing for efficient coding.
  • 🛠️ It provides auto-completion for function calls and can generate code for adding and removing nodes in a graph.
  • 📐 The assistant can help in updating the position of nodes and edges, and even auto-generate functions based on the context.
  • 📚 Reference documents can be added to enhance the assistant's understanding and provide more accurate code suggestions.
  • 🌈 It can help in styling and theming elements, such as changing edge colors and making step edges in a graph.
  • 🔄 The iterative control feature allows users to correct mistakes made by the assistant, ensuring precision in code generation.
  • 📈 The use of AI coding assistants can help engineers uplevel their skills, focusing more on high-level logic and decision-making rather than individual lines of code.
  • 🔑 The key to utilizing AI coding assistants effectively is to enhance engineering abilities and stay relevant in a competitive job market.

Q & A

  • What is the main topic of the video script?

    -The main topic of the video script is comparing Cursor's Copilot++ with Github Copilot and demonstrating how to use AI coding assistance for tasks such as auto-completion and code generation in a coding project.

  • What is Cursor's Copilot++ and how does it differ from Github Copilot?

    -Cursor's Copilot++ is an AI coding assistant that was launched recently. It is similar to Github Copilot in providing inline auto-completion, but it is designed to be more context-aware and capable of auto-completing multiple lines without the cursor necessarily being in the position for the completion.

  • How can multiple prompts be run simultaneously in the AI coding assistant?

    -Multiple prompts can be run simultaneously by initiating different tasks or commands at the same time, as demonstrated in the script where the user runs different prompts for adding and removing nodes.

  • What is the significance of auto-completing multiple lines in AI coding assistance?

    -Auto-completing multiple lines is significant as it allows the AI to understand the broader context of the code and make more intelligent suggestions, which can greatly speed up the coding process and reduce the need for manual input.

  • What is the 'fit to view' function used for in the script?

    -The 'fit to view' function is used to automatically resize the view to fit the newly added nodes and edges in the graph, ensuring that all elements are visible without the need for manual scrolling.

  • How does the AI coding assistant handle iterative corrections in the code?

    -The AI coding assistant allows for iterative corrections by providing suggestions and auto-completions that can be accepted or modified by the user. It is designed to learn from the corrections made by the user to improve its future suggestions.

  • What is the role of the 'use view flow' library in the script?

    -The 'use view flow' library is used to create programmatically interesting graphs and charts in Vue.js. It is a tool that helps in manipulating the nodes and edges in the graph, as demonstrated in the script.

  • How can reference documents be added and utilized in the AI coding assistant?

    -Reference documents can be added through the chat interface of the AI coding assistant. Once added, they can be referenced in inline commands to guide the AI in providing accurate and context-specific code suggestions.

  • What is the importance of moving up the stack in terms of coding with AI assistants?

    -Moving up the stack in coding with AI assistants means focusing more on high-level logic and decision-making rather than individual lines of code. This approach allows developers to work more like product managers or UX engineers, leveraging AI to enhance their engineering abilities and stay relevant in the industry.

  • How does the AI coding assistant handle the creation of functions based on context?

    -The AI coding assistant can create functions based on the context of the code and the user's instructions. It uses the surrounding code and user prompts to generate the necessary function code, as shown when creating the 'create custom edge' function in the script.

  • What is the 'apply diff' functionality mentioned in the script?

    -The 'apply diff' functionality is a feature that is supposed to apply changes to the code based on the suggestions made by the AI assistant. However, in the script, it is noted that this functionality may not be working as expected and requires manual copy-pasting of the suggested code changes.

Outlines

00:00

🤖 Introduction to AI Coding Assistants

The video script introduces the capabilities of AI coding assistants, specifically focusing on Cursor, which recently launched a feature called co-pilot Plus+. The script demonstrates how AI can handle multiple coding prompts simultaneously, such as creating buttons and implementing features like auto-completion across multiple lines of code without the need for the cursor to be in the exact position. The assistant also showcases how to use Cursor's features to manipulate UI elements and improve coding efficiency.

05:03

🔄 Enhancing Productivity with AI Coding Features

This section delves into the advanced features of Cursor's AI coding assistance, emphasizing the iterative control and correction capabilities of the tool. It illustrates how to use view watchers for reactive updates and the co-pilot Plus+ feature for contextual auto-completion. The script also covers the process of adding reference documents to Cursor for inline command prompts, demonstrating how to integrate documentation into the coding process to enhance productivity and accuracy.

10:05

🌐 Building a Node Graph System with AI Assistance

The final paragraph of the script details the process of building a node graph system using AI coding assistance. It explains how to utilize Cursor's co-pilot Plus+ to auto-generate functions, create edges, and manage node IDs efficiently. The script also highlights the importance of moving up the decision-making stack in software development, focusing on high-level logic manipulation rather than individual lines of code, and emphasizes the use of AI to expedite the coding process and maintain relevance in the engineering field.

Mindmap

Keywords

💡AI coding assistant

An AI coding assistant is an artificial intelligence tool designed to assist programmers by providing code suggestions, autocompletions, and sometimes even writing code snippets. In the context of the video, the assistant is used to streamline the coding process, allowing the developer to focus on higher-level tasks. For example, the video showcases how the AI can autocomplete multiple lines of code without the need for the user's cursor to be in a specific position.

💡Cursor's Copilot++

Cursor's Copilot++ is a specific AI coding assistant mentioned in the video, which is positioned as an advanced version of the typical AI coding assistance. It is designed to be more context-aware and provide more sophisticated code completions. The video demonstrates its capabilities through various coding tasks, such as creating buttons and updating node positions in a graph.

💡Autocompletion

Autocompletion in coding refers to the feature where the AI suggests or completes code for the programmer, based on the context and common coding patterns. In the video, autocompletion is highlighted as a key feature of Cursor's Copilot++, which can autocomplete multiple lines and even entire functions, as seen when adding 'add node' and 'remove node' functionalities.

💡Vue.js

Vue.js is a popular JavaScript framework for building user interfaces and single-page applications. It is mentioned in the video as the framework the developer is using to create a graph application. Vue.js is known for its reactivity system and component-based architecture, which are utilized in the script to dynamically update the UI as nodes and edges are added or removed.

💡Graph

In the context of the video, a graph represents a structure that consists of nodes and edges, used to model relationships between data points. The video demonstrates how to create and manipulate a graph using Vue.js and an AI coding assistant, including adding nodes, removing nodes, and creating edges between them.

💡Nodes

Nodes in a graph are the individual elements or vertices that represent data points. The video script discusses adding and removing nodes, as well as updating their positions and creating edges between them. Nodes are fundamental to the structure of the graph being developed in the video.

💡Edges

Edges in a graph are the connections between nodes, representing relationships or interactions between the data points. The video shows how to label edges and change their visual style, such as making them step edges and coloring them red, to enhance the graph's readability and aesthetics.

💡Inline instructions

Inline instructions are commands or prompts given directly within the code or the development environment, which the AI coding assistant uses to generate or modify code. In the video, the developer uses inline instructions to guide the AI in tasks such as adding types to edges or updating the style of the edges.

💡Documentation

Documentation in coding refers to the written instructions or guides that explain how to use a particular library, framework, or codebase. The video demonstrates adding reference documents to the AI assistant, which it uses to understand the context and provide accurate code suggestions, such as setting up step edges and changing edge colors.

💡Apply diff

Apply diff is a term used in version control and coding to merge changes from one version of code to another. In the video, the developer mentions trying the 'apply diff' functionality of the AI assistant, which is intended to integrate suggested code changes into the existing codebase seamlessly.

💡Context awareness

Context awareness in AI coding assistants refers to the ability of the AI to understand the surrounding code and the developer's intent, in order to provide relevant suggestions. The video emphasizes Cursor's Copilot++'s advanced context awareness, as it autocompletes code in multiple places at once and makes changes based on the overall structure of the code, not just the immediate cursor position.

Highlights

Cursor's AI coding assistant, Copilot++, was recently launched and is being compared to Github Copilot.

AI coding assistance can run multiple prompts simultaneously, enhancing productivity.

Copilot++ offers inline auto-completion that is aware of more context, unlike traditional autocomplete tools.

The new feature of Cursor's Copilot++ auto-completes multiple lines without the cursor being in the exact position.

Cursor's Copilot++ is shown to be more advanced than Github Copilot by making changes wherever needed, not just in front of the cursor.

AI coding assistants are iteratively controllable, allowing for corrections of mistakes made by the AI or requested by the user.

Cursor's ability to add reference documents is highlighted as a key feature, enhancing the context understanding of the AI.

The integration of documentation with coding prompts allows for more accurate and context-aware code generation.

A demonstration of updating edges and nodes in a graph using AI coding assistance is provided.

Auto-completion of code is shown to be significantly faster and more accurate with Cursor's Copilot++.

Cursor's Copilot++ is capable of understanding and applying changes to code based on the context of the entire file.

The use of 'fit to view' functionality is shown to automatically resize and adjust the view after adding new nodes.

AI coding assistants are recommended for upleveling one's position on the stack, focusing more on high-level logic rather than individual lines of code.

The importance of using AI coding assistants to stay relevant and enhance engineering abilities in the face of industry changes is discussed.

The video concludes with a call to utilize technology like AI coding assistants to create concrete value in daily life as engineers.