How to use GitHub Copilot Enterprise | full demo

The video provides a comprehensive guide on utilizing GitHub Copilot Enterprise for developers. It showcases how to leverage AI assistance when starting a new project or job, especially when faced with unfamiliar programming languages or project structures. The presenter demonstrates using GitHub Copilot to ask generic and repository-specific questions, explaining how to index a repository for tailored assistance. The script also covers local development practices, including cloning a repository, using GitHub CLI, and editing files in VS Code with GitHub Copilot installed. It illustrates how to enhance a project, such as adding a location input to a form, and creating a dropdown selector, all while emphasizing the importance of testing and reviewing code. The guide concludes with a discussion on creating descriptive pull requests with GitHub Copilot, encouraging developers to remain in control and responsible for their code.

Takeaways

• 🤖 GitHub Copilot can act as an AI pair programmer, assisting developers with coding tasks and answering specific questions about a project's codebase.
• 🔍 Before asking specific questions about a repository, you need to index it through GitHub Copilot to ensure the AI has a clear understanding of the project's context.
• 📚 The AI can provide explanations for code snippets and guide developers on how to modify or extend the functionality of their code.
• 🌐 GitHub Copilot can generate answers to general programming questions, such as how to shorten a URL, without needing a specific repository context.
• 📂 The AI can assist with local development by helping to clone repositories to a developer's local machine and guide them through the files and structure.
• 💻 Developers can use GitHub CLI to clone repositories and open them in their preferred code editors, such as Visual Studio Code.
• 🧩 GitHub Copilot chat can explain the functionality of code on the screen and provide insights into how the code works, including conditional rendering.
• 📝 When modifying code, GitHub Copilot can suggest specific changes and provide code snippets to implement new features, such as adding a location input to a form.
• 🔄 It's important for developers to add new properties to their model classes when introducing new features, and GitHub Copilot can guide them through this process.
• 📝 Committing changes and creating descriptive, informative pull requests is a crucial part of the development process, and GitHub Copilot can assist in generating summaries for these requests.
• 👨‍💼 While GitHub Copilot is a powerful tool, developers remain in control and are responsible for the code they ship. It's important to review the AI's suggestions and consult with senior developers when in doubt.

Q & A

What is the primary use case for GitHub Copilot as described in the transcript?

The primary use case for GitHub Copilot, as described, is to assist developers in writing code, understanding project structures, and getting up to speed with new programming languages or projects, especially when other developers are not available for consultation.

How does GitHub Copilot help with generic coding questions?

GitHub Copilot can answer generic coding questions by providing information and code snippets. For example, it can explain how to shorten a URL and even provide links to websites that can accomplish this task.

What is the process of using GitHub Copilot for specific repository-related queries?

To use GitHub Copilot for specific repository-related queries, you need to index the repository first. After indexing, which may take a few minutes, you can ask questions directly related to the repository's code base and structure.

How does GitHub Copilot assist with local development?

GitHub Copilot assists with local development by allowing you to clone the repository to your local machine using GitHub CLI or other methods. Once cloned, you can open it in your preferred code editor, like VS Code, where GitHub Copilot is installed and can provide real-time assistance and code explanations.

What is the role of GitHub Copilot in explaining code functionality within a project?

GitHub Copilot can explain the functionality of the code by analyzing the code on the screen and providing a breakdown of how it works, including references to specific files and components. It can also suggest changes and improvements to the code.

How does GitHub Copilot help in modifying and adding new features to an application?

GitHub Copilot assists in modifying and adding new features by generating code snippets for the required changes, explaining the code's purpose, and guiding the developer on where and how to integrate the new code into the existing code base.

What is the significance of indexing a repository before asking specific questions about it?

Indexing a repository allows GitHub Copilot to understand the context and specifics of the repository's code. This enables it to provide more accurate and relevant answers to questions about the code base, its structure, and how to interact with or modify it.

How does GitHub Copilot facilitate the process of creating a pull request on GitHub?

GitHub Copilot can create a descriptive and informative summary of the changes made in a pull request. It analyzes the differences between the files, identifies what has been added or modified, and generates a summary that can be used to create a more detailed and clear pull request.

What are the steps to clone a repository from GitHub using the GitHub CLI?

To clone a repository using the GitHub CLI, you open a terminal with administrator privileges, ensure GitHub CLI is installed by running `gh`, navigate to the directory where you want to store your repositories, and then use the command `gh repo clone /` to clone the desired repository.

How does GitHub Copilot assist with adding a new input field to a form in a web application?

GitHub Copilot can guide you through adding a new input field by suggesting the necessary HTML and potentially backend code. It provides an explanation of how to integrate the new input within the existing form structure and how to bind it to the application's data model.

What is the importance of testing code before committing and pushing changes to a repository?

Testing code before committing and pushing changes ensures that the modifications work as intended and do not introduce bugs or conflicts. It is a critical step in maintaining code quality and project stability, and it helps in identifying issues early in the development process.

Outlines

00:00

🤖 Introducing GitHub Copilot for New Developers

This paragraph introduces GitHub Copilot as an AI pair programmer that assists developers, especially when they are new to a project or programming language. It discusses a scenario where a developer might not have colleagues to ask for help or might be unfamiliar with the project's structure or programming language. The speaker demonstrates how to use GitHub Copilot to ask generic questions and get answers, as well as how to index a specific repository for more tailored assistance. The process of indexing the 'PetSpotR' repository is shown, and the speaker explores how to ask specific questions about the repository's functionality and structure.

05:01

🧐 Enhancing the PetSpotR App with GitHub Copilot

The speaker continues by discussing how to enhance the PetSpotR application using GitHub Copilot. They explain the app's functionality, which involves users reporting lost pets and others using AI image matching to identify found pets. The focus then shifts to improving the app's form for reporting lost pets by adding a location input field and expanding the selection of pet types. GitHub Copilot is shown to provide code suggestions, explanations, and guidance on implementing these changes. The speaker emphasizes the importance of understanding the code and making informed decisions when using AI-generated code snippets.

10:01

🛠️ Committing Changes with GitHub Copilot and Desktop

The final paragraph covers the process of committing changes to the codebase using GitHub Copilot and GitHub Desktop. After making changes and ensuring they are tested, the speaker demonstrates how to save files and create a new branch for the changes. They then show how to commit the changes with a descriptive message, push the branch to GitHub, and create a pull request. A new feature of GitHub Copilot is introduced, which automatically generates a descriptive summary for the pull request based on the changes made. The speaker highlights the importance of reviewing the code and seeking help from senior developers when needed, emphasizing that the developer is always in control and responsible for the final code.

Keywords

GitHub Copilot

GitHub Copilot is an AI-powered programming assistant that helps developers write code, understand existing codebases, and solve programming problems. In the video, it is portrayed as an AI pair programmer that assists in various tasks such as shortening URLs, explaining code, and generating code snippets for specific functionalities. It is used to demonstrate how it can aid a developer in understanding a new project and making necessary code changes.

Repository

A repository in the context of the video refers to a project location where the complete codebase, along with version control, is stored. The PetSpotR repository mentioned is a project that aims to help locate lost pets using an app with AI image matching. It is the central place where developers collaborate and manage the code for the project.

Indexing

Indexing, as used in the video, is the process by which GitHub Copilot prepares a repository to understand its content better. This allows the AI to provide more accurate and specific assistance related to the codebase. The script mentions that the PetSpotR repository needs to be indexed to enable GitHub Copilot to answer questions about the project's specific code.

Code Snippets

Code snippets are small, reusable pieces of code that can be quickly inserted into a larger program. In the video, GitHub Copilot provides code snippets to the user to help implement new features, such as adding a location input to a form. These snippets are examples of how GitHub Copilot assists in writing and understanding code.

Blazor

Blazor is a web framework developed by Microsoft that allows developers to build interactive web applications using C# and .NET. In the video, the PetSpotR app is mentioned to be running in Blazor, and GitHub Copilot helps explain and modify the Blazor components, particularly a form for reporting a lost pet.

Model Class

A model class in object-oriented programming is a blueprint for creating objects. It defines the structure of the data and the operations that can be performed on it. In the video, the pet model class is discussed, where GitHub Copilot guides the user on how to add a new property to this class to accommodate location data for the PetSpotR app.

Pull Request

A pull request is a feature in version control systems that allows developers to propose changes to a project's codebase. It is a way to notify project maintainers about the modifications made and to initiate a discussion about these changes. In the video, the user creates a pull request for the changes made to the PetSpotR app using GitHub Copilot to generate a descriptive summary of the changes.

Commit

Committing in version control systems is the act of saving changes to a local repository. It is a snapshot of the code at a particular point in time. The video demonstrates how the user commits changes to the local machine before pushing them to a remote repository and creating a pull request.

GitHub CLI

GitHub CLI, or Command Line Interface, is a tool that allows users to work with GitHub repositories directly from the terminal. In the video, the user utilizes GitHub CLI to clone the PetSpotR repository to their local machine, showcasing one of the ways developers can interact with GitHub repositories.

VS Code

VS Code, or Visual Studio Code, is a popular source-code editor developed by Microsoft. It is used for debugging, task running, and version control. In the video, VS Code is the editor of choice for the user to open and work on the PetSpotR repository's code.

AI Image Matching

AI image matching is a technology that uses artificial intelligence to analyze and compare images to find similarities or matches. In the context of the PetSpotR app, it is used to match photos of found pets with those submitted by people who have lost pets, aiding in reuniting lost pets with their owners.

Highlights

GitHub Copilot can assist developers who are new to a project or programming language.

AI can provide answers to generic coding questions, such as how to shorten a URL.

To get specific assistance, a repository must be indexed by GitHub Copilot, which may take a few minutes.

GitHub Copilot offers an immersive view with topics and popular repositories for more tailored questions.

It can generate code snippets and explanations for specific tasks, like creating a token for an API call.

Once a repository is indexed, developers can ask detailed questions about the project's codebase.

GitHub CLI can be used to clone repositories to a local machine for further work.

Visual Studio Code with GitHub Copilot extension can explain code on the screen and suggest improvements.

GitHub Copilot can guide through adding new features, such as a location input to a form.

It provides not just code, but also an explanation of what the code does and how it integrates with the existing codebase.

Developers can get suggestions on how to implement changes, like turning an input field into a dropdown selector.

GitHub Copilot can assist in modifying model classes and suggest where to add new properties.

It considers the context of open files to provide more accurate and relevant suggestions.

GitHub Copilot can help create more descriptive and informative pull requests with a summary of changes.

The tool encourages developers to remain in control and to always review the code before shipping.

GitHub Copilot serves as an AI pair programmer, helping to unblock developers and enhance their productivity.

It's important for developers to understand that they are still responsible for the final code quality.

GitHub Copilot can be a valuable tool for developers to accelerate their workflow and solve problems more efficiently.