Ai Coding Tools

How to Use GitHub Copilot for Efficient Pair Programming in 1 Hour

By BTW Team3 min read

How to Use GitHub Copilot for Efficient Pair Programming in 2026

Pair programming is one of those practices that can either catapult your coding efficiency or turn into a frustrating experience. In 2026, tools like GitHub Copilot have revolutionized how we approach coding together, making it easier to collaborate and innovate. But how do you leverage Copilot effectively to enhance your pair programming sessions? In this guide, I’ll walk you through how to do just that in about an hour.

Prerequisites for Using GitHub Copilot

Before diving in, here’s what you need:

  • GitHub Account: Sign up for a free account if you don’t have one.
  • Visual Studio Code: Install this code editor if you haven’t already.
  • GitHub Copilot Subscription: Pricing starts at $10/month for individuals. There’s a free trial available for new users.
  • Basic Understanding of Git: Familiarity with Git and GitHub will help you navigate your projects more smoothly.

Step-by-Step Setup for Pair Programming with GitHub Copilot

Step 1: Install GitHub Copilot

  1. Open Visual Studio Code.
  2. Go to Extensions (Ctrl+Shift+X).
  3. Search for "GitHub Copilot" and click "Install".
  4. Sign in with your GitHub account when prompted.

Step 2: Create a New Repository

  1. In GitHub, create a new repository for your pair programming session.
  2. Clone the repository to your local machine using Git.
  3. Open the project folder in Visual Studio Code.

Step 3: Start Pair Programming

  1. Invite your pair programming partner to the repository.
  2. Set up a live share session (you'll need the Live Share extension).
  3. Begin coding together, using GitHub Copilot to suggest code snippets.

Step 4: Use Copilot Effectively

  • Contextual Suggestions: Copilot provides context-aware suggestions based on what you’re typing. For example, if you start writing a function, Copilot can suggest the full implementation.
  • Iterate on Suggestions: Don’t just accept the first suggestion; iterate on it. You can accept, reject, or modify suggestions to fit your needs.
  • Comment-Driven Development: Write comments in natural language about what you want to achieve, and let Copilot generate the code for you.

Step 5: Review and Test Code Together

  1. After implementing code, review it together.
  2. Use Git to commit changes and push them to GitHub.
  3. Test the code collaboratively, ensuring it meets your requirements.

Expected Outputs

By the end of this session, you should have:

  • A functional piece of software developed collaboratively.
  • Enhanced understanding of how to utilize GitHub Copilot.
  • A repository with committed changes reflecting your pair programming efforts.

Troubleshooting Common Issues

  • Copilot Not Suggesting Code: Make sure you’re connected to the internet and that you’ve signed in to your GitHub account.
  • Slow Suggestions: Sometimes, the suggestions can be laggy. Restart Visual Studio Code if this happens.
  • Conflicting Suggestions: If you and your partner receive different suggestions, discuss which option fits best for your project.

What's Next?

Now that you've successfully used GitHub Copilot for pair programming, consider these next steps:

  • Explore advanced features of GitHub Copilot, such as working with different programming languages.
  • Try using Copilot in different collaborative setups, like remote pair programming.
  • Share your experience with the community; feedback can lead to better practices.

Conclusion

Using GitHub Copilot for pair programming can significantly streamline your workflow and enhance collaboration. Start by setting it up as outlined, and soon you’ll find yourself coding more efficiently with your partner. Remember, it’s not just about accepting suggestions but leveraging them to create a better final product.

What We Actually Use

In our experience, we find GitHub Copilot invaluable for quick prototyping and generating boilerplate code. However, we still rely on manual coding for complex logic to ensure quality control.

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