How to Use GitHub Copilot to Debug Code in 30 Minutes

Debugging can be a real pain, especially for beginners. You're staring at lines of code, trying to figure out why something isn't working, and all you really want is a little help. That's where GitHub Copilot comes into play. In just 30 minutes, you can harness the power of this AI coding assistant to debug your code more efficiently. Let’s dive into the specifics.

Prerequisites: What You Need to Get Started

Before you can start debugging with GitHub Copilot, make sure you have the following:

1. A GitHub Account: You'll need this to access Copilot.
2. Visual Studio Code (VS Code): This is where you’ll be coding. Make sure you have it installed.
3. GitHub Copilot Subscription: As of January 2026, Copilot costs $10/month after a 60-day free trial.
4. Basic Understanding of Your Code: You should know what your code is supposed to do, even if you don’t know why it’s failing.

Step 1: Install GitHub Copilot in VS Code

1. Open Visual Studio Code.
2. Go to the Extensions view by clicking on the Extensions icon in the Activity Bar on the side or pressing Ctrl+Shift+X.
3. Search for GitHub Copilot and install the extension.
4. Once installed, sign in with your GitHub account.

Expected Output: You should see Copilot suggestions as you type.

Step 2: Identify Your Bug

Before you can fix anything, you need to know what’s broken. Here’s how to efficiently identify the bug:

1. Run your code and observe any error messages.
2. Locate the line or section of code where the error occurs.
3. Copy that line of code or write a comment describing what you believe the issue is.

Expected Output: A clear understanding of the bug location.

Step 3: Use Copilot to Suggest Fixes

Now that you’ve pinpointed the problem, it’s time to leverage Copilot:

1. Place your cursor on the line of code with the bug.
2. Type a comment like // fix this error or // why is this not working?
3. Wait for Copilot to suggest a fix. You can cycle through different suggestions using the keyboard shortcuts Ctrl+[ and Ctrl+].

Expected Output: A suggested code fix that you can review.

Step 4: Evaluate and Implement the Suggestions

Not every suggestion will be perfect. Here’s how to evaluate them:

1. Check if the suggested code logically fits your codebase.
2. Implement the suggestion by accepting it or modifying it as needed.
3. Run your code again.

Expected Output: A functional code that resolves the previous error.

Step 5: Iterate as Necessary

Sometimes, the first fix might not resolve all issues. If your code is still not working:

1. Revisit your initial identification of the bug.
2. Use Copilot again with new comments based on the updated understanding of the issue.
3. Continue to iterate until your code runs as expected.

Expected Output: A successfully running code.

Troubleshooting: What Could Go Wrong

1. Bad Suggestions: Copilot can sometimes suggest incorrect code. Always double-check.
2. Context Limitations: If your code is too complex, Copilot might not understand it fully. You may need to simplify your comments.
3. Subscription Issues: Ensure your GitHub Copilot subscription is active; otherwise, you won’t receive suggestions.

What's Next: Further Debugging and Learning

After you get comfortable with basic debugging using GitHub Copilot, consider exploring additional features:

• Refactoring suggestions: Use comments like // improve this code to get suggestions for cleaner code.
• Learning from examples: Look at Copilot's suggestions to understand better coding practices.

Conclusion: Start Debugging with GitHub Copilot

If you’re a beginner struggling with debugging, GitHub Copilot is a practical tool that can significantly speed up your process. Just remember to critically evaluate its suggestions and continue learning as you go.

What We Actually Use: For our own debugging, we rely on GitHub Copilot for quick fixes but always verify its recommendations against our understanding of the code.

Ready to streamline your debugging process? Give GitHub Copilot a try today, and see how it can help you solve coding issues in just 30 minutes.