Ai Coding Tools

How to Use GitHub Copilot to Write and Debug Code in 1 Hour

By BTW Team4 min read

How to Use GitHub Copilot to Write and Debug Code in 1 Hour

As a solo founder or indie hacker, time is often your most precious resource. You want to write code quickly and efficiently, but debugging can be a time-consuming hassle. Enter GitHub Copilot, an AI-powered coding assistant that can help you write and debug code faster than ever. In this guide, I'll walk you through how to get started with GitHub Copilot in just one hour, including practical tips and real-world insights from my own experience.

Prerequisites: What You Need

Before diving in, make sure you have:

  1. A GitHub Account: Free or paid, but you'll need an account to use GitHub Copilot.
  2. Visual Studio Code (VSCode): This is the IDE where you'll integrate GitHub Copilot.
  3. GitHub Copilot Subscription: As of April 2026, GitHub Copilot is priced at $10/month for individual developers.
  4. Basic Coding Knowledge: Familiarity with at least one programming language (like JavaScript, Python, or Ruby) will help you make the most of the tool.

Step 1: Setting Up GitHub Copilot

  1. Install Visual Studio Code: Download and install VSCode if you haven't already.
  2. Install the GitHub Copilot Extension:
    • Open VSCode.
    • Go to Extensions (Ctrl+Shift+X).
    • Search for "GitHub Copilot" and click "Install".
  3. Sign In to GitHub: After installation, you will be prompted to sign in to your GitHub account. Follow the instructions to authorize the extension.

Expected Output: You should see a Copilot icon in the bottom right corner of your VSCode window, indicating that it’s active.

Step 2: Writing Code with Copilot

Now that you have GitHub Copilot set up, let’s start writing code.

  1. Create a New File: Open a new file in your preferred programming language.
  2. Start Typing a Function: Begin by typing a comment or a function name. For example, type // Function to add two numbers and then press Enter.
  3. Accept Suggestions: GitHub Copilot will provide suggestions in a faded text format. You can accept a suggestion by pressing Tab.

Example:

// Function to add two numbers
function add(a, b) {
    return a + b;
}

Step 3: Debugging with Copilot

Debugging can be tedious, but Copilot can assist here too.

  1. Introduce an Error: Intentionally introduce a bug in your code to see how Copilot reacts. For example, change return a + b; to return a + c;.
  2. Run Your Code: Execute your code to see the error message.
  3. Ask Copilot for Help: Highlight the error line and type a comment like // Fix this error. Copilot will attempt to suggest a fix.

Troubleshooting Tips:

  • If Copilot doesn’t suggest a fix, try rephrasing your comment or providing more context.
  • Remember that Copilot learns from your coding habits, so the more you use it, the better it gets.

Step 4: Best Practices for Using Copilot

  1. Be Specific: The more context you provide, the better the suggestions. Use comments to guide Copilot.
  2. Review Suggestions Carefully: Always double-check the code Copilot generates. It can sometimes produce incorrect or suboptimal code.
  3. Use It for Repetitive Tasks: Copilot excels at generating boilerplate code. Use it for tasks like setting up API calls or writing tests.

Limitations of GitHub Copilot

While GitHub Copilot is a powerful tool, it does have limitations:

  • Contextual Understanding: It may not fully grasp the context of your project, leading to irrelevant suggestions.
  • Learning Curve: It requires some time to get used to its workflow.
  • Not a Replacement for Debugging Skills: It’s a tool to assist, not replace your own debugging process.

What We Actually Use

In our experience, we rely on GitHub Copilot primarily for generating boilerplate code and speeding up our development process. However, we don't rely solely on it for complex logic or critical functions, as it can sometimes miss the nuances of our specific use cases.

Conclusion: Start Here

Ready to give GitHub Copilot a shot? Set aside an hour, follow the steps outlined above, and start experimenting with code writing and debugging. It might just become your new coding companion.

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