How to Use GitHub Copilot for Improved Code Quality in 30 Minutes

As a solo founder or indie hacker, you’re often wearing multiple hats. Writing quality code can be time-consuming and sometimes frustrating. Enter GitHub Copilot, an AI-powered coding assistant that aims to streamline your development process. But is it really worth the hype? I’ve spent some time testing it out, and I’m here to share how you can improve your code quality using GitHub Copilot in just 30 minutes.

Prerequisites: What You Need to Get Started

Before diving in, make sure you have the following:

1. GitHub Account: You’ll need this to access GitHub Copilot.
2. Visual Studio Code: Copilot works best within this IDE.
3. GitHub Copilot Subscription: As of February 2026, it costs $10/month after a free trial.
4. Basic Programming Knowledge: You should be familiar with the language you’re working in.

Step 1: Setting Up GitHub Copilot

1. Install Visual Studio Code: Download and install it from here.
2. Add GitHub Copilot Extension:
   • Open VS Code.
   • Go to Extensions (Ctrl+Shift+X).
   • Search for "GitHub Copilot" and click Install.
3. Sign In to GitHub: Once installed, sign in to your GitHub account to enable Copilot.

Expected output: You should see a small Copilot icon in the bottom right of your VS Code window, indicating it's active.

Step 2: Writing Your First Function

Let’s write a simple function to illustrate Copilot's capabilities. For example, create a function that calculates the factorial of a number.

1. Type the function name and a brief comment:

   // Function to calculate factorial
   function factorial(n) {
   

Expected output: GitHub Copilot will suggest code completions. Accept the suggestion by pressing Tab.

Step 3: Improving Code Quality with Suggestions

1. Add More Comments: As you write, use comments to guide Copilot. For instance:

   // Check if n is less than 0
   // If so, return undefined
   

Expected output: Copilot might suggest a conditional statement to handle this case.

2. Refactor Suggestions: If you want to improve performance, you can ask Copilot to suggest optimizations. For example:

   // Can you refactor this for better performance?
   

Expected output: Copilot will provide alternative code snippets that may offer better performance.

Step 4: Testing Your Code

1. Write Tests: After writing your function, it’s crucial to test it. Create a test file:

   // Test cases for factorial function
   console.assert(factorial(5) === 120, "Test Case 1 Failed");
   console.assert(factorial(0) === 1, "Test Case 2 Failed");
   

Expected output: Run your tests to ensure everything works as expected. You can also ask Copilot to generate test cases for you.

Troubleshooting: What Could Go Wrong

• Inaccurate Suggestions: Sometimes Copilot might suggest incorrect code. Always review and test the output.
• Limited Context: If your code is too complex, Copilot may struggle to provide relevant suggestions. Simplify your comments or break down your functions.

What’s Next: Leveling Up Your Coding Game

Now that you've seen how to integrate GitHub Copilot into your workflow, consider exploring other AI coding tools like Tabnine or Codeium. They may offer different suggestions or work better for specific programming languages.

Conclusion: Start Here for Better Code Quality

If you're looking to improve your coding efficiency and quality, GitHub Copilot is an excellent starting point. With just 30 minutes of setup and practice, you can leverage AI to enhance your coding experience and produce cleaner, more efficient code.

What We Actually Use

In our experience, we use GitHub Copilot for rapid prototyping and code suggestions, but we always double-check the output for accuracy. If you need more advanced features, consider trying out other AI tools alongside Copilot.