How to Use GitHub Copilot to Accelerate Your Coding Projects in 30 Minutes

If you’re a solo founder or indie hacker, you know the struggle of juggling multiple projects while trying to write code efficiently. Enter GitHub Copilot, an AI-powered coding assistant that promises to speed up your development process. But does it really deliver? In this article, I’ll show you how to get started with GitHub Copilot in just 30 minutes, sharing tips from our own experience along the way.

Time Estimate: 30 Minutes

You can set up GitHub Copilot and start using it effectively in about 30 minutes.

Prerequisites

Before diving in, make sure you have:

• A GitHub account (Free or Pro)
• Visual Studio Code (VS Code) installed
• GitHub Copilot subscription: $10/month or $100/year
• Basic understanding of JavaScript, Python, or any programming language of your choice

Step-by-Step Setup

1. Install GitHub Copilot in VS Code

• Open Visual Studio Code.
• Go to the Extensions view by clicking on the Extensions icon in the Activity Bar.
• Search for "GitHub Copilot" and click "Install."

Expected Output: You should see a Copilot icon in the bottom right corner of your VS Code window once installed.

2. Sign In to GitHub

• Click on the Copilot icon and sign in with your GitHub account.

Expected Output: A prompt indicating successful authentication.

3. Start Coding

• Create a new file and set the language (e.g., .js for JavaScript).
• Begin typing a comment describing what you want to do. For example, // Function to calculate factorial.

Expected Output: GitHub Copilot will suggest a function based on your comment. Accept the suggestion by pressing Tab or continue typing to refine it.

4. Use Inline Suggestions

• As you write, Copilot will provide inline suggestions. Use the arrow keys to navigate between suggestions.

Expected Output: You should see multiple code completions as you type.

5. Experiment with Different Prompts

• Don’t hesitate to change your comments or prompts to see how Copilot adapts. Try asking for different algorithms or functions.

Expected Output: Copilot will generate various code snippets based on your prompts.

6. Review and Test the Code

• Always review the code generated by Copilot. While it’s good, it’s not perfect.
• Run tests to ensure the code behaves as expected.

Expected Output: Your code should run smoothly if Copilot's suggestions were accurate.

Troubleshooting Common Issues

• Issue: Copilot doesn’t suggest anything.

  • Solution: Make sure your file is saved and the correct language is set.

• Issue: Suggestions are irrelevant.

  • Solution: Refine your comments or prompts for better context.

What's Next?

Now that you’ve got the basics down, consider integrating GitHub Copilot into your regular workflow. Use it for rapid prototyping, generating boilerplate code, or even learning new programming languages by observing how it suggests code based on your comments.

Conclusion: Start Here

If you’re looking to speed up your coding projects, GitHub Copilot is worth considering. With a quick setup and the right prompts, you can significantly enhance your productivity. Just remember to review the generated code and keep experimenting with different use cases.

What We Actually Use

In our experience, we use GitHub Copilot primarily for generating boilerplate code and testing out new libraries. It has saved us hours of manual coding, but we also rely on manual coding for critical components to ensure quality.