How to Use GitHub Copilot to Write 10x More Code in Just 1 Hour

As indie hackers and solo founders, we all know that time is our most valuable resource. When it comes to coding, the last thing you want is to spend hours on repetitive tasks or struggling with syntax. Enter GitHub Copilot, an AI-powered coding assistant that can help you crank out code faster than ever. In this guide, I’ll show you how to leverage GitHub Copilot effectively to boost your coding efficiency and get more done in less time.

What is GitHub Copilot?

GitHub Copilot is an AI coding assistant developed by GitHub and OpenAI. It suggests code snippets and entire functions as you type, effectively acting like a pair of virtual hands that can help you write code more efficiently. It’s particularly useful for repetitive tasks, boilerplate code, and even debugging.

Pricing Breakdown

• Free for Individual Use: Limited features, suitable for casual coding.
• $10/month for Personal Plan: Full access to features with priority support.
• $19/month for Business Plan: Advanced features for teams, including security and compliance tools.

Best For

• Solo developers looking to speed up their workflow.
• Indie hackers who need to maximize productivity.
• Teams wanting to maintain coding standards while encouraging collaboration.

Limitations

• May struggle with complex logic or less common programming languages.
• Suggestions might not always follow best practices, requiring human oversight.
• Limited in understanding project context unless it’s explicitly stated.

In our experience, we’ve found Copilot to be a great tool for speeding up coding tasks, but we always double-check the suggestions it provides.

Getting Started: Prerequisites

Before diving into using GitHub Copilot, make sure you have:

1. A GitHub account (Free).
2. Visual Studio Code installed (Free).
3. The GitHub Copilot extension installed in VS Code (Free trial available).

Step-by-Step: Using GitHub Copilot Effectively

1. Set Up Your Environment

1. Install Visual Studio Code from here.
2. Install the GitHub Copilot extension from the VS Code marketplace.
3. Sign in to your GitHub account to activate the extension.

2. Create a New Project

• Start a new project or open an existing one in VS Code.
• Make sure you have a clear idea of what you want to build.

3. Write Comments to Guide Copilot

• Use comments to describe what you want to achieve. For example:

  // Function to calculate the factorial of a number
  

• Copilot will suggest code based on your comment.

4. Accept and Modify Suggestions

• As you type, accept Copilot’s suggestions by pressing Tab.
• If the suggestion isn’t quite right, modify it as needed.

5. Test and Iterate

• Run your code regularly to ensure it works as expected.
• Use Copilot for testing suggestions, for instance:

  // Test case for factorial function
  

6. Review and Refactor

• After completing your code, review it for best practices and refactor as necessary.
• Copilot can assist in refactoring by suggesting improvements.

Expected Outputs

By the end of this hour-long session, you should have a significant portion of your project coded, with Copilot having handled repetitive tasks and boilerplate code.

Troubleshooting Common Issues

• Suggestion Quality: If the suggestions are off, try providing clearer comments or instructions.
• Code Context: Ensure that the code you’re writing has enough context for Copilot to provide relevant suggestions.
• Language Support: If you're coding in a niche language, Copilot may not be as effective. Stick to mainstream languages for better results.

What’s Next?

Once you’ve mastered using GitHub Copilot, consider exploring other AI tools that can enhance your coding experience. Tools like TabNine and Kite offer additional features and integrations that can complement Copilot.

Conclusion: Start Here

GitHub Copilot can be a game-changer for indie hackers and solo developers looking to increase their coding efficiency. By following the steps outlined above, you can quickly harness the power of AI to write code faster, allowing you to focus more on building your product.

If you’re looking to dive deeper into the world of AI coding tools, check out our podcast, Built This Week, where we discuss tools we’re testing and lessons learned from building in public.