Ai Coding Tools

How to Use GitHub Copilot to Improve Your Coding Speed by 50%

By BTW Team3 min read

How to Use GitHub Copilot to Improve Your Coding Speed by 50%

As indie hackers and solo founders, we often face the challenge of maximizing our productivity while juggling multiple projects. Coding can be time-consuming, and any tool that promises to boost our efficiency is worth exploring. In 2026, GitHub Copilot stands out as a game-changer for developers looking to improve their coding speed by up to 50%. But how do you actually use it effectively? Let's break it down.

What is GitHub Copilot?

GitHub Copilot is an AI-powered coding assistant developed by GitHub and OpenAI that suggests code snippets in real-time as you type. It’s like having a pair of extra hands that can help you write boilerplate code, solve common problems, and even generate functions based on comments.

Pricing:

  • Free tier for individuals
  • $10/month for Pro version
  • $19/month for Teams

Best for: Developers looking to speed up routine coding tasks.

Limitations: It may struggle with complex logic or domain-specific languages and can sometimes suggest insecure code patterns.

Our take: We use GitHub Copilot for prototyping and writing repetitive code quickly, but we still review suggestions carefully to ensure quality.

Getting Started: Prerequisites

Before you dive in, make sure you have the following:

  • A GitHub account (free)
  • Visual Studio Code (free)
  • GitHub Copilot extension installed (free for individuals, paid for teams)

Step-by-Step Guide to Using GitHub Copilot

1. Install GitHub Copilot

  1. Open Visual Studio Code.
  2. Go to Extensions (Ctrl+Shift+X).
  3. Search for "GitHub Copilot."
  4. Click "Install."
  5. Log in with your GitHub account.

2. Write Comments for Context

GitHub Copilot works best when you provide context. Start by writing a comment that describes what you want to do. For example:

// Function to calculate factorial

3. Accept or Modify Suggestions

As you type, Copilot will suggest code snippets. You can accept a suggestion by pressing Tab. If it’s not quite right, you can modify it or ask for a different suggestion.

4. Experiment with Different Languages

Copilot supports multiple programming languages like JavaScript, Python, TypeScript, and more. Experiment with it in different contexts to see where it shines.

5. Review Security and Performance

Always review the code suggested by Copilot for security vulnerabilities and performance issues. It’s a great assistant, but it’s not perfect.

6. Use it for Testing and Documentation

Copilot can also help you write tests and documentation. Use comments to describe what the tests should cover, and let Copilot generate the code.

Expected Output: You’ll notice a significant drop in the time spent on boilerplate code and routine tasks, potentially improving your speed by 50%.

What Could Go Wrong?

  • Over-reliance: Don't depend solely on Copilot. It can suggest insecure or inefficient code.
  • Context loss: If you switch contexts frequently, Copilot may not provide relevant suggestions.
  • Misunderstanding: Sometimes, it might misinterpret your comment, leading to incorrect code.

Troubleshooting Tips

  • If you’re not getting useful suggestions, try to provide clearer comments.
  • Regularly update your Visual Studio Code and Copilot extension to benefit from improvements.

What's Next?

Once you’re comfortable with GitHub Copilot, consider integrating it into your workflow more deeply. Explore its use in collaborative coding sessions with team members or try combining it with other tools like code linters and formatters for an even smoother experience.

Conclusion: Start Here

To kick off your journey with GitHub Copilot, follow the steps outlined above. Remember, it’s not just about speeding up your coding but also about enhancing your overall development workflow. By leveraging Copilot effectively, you can indeed improve your coding speed—perhaps even by 50%.

What We Actually Use

In our own projects, we’ve found GitHub Copilot invaluable for generating boilerplate code and writing tests quickly. However, we still prefer manual coding for critical components to ensure quality and security.

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