How to Use GitHub Copilot to Reduce Coding Time by 50% in 2 Weeks

As indie hackers and solo founders, we often juggle multiple roles, one of which is coding. If you’re like me, you’ve felt the frustration of endless hours spent debugging or writing boilerplate code. Enter GitHub Copilot, an AI-powered coding assistant that can potentially cut your coding time in half. But does it really deliver? Here’s how you can harness its power in just two weeks.

What is GitHub Copilot?

GitHub Copilot is an AI tool that suggests code snippets and entire functions as you type, leveraging a vast dataset from public code repositories. It integrates seamlessly with popular IDEs like Visual Studio Code.

• Pricing: $10/month for individuals, $19/month for teams.
• Best for: Developers looking to speed up repetitive coding tasks.
• Limitations: It may not always understand your specific context and can generate incorrect or insecure code.
• Our take: We've found it immensely helpful for boilerplate code but still double-check suggestions.

Prerequisites: Getting Started with GitHub Copilot

Before diving in, ensure you have the following:

1. GitHub Account: You’ll need a GitHub account to use Copilot.
2. IDE Setup: Install Visual Studio Code (free) and the GitHub Copilot extension.
3. Basic Coding Knowledge: Familiarity with the programming language you’ll be working in (e.g., JavaScript, Python).

Step-by-Step Guide to Using GitHub Copilot

Step 1: Install GitHub Copilot

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

Step 2: Start Coding with Copilot

1. Create a new file and start typing a function name.
2. Observe how Copilot suggests code snippets. Use the Tab key to accept suggestions.
3. Refine the output by editing as needed.

Step 3: Explore Advanced Features

• Comments for Context: Write comments describing what you want, and Copilot will generate relevant code.
• Multi-line Suggestions: If a suggestion isn’t quite right, use the arrow keys to cycle through alternatives.

Step 4: Build a Small Project

Set a goal to build a small project (like a to-do app) in two weeks. Use Copilot for tasks like:

• Generating CRUD operations.
• Writing unit tests.
• Creating user interfaces.

Expected Outputs

At the end of two weeks, you should have a functional prototype. Track your time spent coding daily and compare it to previous projects.

Potential Challenges and Troubleshooting

• Incorrect Suggestions: Always review the code. Copilot can produce errors or insecure code.
• Learning Curve: It may take time to get used to how Copilot generates suggestions. Be patient.

What Could Go Wrong

1. Over-reliance on Suggestions: Don't let Copilot do all the thinking. Understand the code it generates.
2. Contextual Misunderstanding: If your code structure is complex, Copilot may struggle to provide relevant suggestions.

What’s Next?

Once you’re comfortable with Copilot, consider these next steps:

• Learn GitHub Actions: Automate workflows using GitHub Actions.
• Explore Other AI Tools: Look into alternatives like Tabnine or Kite for different perspectives on code completion.

Conclusion: Start Here

To truly maximize your coding efficiency, start using GitHub Copilot today. Set aside two weeks for focused practice, and you may find that your coding time is reduced by 50% or more. It’s not a magic solution, but it’s a powerful tool that, when used correctly, can significantly boost your productivity.

What We Actually Use

In our stack, we rely heavily on GitHub Copilot for initial drafts of code, especially for boilerplate and repetitive tasks. We supplement this with manual coding for complex logic to ensure quality and security.