Ai Coding Tools

How to Use GitHub Copilot to Write a Feature in Under 30 Minutes

By BTW Team4 min read

How to Use GitHub Copilot to Write a Feature in Under 30 Minutes

If you’re a solo founder or indie hacker, you know the struggle of balancing feature development with everything else on your plate. Often, the thought of coding can be overwhelming, especially when you’re trying to ship something quickly. Enter GitHub Copilot, an AI-powered coding assistant that can drastically speed up your development process. In this guide, I’ll walk you through how to use GitHub Copilot to write a feature in under 30 minutes, sharing real experiences and practical tips along the way.

Time Estimate and Prerequisites

You can finish this in about 30 minutes if you have the following ready:

  • GitHub Account: You’ll need an active GitHub account to use Copilot.
  • Visual Studio Code (VS Code): Download and install VS Code if you haven't already.
  • GitHub Copilot Subscription: As of April 2026, Copilot costs $10/month for individuals, with a free trial available.
  • Basic Understanding of JavaScript/Python: You should know the basics of the programming language you’ll be using.

Step-by-Step Guide to Writing a Feature

Step 1: Set Up Your Environment

  1. Open VS Code: Launch Visual Studio Code.
  2. Install GitHub Copilot: Go to the Extensions Marketplace (Ctrl+Shift+X) and search for "GitHub Copilot". Click "Install".

Step 2: Create a New File

  1. New JavaScript File: Create a new .js file for your feature.
  2. Define the Feature: Start by typing a comment describing the feature you want to build. For example:
    // Create a function that generates a random user profile
    

Step 3: Let Copilot Work Its Magic

  1. Trigger Copilot: After typing the comment, wait a second, and you should see suggestions from Copilot. If you don’t, hit Ctrl + Enter to manually trigger it.
  2. Review Suggestions: Copilot will suggest code snippets. Review them carefully and select the one that fits your needs.

Step 4: Test the Feature

  1. Run Your Code: Make sure your feature works as expected by running it in your local development environment.
  2. Debugging: If something doesn’t work, Copilot can help. Type a comment like // Fix the error and see what suggestions it offers.

Step 5: Refine and Finalize

  1. Optimize Your Code: After getting the basic functionality, ask Copilot for improvements. For example:
    // Optimize the random user profile function
    
  2. Add Comments and Documentation: Good documentation is crucial. Ask Copilot to help you generate comments for your code.

Expected Outputs

By the end of this process, you should have a fully functional feature with minimal manual coding. Expect to see something like this:

function generateRandomUserProfile() {
    const names = ["Alice", "Bob", "Charlie"];
    const randomName = names[Math.floor(Math.random() * names.length)];
    return { name: randomName, age: Math.floor(Math.random() * 50) + 20 };
}

Troubleshooting: What Could Go Wrong

  1. No Suggestions from Copilot: Ensure you’re logged in and that the extension is active.
  2. Inaccurate Code: Always review suggestions critically; AI isn’t perfect.
  3. Performance Issues: If Copilot is slow, check your internet connection.

What's Next?

Once you’ve built your feature, consider integrating it into your larger project. You can also explore other AI tools to enhance your coding efficiency. If you’re looking for alternatives to GitHub Copilot, tools like Tabnine or Codeium might be worth exploring.

Conclusion: Start Here

If you’re looking to speed up your development process and reduce the time spent coding, GitHub Copilot is a powerful tool that can help you ship features quickly. Start by setting up your environment and following the steps outlined above. In our experience, you can realistically write a feature in under 30 minutes with Copilot’s assistance.

What We Actually Use

For our projects, we primarily use GitHub Copilot for rapid prototyping and initial feature development. We find it particularly helpful for generating boilerplate code, but always double-check its suggestions for accuracy.

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