How to Use GitHub Copilot to Complete a Project in 2 Hours

If you’re a solo founder or an indie hacker, you know that time is of the essence. You want to ship products fast, but coding can feel like a never-ending journey. Enter GitHub Copilot, a tool that promises to help you code faster and smarter. In this guide, we’ll show you how to use GitHub Copilot to complete a project in just 2 hours. Spoiler alert: it’s not magic, but with the right approach, you can make it work for you.

Prerequisites: What You Need to Get Started

Before diving in, you’ll need a few essentials:

1. GitHub Account: You need this to access Copilot.
2. Visual Studio Code (VS Code): The IDE where Copilot works best.
3. GitHub Copilot Subscription: As of 2026, it costs $10/month after a free trial.
4. A Project Idea: Have a small project in mind, like a simple web app or a script.

Step-by-Step: Using GitHub Copilot to Ship Your Project

Step 1: Set Up Your Environment (30 minutes)

1. Install VS Code: Download and install Visual Studio Code.
2. Install GitHub Copilot: Go to the extensions marketplace in VS Code and install the GitHub Copilot extension.
3. Sign In: Authenticate your GitHub account to enable Copilot.

Step 2: Start Coding (1 hour)

1. Create Your Project: Open a new folder in VS Code and create a new file (e.g., app.js for a Node.js project).
2. Write Your First Function: Start typing a function name. For instance, if you're building a simple calculator, you might start with function add(a, b) {.
3. Let Copilot Suggest: As you type, Copilot will suggest code. Accept suggestions by pressing Tab. If it doesn’t fit, try typing a bit more context.
4. Iterate: Continue this process for all the functions you need. For instance, function subtract(a, b) {, function multiply(a, b) {, etc.
5. Test Your Code: Run your code frequently to catch any issues early.

Step 3: Final Touches (30 minutes)

1. Add Comments: Use comments to explain complex parts of your code. Copilot can help generate comments too.
2. Debugging: Use the built-in debugging tools in VS Code to troubleshoot any errors.
3. Documentation: Consider generating a simple README file for your project, which Copilot can also assist with.

Troubleshooting: What Could Go Wrong

• Inaccurate Suggestions: Sometimes Copilot’s suggestions can be off. Always double-check critical logic.
• Learning Curve: If you're not familiar with the coding language, Copilot might confuse you with its suggestions. Spend a bit of time learning the basics first.

What's Next: Moving Forward After Your Project

Once you've completed your first project with Copilot, consider:

1. Iterating: Add more features based on user feedback.
2. Exploring More Tools: Look into other AI coding tools to see how they compare. For example, tools like Tabnine or Kite may offer different benefits.
3. Building a Portfolio: Use your completed projects to showcase your skills to potential clients or investors.

Tool Comparison: GitHub Copilot vs. Other AI Coding Tools

| Tool Name | Pricing | Best For | Limitations | Our Verdict | |----------------|------------------------|------------------------------|-----------------------------------|--------------------------------| | GitHub Copilot | $10/mo, free trial | Fast coding assistance | Not always accurate | Great for quick prototyping | | Tabnine | Free, Pro at $12/mo | AI-assisted coding | Limited language support | Good for multi-language setups | | Kite | Free, Pro at $19.90/mo| Python-focused development | Limited IDE support | Best for Python developers | | Codex | $0.002 per request | Complex code generation | Pricing can add up | Best for large projects | | Sourcery | Free, Pro at $12/mo | Python code reviews | Limited to Python | Great for improving code quality |

Conclusion: Start Here

To leverage GitHub Copilot effectively and complete your project in 2 hours, follow the outlined steps, stay focused, and don’t hesitate to iterate based on feedback. While it’s a powerful tool, remember that it works best when you have a solid understanding of what you want to build.

What we actually use? We rely heavily on GitHub Copilot for rapid prototyping, but we also keep Tabnine in our toolkit for multi-language support.