How to Use GitHub Copilot to Increase Your Coding Efficiency in Just 2 Hours

If you're a solo founder or side project builder, you know that time is your most precious resource. Spending hours on repetitive coding tasks can be frustrating, especially when you could be focusing on building features that actually delight users. Enter GitHub Copilot—an AI-powered coding assistant that promises to boost your coding efficiency. But does it really deliver? After spending a couple of hours getting acquainted with it, I can share practical insights on how to effectively use GitHub Copilot to streamline your coding process.

What is GitHub Copilot?

GitHub Copilot is an AI-driven tool that suggests code snippets and entire functions based on context. Think of it as a pair programmer that helps you write code faster. It integrates seamlessly with popular code editors, allowing you to generate code without leaving your workflow.

• Pricing: $10/month or $100/year (as of June 2026)
• Best for: Developers looking to speed up coding tasks, especially in languages like JavaScript, Python, and TypeScript.
• Limitations: It may not always generate optimal or secure code, so you need to review its suggestions carefully.

Prerequisites: What You'll Need

Before diving in, make sure you have:

1. A GitHub account (free to create).
2. Visual Studio Code or another supported code editor.
3. GitHub Copilot installed as an extension.

Step-by-Step Guide to Get Started with GitHub Copilot

Step 1: Install and Set Up GitHub Copilot

1. Go to the Extensions section in Visual Studio Code.
2. Search for "GitHub Copilot" and click Install.
3. Sign in with your GitHub account when prompted.

Step 2: Familiarize Yourself with the Interface

After installation, open a new file and start typing a comment that describes what you want to code. For example, type // Function to calculate the factorial of a number.

Step 3: Accept Code Suggestions

Copilot will automatically suggest code snippets. Use the Tab key to accept a suggestion. If it doesn't fit your needs, you can cycle through alternatives by pressing Ctrl + ] or Ctrl + [.

Step 4: Experiment with Different Prompts

The more context you provide, the better Copilot’s suggestions will be. Try writing comments or starting a function, and see how it adapts to different scenarios.

Step 5: Review and Refine the Code

Always review the code generated by Copilot. While it can save you time, it may not be perfect or secure. Make necessary adjustments and validate the logic.

Expected Outputs

By the end of this process, you should have a better understanding of how to use GitHub Copilot effectively. Expect to see reduced coding time and improved productivity, especially for common tasks.

Troubleshooting: What Could Go Wrong

1. Inaccurate Suggestions: If Copilot suggests something that doesn’t make sense, try to rephrase your comment or provide more context.
2. Performance Issues: If you notice lag, ensure your internet connection is stable since Copilot relies on cloud processing.

What's Next?

Once you're comfortable with Copilot, consider exploring other AI tools that can complement your coding experience. For example, tools like Tabnine and Kite can provide additional coding suggestions and insights.

Conclusion: Start Here

If you’re looking to enhance your coding efficiency, GitHub Copilot is a practical choice that can save you time and effort. Spend a couple of hours getting familiar with it, and you'll likely find that it transforms the way you code.

What We Actually Use

In our experience at Ryz Labs, we use GitHub Copilot primarily for writing boilerplate code and handling repetitive tasks. It helps us maintain momentum in our projects without getting bogged down in details.