How to Efficiently Use GitHub Copilot to Boost Your Coding Speed in 2 Hours

If you're a solo founder or indie hacker like me, you know that time is your most precious resource. Every minute spent writing boilerplate code is a minute you could be validating your product or talking to customers. Enter GitHub Copilot, an AI-powered coding assistant that promises to help you code faster. But does it really deliver? After diving into it for a couple of hours, I found some practical ways to leverage Copilot effectively. Here's how you can boost your coding speed with GitHub Copilot in just two hours.

Prerequisites: What You'll Need

Before we dive into the setup, make sure you have:

1. A GitHub Account: You’ll need this to access Copilot.
2. Visual Studio Code (VS Code): Copilot works seamlessly with this editor.
3. GitHub Copilot Subscription: As of August 2026, pricing is $10/month or $100/year. There’s a free trial for 60 days, which is great for testing.
4. Basic Knowledge of Coding: Familiarity with your programming language of choice (like JavaScript, Python, etc.).

Step 1: Installing GitHub Copilot

1. Open Visual Studio Code.
2. Go to the Extensions view by clicking on the Extensions icon in the Activity Bar or pressing Ctrl+Shift+X.
3. Search for "GitHub Copilot" and click Install.
4. Once installed, sign in to your GitHub account when prompted.

Expected Output: You should see a Copilot icon in the bottom right corner of your VS Code window, indicating that it’s active.

Step 2: Configuring Settings for Optimal Use

To make Copilot work for you, tweak the settings:

1. Go to Settings (File > Preferences > Settings).
2. Search for "Copilot" and adjust the following:
   • Enable Suggestions: Ensure this is turned on.
   • Inline Suggestions: Enable it for real-time assistance.
   • Suggestion Delay: Set it to 0.5 seconds for quicker responses.

Expected Output: You’ll start seeing suggestions as you type.

Step 3: Learning How to Ask for Help

Copilot thrives on context. Here’s how to effectively prompt it:

• Commenting: Write a comment describing what you want. For example, // function to calculate Fibonacci numbers.
• Partial Code: Start writing a function, and let Copilot complete it based on your input.

Expected Output: Copilot should generate relevant code snippets based on your comments or partial code.

Step 4: Reviewing and Modifying Suggestions

Not every suggestion will be perfect, and that’s okay. Here’s how to handle them:

1. Evaluate the Code: Make sure you understand the generated code. Don’t just copy-paste.
2. Refine and Adjust: Modify the code as needed to fit your project requirements.

Expected Output: You’ll find that Copilot can save you time, but it’s essential to maintain code quality.

Troubleshooting Common Issues

1. No Suggestions: If Copilot isn’t suggesting anything, check that you’re connected to the internet and that your subscription is active.
2. Irrelevant Suggestions: If the suggestions are off, try writing more context in your comments or refining your initial code.

Our Take: Copilot is not perfect, but it can reduce your coding time by up to 30% once you get the hang of it.

What's Next: Building on Your New Skills

Once you’re comfortable with Copilot, consider the following:

• Integrate Other Tools: Use it alongside other AI tools like ChatGPT for brainstorming or documentation.
• Explore More Features: Check out additional VS Code extensions that complement Copilot, like Prettier for code formatting.

Conclusion: Start Here

To truly leverage GitHub Copilot, spend your first two hours getting it set up and learning how to communicate effectively with it. By doing so, you’ll be able to focus on building your product instead of getting bogged down by repetitive coding tasks. Remember, the key to success with Copilot is not just using it but using it wisely.

What We Actually Use: In our experience, we use GitHub Copilot primarily for generating boilerplate code and function templates, which saves us considerable time during our development cycles.