How to Use GitHub Copilot to Improve Your Coding Speed in 1 Hour

If you’re like most indie hackers or solo founders, you’re always looking for ways to boost productivity and get more done in less time. Enter GitHub Copilot—an AI-powered code assistant that promises to help you write code faster. But does it really deliver, or is it just another tool that sounds good on Twitter? In this guide, we’ll explore how to effectively use GitHub Copilot to improve your coding speed in just one hour, along with some honest insights from our own experiences.

Prerequisites: What You Need Before Getting Started

Before you dive in, make sure you have the following:

• GitHub Account: Create a free account if you don’t already have one.
• Visual Studio Code (VS Code): Download and install it if you haven’t already.
• GitHub Copilot Subscription: As of April 2026, it costs $10/month or $100/year. There’s a free trial available for 30 days.

Step 1: Installing GitHub Copilot

To start using GitHub Copilot, follow these steps:

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

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

Step 2: Writing Code with Copilot

Now that you have Copilot set up, let’s get coding. Here’s how to effectively leverage its features:

1. Start Typing: Begin by typing a comment or a function name. For example, type // Function to calculate the factorial of a number.
2. Accept Suggestions: Copilot will automatically suggest code. Press Tab to accept the suggestion or keep typing for more options.
3. Iterate: If you don’t like the first suggestion, keep typing, and Copilot will offer alternatives.

Expected Output: You should see Copilot generating relevant code snippets in real-time, which can significantly speed up the writing process.

Step 3: Fine-Tuning Suggestions

While Copilot is pretty smart, it’s not perfect. Here’s how to get the best results:

• Be Specific: The more specific your comments or function names, the better the suggestions.
• Review and Edit: Always review the generated code to ensure it meets your needs. Copilot can sometimes produce incorrect or inefficient code.

Expected Output: You’ll notice a reduction in the time spent writing boilerplate code or common algorithms.

Step 4: Troubleshooting Common Issues

While using Copilot, you might encounter some hiccups. Here’s how to troubleshoot:

• Suggestion Quality: If suggestions aren’t relevant, try rephrasing your comments.
• Connection Issues: Ensure you’re connected to the internet, as Copilot requires real-time access to function.

Expected Output: By addressing these issues quickly, you can maintain your coding flow without significant interruptions.

Step 5: What’s Next? Expand Your Toolset

Once you’re comfortable with Copilot, consider exploring other AI coding tools to complement your workflow. Here are some alternatives:

| Tool Name | Pricing | Best For | Limitations | Our Take | |---------------------|-----------------------|------------------------------------|----------------------------------|----------------------------------| | Tabnine | $12/mo, free tier | Autocompletion for various languages | Limited context understanding | We use it for quick suggestions. | | Codeium | Free, Pro at $19/mo | Team collaboration | Lacks advanced features | We don’t use it; not robust enough. | | Replit | Free, $20/mo Pro | Collaborative coding | Performance issues with large projects | We use it for quick prototyping. | | Sourcery | Free, $15/mo Premium | Code quality improvement | Limited language support | We don’t use it; too niche for our needs. | | AI21 Studio | $0-40/mo | Generating text-based code | Costly for heavy usage | We don’t use it; pricing is high. |

Conclusion: Start Here to Boost Your Coding Speed

In just one hour, you can set up GitHub Copilot and start using it to improve your coding speed. Remember to be specific with your prompts and review the AI’s suggestions to ensure quality. If you find Copilot helpful, consider integrating it with other tools listed above to further enhance your workflow.

What We Actually Use: We primarily rely on GitHub Copilot for everyday coding tasks and supplement it with Tabnine for additional autocomplete suggestions. This combination has worked well for us as we build and ship products.