How to Use GitHub Copilot to Speed Up Your Coding in Just 1 Hour

If you're a solo founder or indie hacker, you know that time is your most precious resource. Every minute spent coding is a minute you could be validating ideas or talking to users. That’s where GitHub Copilot comes in—a tool that can seriously speed up your coding process. But how do you actually use it effectively? In this guide, I’ll walk you through setting up and using GitHub Copilot in just one hour, while sharing some real insights from our experience.

Time Estimate: 1 Hour

You can finish this setup and learn the basics of using GitHub Copilot in about one hour.

Prerequisites

• A GitHub account (free)
• An IDE that supports GitHub Copilot (like Visual Studio Code)
• Some basic familiarity with coding (you should know the basics of the language you’re using)

Step-by-Step Guide to Setting Up GitHub Copilot

1. Sign Up for GitHub Copilot

Head over to the GitHub Copilot page and sign up. As of 2026, pricing is $10/month or $100/year. There’s a free trial available for the first 30 days, which is perfect for testing it out.

2. Install the GitHub Copilot Extension

1. Open Visual Studio Code.
2. Go to the Extensions Marketplace (Ctrl+Shift+X).
3. Search for "GitHub Copilot" and click "Install."

3. Activate GitHub Copilot

Once installed, you’ll need to log in to your GitHub account within the IDE. You’ll see a prompt to authenticate. Follow the instructions, and you’re good to go.

4. Start Coding with Copilot

Open a new file, and start writing code. For example, if you start typing a function for sorting an array, Copilot will suggest completions based on what you’re typing.

• Tip: Use comments to prompt Copilot for specific tasks. For instance, writing // function to calculate factorial will lead Copilot to suggest a function that does just that.

5. Review and Accept Suggestions

As you code, you'll see suggestions pop up. You can accept a suggestion by pressing Tab or ignore it if it doesn't fit your needs.

6. Experiment with Different Languages

Copilot supports multiple programming languages including Python, JavaScript, and Go. Don’t hesitate to switch languages and see how well it adapts to different coding styles.

7. Get Feedback

Once you've written some code, take a moment to review it. Copilot is not perfect—it can make errors or suggest suboptimal solutions. Always validate the output!

What Could Go Wrong

• Over-reliance on Suggestions: Beginners might become overly dependent on Copilot's suggestions, leading to a decline in coding skills.
• Incorrect Code: Suggestions can sometimes be incorrect or inefficient. Always test the code before deploying.

What's Next

After you’ve gotten comfortable with Copilot, consider diving deeper into its features, like using it for documentation or code refactoring. Explore community plugins that enhance its capabilities and keep an eye on updates as GitHub continues to improve Copilot.

Conclusion: Start Here

If you're looking to speed up your coding process, start with GitHub Copilot. Follow the steps outlined above, and you’ll be integrating it into your workflow in no time. Remember, it's a tool to assist you, not replace your coding skills.

Pricing Comparison Table

| Tool | Pricing | Best For | Limitations | Our Verdict | |---------------------|-----------------------|-------------------------------|-------------------------------------|------------------------------------| | GitHub Copilot | $10/mo or $100/yr | Speeding up coding | Sometimes suggests incorrect code | Great for rapid prototyping | | TabNine | Free + $12/mo pro | AI-driven code completions | Less context-aware than Copilot | Good for specific language support | | Kite | Free + $19.90/mo pro | Python and JavaScript coding | Limited language support | Useful for Python-heavy projects | | Sourcery | Free + $20/mo pro | Code quality improvements | Fewer features than Copilot | Focuses on refactoring | | Codex | $0-20/mo | General AI coding assistance | Requires more setup | Good for advanced users |

What We Actually Use

In our experience, we primarily use GitHub Copilot for quick prototyping and generating boilerplate code. We complement it with TabNine for additional language support and Kite for Python projects.