How to Use GitHub Copilot to Reduce Your Coding Time by 50%

As a solo founder or indie hacker, time is your most precious resource. You probably find yourself coding late into the night, trying to ship your next big feature or fix that bug that just won't go away. What if I told you that you could cut your coding time by 50% using GitHub Copilot? Sounds too good to be true? Let’s break it down and see how it actually works.

What is GitHub Copilot?

GitHub Copilot is an AI-powered coding assistant that suggests entire lines or blocks of code based on what you’re currently writing. It’s like having a pair of extra hands that can help you code faster. But it’s not just about speed; it also helps you learn better coding practices by suggesting idiomatic solutions.

Pricing Breakdown

• Free Tier: Limited access with basic suggestions
• Pro Plan: $10/month for full access
• Business Plan: $19/month per user for team collaboration features

Best for: Developers who want to speed up their coding without sacrificing quality.

Limitations: Sometimes the suggestions can be off-base, requiring you to double-check its output. It can also struggle with very niche libraries or frameworks.

Getting Started: Prerequisites

Before diving into GitHub Copilot, here’s what you need:

1. GitHub Account: Free to create.
2. Visual Studio Code: Download and install if you haven’t already.
3. GitHub Copilot Extension: Install the Copilot extension in VS Code.

This setup should take you about 30 minutes.

Step-by-Step Guide to Using GitHub Copilot

1. Install the Extension: Open Visual Studio Code, go to the Extensions Marketplace, and search for "GitHub Copilot". Hit install.

2. Sign In: Once installed, sign in with your GitHub account to activate the extension.

3. Start Coding: Begin typing your code. For example, if you type function fetchData(), Copilot might suggest the entire function body.

4. Accepting Suggestions: If you like a suggestion, hit Tab to accept it. If not, continue typing, and it will adjust its suggestions.

5. Iterate and Refine: Use the suggestions as a base, but don’t hesitate to modify them to fit your specific needs.

Expected Outputs

You should start seeing a significant reduction in the time it takes to write boilerplate code or common functions. In our experience, we’ve been able to complete tasks that previously took an hour in about 30 minutes.

Troubleshooting: What Could Go Wrong

• Inaccurate Suggestions: Sometimes the suggestions can be completely off. Always review the code before implementing it.

• Over-reliance on AI: It’s easy to let Copilot do too much of the heavy lifting, which can hinder your learning. Balance is key.

What's Next?

After you get comfortable with Copilot, consider integrating it with other tools like Prettier for code formatting and ESLint for linting. This combination can help maintain code quality while you speed up your workflow.

Tools for Comparison

While GitHub Copilot is a solid choice, you might also consider other AI coding assistants. Here’s a quick comparison of some alternatives:

| Tool Name | Pricing | Best For | Limitations | Our Verdict | |-------------------|-----------------------------|-------------------------------|--------------------------------------|-------------------------------| | GitHub Copilot | $10/mo for Pro | General coding assistance | Sometimes off-base suggestions | Great for quick coding boosts | | Tabnine | Free + $12/mo for Pro | Code completion | Limited to certain languages | Good for specific languages | | Codeium | Free | Collaborative coding | Lacks advanced features | Great for team projects | | Replit | Free + $7/mo for Pro | Online coding environment | Limited offline capabilities | Best for quick prototypes | | Sourcery | Free + $12/mo for Pro | Code quality improvements | Limited language support | Use alongside Copilot |

Conclusion

If you want to significantly reduce your coding time, GitHub Copilot is a tool worth trying. Start by integrating it into your daily coding routine and see how much faster you can get things done. Just remember to keep an eye on the suggestions and modify them as needed.

What We Actually Use

In our stack, we primarily use GitHub Copilot for rapid prototyping and writing boilerplate code. We occasionally mix in Tabnine when working with niche languages. Overall, GitHub Copilot remains our go-to for enhancing productivity.