How to Use GitHub Copilot for Faster Code Reviews in Under 30 Minutes

If you're a solo founder or indie hacker, you're probably juggling multiple roles—developer, marketer, and sometimes even project manager. Code reviews can be a time-consuming process, often taking hours when they should be a quick check. Enter GitHub Copilot, an AI-powered coding assistant that can help streamline your code review process. In this guide, I'll show you how to leverage GitHub Copilot effectively to speed up your code reviews, all in under 30 minutes.

Prerequisites

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

• GitHub Account: You need to be signed up on GitHub.
• Visual Studio Code: Install the latest version of VS Code as it integrates seamlessly with Copilot.
• GitHub Copilot Subscription: The pricing is $10/month per user or $100/year, which is pretty reasonable for the time savings it offers.

Step 1: Setting Up GitHub Copilot

1. Install GitHub Copilot: Go to the Extensions view in VS Code (Ctrl+Shift+X), search for "GitHub Copilot," and click "Install."
2. Sign In: After installation, sign in with your GitHub account to activate the extension.
3. Enable Suggestions: Ensure that Copilot is enabled in your editor settings. You can do this by navigating to Settings (Ctrl+,) and searching for "Copilot."

Expected Output: You should see Copilot suggestions pop up as you type in your code editor.

Step 2: Reviewing Code with Copilot

1. Open Your Pull Request: Navigate to the pull request you want to review on GitHub.
2. Clone Locally: Clone the repository to your local machine if you haven't already.
3. Use Copilot for Suggestions: As you review the code, start typing comments or suggestions. For example, you can type // Suggest improvements followed by your request. Copilot will provide suggestions based on the context.

Expected Output: Copilot will generate relevant code snippets or improvements that you can directly insert into your review comments.

Step 3: Automating Common Review Tasks

1. Common Patterns: If you notice repetitive patterns in the code, you can ask Copilot to generate a summary comment. For instance, you could type // Summarize this function and see what it produces.
2. Refactoring Suggestions: If you find a block of code that could be refactored, simply type // Refactor this and let Copilot generate a cleaner version.

Expected Output: A streamlined version of the code or a summary that highlights the function's purpose.

Troubleshooting Common Issues

• Limited Context: Sometimes Copilot might not fully understand the context. If it suggests something irrelevant, don't hesitate to rephrase your request.
• Incomplete Suggestions: If you notice that suggestions are incomplete, ensure your code comments are clear and direct. Copilot works best with specific prompts.

What's Next

Once you’ve wrapped up your code review using GitHub Copilot, consider the following actions:

• Implement Suggestions: Merge the pull request if everything looks good or implement the suggestions directly into the codebase.
• Feedback Loop: Give feedback on Copilot’s suggestions to improve its accuracy over time.
• Explore Other Tools: If Copilot doesn't meet your needs, consider alternatives like Tabnine or Kite, which also provide AI-based code suggestions.

Conclusion

GitHub Copilot can significantly reduce the time you spend on code reviews, allowing you to focus on building your project. In my experience, combining Copilot with clear prompts has made our code reviews faster and more efficient. Start by setting up Copilot today, and you’ll likely find yourself saving hours each week.

What We Actually Use

For code reviews, we primarily use GitHub Copilot. While it’s not perfect, it saves us time and helps maintain code quality. If Copilot isn’t cutting it for you, consider checking out Tabnine for different suggestions.