How to Use GitHub Copilot to Improve Your Coding Speed in One Week

As developers, we all know that time is money. The faster we can write code, the more projects we can tackle and the quicker we can deliver value. Enter GitHub Copilot, an AI-powered coding assistant designed to help you write code faster and with fewer errors. But can it really improve your coding speed in just one week? Spoiler alert: yes, if you know how to leverage it effectively.

Prerequisites: What You Need Before You Start

To get the most out of GitHub Copilot, you’ll need:

• A GitHub account: Sign up at GitHub if you don’t have one.
• Visual Studio Code: GitHub Copilot integrates seamlessly with VS Code. Download it here.
• GitHub Copilot subscription: Pricing is $10/month or $100/year as of July 2026, with a 60-day free trial available.

Step 1: Set Up GitHub Copilot

1. Install the GitHub Copilot extension: Open VS Code, go to the Extensions view, and search for "GitHub Copilot." Click "Install."
2. Sign in with GitHub: After installation, you’ll be prompted to sign in to your GitHub account.
3. Enable Copilot: Once logged in, you’ll need to enable Copilot in your settings. Go to File > Preferences > Settings, search for "Copilot," and ensure it's enabled.

Expected Output: You should see Copilot suggestions appear as you type code.

Step 2: Understand How to Use Copilot Effectively

Learn the Shortcuts

Copilot offers several keyboard shortcuts to optimize your workflow:

• Tab: Accept a suggestion.
• Esc: Dismiss a suggestion.
• Ctrl + Enter: Trigger more suggestions.
• Arrow keys: Browse through suggestions.

In our experience, getting comfortable with these shortcuts can save you a lot of time.

Write Descriptive Comments

One of the best ways to get useful suggestions from Copilot is to write clear, descriptive comments about what you want. For example:

// Function to calculate the factorial of a number
function factorial(num) {
    // Copilot will suggest the implementation
}

Expected Output: Copilot will generate a function to calculate the factorial based on your comment.

Step 3: Practice Daily Coding with Copilot

Set aside at least 30 minutes each day for a week to work on small projects or coding exercises using Copilot. This is crucial for building familiarity with its capabilities.

Suggested Practice Projects

1. Build a simple CRUD app: Use Copilot to generate the API endpoints and basic UI.
2. Algorithm challenges: Take on coding challenges on platforms like LeetCode or HackerRank and see how Copilot assists you.

Expected Output: You should notice a significant reduction in the time it takes to write code and debug.

Step 4: Review and Optimize the Generated Code

While Copilot can save you time, it’s not perfect. Always review the generated code for quality and security. Make sure you understand what it’s suggesting and that it meets your project requirements.

Common Limitations

• Context understanding: Copilot may not fully understand complex project contexts.
• Security risks: Generated code might introduce vulnerabilities if not reviewed carefully.
• Learning curve: It takes time to learn how to communicate effectively with Copilot.

Our take: We often use Copilot for boilerplate code but still review everything for potential issues.

Step 5: Measure Your Speed and Efficiency

At the end of the week, compare your coding speed and project completion times to your baseline.

Metrics to Track

• Lines of code written per hour: Measure how many lines of code you can produce with and without Copilot.
• Project completion time: Track how long it takes to finish small projects.

Expected Output: You should see an improvement in both metrics.

Conclusion: Start Here to Boost Your Coding Speed

If you want to improve your coding speed, GitHub Copilot can be a valuable tool when used correctly. Set it up, practice daily, and always review the code it generates. After a week of focused use, you’ll likely see a noticeable boost in your efficiency.

What We Actually Use: We rely on GitHub Copilot for quick prototypes and boilerplate code, but we always double-check its output to ensure quality.