5 Common Mistakes New Users Make with GitHub Copilot

As a tool that promises to streamline coding and assist developers, GitHub Copilot has quickly become a go-to for many. However, as with any new tool, beginners often stumble into common pitfalls that can hinder their productivity. After using GitHub Copilot extensively, I've seen firsthand the mistakes that can waste time and lead to frustration. Let's dive into five of the most common mistakes new users make with GitHub Copilot in 2026, and how to avoid them.

1. Ignoring the AI's Limitations

What It Actually Does

GitHub Copilot is an AI-powered coding assistant that anticipates your next lines of code based on the context provided. It can generate code snippets, comments, and even entire functions.

Pricing

• Free trial available
• $10/month for individual users
• $19/month for business users

Limitations

While Copilot is powerful, it can produce incorrect or insecure code. It doesn't understand the context of your entire project, and its suggestions can sometimes be nonsensical or overly complex.

Our Take

We use Copilot to speed up repetitive tasks, but we always double-check its output. Relying solely on it without understanding the code can lead to security vulnerabilities or bugs.

2. Over-Relying on Copilot for Learning

What It Actually Does

Copilot can suggest code snippets and explanations, which is great for learning new syntax or libraries.

Limitations

However, it can lead to a lack of understanding of fundamental concepts. If you rely solely on Copilot, you may miss out on learning opportunities.

Our Take

We recommend using Copilot as a supplemental tool while learning. Pair it with resources like online courses or documentation to deepen your understanding.

3. Lack of Context in Code Comments

What It Actually Does

Copilot generates comments based on your code, which can save time.

Limitations

If your comments are unclear, Copilot might generate suggestions that don’t fit your intent. This can lead to a mismatch between your expectations and the generated code.

Our Take

Always provide clear context in comments. It helps Copilot generate more relevant suggestions. If you see irrelevant code, consider rewriting your comments for clarity.

4. Not Customizing Settings and Preferences

What It Actually Does

Copilot has several settings that can be customized to better fit your workflow.

Limitations

Many users stick to default settings, which may not align with their coding style or project needs.

Our Take

Spend some time customizing Copilot's settings. Adjusting the context length or the types of suggestions can significantly improve its usefulness for your specific projects.

5. Forgetting to Review and Test Generated Code

What It Actually Does

Copilot can generate entire functions, which can save time during development.

Limitations

However, generated code often requires thorough testing. Failing to do so can lead to bugs and unexpected behavior in your applications.

Our Take

Always review and test any code generated by Copilot. Incorporating unit tests and code reviews into your workflow will help catch errors early.

Conclusion: Start Here

To get the most out of GitHub Copilot, avoid these common mistakes by understanding its limitations, using it as a learning tool, providing clear context, customizing your settings, and thoroughly reviewing generated code. By adopting these practices, you can enhance your coding experience and utilize Copilot effectively.

What We Actually Use

In our experience, we use GitHub Copilot primarily for writing boilerplate code and exploring new libraries. While it accelerates our workflow, we make sure to review and test everything it generates.