5 Common Mistakes New Users Make with GitHub Copilot

As a solo founder or indie hacker, diving into AI tools like GitHub Copilot can feel like a game-changer. But let’s be real: it’s easy to trip over your own feet when you’re just getting started. In 2026, with Copilot being more accessible than ever, I’ve seen plenty of new users make the same mistakes. Here’s a rundown of the five common pitfalls you should avoid to make the most of this powerful coding assistant.

Mistake #1: Ignoring Context

What It Is:

New users often forget that Copilot thrives on context. If you provide vague comments or incomplete function signatures, you’ll get back suggestions that may not fit your needs.

Why It Matters:

Copilot generates code based on the context you provide. Without clear, descriptive comments and complete function definitions, you might end up with code that’s not useful or relevant.

Our Take:

We’ve learned to be explicit with our comments and code structure. When we took the time to describe what a function should do, the suggestions were significantly better.

Mistake #2: Over-Reliance on Suggestions

What It Is:

Many beginners treat Copilot like a magic wand, expecting it to write perfect code without any input or review on their part.

Why It Matters:

While Copilot is powerful, it’s not infallible. Blindly accepting its suggestions can lead to bugs and security vulnerabilities in your code.

Our Take:

We always review the suggestions before accepting them. It’s crucial to understand what the code is doing, especially for critical sections of your application.

Mistake #3: Not Customizing Settings

What It Is:

New users often stick with the default settings and configurations of GitHub Copilot, missing out on features that could enhance their experience.

Why It Matters:

Copilot offers customization options that can help tailor its suggestions to your coding style and preferences.

Our Take:

We’ve adjusted our settings to better match our coding standards, including disabling certain languages we don’t use. It’s saved us time and improved the relevance of suggestions.

Mistake #4: Neglecting Documentation

What It Is:

Many beginners dive straight into coding with Copilot without taking the time to read the documentation or tutorials available.

Why It Matters:

Understanding how Copilot works and its limitations can help you use it more effectively and avoid common mistakes.

Our Take:

We recommend spending a little time with the official GitHub Copilot documentation. It’s full of valuable tips that can help you get up to speed quickly.

Mistake #5: Forgetting About Privacy and Security

What It Is:

Some users overlook the potential privacy and security implications of using an AI tool that generates code based on public repositories.

Why It Matters:

Using Copilot can inadvertently lead to incorporating insecure or outdated code if you’re not careful about what you accept.

Our Take:

We’ve made it a practice to run security audits on the code that Copilot generates, especially for critical applications. It’s an essential step that shouldn’t be skipped.

Conclusion: Start Here

To get the most out of GitHub Copilot in 2026, start by improving your context, avoid blind acceptance of suggestions, customize your settings, read the documentation, and prioritize security. By steering clear of these common mistakes, you’ll be well on your way to integrating AI coding tools into your workflow effectively.

If you're interested in diving deeper into AI tools for coding, check out our podcast, Built This Week, where we share practical insights on tools we’re using and lessons learned along the way.