Why GitHub Copilot is Overrated: Mistakes Developers Make

In 2026, GitHub Copilot remains a hot topic in the development community, and while it has its merits, I can't help but feel that it’s overrated. Many developers jump into using Copilot without fully understanding its limitations, leading to mistakes that can cost time and quality in their projects. Here’s a rundown of what we’ve observed and learned from our experiences.

Common Mistakes Developers Make with GitHub Copilot

1. Relying Too Heavily on Suggestions

Many developers treat Copilot as a crutch instead of a tool. It’s easy to get lazy and accept its suggestions without questioning them. This can lead to sub-optimal code that lacks a developer's unique touch or understanding of best practices.

Our take: We use Copilot for boilerplate code but always review and refactor suggestions.

2. Ignoring Context

Copilot generates suggestions based on the code context, but it doesn’t understand project-level goals or architecture. Relying on it without providing sufficient context can result in code that doesn’t align with your project’s needs.

Our take: We’ve learned to provide comments that outline what we want to achieve, which helps in getting better suggestions.

3. Skipping Code Reviews

Just because Copilot suggests code doesn’t mean it’s bug-free. Some developers skip code reviews when using Copilot, assuming the AI is infallible. This can introduce bugs and security vulnerabilities.

Our take: Code reviews are non-negotiable in our workflow, regardless of whether we used Copilot or not.

4. Overlooking Documentation

Copilot can generate code snippets quickly, but it doesn’t replace the need for understanding the libraries and frameworks you’re using. Developers often forget to read the documentation, leading to misused functions or features.

Our take: We always cross-reference generated code with documentation to ensure proper usage.

5. Misunderstanding Licensing

Since Copilot is trained on publicly available code, it raises concerns about code ownership and licensing. Developers often overlook these aspects, which can lead to legal issues down the line.

Our take: We’re careful to verify code snippets against our licensing requirements before using them.

Tools That Complement or Compete with GitHub Copilot

If you’re looking for alternatives or tools that can work alongside Copilot, here’s a breakdown of some options:

| Tool | Pricing | Best for | Limitations | Our Verdict | |---------------------|-----------------------------|----------------------------|------------------------------------------|-------------------------------------| | Tabnine | Free tier + $12/mo pro | Autocompletion | Limited language support | We use it for JavaScript projects. | | Codeium | Free | AI-powered code suggestions| Less accurate than Copilot | We don’t use it because of accuracy.| | Kite | Free + $19.90/mo pro | Python development | Limited to Python | We use it for Python only. | | Sourcery | Free + $12/mo pro | Code quality improvement | Not a full IDE integration | We use it for code reviews. | | Replit | Free + $20/mo pro | Collaborative coding | Performance issues on large projects | We don’t use it for big projects. | | Codex | $0-200/month | Custom AI solutions | Requires setup, not beginner-friendly | We haven’t explored this yet. | | IntelliCode | $0-19.99/mo | C# and .NET development | Limited to Visual Studio | We don’t use it as we prefer VS Code.| | OpenAI API | Pay-as-you-go | Custom AI applications | Costs can add up quickly | We use it for specific projects. | | DeepCode | Free + $19/mo pro | Static code analysis | Doesn’t integrate with all languages | We don’t use it due to integration issues.| | Sourcegraph | Free tier + $50/mo | Code search and navigation | Can be overwhelming for small projects | We use it for larger codebases. |

What We Actually Use

In our stack, we primarily rely on GitHub Copilot for boilerplate and repetitive tasks, but we supplement it with Tabnine for JavaScript and Sourcery for Python code quality checks. This combination helps us avoid the pitfalls of over-reliance on any single tool.

Conclusion: Start Here

If you're considering using GitHub Copilot, approach it with caution. Use it as a supportive tool, not a replacement for your coding skills. Always question its suggestions, keep up with documentation, and maintain a rigorous code review process. For those looking for alternatives, try Tabnine or Sourcery based on your specific needs.