GitHub Copilot for coding help

What is GitHub Copilot?

GitHub Copilot is an AI coding assistant that suggests code as you type. It works directly inside your code editor (like Visual Studio Code) and provides line-by-line suggestions, entire functions, and even explanations of complex code.

Copilot is built by GitHub and OpenAI, using the same technology behind ChatGPT. It was trained on billions of lines of public code, so it understands programming patterns across many languages.

What does GitHub Copilot do?

Code suggestions: As you type, Copilot suggests the next line or block of code. Press Tab to accept a suggestion or keep typing to ignore it.

Function generation: Describe what you want in a comment, and Copilot can generate an entire function based on your description.

AI prompt in comment: // Function that takes a list of numbers and returns the median value

Copilot will suggest a complete function that calculates the median.

Code explanations: Copilot can explain what existing code does, which is helpful when working with unfamiliar codebases.

Test generation: Copilot can help write unit tests for your functions, saving time on boilerplate testing code.

Language support: Works with dozens of programming languages including Python, JavaScript, TypeScript, Ruby, Go, Java, C++, and more.

How to use GitHub Copilot

1. Install Visual Studio Code (or another supported editor like JetBrains IDEs, Neovim, etc.)
2. Sign up for GitHub Copilot at GitHub Copilot
3. Install the Copilot extension in your code editor
4. Start coding and Copilot will automatically suggest code as you type

GitHub Copilot pricing

Free for students, teachers, and open-source maintainers: If you're a verified student or teacher, or maintain popular open-source projects, Copilot is free.

Copilot Individual ($10/month): For individual developers. Includes code suggestions, chat interface, and support for multiple languages and editors.

Copilot Business ($19/user/month): For teams and organizations. Adds admin controls, policy management, and organization-wide licensing.

Check your eligibility and sign up at GitHub Copilot.

What GitHub Copilot is good at

Boilerplate code: Writing repetitive code like API endpoints, data models, or configuration files. Copilot excels at patterns it has seen many times.

Common algorithms: Sorting, searching, data manipulation, and other standard programming tasks. Copilot often generates correct implementations quickly.

Autocompleting patterns: If you start a function or loop, Copilot can predict what you're trying to do and complete it.

Learning new frameworks: When working with unfamiliar libraries, Copilot suggests syntax and patterns, acting like a reference guide.

What GitHub Copilot struggles with

Novel or complex logic: If your task is unique or requires deep reasoning, Copilot may suggest incorrect or incomplete code.

Security-sensitive code: Copilot might suggest code with security vulnerabilities. Always review suggestions carefully, especially for authentication, data validation, or encryption.

Project-specific context: Copilot doesn't deeply understand your entire codebase, so it might suggest code that doesn't fit your project's architecture or conventions.

Bugs in suggestions: Copilot can suggest code that looks correct but contains subtle bugs. Always test and review.

Using Copilot effectively

Write descriptive comments: Copilot works best when you describe what you want in plain language comments before writing code.

Review every suggestion: Don't blindly accept Copilot's suggestions. Read the code, understand what it does, and make sure it fits your needs.

Iterate: If the first suggestion isn't right, keep typing or rephrase your comment to guide Copilot in a different direction.

Combine with testing: Write tests for code that Copilot generates. This catches errors and ensures the code works as expected.

Use Copilot Chat: The chat interface lets you ask Copilot questions about your code, request refactoring, or get explanations without leaving your editor.

GitHub Copilot vs chatbots

Both GitHub Copilot and chatbots like ChatGPT can help with coding, but they serve different purposes:

GitHub Copilot works inline as you code. It's fast, context-aware within your file, and integrates directly into your editor.

Chatbots are better for brainstorming, debugging complex issues, learning concepts, or rewriting large blocks of code. You copy and paste code to and from the chatbot.

Use Copilot when: You're actively coding and want quick inline suggestions.

Use a chatbot when: You need to understand a concept, debug a tricky issue, or redesign an approach.

Many developers use both: Copilot for day-to-day coding and a chatbot for higher-level problem-solving.

Ethical and legal considerations

Code licensing: Copilot was trained on public code, including open-source projects. There's ongoing debate about whether Copilot's suggestions might inadvertently replicate copyrighted code. GitHub says Copilot rarely suggests code that matches its training data exactly, but it's something to be aware of.

Code ownership: You own the code you write with Copilot's help, but review GitHub's terms of service for details.

Privacy: Copilot sends your code to GitHub's servers for processing. Avoid using it with highly confidential or proprietary code unless your organization has reviewed and approved it.

Related resources

Want to explore other coding assistants? See Other AI coding assistants. Looking for general AI help? Check out Which chatbot should I use?.