What Is GitHub Copilot? The AI Pair Programmer Explained — Features, Pricing, and How It Compares to Cursor and Claude Code

What Is GitHub Copilot?

GitHub Copilot is an AI coding assistant developed by GitHub (a Microsoft subsidiary) in collaboration with OpenAI. It integrates directly into a developer’s editor to provide inline code completions, a natural-language chat panel, an autonomous agent that can edit multiple files from a single prompt, automated pull-request reviews, and shell-command suggestions in the terminal.

Think of GitHub Copilot as a pair programmer sitting next to you. When you start writing a function, Copilot offers the rest in grey text. When you type a code comment describing what you want, Copilot drafts the implementation. When you ask “write unit tests for this function,” Copilot generates them. Originally launched as a technical preview in June 2021 and generally available in June 2022, Copilot has since grown from a single autocomplete tool into a full product family — completion, chat, agent, review, CLI — with multi-model support.

How to Pronounce GitHub Copilot

How GitHub Copilot Works

GitHub Copilot is delivered as a cloud service with editor extensions (VS Code, JetBrains, Visual Studio, Xcode, Neovim, and more). The extension collects contextual signals — the file you’re editing, surrounding files, cursor position, recent edits, repository metadata — and sends them to GitHub’s cloud. An LLM on the server side produces candidate completions, which are filtered (for license-matching code, unsafe content, etc.) and streamed back to the editor.

Feature lineup

Model choices

Copilot initially ran on OpenAI Codex, then GPT-3.5 and GPT-4. Since 2024 users can select between multiple models — OpenAI GPT-4o, Anthropic Claude Sonnet, Google Gemini — with reasoning models like OpenAI o3 available for heavier tasks as of 2025. Being able to pick the right model for the job is one of Copilot’s clearest advantages.

GitHub Copilot Usage and Examples

Installing in VS Code

From the VS Code marketplace, install the GitHub Copilot and GitHub Copilot Chat extensions, then sign in with your GitHub account. A Copilot subscription is required (a free tier exists).

Inline completion example

def fibonacci(n):
    # Return the n-th Fibonacci number.
    # Placing the cursor here triggers a grey-text suggestion like:
    if n < 2:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

Press Tab to accept. In practice, completion is most valuable on tests, validation code, and repetitive boilerplate — anything where you already know the shape of the answer.

Chat and slash commands

Inside the chat panel, slash commands unlock focused workflows:

/fix rewrite this for-loop as a list comprehension
/explain walk through what this regex does
/tests generate pytest tests for this function
/doc add a Google-style docstring to this function

An important point to note: always review generated code before merging, especially anything touching authentication, secrets, or external APIs.

Copilot Agent

In agent mode you describe a multi-step task in plain English, and Copilot plans and edits across files on its own:

# Example agent prompt
"Introduce JWT authentication:
- Add a login endpoint under /auth
- Create a token-verification middleware
- Replace existing auth checks with the new middleware
- Update related unit tests"

The agent explores the repo, drafts a plan, then applies the edits as a diff for your approval. The human still owns the merge decision.

GitHub Copilot Pricing

The main tiers as of 2025:

Students, teachers, and open-source maintainers can qualify for free access. Always check the official pricing page for the latest terms.

Advantages and Disadvantages of GitHub Copilot

Advantages

Disadvantages

GitHub Copilot vs Cursor vs Claude Code

GitHub Copilot, Cursor, and Claude Code all target “AI for developers” but approach the problem differently. It’s important to note that many teams now use more than one — for example, Copilot in the IDE and Claude Code in the terminal.

Common Misconceptions

Misconception 1: “Copilot writes all my code”

Keep in mind that the developer remains responsible for final code quality, security, and compliance. Copilot accelerates boilerplate, but you still need to reason about design, test edge cases, and verify behavior.

Misconception 2: “Copilot trains on my private code”

According to GitHub’s policy, Business and Enterprise plans do not use customer code for training. Individual plans default to data collection but offer an opt-out. Check your organization’s Copilot settings to confirm.

Misconception 3: “If Copilot wrote it, you don’t need tests”

Note that AI-generated code is still code — with potential bugs. If anything, Copilot raises the importance of tests. A common pattern is to use Copilot itself to write the tests, then review them carefully.

Real-World Use Cases

Accelerating boilerplate

CRUD endpoints, validators, config scaffolds, DTOs — the high-structure, low-creativity parts of software. Copilot shaves meaningful time off these tasks without breaking a developer’s flow.

Lowering learning curves

When working in an unfamiliar framework, Copilot surfaces idiomatic examples inline instead of forcing context switches to docs. You type what you want in a comment, and relevant API calls materialize.

Docs and comments

Generating docstrings, README scaffolds, or API reference notes from existing code is a classic use — humans still review, but they start from a draft rather than a blank page.

Assisted code review

Copilot Code Review posts first-pass feedback on PRs automatically, so human reviewers arrive with the AI’s notes in front of them. In practice this tends to catch style issues and small bugs before a person even opens the diff.

Frequently Asked Questions (FAQ)

Q1: Is the free plan enough for individual use?

For light experimentation, yes. But the free tier has monthly caps on completions and chat messages. Daily users typically move to Pro.

Q2: Who owns Copilot-generated code?

Code produced in response to your prompts is owned by you. That said, suggestions can occasionally match public code; enabling the duplication-detection filter is recommended for license-sensitive commercial work.

Q3: Can Copilot work offline?

Note that Copilot is a cloud service. It does not work without an internet connection.

Q4: Does Copilot support editors other than VS Code?

Yes — JetBrains IDEs, Visual Studio, Xcode, Neovim, Azure Data Studio, and Eclipse all have supported extensions.

Q5: Can I opt out of data collection?

Business and Enterprise plans opt out by default. Individual plans expose settings under “Suggestions matching public code” and “Allow GitHub to use my code snippets for product improvements.”

Conclusion

• GitHub Copilot is an AI coding assistant from GitHub built with OpenAI.
• It spans completion, chat, agent, code review, and terminal suggestions.
• Multi-model support as of 2025: OpenAI GPT and o-series, Anthropic Claude, Google Gemini.
• Works in VS Code, JetBrains IDEs, Visual Studio, Xcode, Neovim, and more.
• Plans: Free, Pro, Pro+, Business, Enterprise — pick the governance you need.
• Business / Enterprise don’t train on customer code by default.
• Review AI-generated code just like any other code — the human is still responsible.

References