GitHub Copilot
AI pair programmer built into your IDE
GitHub's AI coding assistant, offering inline code completions, a chat interface and an autonomous agent mode across VS Code, JetBrains, Visual Studio and GitHub.com.
Picked for AI-Native Code Editors for Developers.
GitHub Copilot was the tool that put AI code completion on the map, and it’s since grown from single-line suggestions into a full assistant: inline completions while you type, a chat panel for questions and explanations, and an agent mode that can plan and carry out changes across multiple files before handing them back for review. It ships as extensions for VS Code, JetBrains IDEs, Visual Studio and Neovim, plus a presence in GitHub Mobile and github.com itself.
Its strength is reach rather than any single standout feature — most developers already live in GitHub, so Copilot’s suggestions, chat and pull-request integration show up exactly where the work already happens. Teams that want one AI subscription across a mix of editors and IDEs are the best fit, since few competitors match its IDE coverage.
2026 brought a real complication: GitHub replaced the old premium-request system with usage-based billing tied to token consumption, so chat and agent interactions against premium models now draw down metered credits instead of a flat monthly allowance. Code completions stay unmetered, but the change makes actual monthly cost less predictable for anyone leaning on agent mode or chat. Suggestion quality also still varies by language and framework — it’s strongest in mainstream, well-represented languages and weaker in niche ones.
Features
Inline completions
Suggests single lines or whole functions as you type, matching the style of the surrounding code.
Copilot Chat
A chat panel inside the editor for asking questions about the codebase, generating tests or explaining an error.
Agent mode
Hands off a task description and lets Copilot plan and execute multi-file changes with a review step before merging.
Pull request review
Leaves line-level comments on a PR before a human opens it, catching the class of issue a reviewer would otherwise spend their first pass on.
Custom instructions
Repository-level guidance that shapes every suggestion, so a team's conventions are stated once rather than corrected in review.
Model choice
Switch the model behind chat and edits, which matters when one is better at the refactor and another at the explanation.
Use cases
- Speeding up boilerplate and repetitive code writing
- Getting a first-pass explanation of unfamiliar code
- Drafting tests and documentation alongside a change
- Getting a first-pass review on a pull request before a human looks
- Holding suggestions to a team's conventions with repository instructions
- Adding tests to code that shipped without any
Compare GitHub Copilot head to head
Side-by-side comparisons, on pricing, platforms and where each one wins.
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