GitHub Copilot

GitHub Copilot is GitHub’s AI developer product for code completion, chat, agent workflows, code review, and delegated repository tasks. It operates across GitHub.com and supported development environments rather than as one standalone downloadable application. Official material lists integrations with Visual Studio Code, Visual Studio, JetBrains IDEs, Vim or Neovim, terminals, GitHub Mobile, and additional editor-specific surfaces whose available features vary. The cloud agent can research a repository, create a plan, change code on a branch, run tests or linters in an ephemeral GitHub Actions environment, and let a user iterate before creating or merging a pull request.

GitHub offers Free and paid individual plans plus organization plans, with feature and usage differences. The current plans page uses GitHub AI Credits for several chat and agent interactions, and the cloud agent is documented for paid Copilot plans. Plan prices, usage allowances, credit rules, and feature availability vary across Copilot tiers and can change. GitHub Copilot is a commercial service; there is no single canonical public source repository or open-source license for the product.

Top features

• Inline code suggestions in supported editors for routine implementation and boilerplate.
• Chat and repository questions with context from the active workspace or GitHub surface.
• IDE agent mode for multi-step edits, command execution, and validation in supported environments.
• Cloud agent that works on a GitHub branch in an ephemeral development environment and returns reviewable changes.
• Pull-request summaries, code review, explanations, and issue-to-change workflows.
• Copilot CLI for terminal-oriented assistance and agent tasks.
• GitHub-native context from repositories, issues, branches, pull requests, and organization policies.
• Organization administration for access, models, policies, usage, and approved capabilities.

Use cases

• Complete repetitive code in an editor while a developer retains control of design and review.
• Ask questions about a repository, draft tests, or explain a proposed change.
• Delegate a contained issue to the cloud agent, inspect the branch, and iterate before opening or merging a pull request.
• Run an agent-mode task in a supported IDE to edit several files and execute project checks.
• Apply centralized access and usage policies when deploying AI development assistance across a team.