Summary

  • 5 minutes

The GitHub Copilot coding agent lets you hand off well-scoped, low- to medium-complexity changes-bug fixes, small features, refactors, tests, documentation-while preserving your GitHub-native workflow. You assign the task; the agent works in a secure, firewalled Actions environment, opens a draft PR, and you review, request changes with @copilot, and approve.

You control security, governance, and spend: branch protections, approval gates, Actions minutes, and PRUs (one premium request per model request). You can customize the build environment, leverage larger runners, enable LFS, and extend capabilities via MCP-all with clear logs and traceability. You're ready to pilot the coding agent in your organization: enable it on a repo, assign a small issue, watch the logs, iterate via PR comments, validate with CI, and measure the time you get back for higher-value work.

Now that you've completed this module, you can:

  • Explain what the Copilot coding agent is, who can use it, and where it runs.
  • Enable the agent at the org or repo level and understand preview terms.
  • Delegate work by assigning issues or asking Copilot to open a pull request.
  • Track progress via PR timelines and live session logs, and iterate with @copilot.
  • Apply the security model and built-in guardrails (branch limits, approvals, firewall).
  • Identify risks and mitigations (permissions, prompt-injection protections, attribution).
  • Recognize workflow and compatibility limits and plan tasks accordingly.
  • Customize the agent's environment with copilot-setup-steps.yml, env vars/secrets, larger runners, and LFS.
  • Extend capabilities with Model Context Protocol (MCP) servers (e.g., GitHub, Playwright).
  • Validate quality with CI, rulesets, and test generation-and use PRUs intentionally.
  • Troubleshoot common issues (availability, approvals, logs, firewall, image limits).

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