Introduction

In earlier modules of this program, you’ve used AI tools interactively: asking questions of a codebase, shaping a feature plan, implementing code, generating tests, and reviewing the results with a human in the loop. Those workflows are powerful, yet they remain manual. Each review or check requires someone to open a pull request, invoke an agent, and interpret the output.

This lesson moves that capability into the continuous-integration pipeline itself. You’ll learn agentic AI code reviews as the first-class CI step that runs automatically on every pull request. The goal isn’t to replace human reviewers, but to give them a consistent, high-signal starting point before they begin their own examination.

The primary tool used for the demonstration will be GitHub Copilot, to highlight configuration steps, and present the resulting review comments on a real iOS pull request in the video. The written portion of the lesson will focus on evergreen concepts and design choices, and how they can be achieved.

In the earlier modules, you used Claude Agent inside Xcode and Cursor as an external editor. This module introduces different tools because the review must run unattended in GitHub Actions. The instruction section tells you briefly how to set up GitHub Copilot for this lesson, and Claude Code and OpenAI Codex for the lessons that follow.

By the end of this lesson you’ll be able to:

• Explain what agentic AI code review means in a CI context.
• Explain how agentic AI code differs from interactive prompting.
• Describe the architectural patterns required to invoke an AI agent on:
  • a pull request
  • a commit
  • authentication
  • context-passing strategies
• Configure GitHub Copilot as an automated review inside a GitHub Actions workflow for an iOS project.
• Estimate approximate token usage (input and output token count) for a typical iOS pull-request review.
• Observe a complete end-to-end integration against the sample codebase.
• Be able to recognize the practical decisions that arise during setup.