How to Review Large Pull Requests with AI | CodeRabbit ChangeStack

Large pull requests are difficult to understand—and even harder to review safely. In this tutorial, you’ll learn how CodeRabbit ChangeStack uses AI-powered code review, semantic layers, and Blast Radius visualization to make complex pull requests easier to navigate. We explore a 35-file pull request containing authentication, SQLite persistence, Qdrant vector search, FastAPI endpoints, AI image processing, and chat functionality. You’ll see how ChangeStack organizes these changes by architecture and dependencies, highlights critical security findings, and helps reviewers focus on the code that needs the most attention. You’ll also learn how Blast Radius reveals components that may be affected even when their files weren’t directly changed—and how CodeRabbit Security maps a vulnerability’s potential exploit path across the application . 🔗 Try CodeRabbit: www.coderabbit.ai 🔗 View the example pull request: https://github.com/Hendrik040/DIY-Finder-Project-Smells/pull/53 Chapters: 00:00 Introduction 00:12 What is CodeRabbit ChangeStack? 01:20 Understanding a pull request with semantic layers 02:36 Reviewing authentication and persistence 03:42 Finding critical security issues 04:51 Introducing Blast Radius 06:11 Connecting security findings to architecture 06:26 Visualizing an identity vulnerability 07:22 Conclusion #CodeReview #SoftwareEngineering #CodeRabbit