System Design for AI Agents – Building a Multi-Agent PR Reviewer // TRAIN BRAIN

System Design for AI Agents – Building a Multi-Agent PR Reviewer

Learn how to design and build a production-ready, multi-agent AI system that automates pull request reviews with senior-level engineering judgment. This comprehensive tutorial covers everything from fault-tolerant system architecture and database modeling to utilizing the Genesis kit for reliable, AI-native development.
Code: https://github.com/ayush488-glitch/genesis-kit
Course created by @AyushSinghSh
❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp
⭐️ Chapters ⭐️
- 0:00:00 Introduction: Building a Production-Ready AI PR Review Agent
- 0:06:35 The System Design Lens & Mapping the Mess
- 0:19:12 Addressing AI Failure Modes & Reliability Engineering
- 0:33:04 Part 1: First Principles & Reclaiming Senior Engineer Attention
- 0:42:44 The Four Mindsets of a Reviewer (Security, Quality, Testing, Docs)
- 0:54:08 Implementing the Agentic Fan-Out and Fan-In Pattern
- 1:00:08 Part 2: Data Engineering & Memory Shapes
- 1:17:23 Database Selection
- 1:28:32 Part 3: System Architecture Assembly
- 1:38:48 Orchestration Engine Selection: LangGraph vs. Temporal
- 1:52:15 Part 4: Implementation Using the Genesis Kit
- 2:03:40 Running Milestones and Independent AI Code Verification
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