YouTube Video
Build a production-ready, multi-agent AI system from scratch using Graph Engineering and Google's Agent Development Kit (ADK). In this hands-on tutorial, we walk through a marathon race demo to demonstrate why large monolithic prompts hallucinate and how graph architecture fixes them. Master core graph design patterns—including fan-out for parallel execution, join nodes for deterministic data aggregation, and deterministic vs. LLM routers—all while optimizing architecture to run an entire multi-branch workflow on just a single LLM call.
Tell us about your experiences creating your own workflows in the comments below!
Try out the Codelab → https://codelabs.developers.google.com/adk2/instructions#0
Build with ADK → adk.dev
Chapters:
00:00 - Intro: What is Graph Engineering?
01:50 - Building a Minimal 2-Node Graph (Functions + Agents)
02:46 - Pattern 1: Fan-Out & Parallel Processing
03:30 - Pattern 2: The Join Node
03:45 - Pattern 3: Router Pattern
05:20 - When to Use Graphs (Static vs. Dynamic Workflows)"
Tell us about your experiences creating your own workflows in the comments below!
Try out the Codelab → https://codelabs.developers.google.com/adk2/instructions#0
Build with ADK → adk.dev
Chapters:
00:00 - Intro: What is Graph Engineering?
01:50 - Building a Minimal 2-Node Graph (Functions + Agents)
02:46 - Pattern 1: Fan-Out & Parallel Processing
03:30 - Pattern 2: The Join Node
03:45 - Pattern 3: Router Pattern
05:20 - When to Use Graphs (Static vs. Dynamic Workflows)"