Uploaded August 2026 | Updated September 2026, 2 weeks ago
🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.
📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1
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Graph engineering is not a new technique. It is a new name for something you have already been doing in LangGraph, Google ADK and AutoGen. This video explains it properly so you can answer it at work or in an interview.
We start with where graph engineering sits among the other agentic AI techniques (prompt, context, harness and loop), then build up to what a node actually is, why graph RAG is not graph engineering, and the cost question interviewers keep asking: can you use graph engineering everywhere? This is a concept lesson, so there is no code. Just the full mental model.
⏱ Chapters:
0:00 Graph engineering is not a new technique
0:36 LangGraph, Google ADK and AutoGen already do this
1:23 Where graph engineering fits among the other techniques
2:47 Why an agent cannot self-prompt itself
3:28 Nodes: agents and self-prompting solutions, orchestrated
4:47 Graph RAG vs graph engineering, and why they are not the same
6:26 Can you use graph engineering everywhere?
7:57 Wrap up
🔗 Resources:
Slides from this video: slideshare.net/slideshow/mastering-graph-engineering-for-coordinated-ai-workflows-in-banking-finance/289045978
📺 Watch next:
What is Loop Engineering? Agentic AI Engineering Explained
youtube.com/watch?v=VTLeQLn-Vn8
🎓 Go deeper with my Udemy course:
Master LangGraph v1 and Ollama - Build Gen AI Agents
kgptalkie.com/langgraph
If this cleared things up, leave a like. Got stuck somewhere, or want a lesson on a related topic? Put it in the comments. I read and reply to every one. Subscribe and hit the bell to catch the rest of this series.
#GraphEngineering #AgenticAI #LangGraph #AIEngineering #GenAI
🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.
📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1
----------
Graph engineering is not a new technique. It is a new name for something you have already been doing in LangGraph, Google ADK and AutoGen. This video explains it properly so you can answer it at work or in an interview.
We start with where graph engineering sits among the other agentic AI techniques (prompt, context, harness and loop), then build up to what a node actually is, why graph RAG is not graph engineering, and the cost question interviewers keep asking: can you use graph engineering everywhere? This is a concept lesson, so there is no code. Just the full mental model.
⏱ Chapters:
0:00 Graph engineering is not a new technique
0:36 LangGraph, Google ADK and AutoGen already do this
1:23 Where graph engineering fits among the other techniques
2:47 Why an agent cannot self-prompt itself
3:28 Nodes: agents and self-prompting solutions, orchestrated
4:47 Graph RAG vs graph engineering, and why they are not the same
6:26 Can you use graph engineering everywhere?
7:57 Wrap up
🔗 Resources:
Slides from this video: slideshare.net/slideshow/mastering-graph-engineering-for-coordinated-ai-workflows-in-banking-finance/289045978
📺 Watch next:
What is Loop Engineering? Agentic AI Engineering Explained
youtube.com/watch?v=VTLeQLn-Vn8
🎓 Go deeper with my Udemy course:
Master LangGraph v1 and Ollama - Build Gen AI Agents
kgptalkie.com/langgraph
If this cleared things up, leave a like. Got stuck somewhere, or want a lesson on a related topic? Put it in the comments. I read and reply to every one. Subscribe and hit the bell to catch the rest of this series.
#GraphEngineering #AgenticAI #LangGraph #AIEngineering #GenAI
