In this video, we will build Your First Multi-Step AI Agent Workflow with LangGraph and Python from scratch.
You will learn:
• What LangGraph is and how to setup LangGraph Environment
• What nodes, edges, and state mean
• How execution flows between nodes
• How StateGraph works
• How to pass and update state between nodes
• How to build a complete Draft → Review → Publish workflow in Python
By the end of this video, you will clearly understand the core building blocks of LangGraph and be ready to create your own AI workflows.
If you are learning AI Agents, LangGraph, Python, or Agentic AI development, this video will give you a strong foundation.
Like, share, and subscribe for the next video where we will start adding real LLM calls into our LangGraph nodes.
Full source code is available here:
https://github.com/Rkssri/agentic-nagivator/tree/main/Langgraph_BasicAgent
📌 What’s Next
In the next video, we’ll start adding real LLM calls into LangGraph nodes to make the agent intelligent.
AI Usage Disclaimer:
This video uses an AI‑generated avatar and AI‑generated voice for presentation purposes.
All educational content, explanations, and examples are created and reviewed by me to ensure accuracy and clarity.
#LangGraph #Python #AIAgents #AgenticAI
