LangGraph Workflow #1 – Prompting & Chaining (Part 2) | Multi-Step AI Workflow | Nidhi Chouhan

Description

In Part 2 of Prompting & Chaining in LangGraph, we’ll expand on our workflow to include multi-step reasoning and message passing 🔁 You’ll see how data flows between chained nodes, how prompts can adapt dynamically, and how LangGraph manages contextual state across multiple runs. 💡 Key Learnings ✅ Building multi-layered prompt chains ✅ Managing context and outputs between nodes ✅ Integrating tools and LLMs inside workflows ✅ Optimizing chained pipelines for complex AI logic ✅ Real-world example of chaining in LangGraph This video will give you hands-on clarity on how to structure intelligent, modular AI workflows inside LangGraph 🧠 📌 GitHub Repository (Code + Notes): 👉 https://github.com/dearnidhi/Agentic-AI-HandsOn-Bootcamp 📩 Contact: ✉️ nidhiyachouhan12@gmail.com 📸 Instagram: @codenidhi | @dear_nidhi 💼 LinkedIn: https://www.linkedin.com/in/nidhi-chouhan-544650b4/ ✨ Don’t forget to LIKE 👍, SHARE 📢 & SUBSCRIBE 🔔 for more LangGraph tutorials & Agentic AI workflow series! LangGraph Chaining, LangGraph Workflow Part 2, LangGraph Prompting, LangGraph Multi-Step Chain, LangGraph Message Flow, LangGraph AI Pipeline, LangChain + LangGraph, LangGraph StateGraph Workflow, Agentic AI Workflow, LangGraph Advanced Tutorial, LangGraph Components, CodeNidhi LangGraph, Nidhi Chouhan LangGraph #LangGraph #LangChain #LangGraphWorkflow #LangGraphChaining #LangGraphPrompting #AgenticAI #LangGraphTutorial #CodeNidhi #NidhiChouhan #AIWorkflow #GenAI #AIBootcamp #MachineLearning #Python