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In this video, we break down the basics of LangChain and LangGraph and explain how they are used to build modern AI agents. If youβre working with LLMs and want to move from simple prompt calls to structured, stateful agent systems β this video is for you. Youβll learn: π What is LangChain? π What is LangGraph? π Chains vs Graphs explained π Stateless vs Stateful workflows π Why LangGraph is better for complex agents π How agent loops work π Real-world use cases π When to use LangChain vs LangGraph π Topics Covered: Prompt chains Tool calling Memory Agent workflows State management DAG vs graph execution Multi-step reasoning Production AI pipelines Perfect for: βοΈ ML Engineers βοΈ GenAI Developers βοΈ Backend Engineers βοΈ Startup Builders βοΈ AI Students If you're learning Agentic AI, LLM orchestration, AI system design, or production ML pipelines, this will give you a solid foundation. π Like π if this helped π Subscribe for more AI engineering deep dives π Comment if you want a hands-on tutorial next #LangChain #LangGraph #AIAgents #AgenticAI #GenerativeAI #LLM #AIEngineering #MachineLearning #GenAI #PythonAI #AIExplained #MLOps #AIArchitecture