LangChain vs LangGraph: Why AI Agents Need Stateful Orchestration Most AI agents look impressive in demos. Then they hit production and break. APIs timeout. Memory disappears. Tool calls fail. Long workflows lose context halfway through execution. A chatbot that looked “smart” in a YouTube video suddenly becomes unreliable the moment real-world complexity enters the system. This is why frameworks like LangChain and LangGraph are becoming critical infrastructure for modern AI systems. We’re moving beyond prompt engineering into something much bigger: Agent engineering. The Problem With Most AI Agent Architectures A lot of AI agents today are basically: prompt -> LLM -> output Enter fullscreen mode Exit fullscreen mode Sometimes developers add: tools APIs retrieval memory layers But the architecture is still fundamentally fragile.…