LangGraph Supervisor Tutorial · Multi-Agent SystemsPart 2 of 6 · View the series guide ← Part 1: Build a conversational agent with LangGraph A LangGraph supervisor tutorial should begin with a simple idea: a useful multi-agent system is not a group of bots talking at random. It is a workflow with a clear decision-maker. One […]
This LangGraph multi-agent systems tutorial series takes you from a single conversational agent to a reliable workflow of a supervisor and specialist agents. Each tutorial adds one practical capability: delegation, shared context, routing, recovery, or evaluation. Who this series is for This series is for Python developers who understand the basics of language models and […]
This multi-agent workflow roadmap introduces coordinated AI roles and workflows working toward one outcome—not magical, fully autonomous AI teams. It is the starting point for the series, and it will become a linked learning path as each tutorial is published. Key takeaways A multi-agent system divides a broader job among defined AI roles and workflow […]
Creating sophisticated conversational agents requires more than just a powerful language model. You need a framework that can manage complex conversational flows, maintain context, and handle decision-making with elegance. Enter LangGraph, a powerful toolkit built on top of LangChain that enables developers to create state-aware, multi-step reasoning systems with remarkable ease. Why LangGraph Matters? Traditional […]