MC 14: Building Multi-Agent AI Systems with LangGraph
Details
From One SOC Assistant to a Coordinated AI Team
Learn how to design and build multi-agent AI systems using LangGraph. This masterclass explores how specialized agents work together through shared state, routing, tool use, memory and human approval. Move beyond a single agent and learn how to control a workflow from the first question to the final result.
We will extend the MC13 security assistant into an AI team that investigates a simulated incident: one agent checks the security logs, another checks the response playbook, and a reviewer brings the evidence together. Designed for AI practitioners, developers and data professionals who want practical multi-agent workflows.
Outline: MC13 recap, when multi-agent helps, LangGraph state/nodes/edges, specialist agents, controlled workflow, memory + retry + human approval, single vs multi-agent comparison, Q&A.