Scaling AI Beyond Single Agents: Multi-Agent Architectures with LangChain

Description

As AI applications grow more complex, single-agent models often struggle with context and reliability. Multi-agent architectures address this by distributing tasks across specialized agents. In this session, you’ll learn how to design scalable multi-agent systems using LangChain, explore key patterns like subagents, skills, handoffs, and routers, and see a live demo of orchestrating agent workflows beyond simple prototypes. What you’ll learn: - When and why to use multi-agent architectures - Key LangChain design patterns and trade-offs - How to orchestrate agent skills and manage context - Practical guidance for building production-ready systems Perfect for practitioners looking to move beyond single-agent AI and build robust, scalable solutions.