Conference SessionIntermediate60 min

Building Scalable Multi-Agentic AI Systems: Orchestrating Agents with Event-Driven Approach

Multi-agent AI gets harder when agents need to coordinate at scale. Coordination patterns matter once agents have to share state, communicate, and keep work moving across a system. Mary Grygleski uses "Building Scalable Multi-Agentic AI Systems: Orchestrating Agents with Event-Driven Approach" to follow that thread into event-driven patterns for communication, memory, workflow state, and MCP, giving attendees a practical way to bring the lesson back to their own systems.

About This Session

This talk will guide developers through the design and implementation of multi-agent generative AI systems using event-driven principles. Attendees will learn how autonomous GenAI agents collaborate, communicate, and adapt in real-time workflows using modern frameworks (such as LangChain or Haystack) and messaging protocols.

Cover core patterns such as pub/sub, orchestrator, and supervisor for managing agent communication, memory, and workflow state. Discuss interoperability with MCP (Model Context Protocol) and how event streaming tools like Kafka, Pulsar, that can facilitate high throughput and reliability.