Multi-agent systems (MAS) consist of multiple autonomous AI agents working together to complete complex tasks. Core components include worker agents (specialized contributors), orchestrator agents (coordinators), execution environments, shared memory and context, protocols like MCP and A2A, and governance policies. Real-world deployments include NTT Data's infrastructure management MAS, Madrigal Pharmaceuticals' research platform built with LangChain/LangSmith, and Fujitsu's healthcare agent platform in Japan. Enterprise interest has surged 1,445% according to Gartner, driven by the ability to automate complex workflows at scale across industries.
Table of contents
Defining Multi-Agent SystemsComponents of a Multi-Agent SystemExamples of Multi-Agent SystemsThe Case for Multi-Agent SystemsAI Summary276 Impressions1 Comment