Multi-agent collaboration

This is a podcast episode titled, Multi-agent collaboration. The summary for this episode is: <p>Explore Think 2026:&nbsp;https://www.ibm.biz/think2026event&nbsp;</p><p>&nbsp;</p><p>This episode of *Techsplainers* explores multi-agent collaboration, where multiple AI agents work together as a coordinated team to&nbsp;accomplish&nbsp;complex tasks. We explain how these systems have evolved beyond traditional LLMs to create autonomous workflows for research, support, analysis, and operations. The discussion covers key collaboration models including rule-based, role-based, and model-based approaches, and examines leading frameworks like IBM's Bee Agent,&nbsp;LangChain, and OpenAI's Swarm. We also highlight&nbsp;Watsonx&nbsp;Orchestrate as an enterprise solution for orchestrating AI-enabled workflows through interconnected components. Throughout the episode, we use the analogy of drone teams searching disaster sites to illustrate how independent agents can coordinate effectively without centralized control to tackle complex challenges that would overwhelm a single agent.&nbsp;</p><p><br></p><p><strong>Find more information at</strong>&nbsp;https://www.ibm.com/think/topics/multi-agent-collaboration&nbsp;</p><p><strong>Find more episodes at</strong>&nbsp;https://www.ibm.biz/techsplainers-podcast&nbsp;</p><p><br></p><p><strong>Narrated by Matt&nbsp;Finio&nbsp;</strong></p>