Enterprises looking to deploy multiple AI agents often need to implement a framework to manage them. To this end, Microsoft researchers recently unveiled a new multi-agent infrastructure called Magnetic-One that allows a single AI model to power various helper agents that work together to complete complex, multi-step tasks in different scenarios. Microsoft calls Magnetic-One a generalist agentic system that can “fully realize the long-held vision of agentic systems that can enhance our productivity and transform our lives.” The framework is open-source and available to researchers and developers, including for commercial purposes, under a custom Microsoft License. In conjunction with the release of Magnetic-One, Microsoft also released an open-source agent evaluation tool called AutoGenBench to test agentic systems, built atop its previously released Autogen framework for multi-agent communication and cooperation. The idea behind generalist agentic systems is to figure out how autonomous agents can solve tasks that require several steps to finish that are often found in the day to day running of an organization or even an individual’s daily life. From the examples Microsoft provided, it looks like the company hopes Magnetic-One fulfills almost mundane tasks. Researchers pointed Magnetic-One to tasks like describing trends in the S&P 500, finding and exporting missing citations, and even ordering a shawarma.

Full report : Microsoft joins multi-AI agent fray with Magnetic-One.