The multi-agent framework built with LangSmith + LangGraph, the key is the governance mechanism of the leadership agent—making AI not just write code, but truly operate like a team.

ME News, April 18 (UTC+8): Recently, Renuka Kumar and Prashanth Ramagopal from the Cisco team built a multi-agent coordination framework based on LangSmith and LangGraph. The framework’s behavior is designed to simulate real-world software team collaboration. It falls under the category of “agent engineering,” with the goal of accelerating the entire software process—from requirements to deployment—by simulating engineering team collaboration, rather than only generating code. The system includes work agents responsible for executing tasks such as development, testing, and debugging, as well as leadership agents responsible for coordination, governance, and providing shared resources and long-term memory. Preliminary practice shows that in more than 20 pilot debugging workflows, root-cause identification time was reduced by 93% compared with the historical baseline. In a single month, with 512 sessions, it saved more than 200 engineering hours; the execution time of development workflows was reduced by 6