Cisco Outshift的高管Vijoy Pandey阐述了实现分布式人工超级智能的关键技术方向。1根据其观点，当前单一AI智能体已具备足够的能力，瓶颈在于缺乏协调机制——"智能已经存在，缺失的是将陌生人转变为一个团队的连接组织。"1为此，Outshift开发了一套系统性解决方案，通过建立语义层和连接层，使多个AI智能体能够共享意图、上下文和推理能力。1
多智能体系统当前的可靠性问题严重，失败率在41%至87%之间。1Outshift的研究表明，在采用协调协议后，非结构化团体的决策成功率可从约33%大幅提升至93%。1为支持这一框架的推广，Outshift开发了AGNTCY（Linux Foundation下的开源项目）和Mycelium（开源协调层）等工具，同时推出了CASA安全框架。1Pandey指出，约90%的情况下，智能体甚至无法确认自己是否被授权执行分配的任务。1对于企业的实际应用，Outshift建议从跨越3-4个团队的单一工作流开始试验多智能体协作系统。1
Vijoy Pandey, an executive at Cisco Outshift, has outlined a technical roadmap for advancing from isolated artificial intelligence systems toward distributed artificial superintelligence by establishing semantic and connectivity layers that enable multiple AI agents to collaborate effectively.1 According to Pandey, "The intelligence is already there. What is missing is the connective tissue that turns four strangers into one team."1 The framework relies on agents sharing intent, context, and reasoning capabilities across different domains and systems, a capability that current multi-agent systems struggle to achieve, with failure rates ranging between 41% and 87%.1
Cisco Outshift has developed several tools to address this challenge, including AGNTCY, an open-source project under the Linux Foundation, and Mycelium, an open coordination layer that organizations can deploy independently.1 The company has also created CASA, a security framework designed to govern agent interactions.1 Testing of the coordination protocol has demonstrated significant improvements: when applied to unstructured teams, decision-making success rates increased from approximately 33% to 93%.1 However, a fundamental obstacle persists in current agent deployment; as Pandey noted, "Roughly 90% of the time, an agent has no way to confirm it is even cleared for the job it was handed."1 For organizations beginning to implement this approach, Outshift recommends starting with a single workflow that spans three to four teams to pilot the technology.1
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