为智能体系统构建类似POSIX和Kubernetes的统一抽象框架
Towards an Agent Operating System - Lessons from Classical and Cloud OS
- 从经典操作系统和云原生系统中提炼可复用的抽象范式
- 提出将传统操作系统抽象扩展至基于自然语言的随机执行场景
- 推动智能体应用跨平台可移植，避免重复开发
每一轮重大平台软件的发展都遵循相同路径：初期是多种框架与临时实现的竞争实验，随后形成一组稳定、语义明确的核心抽象，最终凝聚为可移植的应用平台。类比而言，POSIX完成了经典操作系统的抽象标准化，Kubernetes则实现了云原生系统的统一。当前，以大模型驱动的自主智能体系统——具备规划、工具使用、记忆维护与协作能力——正处于第三轮浪潮的实验阶段。尽管已有数十种框架与协议涌现，但社区尚未就核心抽象及其保证达成共识。缺乏共识导致智能体应用无法跨平台移植，平台间难以可靠组合，整个领域仍停滞于原型部署阶段。本文主张沿袭前两轮的成功方法：通过将经典操作系统与云操作系统中的基础抽象延伸至随机性、自然语言交互的执行环境，明确定义其语义，并在此基础上实现统一与固化，正如POSIX与Kubernetes所完成的那样。
原文摘要 · Abstract (English)
Every major wave of platform software follows the same arc: an initial period of experimentation with competing frameworks and ad-hoc implementations, followed by the articulation of a small set of stable abstractions with well-defined semantics, and finally consolidation around those abstractions into a platform that applications can portably target. POSIX did this for classical operating systems; Kubernetes did it for the cloud. Agentic AI systems - autonomous, LLM-driven agents that plan, use tools, maintain memory, and collaborate - are currently in the experimentation phase of the third such wave. dozens of frameworks and protocols have emerged, but no community consensus exists on what the core abstractions are or what guarantees they carry. Without that consensus, agentic applications cannot be written portably, platforms cannot compose reliably, and the field cannot advance beyond prototype deployments. We argue that the path forward is to follow the prior-wave methodology: derive new agentic abstractions by extending classical OS and cloud OS primitives to stochastic, natural-language-mediated execution, specify their semantics precisely, and consolidate around them - just as POSIX and Kubernetes consolidated their respective waves.
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