提出控制平面作为工具的架构模式，解决智能体系统规模化时的工具调度难题。
Control Plane as a Tool: A Scalable Design Pattern for Agentic AI Systems
- 将控制平面抽象为单一工具接口，封装复杂的路由逻辑。
- 支持多工具高效调度，提升系统可扩展性与安全性。
- 适合构建大规模、可维护的智能体系统，尤其对开发者友好。
智能体系统代表了人工智能的新前沿，其中基于大语言模型（LLMs）的智能体能够自主与工具、环境及其他智能体交互以完成任务。尽管该领域前景广阔，但其架构基础仍不成熟。本文全面回顾了智能体类型、与环境的交互方式，以及由此产生的基础设施与架构挑战。研究发现，现有系统在规模化工具调度方面存在明显短板，为此提出一种可复用的设计抽象：'控制平面作为工具'模式。该模式使开发者仅需暴露单一工具接口给智能体，而将模块化的工具路由逻辑封装于其后。本文将该模式置于智能体设计的整体框架中，论证其能有效应对规模化、安全性和可扩展性等关键挑战。
原文摘要 · Abstract (English)
Agentic AI systems represent a new frontier in artificial intelligence, where agents often based on large language models(LLMs) interact with tools, environments, and other agents to accomplish tasks with a degree of autonomy. These systems show promise across a range of domains, but their architectural underpinnings remain immature. This paper conducts a comprehensive review of the types of agents, their modes of interaction with the environment, and the infrastructural and architectural challenges that emerge. We identify a gap in how these systems manage tool orchestration at scale and propose a reusable design abstraction: the "Control Plane as a Tool" pattern. This pattern allows developers to expose a single tool interface to an agent while encapsulating modular tool routing logic behind it. We position this pattern within the broader context of agent design and argue that it addresses several key challenges in scaling, safety, and extensibility.
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