AI 中文总结
本文提出一种分层框架，分离智能体原生组织的持久与动态层，通过多类智能体与角色组实现灵活执行与刚性底层，已实现原型并完成小样本实验，贡献为可证伪的组织设计治理框架。
AI 中文摘要
尽管多智能体系统（MAS）仍大多将组织操作化为对话拓扑、角色提示或固定工作流，但智能体组织不应是一组带有企业头衔的模型实例。本文开发了一种智能体原生组织结构框架，该框架将操作的持久层与动态层分离。持久层包含四存储记录架构和常驻专业化智能体池；协调层将Permission定义为智能体可用操作世界的边界，将Privilege定义为智能体被授权发起的组织状态变更集合，这些机制共同编译出特定任务的操作世界；运行时层将外部Workflow Protocol与隔离的运行时存储结合，动态组装任务组；人机交互层通过非决策型Translation Agent介导的Control Plane暴露组织。三个正交角色组进一步分离操作、审核与监督：操作者在窄范围租期内执行；审核者拥有更高但按需激活的修改组织状态权限；监督者保留广泛观测权限，仅拥有有限修改权限。所得架构在执行层面灵活，底层结构刚性：任务和事件可改变团队组成、拓扑、视图、工具及工作流，而记录、写入约束、权限边界与权力分立保持持久。该架构已实现为原型并在小样本实验中评估，大规模实证验证仍未完成，因此暂不宣称通用性能，其贡献是一套连贯且可证伪的智能体原生组织设计、治理、恢复与评估框架。
英文摘要
An agentic organization should not be a set of model instances with corporate titles, despite most MAS still operationalizing organization as a conversational topology, a role prompt, or a fixed workflow. This paper develops an agent-native organizational structure framework that separates the persistent and dynamic layers of operations. The persistent layer consists of a four-store record architecture and a pool of resident specialization agents. A coordination layer defines Permission as the boundary of the operational world available to an agent, and Privilege as the set of organizational state changes that the agent is authorized to initiate. Together, these mechanisms compile task-specific operational worlds. A runtime layer combines an external Workflow Protocol with an isolated runtime store to dynamically assemble Task Groups. A human-interaction layer exposes the organization through a Control Plane mediated by a non-decision-making Translation Agent. Three orthogonal Role Groups further separate Operation, Review, and Supervision. Operators execute within narrowly scoped leases; reviewers receive elevated but demand-activated authority to modify organizational state; supervisors retain broad observational access while holding limited modification authority. The resulting architecture is fluid at the execution surface but structurally rigid underneath: tasks and events may alter team composition, topology, views, tools, and workflows, while records, write constraints, authority boundaries, and separation of powers remain persistent. The architecture has been implemented as a prototype and evaluated in small-sample experiments. Large-scale empirical validation remains incomplete, therefore no general performance claimed is made yet. Instead, the contribution is a coherent and falsifiable framework for designing, governing, recovering, and evaluating agent-native organizations.
