The boundary of the firm is determined by coordination cost. We argue that agentic AI induces a structural change in how coordination costs scale: in prior modular systems, integration cost grew with interaction topology (O(n^2) in the number of components); in protocol-mediated agentic systems, integration cost collapses to O(n) while verification scales with task throughput rather than interaction count. This shift selects for a specific organizational equilibrium -- the Headless Firm -- structured as an hourglass: a personalized generative interface at the top, a standardized protocol waist in the middle, and a competitive market of micro-specialized execution agents at the bottom. We formalize this claim as a coordination cost model with two falsifiable empirical predictions: (1) the marginal cost of adding an execution provider should be approximately constant in a mature hourglass ecosystem; (2) the ratio of total coordination cost to task throughput should remain stable as ecosystem size grows. We derive conditions for hourglass stability versus re-centralization and analyze implications for firm size distributions, labor markets, and software economics. The analysis predicts a domain-conditional Great Unbundling: in high knowledge-velocity domains, firm size distributions shift mass from large integrated incumbents toward micro-specialized agents and thin protocol orchestrators.

翻译：企业的边界由协调成本决定。我们认为，智能体人工智能引发了协调成本规模变化的结构性变革：在以往的模块化系统中，集成成本随交互拓扑结构增长（与组件数量呈O(n²)关系）；而在协议中介的智能体系统中，集成成本降至O(n)，验证成本则随任务吞吐量而非交互次数变化。这种转变选择了一种特定的组织均衡态——无头企业——其结构呈沙漏状：顶部是个性化生成界面，中部是标准化协议层，底部则是高度专业化执行智能体构成的竞争性市场。我们将此主张形式化为包含两个可证伪实证预测的协调成本模型：（1）在成熟的沙漏生态系统中，增加执行提供者的边际成本应近似恒定；（2）总协调成本与任务吞吐量的比值应随生态系统规模扩大保持稳定。我们推导了沙漏结构稳定与再中心化的条件，并分析了其对企规模分布、劳动力市场和软件经济的影响。该分析预测了领域条件性的"大解绑"：在高知识流速领域，企业规模分布将从大型综合型企业向高度专业化智能体与精简化协议协调者转移。