The Internet has evolved by progressively expanding what humanity connects: first computers, then people, and later billions of devices through the Internet of Things (IoT). While IoT succeeded in digitizing perception at scale, it also exposed fundamental limitations, including fragmentation, weak security, limited autonomy, and poor long-term sustainability. Today, advances in edge hardware, sensing, connectivity, and artificial intelligence enable a new phase: the Internet of Physical AI Agents. Unlike IoT devices that primarily sense and report, Physical AI Agents perceive, reason, and act in real time, operating autonomously and cooperatively across safety-critical domains such as disaster response, healthcare, industrial automation, and mobility. However, embedding fast-evolving AI capabilities into long-lived physical infrastructure introduces new architectural risks, particularly around interoperability, lifecycle management, and premature ossification. This article revisits lessons from IoT and Internet evolution, and articulates design principles for building resilient, evolvable, and trustworthy agentic systems. We present an architectural blueprint encompassing agentic identity, secure agent-to-agent communication, semantic interoperability, policy-governed runtimes, and observability-driven governance. We argue that treating evolution, trust, and interoperability as first-class requirements is essential to avoid hard-coding today's assumptions into tomorrow's intelligent infrastructure, and to prevent the high technical and economic cost of getting it wrong.

翻译：互联网的发展历程体现了人类连接对象的逐步扩展：首先是计算机，随后是人，最后通过物联网（IoT）连接了数十亿设备。虽然物联网成功实现了大规模感知数字化，但也暴露出根本性局限，包括碎片化、安全性薄弱、自主性有限以及长期可持续性不足。当前，边缘硬件、传感技术、连接能力与人工智能的进步正推动着新阶段的到来：物理人工智能代理互联网。与主要进行感知与上报的物联网设备不同，物理人工智能代理能够实时感知、推理与行动，在灾害响应、医疗健康、工业自动化与移动出行等安全关键领域实现自主协同运作。然而，将快速演进的人工智能能力嵌入长寿命物理基础设施会带来新的架构风险，尤其在互操作性、生命周期管理与过早固化等方面。本文重新审视物联网与互联网演进的历史经验，阐述了构建弹性、可演进且可信赖的代理系统的设计原则。我们提出一种架构蓝图，涵盖代理身份认证、安全的代理间通信、语义互操作性、策略管控的运行环境以及可观测性驱动的治理机制。我们认为，将演进性、可信度与互操作性作为首要需求至关重要，这既能避免将当前假设硬编码至未来的智能基础设施中，也能防止因设计失误而付出高昂的技术与经济代价。