一句话：提出面向数字孪生与 AI 智能体融合系统的领域驱动架构方法，并给出应对同步、扩展与互操作的设计模式。
数字孪生与 AI 智能体的融合正在重塑制造、医疗和智能基础设施等领域的智能系统设计与运行。数字孪生提供物理系统的实时虚拟表示，AI 智能体则带来自主性与自适应决策，二者结合可增强监控、预测与优化能力。本文介绍一种系统化、领域驱动的方法，用于架构同时包含数字孪生与 AI 智能体的系统；它描述如何建模并同步物理实体与虚拟实体之间的关系，并提出若干新颖设计模式，以应对实时同步、可扩展性、互操作性和 AI 驱动自动化等关键挑战。通过示例性案例研究，说明这些原则可跨行业应用，以构建韧性、自适应且智能的系统，并整合 IoT、AI 与数据分析。
The integration of Digital Twins and AI Agents is reshaping how smart systems are designed and operated across domains such as manufacturing, healthcare, and smart infrastructures. Digital Twins provide real-time virtual representations of physical systems, while AI Agents enable autonomy and adaptive decision-making. Together, they enhance monitoring, prediction, and optimization capabilities. This technical brief introduces a systematic, domain-driven approach for architecting systems that combine Digital Twins with AI Agents. It outlines how to model and synchronize relationships between physical and virtual entities and presents novel design patterns addressing key challenges, including real-time synchronization, scalability, interoperability, and AI-driven automation. Through illustrative case studies, the session demonstrates how these principles can be applied across industries to build resilient, adaptive, and intelligent systems. Attendees will gain practical insights into designing Digital Twin architectures that effectively integrate IoT, AI, and data analytics to meet the demands of modern digital transformation.