Design patterns have been used in various fields of inquiry and endeavour to externalize procedural knowledge in a form that supports human reasoning and coordination. In this paper, we show that contemporary Large Language Model (LLM)-based systems can also read, generate, and reason with design patterns written in a structured template. We describe an experimental workflow in which patterns function as shared priors for action selection, reflection, and revision in hybrid human/agent settings. Drawing on the Active Inference Framework, we illustrate how patterns can guide agent behavior without fully prescribing it. This provides a proof of concept that pattern-capable agents can be created using now-standard software tools. We discuss implications for software development, education, business, and AI governance.

翻译：设计模式已被广泛应用于各个研究与实践领域，以结构化形式外化过程性知识，从而支持人类的推理与协作。本文研究表明，基于当代大语言模型（LLM）的系统同样能够读取、生成并推理以结构化模板编写的设计模式。我们描述了一种实验性工作流程，其中设计模式在人类/智能体混合场景中作为行动选择、反思与修正的共享先验知识发挥作用。借鉴主动推理框架，我们阐释了模式如何在不完全限定行为的前提下指导智能体决策。这为利用现有标准软件工具构建具备模式处理能力的智能体提供了概念验证。最后，我们探讨了该研究在软件开发、教育、商业及人工智能治理领域的潜在影响。