Karl Marx once wrote that ``the human essence is the ensemble of social relations'', suggesting that individuals are not isolated entities but are fundamentally shaped by their interactions with other entities, within which contexts play a constitutive and essential role. With the advent of computers and artificial intelligence, these contexts are no longer limited to purely human--human interactions: human--machine interactions are included as well. Then a central question emerges: How can machines better understand our situations and purposes? To address this challenge, researchers have recently introduced the concept of context engineering. Although it is often regarded as a recent innovation of the agent era, we argue that related practices can be traced back more than twenty years. Since the early 1990s, the field has evolved through distinct historical phases, each shaped by the intelligence level of machines: from early human--computer interaction frameworks built around primitive computers, to today's human--agent interaction paradigms driven by intelligent agents, and potentially to human--level or superhuman intelligence in the future. In this paper, we situate context engineering, provide a systematic definition, outline its historical and conceptual landscape, and examine key design considerations for practice. By addressing these questions, we aim to offer a conceptual foundation for context engineering and sketch its promising future. This paper is a stepping stone for a broader community effort toward systematic context engineering in AI systems.

翻译：卡尔·马克思曾写道：“人的本质是一切社会关系的总和”，这表明个体并非孤立存在，而是从根本上由其与其他实体的互动所塑造，其中情境发挥着构成性和本质性的作用。随着计算机和人工智能的出现，这些情境不再局限于纯粹的人与人互动：人机互动也被纳入其中。随之而来的核心问题是：机器如何能更好地理解我们的处境与意图？为应对这一挑战，研究者近期提出了情境工程的概念。尽管它常被视为智能体时代的新兴产物，我们认为相关实践可追溯至二十余年前。自20世纪90年代初以来，该领域经历了不同的历史阶段，每个阶段均受机器智能水平的影响：从围绕早期原始计算机构建的人机交互框架，到当今由智能体驱动的人-智能体交互范式，未来可能迈向人类水平或超人类智能。本文通过定位情境工程，提出系统性定义，勾勒其历史与概念脉络，并探讨实践中的关键设计考量。通过回答这些问题，我们旨在为情境工程奠定概念基础，并描绘其充满前景的未来。本文是推动AI系统系统性情境工程更广泛社区努力的基石。