The integration of Generative AI (GenAI) and Agentic AI into software development is reconfiguring software engineering from an activity centered on human authorship of code into a discipline centered on directing, verifying, and governing autonomous and semi-autonomous systems. Drawing on a curated, multi-source evidence base of recent peer-reviewed and archival studies -- including large-scale empirical observations of autonomous coding agents contributing hundreds of thousands of pull requests to open-source repositories -- this paper synthesizes how the locus of engineering work is shifting from individual coding productivity toward human--AI collaboration, agent orchestration, verification and validation, governance, and socio-technical systems thinking. We adopt a structured interpretive synthesis to characterize three coexisting paradigms: Traditional, Generative AI-Enabled, and Agentic AI-Enabled software engineering. We map which traditional activities are being automated, which are being augmented, and which are newly emerging, and we trace plausible role trajectories over the next decade. The paper's principal contribution is an original, theory-driven competency framework that organizes the capabilities required of future engineers into five interacting categories -- % technical, cognitive, socio-technical, governance, and organizational -- % operationalized through a competency matrix and a transformation framework linking paradigm shifts to capability demands. We derive nine empirically testable propositions and articulate implications for theory, industry workforce transformation, university curricula, and organizational leadership. We argue that, as code becomes abundant, the durable value of the software engineer increasingly resides in intent specification, critical judgment, and accountable oversight rather than in the sheer volume of code produced.

翻译：生成式人工智能（GenAI）与自主式人工智能在软件开发中的整合，正在将软件工程从以人类编写代码为中心的活动，重构为以指导、验证和治理自主及半自主系统为核心的学科。基于对近期同行评审及档案研究（包括对自主编码代理向开源代码库贡献数十万拉取请求的大规模实证观察）进行系统筛选与多源证据整合，本文综合阐述了工程工作的重心如何从个人编码生产力转向人机协作、代理编排、验证与确认、治理以及社会技术系统思维。我们采用结构化解释性综合方法，刻画了三种共存范式：传统软件工程、生成式AI赋能软件工程和自主式AI赋能软件工程。我们梳理了传统活动中哪些正被自动化、哪些得到增强、哪些属于新涌现的工作，并预测了未来十年内可能的角色演变路径。本文的主要贡献在于提出了一个原创性的、理论驱动的能力框架，将未来工程师所需的能力组织为五个相互作用的类别——技术能力、认知能力、社会技术能力、治理能力与组织能力——并通过能力矩阵和连接范式转变与能力需求的转型框架加以操作化。据此，我们推导出九条可实证检验的命题，并阐述了其对理论构建、行业劳动力转型、大学课程设置及组织领导力的启示。我们主张，当代码变得充裕时，软件工程师的持久价值将日益体现在意图明确、关键判断与负责任的监督之中，而非所编写代码的数量之上。