This paper examines the organizational implications of Generative AI adoption in software engineering through a multiple-case comparative study. We contrast two development environments: a traditional enterprise (brownfield) and an AI-native startup (greenfield). Our analysis reveals that transitioning from Horizontal Layering (functional specialization) to Vertical Integration (end-to-end ownership) yields 8-fold to 33-fold reductions in resource consumption. We attribute these gains to the emergence of Super Employees, AI-augmented engineers who span traditional role boundaries, and the elimination of inter-functional coordination overhead. Theoretically, we propose Human-AI Collaboration Efficacy as the primary optimization target for engineering organizations, supplanting individual productivity metrics. Our Total Factor Productivity analysis identifies an AI Distortion Effect that diminishes returns to labor scale while amplifying technological leverage. We conclude with managerial strategies for organizational redesign, including the reactivation of idle cognitive bandwidth in senior engineers and the suppression of blind scale expansion.

翻译：本文通过多案例比较研究，探讨了生成式AI在软件工程中应用所带来的组织影响。我们对比了两种开发环境：传统企业（棕地项目）与AI原生初创公司（绿地项目）。分析表明，从水平分层（职能专业化）向垂直整合（端到端责任制）的转型，可使资源消耗降低8至33倍。我们将此成效归因于超级员工的涌现——即跨越传统角色边界的AI增强工程师，以及跨职能协调开销的消除。在理论层面，我们提出人机协作效能应成为工程组织的主要优化目标，取代个体生产力指标。全要素生产率分析揭示了一种AI扭曲效应：该效应削弱了劳动规模的回报，同时放大了技术杠杆作用。最后，我们提出了组织重构的管理策略，包括重新激活资深工程师闲置的认知带宽，以及抑制盲目的规模扩张。