Generative AI is transforming software development from localized tool support into development work that is embedded in processes, tools, and organizational structures. Its use now extends beyond code completion to requirements, architecture, implementation, testing, review, operations, and maintenance. Existing research shows a differentiated picture. Productivity gains are possible, but depend on task type, codebase characteristics, and developers' experience. At the same time, AI-generated artifacts require additional control and governance. Building on these observations, this paper develops a pragmatic organizing framework for the transition toward AI-driven Software Development. It describes a progression from informal and assistive AI use through integrated AI workflows toward controlled agentic development processes. The focus is not on individual tools or models, but on the technical, organizational, and quality-assurance mechanisms needed to embed AI across central software engineering activities. Particular importance is assigned to a harness that connects project context, tool access, verification, permissions, logging, and human approval. The paper draws on current research, practice-oriented sources, established software engineering practices, and project experience. A mid-sized software company is used as an exploratory case study to assess the plausibility of the framework and to illustrate how prerequisites, governance requirements, design practices, and transformation paths can be shaped in a concrete organizational context. The paper provides a conceptual basis for further scholarly discussion and empirical investigation of AI-driven Software Development.

翻译：生成式人工智能正将软件开发从局部工具支持，转变为嵌入流程、工具和组织结构中的开发工作。其应用现已超越代码补全，拓展至需求、架构、实现、测试、评审、运维与维护。现有研究呈现出差异化的图景：生产力提升是可能的，但取决于任务类型、代码库特征以及开发者的经验；同时，AI生成的工件需要额外的控制与治理。基于上述观察，本文构建了一个迈向AI驱动软件开发的务实组织框架。该框架描述了从非正式、辅助性的AI使用，到集成化的AI工作流，直至受控的智能代理开发过程的演进路径。本文的关注点并非单个工具或模型，而是将AI嵌入核心软件工程活动所需的技术、组织与质量保障机制。其中，一个连接项目上下文、工具访问、验证、权限、日志记录和人工审批的“总控”机制被赋予特别重要的地位。本文借鉴了当前研究、实践导向的文献、成熟的软件工程实践及项目经验，并以一家中型软件公司作为探索性案例研究，来评估该框架的可行性，并阐明如何在具体的组织环境中塑造前提条件、治理要求、设计实践与转型路径。本文为AI驱动软件开发的后续学术讨论与实证研究提供了概念基础。