用自然语言生成原型，重塑产品团队协作与开发流程。
Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration
- 通过自然语言输入让AI生成可运行的原型代码。
- 四阶段工作流提升迭代速度，但存在代码不可靠问题。
- 适合关注AI辅助设计中责任归属与创意保护的团队。
生成式AI正通过“情绪编码”（vibe coding）重塑产品设计实践：团队成员以自然语言表达意图，AI将其转化为功能原型和代码。基于对22名来自企业、初创公司和学术机构的产品团队成员的访谈，我们发现该过程遵循构思、生成、调试和评审四阶段流程，显著加速迭代、激发创意并降低参与门槛。然而，参与者反映代码可靠性差、集成困难及对AI过度依赖等问题。在效率驱动的快速原型（“设计正确的方案”）与深度反思（“思考正确的意图”）之间存在张力，引发团队内部信任、责任分配与社会偏见的新不平等。本文从负责任的人机协作视角，揭示了情绪编码时代下技能退化、所有权归属与创意保护的核心挑战。
原文摘要 · Abstract (English)
Generative AI is reshaping product design practices through "vibe coding," where product team members express intent in natural language and AI translates it into functional prototypes and code. Despite rapid adoption, little research has examined how vibe coding reconfigures product development workflows and collaboration. Drawing on interviews with 22 product team members across enterprises, startups, and academia, we show how vibe coding follows a four-stage workflow of ideation, generation, debugging, and review. This accelerates iteration, supports creativity, and lowers participation barriers. However, participants reported challenges of code unreliability, integration, and AI over-reliance. We find tensions between efficiency-driven prototyping ("intending the right design") and reflection ("designing the right intention"), introducing new asymmetries in trust, responsibility, and social stigma within teams. Through a responsible human-AI collaboration lens for AI-assisted product design and development, we contribute a deeper understanding of deskilling, ownership and disclosure, and creativity safeguarding in the age of vibe coding.
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