Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866913078649552896 |
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| author | Li, Jie Hou, Youyang Lin, Laura Zhu, Ruihao Cao, Hancheng Ali, Abdallah El |
| author_facet | Li, Jie Hou, Youyang Lin, Laura Zhu, Ruihao Cao, Hancheng Ali, Abdallah El |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_10652 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration Li, Jie Hou, Youyang Lin, Laura Zhu, Ruihao Cao, Hancheng Ali, Abdallah El Human-Computer Interaction Artificial Intelligence Computers and Society Emerging Technologies 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. |
| title | Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration |
| topic | Human-Computer Interaction Artificial Intelligence Computers and Society Emerging Technologies |
| url | https://arxiv.org/abs/2509.10652 |