Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration

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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Publication Details

Published
2026-06-19
DOI
https://doi.org/10.1145/3808045.3808062
Citations
1
Primary Topic
Design Education and Practice
Type
preprint
Field-Weighted Citation Impact
5.54
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preprint

Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration

Hancheng Cao, Youyang Hou, Abdallah El Ali, Ruihao Zhu et al.
1 citations
Design Education and Practice
5.54
preprint

Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration

Hancheng Cao, Youyang Hou, Abdallah El Ali, Ruihao Zhu, Jie Li, L. Lin
preprint en
1 citations

Abstract

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.

Centrum Wiskunde & Informatica (NL), Emory University (US), Cornell University (US), Lumos Labs (United States) (US), Electronic Arts (United States) (US), Delft University of Technology (NL)
Openalex Percentile: Top 11%
Design Education and Practice
5.54
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Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration — Hancheng Cao, Youyang Hou, et al. · (2026) | TGRS Research Map | TGRS