2026-06-21
Vibe coding in product teams: Reconfiguring AI-assisted workflows, prototyping, and collaboration
Publication
Publication
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.
| Additional Metadata | |
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| , , , , , , | |
| doi.org/10.1145/3808045.3808062 | |
| CHIWORK'26, the 5th Annual Symposium on Human-Computer Interaction for Work | |
| creativecommons.org/licenses/by/4.0/ | |
| Organisation | Distributed and Interactive Systems |
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Li, J., Hou, Y., Lin, L., Zhu, R., Hancheng, C.& El Ali, A. (2026, June 21). Vibe coding in product teams: Reconfiguring AI-assisted workflows, prototyping, and collaboration. Proceedings of the Symposium on Human-Computer Interaction for Work.https://doi.org/10.1145/3808045.3808062 |
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| Additional Files | |
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| Supplementary_Material_A.pdf Supplementary Material A - Interview Guide , 44kb | |
| Supplementary_Material_B.pdf Supplementary Material B - Description of Hybrid Thematic Analysis Approach , 2mb | |