Vibe Coding Reshapes Product Design Workflows and Collaboration
A recent study published on arXiv (2509.10652) investigates how generative AI facilitates 'vibe coding' among product teams, allowing them to convert natural language prompts into working prototypes and code. Conducted through interviews with 22 members from various sectors, including enterprises, startups, and academia, the study outlines a four-part workflow: ideation, generation, debugging, and review. While vibe coding enhances iteration speed, fosters creativity, and reduces barriers to participation, it also presents challenges like code reliability issues, integration difficulties, and excessive dependence on AI. This dynamic creates conflicts between efficiency-focused prototyping ('intending the right design') and thoughtful practice ('designing the right intention'), leading to new disparities in trust, accountability, and social stigma within teams.
Key facts
- Study published on arXiv with ID 2509.10652
- Based on interviews with 22 product team members
- Participants from enterprises, startups, and academia
- Four-stage workflow: ideation, generation, debugging, review
- Vibe coding accelerates iteration and supports creativity
- Challenges include code unreliability, integration, and AI over-reliance
- Tensions between efficiency-driven prototyping and reflection
- New asymmetries in trust, responsibility, and social stigma
Entities
Institutions
- arXiv