Vibe Coding for UX Design: Understanding UX Professionals' Perceptions of AI-Assisted Design and Development
- URL: http://arxiv.org/abs/2509.10652v1
- Date: Fri, 12 Sep 2025 19:28:38 GMT
- Title: Vibe Coding for UX Design: Understanding UX Professionals' Perceptions of AI-Assisted Design and Development
- Authors: Jie Li, Youyang Hou, Laura Lin, Ruihao Zhu, Hancheng Cao, Abdallah El Ali,
- Abstract summary: Generative AI is reshaping UX design practices through "vibe coding," where UX professionals express intent in natural language and AI generates prototypes and code.<n>We show how vibe coding follows a four-stage workflow of ideation, AI generation, debug, and review.<n>We find tensions between efficiency-driven prototyping and reflection, introducing new asymmetries in trust, responsibility, and social stigma within teams.
- Score: 17.585262775172055
- License: http://creativecommons.org/publicdomain/zero/1.0/
- Abstract: Generative AI is reshaping UX design practices through "vibe coding," where UX professionals 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 UX workflows and collaboration. Drawing on interviews with 20 UX professionals across enterprises, startups, and academia, we show how vibe coding follows a four-stage workflow of ideation, AI generation, debugging, and review. This accelerates iteration, supports creativity, and lowers barriers to participation. However, professionals 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 the lens of responsible human-AI collaboration for AI-assisted UX design and development, we contribute a deeper understanding of deskilling, ownership and disclosure, and creativity safeguarding in the age of vibe coding.
Related papers
- "Can you feel the vibes?": An exploration of novice programmer engagement with vibe coding [42.82674998306379]
"vibe coding" refers to creating software via natural language prompts rather than direct code authorship.<n>This paper reports on a one-day educational hackathon investigating how novice programmers and mixed-experience teams engage with vibe coding.
arXiv Detail & Related papers (2025-12-02T13:32:23Z) - Vibe Coding in Practice: Motivations, Challenges, and a Future Outlook -- a Grey Literature Review [2.5195922470930614]
Vibe coding is the practice where users rely on AI code generation tools through intuition and trial-and-error without necessarily understanding the underlying code.<n>No research has systematically investigated why users engage in vibe coding, what they experience while doing so, and how they approach quality assurance (QA) and perceive the quality of the AI-generated code.<n>Our analysis reveals a speed-quality trade-off paradox, where vibe coders are motivated by speed and accessibility, often experiencing rapid instant success and flow'', yet most perceive the resulting code as fast but flawed.
arXiv Detail & Related papers (2025-09-30T22:35:00Z) - Good Vibrations? A Qualitative Study of Co-Creation, Communication, Flow, and Trust in Vibe Coding [6.862249355928346]
We propose a grounded theory of vibe coding centered on conversational interaction with AI, co-creation, and developer flow and joy.<n>We find that AI trust regulates movement along a continuum from delegation to co-creation and supports the developer experience by sustaining flow.
arXiv Detail & Related papers (2025-09-15T22:28:42Z) - Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows [60.04362496037186]
We present the first controlled study of developer interactions with coding agents.<n>We evaluate two leading copilot and agentic coding assistants.<n>Our results show agents can assist developers in ways that surpass copilots.
arXiv Detail & Related papers (2025-07-10T20:12:54Z) - Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI [0.36868085124383626]
Review presents a comprehensive analysis of two emerging paradigms in AI-assisted software development: vibe coding and agentic coding.<n> Vibe coding emphasizes intuitive, human-in-the-loop interaction through prompt-based, conversational interaction.<n>Agentic coding enables autonomous software development through goal-driven agents capable of planning, executing, testing, and iterating tasks with minimal human intervention.
arXiv Detail & Related papers (2025-05-26T03:00:21Z) - FeedQUAC: Quick Unobtrusive AI-Generated Commentary [8.057486493973304]
We introduce FeedQUAC, a design companion that delivers real-time AI-generated commentary from a variety of perspectives.<n>We discuss the role of AI feedback, its strengths and limitations, and how to integrate it into existing design.<n>Our findings suggest that ambient interaction is a valuable consideration for both the design and evaluation of future creativity support systems.
arXiv Detail & Related papers (2025-04-23T04:48:00Z) - AI Automatons: AI Systems Intended to Imitate Humans [54.19152688545896]
There is a growing proliferation of AI systems designed to mimic people's behavior, work, abilities, likenesses, or humanness.<n>The research, design, deployment, and availability of such AI systems have prompted growing concerns about a wide range of possible legal, ethical, and other social impacts.
arXiv Detail & Related papers (2025-03-04T03:55:38Z) - User Experience Design Professionals' Perceptions of Generative
Artificial Intelligence [15.833434677266427]
We interviewed 20 UX Designers, with diverse experience and across companies (startups to large enterprises).
We found that experienced designers are confident in their originality, creativity, and empathic skills, and find GenAI's role as assistive.
We discuss implications for human-GenAI collaboration, specifically copyright and ownership, human creativity and agency, and AI literacy and access.
arXiv Detail & Related papers (2023-09-26T20:04:30Z) - Designerly Understanding: Information Needs for Model Transparency to
Support Design Ideation for AI-Powered User Experience [42.73738624139124]
Designers face hurdles understanding AI technologies, such as pre-trained language models, as design materials.
This limits their ability to ideate and make decisions about whether, where, and how to use AI.
Our study highlights the pivotal role that UX designers can play in Responsible AI.
arXiv Detail & Related papers (2023-02-21T02:06:24Z) - Seamful XAI: Operationalizing Seamful Design in Explainable AI [59.89011292395202]
Mistakes in AI systems are inevitable, arising from both technical limitations and sociotechnical gaps.
We propose that seamful design can foster AI explainability by revealing sociotechnical and infrastructural mismatches.
We explore this process with 43 AI practitioners and real end-users.
arXiv Detail & Related papers (2022-11-12T21:54:05Z) - Investigating Explainability of Generative AI for Code through
Scenario-based Design [44.44517254181818]
generative AI (GenAI) technologies are maturing and being applied to application domains such as software engineering.
We conduct 9 workshops with 43 software engineers in which real examples from state-of-the-art generative AI models were used to elicit users' explainability needs.
Our work explores explainability needs for GenAI for code and demonstrates how human-centered approaches can drive the technical development of XAI in novel domains.
arXiv Detail & Related papers (2022-02-10T08:52:39Z) - A User-Centred Framework for Explainable Artificial Intelligence in
Human-Robot Interaction [70.11080854486953]
We propose a user-centred framework for XAI that focuses on its social-interactive aspect.
The framework aims to provide a structure for interactive XAI solutions thought for non-expert users.
arXiv Detail & Related papers (2021-09-27T09:56:23Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.