Vibe Coding for UX Design: Understanding UX Professionals' Perceptions of AI-Assisted Design and Development
This study investigates how generative AI–enabled “vibe coding”—the rapid prototyping and code generation driven by natural language instructions—reconfigures UX workflows and collaborative practices. Drawing on in-depth interviews with 20 UX practitioners, and integrating insights from human–computer interaction and organizational behavior theory, the research identifies a four-phase practice model (ideation → generation → debugging → review) and introduces a conceptual tension framework between *intentional design* and *design intention*. Results indicate that vibe coding significantly accelerates prototype iteration and lowers technical barriers for designers; however, it concurrently introduces critical challenges—including diminished code reliability, integration complexity, ambiguous accountability, contested creative ownership, and erosion of team trust—thereby exposing risks of skill atrophy and professional stigmatization. The study contributes a theoretically grounded, empirically validated framework for responsible human–AI co-design in UX practice.