Vibe Coding: intention instead of implementation

Hohn, Christian

doi:10.1515/icom-2026-0018

Vibe Coding: intention instead of implementation

2026-01-01

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DOI：10.1515/icom-2026-0018

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Large Language Models (LLMs) and AI-assisted development tools are reshaping the way designers and UX professionals work. Under the term Vibe Coding, we describe a practice-oriented mode of working in which functional prototypes and software artifacts primarily emerge through iterative, natural language conversation with an LLM. Based on real-world projects, this article examines Vibe Coding from the perspective of two UX practitioners. Rather than representing a technological rupture, our observations suggest that Vibe Coding can be understood as a consistent extension of rapid prototyping. The key difference lies in the division of labor: instead of manual implementation, the emphasis shifts toward intent formulation, contextual steering, and continuous quality assessment. At the same time, diverse use cases reveal clear limitations. Without a defined UX process, user understanding, and explicit quality criteria, Vibe Coding quickly produces functional but generic output. Based on practical experience, we derive an Intent-Context-Quality model and discuss which competencies become newly important in Vibe Coding and which remain fundamentally central. This article presents a practice-based reflection grounded in real-world projects. It critically examines how Vibe Coding operates in professional UX contexts and outlines transferable insights for practitioners and researchers alike.

Keywords:

Vibe Coding

AI-assisted design

conversational prototyping

human-AI collaboration

UX skills

design-development convergence

Vibe Coding: intention instead of implementation

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