Related papers: Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agenda

Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agenda

URL: http://arxiv.org/abs/2507.21928v1
Date: Tue, 29 Jul 2025 15:44:55 GMT
Title: Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agenda
Authors: Christian Meske, Tobias Hermanns, Esther von der Weiden, Kai-Uwe Loser, Thorsten Berger,
Abstract summary: vibe coding is a software development paradigm where humans and generative AI engage in collaborative flow to co-create software artifacts.<n>We show that vibe coding reconfigures cognitive work by redistributing labor between humans and machines.<n>We identify key opportunities, including democratization, acceleration, and systemic leverage, alongside risks.
Score: 4.451779041553598
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
Abstract: Software development is undergoing a fundamental transformation as vibe coding becomes widespread, with large portions of contemporary codebases now being AI-generated. The disconnect between rapid adoption and limited conceptual understanding highlights the need for an inquiry into this emerging paradigm. Drawing on an intent perspective and historical analysis, we define vibe coding as a software development paradigm where humans and generative AI engage in collaborative flow to co-create software artifacts through natural language dialogue, shifting the mediation of developer intent from deterministic instruction to probabilistic inference. By intent mediation, we refer to the fundamental process through which developers translate their conceptual goals into representations that computational systems can execute. Our results show that vibe coding reconfigures cognitive work by redistributing epistemic labor between humans and machines, shifting the expertise in the software development process away from traditional areas such as design or technical implementation toward collaborative orchestration. We identify key opportunities, including democratization, acceleration, and systemic leverage, alongside risks, such as black box codebases, responsibility gaps, and ecosystem bias. We conclude with a research agenda spanning human-, technology-, and organization-centered directions to guide future investigations of this paradigm.

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