Good Vibrations? A Qualitative Study of Co-Creation, Communication, Flow, and Trust in Vibe Coding

• URL: http://arxiv.org/abs/2509.12491v1
• Date: Mon, 15 Sep 2025 22:28:42 GMT
• Title: Good Vibrations? A Qualitative Study of Co-Creation, Communication, Flow, and Trust in Vibe Coding
• Authors: Veronica Pimenova, Sarah Fakhoury, Christian Bird, Margaret-Anne Storey, Madeline Endres,
• Abstract summary: 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.
• Score: 6.862249355928346
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Vibe coding, a term coined by Andrej Karpathy in February 2025, has quickly become a compelling and controversial natural language programming paradigm in AI-assisted software development. Centered on iterative co-design with an AI assistant, vibe coding emphasizes flow and experimentation over strict upfront specification. While initial studies have begun to explore this paradigm, most focus on analyzing code artifacts or proposing theories with limited empirical backing. There remains a need for a grounded understanding of vibe coding as it is perceived and experienced by developers. We present the first systematic qualitative investigation of vibe coding perceptions and practice. Drawing on over 190,000 words from semi-structured interviews, Reddit threads, and LinkedIn posts, we characterize what vibe coding is, why and how developers use it, where it breaks down, and which emerging practices aim to support it. We propose a qualitatively grounded theory of vibe coding centered on conversational interaction with AI, co-creation, and developer flow and joy. We find that AI trust regulates movement along a continuum from delegation to co-creation and supports the developer experience by sustaining flow. We surface recurring pain points and risks in areas including specification, reliability, debugging, latency, code review burden, and collaboration. We also present best practices that have been discovered and shared to mitigate these challenges. We conclude with implications for the future of AI dev tools and directions for researchers investigating vibe coding.

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