Vibe Coding a Research Probe for Exploring AI/Voice Based Code Reviews

Abstract

Generative AI tools increasingly shape established software engineering practices such as code review, but the socio-technical implications of using AI for these practices remain understudied. In this paper we first introduce vibe coding (Andrej Karpathy [@karpathy], 2025) as a method for allowing researchers with limited coding experience to rapidly create custom made probes for conducting research. Guided by Alami and Ernst’s (2025) findings on AI-generated feedback for code review, we introduce a vibe coded AI/Voice based code review prototype as a provotype (Boer and Donovan, 2012). We then outline an explorative study to critically assess the socio-technical effects of using AI based voice interfaces in code reviews. We propose a qualitative approach, based on the Disruptive Research Playbook (Storey et al., 2024), involving Danish software developers to investigate voice-based feedback's impact on topics including trust, collaboration, and perceived skill shifts. Initial methodological reflections emphasize the need for cautious exploration using the provotype as an intervention for gathering data in the form of reactions, expectations, and concern about the effects of AI interactions, in the established professional practise of code review. Next steps are to finalize the provotype, complete the research design and collect and analyze qualitative data from interventions with danish software developer teams.