Comparative analysis between Scientific Research Methodology, Industrial Design Project Methodology and Vibe Coding Methodology with Artificial Intelligence

Abstract

The text analyzes three distinct but complementary methodologies: (1) the scientific methodology, (2) the industrial design methodology, and (3) the emerging methodology of Vibe Coding with artificial intelligence (AI); highlighting their objectives, validation criteria, and applications. Science seeks to generate verifiable knowledge through systematic processes (such as MC14 or the validation instances of Juan Samaja-UBA), prioritizing replicability and theoretical rigor. Industrial design, synthesized in frameworks such as MUDI, is oriented towards transforming reality through innovative and functional solutions, validated by their usability and context. Vibe Coding democratizes digital development through human-AI collaboration, accelerating prototyping, although it faces technical and ethical limits (scalability, algorithmic biases). Although they are not mutually exclusive, their differences lie in their core validations: science in theory and replicability, design in practical functionality, and Vibe Coding in efficiency and digital experience. Their strategic integration depends on the project objective: theoretical understanding, material transformation, or agile innovation. For example, scientific techniques can validate design needs, while Vibe Coding combined with MUDI enables iterative prototyping. MUDI stands out as a flexible framework for industrial design, while Vibe Coding redefines digital development, provided it is managed ethically. Together, these methodologies reflect disciplinary evolutions: science toward causal precision, design toward responsible innovation, and AI toward technological accessibility. However, AI remains an enabler, not a substitute, for human creativity, underscoring the need for methodological rigor in a technologically dynamic environment.