Vibe Coding in nephrology education: clinician-led, AI-assisted development of open-source interactive learning tools

Medical education increasingly incorporates digital technologies; however, many tools remain passive and text-based. Vibe Coding is a clinician-led design framework that embeds expert reasoning and the cognitive 'feel' of clinical decision-making into interactive educational tools. This study demonstrates its application in nephrology training through the rapid development of open-source, AI-assisted, web-based applications. We conducted a proof-of-concept development study using a structured, physician-led, AI-assisted process combining (1) deconstruction of clinical algorithms, (2) natural-language-to-code generation with modern large language models, and (3) iterative refinement of user interfaces. The target audience included nephrology trainees and educators, with source content derived from peer-reviewed educational literature. Four open-source, web-based applications were developed: (1) Kidney Stone Navigator for 24-hour urine analysis interpretation, (2) NephroFlow CKRT Clinical Copilot for dose and anticoagulation management, (3) Renal Tubular Acidosis Diagnostic Assistant for algorithmic diagnosis, and (4) Interactive Guide to Disorders of Volume for dynamic visualization of pathophysiology. Each tool mirrored expert reasoning, integrated automated calculations, and was publicly released on GitHub with live deployment for global educational use. Clinician-led, AI-assisted development enables the translation of static educational materials into interactive, open-access tools. The Vibe Coding framework demonstrates a scalable, reproducible model for innovation in medical education and supports transparent digital scholarship in nephrology.