Introduction to Vibe Coding for Dermatologists
What is Vibe Coding?
Vibe coding is a term coined to describe the practice of building software by describing what you want to an AI coding assistant, then iterating on the output through conversation. Instead of writing code line by line, you describe the behavior, the interface, the data flow -- and the AI generates the implementation. You review, refine, and redirect. The skill is not in syntax -- it is in knowing what to ask for, recognizing when the output is wrong, and understanding enough about the system to guide the AI toward a working solution.
Why Physicians Should Care
Physicians are domain experts. We know what clinical tools should do because we use them every day. But traditionally, translating clinical knowledge into software required either hiring a developer or spending years learning to code. Vibe coding changes that equation. A physician who can clearly articulate a clinical workflow can now build the tool to support it -- not perfectly, not at enterprise scale, but well enough to solve real problems in their own practice. The barrier between clinical need and software solution has never been lower.
The DermTools Case Study
DermTools started as a personal frustration. I was writing the same clinical notes over and over -- surgical reports, biopsy documentation, follow-up letters. Each note followed a predictable structure, but the existing EHR templates were rigid and poorly designed. I described what I wanted to an AI assistant: a template engine that could generate structured clinical notes with customizable fields, conditional sections, and bilingual support. Over several weeks of iterative development, the template engine grew into a comprehensive clinical platform -- DermTools -- incorporating differential diagnosis wizards, dermoscopic algorithms, scoring calculators, drug references, and patient education materials, all tailored for the Israeli dermatologist.
The Clinician-Coder Paradigm
Vibe coding enables a new role: the clinician-coder. This is not a physician who happens to know Python. It is a physician who uses AI-assisted development as a clinical tool -- the same way we use a dermatoscope or a surgical loupe. The clinician-coder does not need to understand compiler theory or database internals. They need to understand their clinical domain deeply enough to specify what the software should do, and to evaluate whether the AI's output meets that specification.
Getting Started: The Minimum Viable Skill Set
To begin vibe coding, you need three things. First, a clear problem statement -- a specific clinical workflow that is inefficient, error-prone, or tedious. Second, an AI coding assistant -- Claude, Cursor, GitHub Copilot, or similar tools. Third, a basic understanding of how software runs -- what a web server is, what a file system looks like, how to open a terminal and run a command. You do not need to know a programming language. You need to know your domain and be willing to iterate.
Common Objections and Honest Answers
Physicians often raise three objections to vibe coding. First: it is not real coding. This is true in the same way that laparoscopic surgery is not real surgery -- the output matters more than the method. Second: AI-generated code is unreliable. This is also true, which is why review and testing are essential parts of the workflow. Third: I do not have time. This is the strongest objection, but the counter-argument is that you are already spending time on the workflows that vibe coding automates. The question is whether a one-time investment in building a tool saves more time than the ongoing cost of the manual process.
The Future of Physician-Built Software
We are at the beginning of a fundamental shift in clinical software development. The next generation of clinical tools will not come from large health IT vendors with eighteen-month development cycles. They will come from clinicians who understand the problem space intimately and can now translate that understanding directly into working software. Vibe coding is the mechanism. The clinician-coder paradigm is the result. And dermatology -- with its visual data, procedural workflows, and entrepreneurial practice culture -- is uniquely positioned to lead this transformation.