As a doctor who learned how to program, I started by writing useless Chrome extensions. One thing I learned early was that programmers generally do not like learning the nuances of medicine, and many are quite open about how little they want to learn it. I have tried convincing my fellow residents to learn a simple language like Lua or even just Python, but the resistance is even greater, despite the fact that they constantly express how they have always wanted to learn programming like I did.

I even went as far as setting up their IDEs, configuring their environments, and encouraging them to just vibe-code. It seems that the mental friction involved in switching domains is too high for most people to justify the reward. Perhaps the reward itself is not compelling enough, or perhaps this is simply the limit of adult motivation.

I started programming with Python around the time GPT-3 arrived, when Cursor had generous free tiers and excellent starter plans. A few Raspberry Pis, laptops, desktops, and countless hours of tinkering later, I discovered how much I enjoyed solving problems with software. There is so much to learn from the programming world: the concept of open-source software, the idea that people from anywhere in the world can collaborate on the same codebase, and the fact that many do so with little or no expectation of reward.

As this post points out, in the project I am currently working on—a comprehensive Clinical Decision Support System—it feels almost second nature to translate the rules, hidden rules, social dynamics of hospitals, and the common mistakes that we and our juniors make every day into software. Taking those observations and turning them into systems that work is surprisingly intuitive.

Perhaps the most valuable thing I gained from medical school, combined with my own personality, is the desire to keep learning. I naturally gravitated toward systems thinking, and the path forward seems clear to me: become a true expert in whichever specialties I ultimately practice, while simultaneously becoming highly skilled at systems thinking.

As for systems thinking itself, I find it useful to create rules not only for the codebase but also for the testing harnesses and development processes around it. The goal is to build systems that can enforce quality automatically as the codebase grows, ensuring that standards scale without requiring constant manual oversight.