Don’t Learn Python. Ever.

Learning a programming language is indisputably useful. It is not a point I am about to argue. However, whether you should learn a programming language like python, or not, is a deeper matter.

If you’re not building a career around software, if your profession is science, medicine, analysis, research, anything where code is a tool rather than your entire profession, I assure you, to “learn Python” is the wrong mountain to climb. Especially in this moment in time. I’m not saying that Python isn’t useful. It absolutely is. But usefulness and return on investment are not the same thing and you should be deliberate about investing your cognitive energy, efficiently.

What actually matters is conceptual fluency and heuristics.

Understanding the system, the structure, the logic, the moving parts. And then use that understanding as shortcuts and mental rules to operate inside that system without needing expert-level training.

Heuristics are simplified strategies the mind uses to navigate complexity. They’re not perfect, and they’re not meant to be exhaustive. They’re effective. They capture the patterns that work most of the time and allow you to reason, troubleshoot, and interpret situations without diving into every technical detail.

Here’s the clean way to think about it:

Conceptual fluency gives you the map. Heuristics tell you how to move through the map efficiently.

For programming, that translates to things like:

• “Always check the shape of your data first.”
• “Functions should do one thing.”
• “If the error makes no sense, your environment is probably broken.”
• “Don’t trust a model you don’t understand.”
• “If something feels overly complicated, you’re solving it the wrong way.”

These aren’t specialist skills. They’re general cognitive tools that let non-programmer scientists make sense of code, debug with intuition, and collaborate with AI effectively.

AI can handle the syntax now.

It can write the loops, load the libraries, debug the annoying errors, and generate the scaffolding. But AI can’t think for you. It can only extend the clarity you already have.

So if you’re a scientist or researcher, your time is better spent building the conceptual foundation rather than memorizing a language you’ll only use in fragments. When you get the principles, Python becomes the easy part. You look at code and it finally makes sense. You can guide the tool instead of feeling like you’re at its mercy.

Don’t learn Python.

Learn the systems of thinking that govern code.

That’s the part that makes everything else — including AI — actually work for you.

def hello():
    print("Hello world")