Ask someone twenty years ago what "financial literacy" meant, and they'd talk about budgeting, compound interest, maybe reading a balance sheet. Ask a sharp 22-year-old today, and the answer increasingly includes something that would have sounded out of place back then: knowing how to code.
That's not a coincidence, and it's not hype either. It's what happens when the tools for managing and growing money stop being locked inside institutions and start living on personal laptops. A decade ago, connecting to live market data, testing an idea against years of history, or automating a rule-based decision required infrastructure only a firm could afford. Today it requires a broker API key, a Python script, and a weekend. That shift alone has quietly redrawn what "being good with money" looks like.
We see this up close every cohort. The students who progress fastest aren't necessarily the ones who understand markets best on day one — they're the ones comfortable enough with code to turn an idea into something testable. They can take a rule like "only act when this condition holds and risk is capped at this level" and actually build it, instead of just describing it. That's a different kind of financial competence than reading a textbook ever produced, because it forces precision. You can't hand-wave logic to a script the way you can to yourself.
This isn't only about markets, either. Personal finance itself is becoming more programmable. People are writing scripts to track spending across accounts, model retirement scenarios, flag unusual transactions, or rebalance a portfolio the moment it drifts from target. None of this needed to be manual before out of choice — it was manual because the tools to automate it weren't accessible to individuals. Now they are, and the gap between "someone who understands their finances" and "someone whose finances quietly manage themselves" is starting to look a lot like the gap between someone who can code and someone who can't.
There's a legitimate question about whether this becomes a genuine literacy issue, the way basic numeracy or reading a contract already is. We think it's heading that way, but not because everyone needs to become a software engineer. Most students who come through don't want a coding career — they want just enough fluency to translate their own thinking into something a machine can execute reliably. That's a narrower, more achievable skill than "learn to code" usually implies, and it's exactly the kind of skill that compounds. Once you can automate one financial decision correctly, you tend to keep finding more that deserve the same treatment.
AI tools are lowering this barrier further, and faster than most people expect. A student who can't write a for-loop from memory can now describe what they want in plain language and get a working first draft, then learn by fixing what's wrong with it. That's a genuinely different on-ramp than the one available even three years ago, and it's pulling in people who would never have called themselves "technical."
None of this replaces judgment. Code that runs perfectly on bad logic just produces confident, well-executed mistakes. But the next generation entering the workforce is going to inherit a world where financial decisions — personal and professional — increasingly run through some form of automated system, whether they build it themselves or simply have to trust one someone else built. Understanding enough code to know what's actually happening inside that system isn't a niche skill anymore. It's closer to knowing how to read the fine print always was — except now the fine print is a script, and the people who can read it have a real advantage over the people who can't.
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