Learn to Code 2.0

The sixteen-year-old deciding what to study. The eighteen-year-old heading into college. The twenty-two-year-old taking on massive debt for a profession already disappearing.

I was born in 1979. Officially I’m Gen X. But, I also sit in a weird transition generation people now call Xennials. We grew up analog and then lived through the transition into digital, and now we are living through the transition into AI in real time.

We had maps in the back seat, corded phones, street lights telling us when to come home, and suitcases without wheels. We also watched America move from being a manufacturing and industrial powerhouse into the internet age, the smartphone age, and now whatever this next AI era is going to become. That is why this moment feels familiar to me. We have seen this kind of economic and technological shift before.

When manufacturing jobs left the United States, people were told to “learn to code” like that was some serious answer to a huge national problem. It was not a serious answer. It was unrealistic, dismissive, and pretty damn offensive. You had people in their forties and fifties, people raising families, paying mortgages, and trying to make it to retirement, being told to just go learn a completely different technical skill and rebuild their lives. Everybody knew that was bullshit. It sounded clean as a slogan, but it did not match the reality of people’s lives.

I think we are back in that same moment again. The difference is that this time it is not factory workers being told to learn to code. This time, it is the people who already learned to code who are watching their jobs change.

The Job Already Changed

Over the weekend I was at a wedding, and I ended up talking to a lot of people who are software developers and engineers. Every single one of them told me some version of the same thing. A year ago, their job was writing code. They sat down in front of their computer, solved problems, debugged, and wrote code all day. Now, their job is much more about prompting AI to write code, checking AI’s work, correcting it, and guiding it toward the result they want. They are not doing the same job the same way. That shift did not take ten years. It took about a year.

That is the part I think people are missing. This is not some far-off theory about the future. It is already happening in the sectors closest to the technology. That does not mean all those jobs are gone, and I am not saying every layoff is directly tied to AI. But the work itself has changed, and once the work changes, the next question is obvious. How many people do you actually need to do it?

That is where we have to start asking questions. Some research says AI could displace or significantly change around 6 to 7 percent of the U.S. workforce over time, while broader estimates range from 3 to 14 percent depending on how adoption unfolds. That is millions of jobs. However, “Predictions that technology will reduce the need for human labor have a long history but a poor track record,” Briggs and Dong

Roughly 60 percent of U.S. workers today are in jobs that did not exist in 1940, and about 85 percent of employment growth since then has come from technology-driven change. So yes, jobs will be created too. That is how these transitions usually work. But that does not mean the transition is painless, and it definitely does not mean it is evenly distributed.

The people I worry about the most are not even the developers I talked to, because at least for now, they still have jobs and are adapting. I worry more about the next group coming up. The sixteen-year-old deciding what to study. The eighteen-year-old heading into college. The twenty-two-year-old taking on massive debt for a profession they think is stable. Entry-level legal work, paralegals, marketing, graphic design, admin work, call centers, software support, and a lot of basic knowledge work all look vulnerable to some degree.

Even in health care, I think a lot of non-specialty or general practice work could get compressed through telehealth and AI tools. The issue is not that AI replaces every human being. The issue is that it reduces the amount of labor needed, and when that happens, the entry point usually disappears first.

The Warning Signs Are Already Here

Now, I am not saying that every big layoff is AI. But when you start seeing tech layoffs pile up while companies are simultaneously making huge investments in AI infrastructure, you would have to be asleep not to at least ask the question. As of April 11, 2026, TrueUp’s tracker shows more than 91,000 tech layoffs this year across more than 200 companies.

That is why I think we are entering “learn to code 2.0.” The first version hit manufacturing towns and industrial workers. This version is likely to hit white-collar and entry-level knowledge work much harder. And if that happens, it becomes a regional problem, a tax base problem, a housing problem, and a social problem. We saw what happened when manufacturing left places like Cleveland, Pittsburgh, and Detroit. We know what dislocation looks like. The only difference this time is that the geography could be different and the workers being hit might wear business casual instead of steel-toed boots.

What really hit me after that wedding was not that the sky is falling tomorrow. It was that the public conversation still feels behind where reality already is. The people closest to the technology are telling you their jobs changed fast. The market data is showing tens of thousands of layoffs in the sectors closest to AI. The research is telling you millions of jobs are at least exposed to change. And yet most of the conversation is still either hype or denial.

The Solutions