A lot of parents I know are feeling a quiet unease right now. Not an acute alarm — more like a background disorientation. They sense the world their children are growing into is changing fast, but when it comes to deciding what to actually do differently, most of them default back to the path they walked themselves: study hard, get the credential, find a job. Not because they still believe it’s the right answer, but because they don’t have a clearer alternative to point to.

I don’t think this is a failure of imagination. I think it’s a structural gap, and it’s worth naming precisely before trying to address it.

The deal underneath entry-level work

For a long time, there was a simple economic logic underneath entry-level jobs: junior employees were cheap enough relative to their output that companies could afford to train them at the same time. The gap between what a junior produced and what they were paid functioned as an informal training subsidy. After a few years, that junior became productive enough to be worth their cost, and the company recovered the investment.

AI is breaking that deal — not because junior work suddenly stopped mattering, but because the same output can now often be produced by a senior person working with AI tools, at lower cost than hiring and training a junior. Juniors are no longer competing against an absolute productivity threshold. They’re competing against “senior plus AI.” That’s a much harder bar, and it changes the economics of whether companies hire junior people at all.

But this matters beyond job availability. The entry-level position was never just a job. It was where a lot of tacit, hard-to-name skills used to get absorbed: how to scope an ambiguous problem, how to tell when your own judgment is good enough, when to ask for help, how to defend a decision to someone whose opinion has real stakes for you. None of that was written down anywhere. It was passed on by people, in the course of real work, under real supervision.

When that rung thins out, the transfer mechanism thins with it — even for people who still get the job title.

Why this doesn’t fix itself

It would be reassuring if this were just a temporary market dislocation. But I don’t think it is, for a fairly plain reason: training juniors has always been something closer to a collective good than any individual firm’s optimal choice. Every company benefits from a supply of trained people existing in the market — but no company is proportionally rewarded for being the one that pays to produce them, especially when a trained person might leave for a competitor, or when AI has now made the investment unnecessary at the margin. That free-rider problem existed before AI. AI just removed the factor that used to make the math work out anyway.

Government subsidies, corporate training mandates, and curriculum reform are all reasonable responses to this kind of problem, and I’d support efforts on all three fronts. But they’re slow by nature — they require institutions to move, and the institutions involved (large firms, legislatures, school systems) happen to be exactly the slowest-moving parts of this whole system. The gap can’t wait for them alone.

A deliberately un-fancy idea

Rebuild the training mechanism of apprenticeship directly, without depending on employer hiring economics to fund it.

The structure is simple. Someone earlier in their formation works on a real project — something with actual external users, not a practice exercise — under the loose guidance of someone who is only a step or two ahead, not necessarily a career ahead. The goal is not to transfer technical skill; AI is honestly a pretty good tutor for that part now. The goal is to train a specific, nameable set of judgment moves that AI doesn’t train on its own: scoping an unclear problem, verifying AI output against reality rather than against plausibility, knowing how much scrutiny a decision deserves, choosing between approaches rather than just using the one at hand, knowing when to escalate rather than guess, and being able to defend a call after the fact to someone whose opinion actually matters.

When a cycle ends, the person who went through it is qualified to guide the next one — not because they’ve spent decades in the field, but because the edge required here is being a little ahead, not far ahead. That’s what makes this potentially scalable in a way the old apprenticeship model, with its dependence on scarce senior mentors, never quite managed to be.

What this is not trying to do

It is not a replacement for school, and it is not a credential. It is not trying to compete with universities or bootcamps at what they already do reasonably well. It is specifically aimed at the part of formation that used to depend on a real job existing to deliver it — and that part is becoming less reliable to count on.

I am starting in one domain — AI-assisted software development — partly because it’s where I have real material and credibility to offer, and partly because it’s one of the clearest places this rupture is already visible. But I don’t think the underlying problem is software-specific. If someone closer to another field wants to try the same pattern there, I would genuinely like to see that.

Why I’m writing this down

I’m not trying to publish a polished argument and move on. I’m starting a small project, and this is the thinking behind it — written down so it’s clear what we’re actually trying to train, why it matters now specifically, and so that if this works, the reasoning is legible enough for someone else to pick up, adapt, and run with.

If you’re a parent feeling the same quiet unease I described at the start, or someone early in a technical career wondering what’s actually worth practicing right now, I’d be glad to hear from you.