Beyond 'Learn to Code': The Case for Apprenticeship in an AI Age

The Davos crowd just told us that 50-60% of white-collar work will be automated in the coming years. The headlines framed this as job elimination. The actual quote was closer to job transformation. I agree with the latter, and the distinction matters enormously.

Because here's what's actually happening: the marginal revenue product of entry-level knowledge work is plummeting. Not because the work disappears, but because a senior person with generative models can now produce what used to require a team. The work exists. The value proposition of paying someone six figures to do it when they can't produce six figures of value does not.

This isn't a prediction. It's already here.

The Credential Lie Reaches Its Final Chapter

When I was trying to break into tech, I had a mechanical engineering degree and a coding bootcamp certificate. I was competing against people with computer science degrees and MBAs. MIS degrees with master's on top. The credential gap made it brutal to get interviews, let alone offers.

Everyone recognized that a bachelor's in mechanical engineering meant I could solve problems. That was my actual skill. But the expectation was that without the right letters after my name, I couldn't possibly be proficient in the details.

Here's what's changed: the details are now the easy part.

Generative models are trained on all that theoretical knowledge. They can do web searches and become fluent in new ideas faster than any human. What you can learn in a classroom, AI already knows. So what exactly are we paying for when we pay for credentials?

Applied knowledge. Experience. Wisdom, even, though that word takes on a theological dimension I won't fully explore here. Wisdom is knowledge applied, experience gained, lessons learned. Not information absorbed and regurgitated on a test.

You cannot learn wisdom in school.

The Inversion Nobody Wants to Talk About

I spent months trying to land my first tech job. Dozens of applications. Half a dozen interviews. Rejections because I didn't have the right certification.

What finally broke through? I took quite a bit less money than the bootcamp said I should be making. Less than the market data suggested for entry-level positions. I knew that once I got in and started adding value, I could demonstrate what I could do and advocate for myself from there.

Which I did.

Now I'm watching the inversion of that experience play out across the industry. The people willing to start working somewhere, accept lower initial compensation, and gain actual experience are going to outcompete people who spend seven to ten years in academia. It's not even going to be close.

The amount of experience and judgment you can cultivate in five years on the job, doing actual work that matters, versus an academic setting where things are pretty removed from reality in many cases? No contest.

Jobs Are Not Products

Dario Amodei says 50% of entry-level white-collar jobs could be eliminated within five years. Larry Fink warns we need a credible plan for broad participation or we'll see the same upheaval blue-collar workers faced from globalization.

But let's be precise about what "eliminated" means.

Jobs aren't products. You don't manufacture them. A job forms when a business leader says: I have a problem, and I can employ someone whose marginal revenue product will exceed their marginal cost. That's it. That's the entire mechanism.

When entry-level marginal revenue product plummets because AI plus a senior person can do that work, the marginal cost of employing entry-level people also has to plummet. The jobs don't disappear. The salary expectations have to change.

This is what I keep trying to explain to people, and they hate it. Everybody hates it.

Look at Hollywood. Look at the music industry. 99% of actors and musicians make very low wages compared to the top 1% making millions or billions. Does that mean there aren't entry-level positions in those fields? No. There are. They just don't pay what a Grammy-winning artist or movie star makes.

Somehow we convinced multiple generations that a bachelor's degree, a liberal arts degree, guarantees a certain level of material comfort and employment. That's not how the world works. It never was. The guarantee was always illusory, and AI is just the final nail in that coffin.

The Disconnect

The biggest disconnect between what business leaders say and what universities prepare students for is simple: universities are still perpetuating the lie that a piece of paper guarantees a good job.

That lie was already being exposed in the 1990s. There was a movie called PCU with Jeremy Piven, a satire on college life, with a line about how you could major in Game Boy if you knew how to BS. That was 30 years ago. Satirical and hyperbolic, sure, but pointing at something real.

We've had three decades of this accelerating. Students using ChatGPT to get through classes nobody was really engaging with anyway. A shift away from the classics and core Western thought toward increasingly niche ideologies divorced from real-world application. And then AI finished the job.

The university was already failing. Generative models just made that failure impossible to ignore.

What 17-Year-Olds Need to Hear

When you're 17 and deciding what to do after high school, you may already be waiting too long.

High school when I was going was a joke. It's even more of a joke now. Teachers are good people for the most part, trying really hard. But when you dig into the statistics and look at reality, it's glorified daycare.

The Prussian model of public education had an explicit goal: produce good citizens who could work in factories. Smart enough to run the machines, dumb enough not to revolt. You can look up the history. This is just reality.

What will it take to shift perception about vocational paths being "less than" academic ones?

Unfortunately, it's going to take a crisis.

Younger millennials and Gen Z were sold a lie. Older millennials like me at least saw what the pathway to success looked like when it actually worked. We saw it happen to our parents. These younger generations only heard about it from their boomer grandparents talking about "back in my day."

Paradigm shifts don't happen through nice conversations where everyone acknowledges that maybe things aren't going the way we thought and maybe we had some bad ideas. There's a crisis. The only question is whether it's sooner or later.

But that doesn't mean smart, enterprising individuals can't take charge of their own destiny.

What Experience Actually Teaches

Let me tell you about my own trajectory.

When I was first starting out, I was all about the technical solution. Can I make it do what we want? Before generative AI, there was actual craft to that. You had to read docs, look at what others were doing, adapt it, write the code, get the syntax right. I was good at it.

Two or three years in, I realized something that changed everything.

Building relationships. Manufacturing buy-in. Getting everybody on the same page. Communicating your intentions and following through with tact, humility, grace, and compassion.

That is way more important than all the technical book knowledge in the world.

I was working for a company maybe six years ago. They had a sharp guy who was the bottleneck for everything. Death grip on their infrastructure, all source code, nothing getting done without his approval. He had good reason for it, having been burned by mediocre hires before.

I came in knowing exactly how to automate and simplify all their manual deployment and versioning work. Had a DevOps friend ready to do the implementation. Talked through the technical approach. Management said they were going to do it.

At the end of the day, they backed out. Changed their minds. Because we couldn't get this guy on board with the idea that someone could make his life easier. We couldn't build that relationship. Couldn't get that buy-in.

It didn't matter that we had the technical know-how. Having the right answer and the technical ability means nothing if you can't get someone to let go of their death grip on control and let somebody help them.

That's not a technical problem. And it's not a problem generative models can solve.

The Strategic Trade

Here's where most people get the math wrong.

They look at shared housing, at living below their means, at taking less money to break in, and they see sacrifice. They see loss of status. They see regression.

That's exactly backwards.

Reducing your personal overhead is the mechanism that allows you to price yourself into environments where you can extract wisdom from people who have it. It's not a defensive reaction to poverty. It's a strategic power move.

When you need six figures to survive, you need six figures to take a job. Which means you can't take the job that pays 25K but puts you in the room with the senior person whose judgment and experience you need to absorb. You've priced yourself out of the apprenticeship.

When your overhead is 15K a year because you're splitting rent four ways or living at home, suddenly that 25K entry point becomes possible. You're not losing money. You're buying equity in something the market can't automate: demonstrated competence and human trust.

Colleagues of mine are doing this right now. Four people to an apartment. That's how they're making it while building the experience that will compound for decades.

We act like this is crazy talk, but people did this for years. Boarding houses existed. They still exist in manufacturing centers around the world. Sometimes that's got to be the first step.

The person who spends five years in a low-overhead, high-learning environment accumulates something that can't be taken away. Meanwhile, the person who spent those same five years in graduate school accumulates debt and theory that AI already knows.

One of them is building an asset. The other is building a liability.

The lifestyle sacrifice isn't the cost of the apprenticeship model. It's the buy-in. And the return on that investment is becoming un-fireable in a market that is increasingly priced for perfection.

What AI Can Never Know

AI can't build a relationship. It's all pattern matching. Generative models aren't your friend and never will be. They don't understand friendship or love or relationship because they don't have the ontological perception required to understand what those concepts mean.

Their level of being isn't high enough to understand these human concepts.

The smartest AI in the world, all the docs perfectly explained, the ability to write exactly the right code: none of it matters when I'm not communicating effectively, not building relationships, not manufacturing buy-in.

This is sad for me personally because I'm great at the technical solutions. Even with generative models, I'm still way better at figuring things out at higher levels of abstraction. That's always been my strength.

Putting in the work to build relationships and community, showing humility and grace and compassion: that doesn't come easily to me. It's hard. Something I have to work at every single day.

But that's what the job actually requires. That's what wisdom looks like applied.

The Debt Cycle Closes

Here's the connection nobody wants to make.

The plummeting marginal revenue product of individual workers is not separate from the declining stability of the institutions that depend on that productivity. They're the same phenomenon viewed from different angles.

For 75 years, and certainly for 50, we've been living on borrowed time. Borrowed capital. Borrowed productivity. Cultural expectations that outpaced physical reality. We let manufacturing capital go overseas. We consumed our accumulated wealth instead of maintaining it. We convinced ourselves that credentials could substitute for competence.

The Soviet Union collapsed in my lifetime. What felt like an unending monolith, nearly 80 years of political domination, completely devolved in just a year or two. I was in school when it happened. I remember seeing the headline in the Tulsa Tribune, the evening paper my dad took, which has since gone defunct.

That was evidence of how the world really works. Empires rise and fall. Political entities come and go. Our modern conception of stability is more illusion than reality.

When I'm asked what the coming crisis looks like, I picture something on the scale of the Great Depression or the French Revolution. Massive dislocation. Massive correction. This is not random catastrophe. This is the natural closing of a debt cycle where a society can no longer fund its own complexity.

The institutions that promised credentials would guarantee prosperity are themselves dependent on the productivity of the people they credentialed. When those people can no longer produce enough value to sustain the system that created them, the whole structure becomes unstable.

Apprenticeship as Survival Strategy

This is why the case for apprenticeship is not just a career hack. It's a survival strategy for a post-institutional world.

The only stable currency in what's coming is demonstrated competence and human trust. Not diplomas. Not certifications. Not credentials that say you absorbed information and regurgitated it on tests.

The ability to solve real problems. The relationships that let you operate in environments where problems get solved. The judgment that comes from years of applied knowledge, not theoretical knowledge.

I'm not watching for signals that crisis is arriving. The signals are already here. What I'm focused on is my own life. Doing what I know is right. Honoring my creator. Trying to live in a Christ-like way. The scope and enormity of these macro events is too great to effectively plan for.

What you can plan for is developing the experience, judgment, and relational capacity that no credential can substitute for and no AI can replicate.

People could attack me and say I don't care about those facing this transition. I do care. I have enormous compassion for them. That's exactly why I'm trying to give them the pathway forward to successful, happy, fulfilled lives.

The people lying to them about making six figures straight out of college? They don't have their best interests at heart. They're trying to maintain a house of cards. Building on a shaking foundation.

The Math That Matters

The ratio of value between time spent learning theory and time spent applying knowledge in the real world has inverted.

The person who accepts the strategic trade, who reduces overhead to buy into high-learning environments, who accumulates five years of judgment while their peers accumulate credentials, will have built something that compounds.

The person still chasing credentials will emerge with debt, theory that AI already knows, and no demonstrated ability to build the relationships and trust that actually make work happen.

Five years is a long time to be behind.

And in a world where institutions are closing out their debt cycles, five years of demonstrated competence and human trust might be the difference between thriving and drowning.

That's the case for apprenticeship in an AI age. Not because classrooms are worthless, but because the game has changed and most people haven't noticed yet.