I’ve been thinking about this for a long time, and the conclusion I keep reaching hasn’t changed — it’s only become clearer. What’s interesting is that I didn’t arrive here by studying history first. I arrived here by watching what was happening around me: at work, in politics, in society, and in the behavior of people entering the workforce. Only later did I realize that what I was seeing fits a pattern that shows up repeatedly across civilizations.
The core issue is simple, even if the implications aren’t:
There is more work to do than there are people capable of doing it.
Once you accept that premise, everything else starts to line up.
For years now, I’ve watched younger workers enter the labor force, and what I’ve seen isn’t best described as laziness. Laziness implies ability without effort. What I see far more often is something worse: an inability to function independently without explicit instruction. Adults in their early twenties who cannot handle ambiguity, cannot problem-solve, cannot confront stress, and shut down the moment something deviates from expectation.
This isn’t an attack on them as individuals. It’s an observation of an environment that produced them. A generation raised with minimal friction, minimal responsibility, and minimal consequences does not magically turn into resilient adults at eighteen. They turn into adults who have never developed agency — the internal belief that this is my problem, and I’ll figure it out.
That loss of agency is not cosmetic. It’s structural.
At the same time, the generation that still possesses that agency — the people who know how to fix things, keep systems running, absorb stress, and operate without supervision — is aging out. Retirements are accelerating. Institutional knowledge is leaving. And the replacements are not arriving at the same rate, nor with the same capability.
This alone would be manageable if it were isolated. It isn’t.
The problem compounds when you look at what kind of work society increasingly needs done.
Modern civilization rests on a surprisingly narrow foundation: energy, logistics, infrastructure, water, food, healthcare. Everything else sits on top of that physical base. And those base systems are not abstract. They require people who show up, make decisions under pressure, and accept that failure has consequences.
Over the last few decades, we optimized those systems for efficiency and cost. Redundancy was stripped out. Just-in-time logistics became the norm. Maintenance was deferred. Slack was eliminated. That worked as long as labor was abundant and competence could be assumed.
COVID didn’t break those systems — it revealed how thin they already were. The system didn’t collapse, but it also didn’t rebuild its margins afterward. It stabilized at a lower tolerance for disruption.
Now layer in demographics.
As the Baby Boomer generation continues to age, healthcare demand doesn’t rise gradually — it accelerates. Chronic conditions, long-term care, multi-system health issues, and end-of-life care all consume enormous amounts of labor. Healthcare is already strained, already burning people out, already competing for the same pool of stress-tolerant workers that infrastructure, logistics, and energy depend on.
This is where the math starts to get ugly.
Even if we add millions of people to the workforce each year on paper, headcount is not the same thing as capacity. An effective workforce — people who can reliably perform essential work under pressure — is a fraction of the total. Managers see this every day, even if the statistics don’t capture it.
At the exact moment when demand for competent labor is exploding across multiple essential sectors, the supply of that labor is shrinking.
That is not a cyclical issue. It’s a structural imbalance.
This is where many people insert AI into the story as the savior. And that’s where the analysis usually goes off the rails.
AI is not free. It is not weightless. It is not purely digital. It is one of the most physically demanding technologies ever deployed at scale. Data centers require massive amounts of electricity, cooling, water, construction, maintenance, and logistics. They demand reliability, not intermittency. They increase load on grids that are already stressed and require infrastructure that is already short on labor.
AI may reduce labor in certain white-collar tasks, but at the system level it adds demand exactly where we are already constrained: energy, construction, logistics, and operations. It does not remove the bottleneck. It tightens it.
And if AI becomes a substitute for developing human competence — a kind of digital helicopter parent — then it delays adaptation while making the eventual correction harsher.
When multiple constraints converge like this, systems don’t innovate their way out smoothly. They simplify.
They pull back.
They attempt fewer projects, in fewer places, with narrower margins for error. They prioritize reliability over expansion. They stop trying to serve everyone equally.
This is where geography reasserts itself.
Regions that can reliably stack energy, water, logistics access, the ability to build, and a remaining base of skilled labor will continue to function at a high level. Regions that cannot will downshift — not necessarily collapse, but degrade in reliability, affordability, and opportunity.
This is why the last thirty years are a poor guide for the next ten.
For decades, places like California and New York dominated because capital, talent, and cultural influence concentrated there. But dominance in a low-constraint world does not guarantee resilience in a high-constraint one. Political and regulatory realities matter once energy, labor, and infrastructure become binding limits instead of background assumptions.
At the same time, regions that are open to reindustrialization, infrastructure investment, and energy realism — Texas and parts of the South being obvious examples — gain relative power. But even they face the same clock: they must rebuild workforce capacity before it disappears entirely.
Capital and political will are not enough if there is no one left who can actually do the work.
Zoom out further, and the global picture doesn’t provide relief.
Interdependence reduces the odds of immediate, total war — too many countries depend on each other to sever ties cleanly. But as standards of living decline and systems strain, instability becomes chronic. Proxy wars, economic warfare, internal unrest, political radicalization. People do not become more rational when their lifestyle worsens. They become emotional, ideological, and angry.
The radicalization of politics in the United States fits this pattern. It is not about one party being right or wrong. It is about a growing disconnect between narrative and physical reality, combined with a population under stress. That combination historically leads to fragmentation, not consensus.
Which brings me to the final, unavoidable conclusion — the one that keeps resurfacing no matter where I start the analysis.
We are entering a decade defined not by collapse, but by constraint.
Labor is the limiting factor.
Energy is the gating factor.
Infrastructure is the bottleneck.
Logistics is the circulatory system.
Healthcare is the load multiplier.
Geography is the selector.
In that environment, societies do not rise or fall evenly. They stratify. They concentrate capability, capital, and stability into fewer hands and fewer places.
And that is why the path from middle-class comfort to elite position has never been about paper wealth or passive appreciation. It has always been about control — control of bottlenecks, control of essential systems, control of assets that cannot be ignored even when everything else contracts.
The uncomfortable truth is that insight alone does nothing. Capital is required to acquire those assets. And generating that initial capital is the hardest part — because it must be done before the dislocation, in the unglamorous work that society still needs but increasingly avoids.
That is how elite classes have always been formed during transitions: not by predicting collapse, but by positioning early, building capital engines in essential sectors, and converting competence into ownership when the window opens.
The die may be cast for the direction of society as a whole. But individual outcomes are not.
The next decade will not reward comfort, abstraction, or consensus thinking. It will reward people who understand constraints, operate close to reality, and are willing to build leverage where others refuse to look.
That isn’t pessimism.
It’s pattern recognition.
KON Investing 