AsianDadEnergy's Podcast

Nine months ago, I was laid off from my Big Tech job.

After 25 years in the technology industry, I suddenly found myself outside the machine I had spent most of my adult life helping to operate.

I call it involuntary early retirement.

And I know how fortunate I am.

I had spent years working in well-paid technology jobs, saving aggressively and investing. That eventually gave me financial independence, the ability to pay for my life without needing a traditional paycheck.

So when the layoff came, I didn’t have to immediately scramble for another job.

Instead, something strange happened.

I got something most people spend their entire lives chasing:

I got my time back.

And with that time came a perspective I never had while I was working.

For the first time, I was able to step outside the flow of normal life and actually watch it.

And from that vantage point, I’ve started to wonder whether many of the things we’ve been taught about how to live are fundamentally wrong.

Maybe we’ve been sold a pack of lies.

Not necessarily by some evil mastermind sitting in a dark room plotting against us.

Rather, these are ideas that have been passed down through families, schools, workplaces, media, and culture for generations.

Ideas that seem so normal that we rarely stop to question them.

Here are four of them.

Lie #1: Compliance Will Keep You Safe

Most of us are trained to comply from the moment we’re children.

Get good grades.

Listen to your parents.

Get into the right school.

Get a good job.

Show up on time.

Work hard.

Follow the rules.

Don’t cause trouble.

I grew up in a fairly traditional East Asian family, and this conditioning was particularly obvious.

Approval was often earned through obedience.

Do what you’re supposed to do, and you are rewarded.

Go against the expectations of your family or society, and you’re risking disapproval.

And this conditioning doesn’t end when you become an adult.

It simply changes form.

At university, you’re expected to follow the curriculum.

At work, you’re expected to follow instructions.

And somehow, being constantly busy has become a proxy for being important.

Look busy.

Answer your emails.

Attend the meetings.

Hit your deadlines.

Work late.

Keep producing.

Eventually, we internalize the idea that our value comes from our usefulness to the machine.

But here’s the uncomfortable part:

The machine doesn’t love you back.

You can spend decades being the perfect employee and still get discarded when you’re no longer needed.

A company can eliminate your position because of a reorganization.

Your skills can become obsolete because of new technology.

Your health can deteriorate.

You can simply get older.

And suddenly, after years of loyalty and compliance, you’re out.

That’s what being laid off taught me.

I had spent 25 years becoming increasingly valuable within the system.

And then one day, the system simply decided it didn’t need me anymore.

That’s when I realized something:

Compliance was never a guarantee of safety.

And it certainly wasn’t proof of my intrinsic worth as a human being.

I was simply a replaceable component in a very large machine.

Lie #2: More Freedom Automatically Increases Well-Being

This one is much harder to accept.

Because freedom sounds wonderful.

Who wouldn’t want complete control over their time?

Imagine waking up every morning with nowhere you have to be.

No boss.

No commute.

No deadlines.

No meetings.

No one telling you what to do.

This is supposed to be the ultimate reward for financial success.

Work hard.

Make money.

Invest.

Become financially independent.

And eventually, you’ll be free.

Except there’s a problem.

Freedom doesn’t automatically give you a reason to use it.

After my layoff, I had almost total autonomy over my time.

And almost immediately, I started drifting toward the path of least resistance.

Social media.

YouTube.

Video games.

Television.

Other forms of passive consumption.

Basically, anything that required very little effort.

And after a while, I found myself in an existential spiral.

Because consumption isn’t the same thing as living.

You can spend an enormous amount of time entertaining yourself without actually doing anything meaningful.

That’s when I realized something uncomfortable:

A job doesn’t just give you money. It gives your day structure.

It gives you obligations.

It gives you goals.

It gives you people to interact with.

It gives you something you are expected to accomplish.

Even a terrible job can provide a kind of artificial purpose.

Take all of that away, and you’re suddenly forced to answer a much harder question:

What exactly am I supposed to do with my life?

That’s a much harder problem than figuring out how to spend a paycheck.

And I suspect this is one of the biggest challenges humanity will face if we eventually reach a world where technology provides everyone’s basic material needs.

Imagine universal basic income.

Food, shelter, healthcare and basic necessities are covered.

Nobody has to work.

Everyone is free.

Sounds like paradise.

But what happens when billions of people suddenly have complete control over their time without any corresponding sense of purpose?

I don’t know.

But I suspect the answer isn’t necessarily paradise.

Because human beings don’t just need comfort. We need meaning.

And discovering what that meaning is can be brutally difficult.

Lie #3: Relationships Are Fungible

Modern society has become extraordinarily good at treating people like commodities.

Employees are resources.

Customers are numbers.

Dating apps turn romantic relationships into catalogs of potential alternatives.

If someone doesn’t work for you anymore, there’s always another person waiting.

Swipe left.

Swipe right.

Next.

We’re increasingly encouraged to think of ourselves as independent economic units whose primary goal is personal happiness and self-actualization.

If something doesn’t make us happy anymore, discard it.

Find something better.

Upgrade.

Move on.

And perhaps that’s sometimes necessary.

But there is something deeply wrong with applying this logic to human relationships.

People aren’t interchangeable.

Your spouse isn’t a product.

Your child isn’t a subscription.

Your friend isn’t an employee.

And your parents aren’t replaceable when a newer model comes along.

Early retirement has given me something I didn’t have for most of my working life:

Time.

And that time has allowed me to see which relationships in my life are genuine.

The people who still want to spend time with you when you no longer have an impressive corporate title or a big salary?

Those relationships are real.

But I’ve also learned something much more painful.

Time isn’t reversible.

You can repair a damaged relationship.

You can reconnect.

You can apologize.

You can try to make up for lost years.

But you can’t go backward.

I learned this personally with my son.

When he was very young, I was almost never around.

My wife and I had a mountain of student debt, and I was working a demanding technology job while simultaneously running a smartphone app business on the side.

I was doing what I thought I was supposed to do.

Work.

Earn.

Pay off debt.

Build a career.

Provide for the family.

And somewhere along the way, I wasn’t there.

Now my son is a teenager, and since my layoff I’ve been able to spend far more time with him.

We do things together.

We hang out.

I’m present in his life in a way I wasn’t when he was little.

And recently he told me something that absolutely broke my heart.

He said that when he was around four or five years old, he didn’t really understand that I was his father.

He thought I was basically some random guy who occasionally showed up and ate his mother’s food.

That one hurt.

Badly.

But it taught me something I don’t think I’ll ever forget.

You can mend a relationship, but you can’t unlive the years you missed.

The circle can be repaired.

But it can never be completely unbroken.

That’s why the people we love deserve our attention now, not someday when we’re finally rich enough, successful enough, or retired enough.

Lie #4: Wealth Will Make You Happy

And this may be the biggest lie of all.

We’re constantly sold the idea that happiness is somewhere on the other side of wealth.

Make more money.

Buy the house.

Get the nice car.

Take the expensive vacation.

Upgrade your lifestyle.

Become financially independent.

Accumulate enough money and eventually you’ll arrive at happiness.

I believed some version of this myself.

But after achieving financial independence, I’ve come to see the distinction more clearly.

Money is incredibly useful.

It can buy food.

Shelter.

Healthcare.

Security.

It can eliminate enormous amounts of stress.

And once you have enough money to cover your basic needs, it can buy something extremely valuable:

Your time back.

But that’s where the magic ends.

Because more money doesn’t automatically tell you what to do with that time.

In fact, having enormous resources can create its own trap.

Your expectations rise.

What once felt luxurious becomes normal.

Then you need something bigger, better or more expensive to produce the same emotional response.

You end up running on a financial version of the hedonic treadmill.

More.

More.

More.

Until eventually you’re not even chasing happiness anymore.

You’re just trying to maintain your new definition of “normal.”

That’s why I no longer think financial independence is the same thing as happiness.

Financial independence is simply freedom.

And freedom is an opportunity.

What you do with that opportunity is up to you.

So What Is the Point of All This?

I don’t have some grand answer.

I’m still figuring it out.

That’s probably the most honest thing I can say.

Early retirement didn’t magically transform me into a wise old man sitting on top of a mountain dispensing the secrets of existence.

If anything, it did the opposite.

It made me realize how little I actually know.

But it did give me something incredibly valuable:

Perspective.

When you’re inside the machine, it’s difficult to see the machine.

You wake up.

Go to work.

Pay the bills.

Raise the kids.

Buy things.

Consume media.

Repeat.

And because everyone around you is doing the same thing, it feels normal.

But step outside of it for a while and suddenly some of the assumptions start looking strange.

Why does being busy equal being valuable?

Why do we assume more freedom automatically creates happiness?

Why do we treat relationships as disposable?

Why do we believe accumulating more wealth is the ultimate objective of human existence?

Maybe the purpose of financial independence isn’t to stop working forever.

Maybe it isn’t about expensive vacations or luxury cars or spending your days playing video games.

Maybe financial independence gives you something much more important:

The time and freedom to figure out what actually matters.

And that’s a much harder journey.

Because once work stops telling you who you are, you’re forced to figure it out yourself.

Once money stops being the goal, you have to find another one.

Once you’re no longer chasing the next promotion, you have to decide what you’re actually running toward.

And once you have the freedom to do anything, you have to confront the terrifying question: What is worth doing?

I don’t think there’s a universal answer.

But I suspect the answer has very little to do with accumulating stuff.

And much more to do with people, purpose, and how we choose to spend the limited amount of time we’ve been given.

Because eventually, all of us run out of time.

And no amount of money can buy it back.

The strange gift of early retirement

Getting laid off was one of the most painful and disorienting experiences of my professional life.

But it may also have been one of the most valuable.

It forced me out of the rat race.

It gave me distance.

It gave me time.

And it forced me to question assumptions I had spent decades accepting without much thought.

I don’t know whether I would have discovered any of this if I had simply continued working until 65.

Maybe I would have eventually figured it out.

Maybe not.

But I do know this:

Financial independence isn’t the destination.

It’s the door.

What lies on the other side is a much harder question.

What will you do with your life once you no longer have to spend it earning money?

I’m still trying to answer that question.

Hello, world.

I’m an unemployed former Big Tech software engineer with 25 years of experience in the technology industry.

And one of the strangest things about early retirement is discovering something I never seemed to have enough of while working:

time.

Free time gives you the opportunity to notice things you were too busy to notice before.

And once I slowed down, I started thinking about a paradox that I find increasingly difficult to ignore.

The Good Life Paradox

Look at the news. Scroll through social media. Listen to people talk about their lives.

It seems like we’re living through crisis after crisis.

A cost-of-living crisis.

A loneliness crisis.

A mental-health crisis.

A birth-rate crisis.

A meaning crisis.

And underneath all of these is a broader feeling that something has gone fundamentally wrong with our society.

Yet here’s the strange part.

If you look at our material standard of living, we are living in an age of extraordinary abundance.

The average American today has access to things that would have been unimaginable to even the wealthiest people a few centuries ago.

Our homes are heated in the winter and cooled in the summer.

We have clean running water and electricity.

We can eat food from virtually anywhere on Earth, year-round.

We have modern medicine.

We have instant communication with people on the other side of the planet.

And we carry, in our pockets, access to an astonishing percentage of humanity’s accumulated knowledge.

A relatively ordinary person today can watch a movie, have dinner, talk to someone across the world, summon transportation, access a library containing millions of books, and ask an AI to explain quantum mechanics, all before going to bed.

By almost any historical measure, we live incredibly comfortable lives.

And yet...

A huge number of people don’t seem particularly happy.

So how can a civilization achieve unprecedented material abundance while simultaneously experiencing widespread loneliness, anxiety, dissatisfaction, and a crisis of meaning?

Maybe the problem isn’t that we have too little.

Maybe we’re optimizing for the wrong things.

So What Actually Makes a Good Life?

This question is obviously not new.

Human beings have been asking it for thousands of years.

Philosophers, religious teachers, prophets, and ordinary people have wrestled with the same fundamental question:

What does it mean to live well?

What’s fascinating to me is how much overlap exists among traditions that developed independently of one another.

Different civilizations disagreed about countless things.

But when you strip away the cultural details, many of them keep circling around a remarkably similar set of ideas.

I would boil them down to three things.

1. Meet Your Basic Material Needs

First, you need enough material security to survive and live with dignity.

Food.

Shelter.

Clothing.

Safety.

A place to sleep.

You don’t need a mansion.

You don’t need a Lamborghini.

You don’t need the newest iPhone.

You need enough.

And historically, there was also an interesting connection between work and human dignity.

The idea wasn’t necessarily that you needed to spend every waking hour maximizing your economic output.

It was that contributing through honest work could be part of living a worthwhile life.

The goal was never supposed to be endless accumulation.

It was supposed to be having enough to live well.

2. Build Strong Relationships

The second ingredient is relationships.

Family.

Friends.

Neighbors.

Community.

People you love and people who love you.

People who depend on you.

People you can depend on.

A human being isn’t designed to exist as an isolated economic unit.

We need other people.

We need to serve other people.

We need to care for them.

We need to forgive them.

We need to be forgiven.

We need companionship.

We need belonging.

And perhaps most importantly, we need to feel that we matter to someone.

You can have an enormous bank account and still be profoundly lonely.

3. Find Meaning and Purpose

And then there’s the big one.

Meaning.

Purpose.

A reason to get out of bed in the morning.

Different cultures have different names for this.

Ikigai.

Raison d’être.

Calling.

Mission.

Faith.

Purpose.

The terminology changes, but the underlying idea is remarkably consistent.

Human beings need something that makes their existence feel meaningful.

That something can be religion.

It can be raising children.

It can be creating art.

It can be helping other people.

It can be building something.

It can be pursuing knowledge.

It can even be a hobby that gives your life structure and joy.

The specific answer is different for every person.

But the need itself seems almost universal.

And I think this is more important than we realize.

Meaning isn’t merely something that makes life better. It may be something that makes life possible.

The Darkest Lesson About Meaning

I learned this lesson from Viktor Frankl.

I read Man’s Search for Meaning during one of the darkest periods of my own life.

I originally assumed it was going to be some kind of self-help book.

The cover looked almost cheerful.

It was not a cheerful book.

Frankl was a Holocaust survivor who spent years in Nazi concentration camps.

He witnessed people being stripped of almost everything that normally gives life comfort and security.

Their possessions were taken.

Their freedom was taken.

Their dignity was attacked.

Food was scarce.

Medical care was scarce.

The environment was designed to dehumanize and destroy them.

And yet Frankl observed something extraordinary.

Even under conditions where almost everything had been taken away, there remained one thing that could not be completely confiscated:

the ability to choose one’s attitude and create meaning from one’s existence.

Frankl believed that people who retained a reason to live were better able to endure unimaginable circumstances.

That idea stayed with me.

Because if meaning can matter under those conditions, imagine how important it must be under ours.

And this brings me to my larger theory.

Hypercapitalism Doesn’t Just Sell You Things

I think the problem with modern capitalism isn’t simply that it encourages us to buy too much stuff.

That’s the easy criticism.

The deeper problem is that the system can begin shaping what we believe a good life actually is.

Think about how much of our environment is designed around optimization.

Optimize your career.

Optimize your productivity.

Optimize your body.

Optimize your finances.

Optimize your home.

Optimize your dating life.

Optimize your children.

Optimize your time.

Optimize your sleep.

Optimize everything.

And then, after optimizing your entire existence...

You’re supposed to be happy.

But what if you’ve optimized yourself toward someone else’s definition of success?

That’s the question that bothers me.

When Luxuries Become Necessities

One of the most powerful mechanisms of hypercapitalism is turning luxuries into perceived necessities.

Imagine taking someone from 1950 and dropping them into an ordinary American home today.

They would probably think we were insanely wealthy.

Air conditioning?

A luxury.

A smartphone?

Science fiction.

Streaming thousands of movies?

Impossible.

Fresh fruits and produce year around?

Ridiculous.

Instant access to virtually all human knowledge?

Magic.

But we’ve normalized all of this.

And once something becomes normalized, it can become psychologically necessary.

Then something strange happens.

A lifestyle that would have looked unbelievably luxurious to previous generations starts feeling like the minimum required to participate in society.

The baseline keeps moving.

And because the baseline keeps moving, “enough” becomes almost impossible to reach.

When Productivity Becomes Identity

But material consumption isn’t the only thing being shaped.

Our identities are shaped too.

I experienced this firsthand working in Big Tech.

My calendar was full.

My inbox was full.

My Slack messages were full.

There were always projects.

Always deadlines.

Always another problem to solve.

From the outside, I was productive.

But there were times when I had to ask myself:

What exactly am I being productive toward?

I was accomplishing things.

But were they things that actually mattered to me?

Maybe the products I worked on had value.

Maybe the projects helped someone.

But they weren’t necessarily my purpose.

And because work consumed so much of my time and mental energy, I had very little opportunity to step back and ask the most important question:

What do I actually want my life to be about?

That’s the trap.

If you’re constantly busy optimizing your career, you may never have enough time to figure out whether you actually want the career you’re optimizing.

Hypercapitalism Can Manufacture Desire

This is where I think things get really interesting.

Hypercapitalism doesn’t merely sell us products.

It can shape our values, ambitions, and aspirations.

It tells us what success looks like.

It tells us what attractiveness looks like.

It tells us what status looks like.

It tells us what happiness looks like.

It tells us what we should aspire to.

And it does this so continuously that we can eventually mistake socially manufactured desires for our own authentic desires.

We think:

“I want this.”

But why?

Where did that desire come from?

Who taught me that this was important?

What happens if I don’t have it?

Would I still want it if nobody else knew I had it?

These are uncomfortable questions.

Because sometimes the answer is:

I don’t actually know.

Maybe I don’t want the bigger house.

Maybe I want more time.

Maybe I don’t want the prestigious career.

Maybe I want meaningful work.

Maybe I don’t want more stuff.

Maybe I want deeper relationships.

Maybe I don’t want to optimize every minute of my life.

Maybe I just want to live.

The Productivity Trap

We’ve somehow arrived at a point where productivity has become almost synonymous with virtue.

If you’re busy, you’re important.

If you’re successful, you’re valuable.

If you’re wealthy, you must be doing something right.

If you’re constantly improving yourself, you’re a good person.

And if you’re doing nothing?

Well...

You’d better have a good explanation.

But here’s something I’ve discovered during early retirement:

Doing nothing can be incredibly productive for the human soul.

Taking a walk.

Reading a book.

Cooking dinner.

Playing with your kids.

Talking to your spouse.

Sitting outside.

Building something because you enjoy building it.

Learning something because you’re curious.

Doing absolutely nothing because you’re tired.

None of these activities necessarily maximize GDP.

None of them necessarily advance your career.

None of them necessarily increase your net worth.

And yet these may be some of the most valuable things a human being can do.

So How Do We Get Our Humanity Back?

I don’t think the answer is to abandon capitalism and move into the woods.

I’m not advocating that.

And I’m certainly not claiming that modern civilization is bad.

Quite the opposite.

The material abundance we’ve created is extraordinary.

The problem is what happens when material abundance becomes the purpose of existence rather than the foundation for it.

So here’s my suggestion.

Start questioning.

Question the things you think you need.

Question the things you think you’re supposed to want.

Question the assumption that your career defines your worth.

Question whether productivity is actually making you happier.

Question whether the next promotion, bigger house, nicer car, or newest gadget will meaningfully improve your life.

And most importantly:

Question who taught you what a good life is supposed to look like.

Because maybe you were never given the opportunity to answer that question for yourself.

You Still Have Free Will

This is the hopeful part.

We’re not completely powerless.

Every one of us has a mind.

Every one of us has some degree of free will.

That means we can examine the values we’ve inherited.

We can decide which ones to keep.

We can reject some of them.

We can experiment with different ways of living.

And we can deliberately construct a life around the things that actually matter to us.

Maybe your purpose is your family.

Maybe it’s your work.

Maybe it’s art.

Maybe it’s faith.

Maybe it’s service.

Maybe it’s adventure.

Maybe it’s learning.

Maybe it’s building something in your garage that nobody else will ever care about.

That’s okay.

Your purpose doesn’t have to impress anyone.

It just has to mean something to you.

The Human Life Is Still Possible

I started this essay with a paradox.

We live in an age of extraordinary material abundance.

And yet so many people feel like they’re living through an age of scarcity.

Maybe that’s because material abundance and human flourishing aren’t the same thing.

We solved many of the problems of physical survival.

But we haven’t solved the problem of figuring out what we are supposed to do with our lives once we’re no longer simply trying to survive.

And perhaps that’s the great challenge of the 21st century.

Not figuring out how to acquire more.

But figuring out what is enough.

Not figuring out how to become more productive.

But figuring out what is worth doing.

Not figuring out how to maximize our economic value.

But figuring out what makes us valuable as human beings.

And not allowing the system around us to answer those questions for us.

Because despite everything modern society throws at us, we still have the ability to stop, think, and choose.

We can choose our relationships.

We can choose what we value.

We can choose what we spend our time doing.

And, perhaps most importantly, we can choose what our lives mean.

Living a good, meaningful, and genuinely human life is still possible in the age of hypercapitalism.

But we have to be willing to step outside the machinery long enough to figure out what that life actually looks like.

That’s my two cents.

Hello World!

I'm finally scratching the live-streaming itch and putting my OBS Studio setup through its paces. This is basically a live test run of my cameras, microphones, scenes, overlays, and all the other Techy nonsense I've been tinkering with.While I'm here, let's talk about something a little more serious: Is the AI Bubble about to burst? I'll share my thoughts on the current state of the AI boom, whether we're in an actual bubble, and what I think could plausibly happen next.Come hang out, watch me potentially break my streaming setup in real time, and let's talk about AI, tech, and the future.No promises that everything will work. That's half the fun. 😅Timestamps:00:00 Introduction & Stream Setup Check06:54 The Biosphere & Boogie Worm Ecosystem12:35 Sound Effects & Diagnostics14:00 What is an "Office Hours"?18:15 Storytime: Dealing with Log4Shell in 202125:52 History & Evolution of LLMs29:18 Key Improvements in Modern AI (RL, Tools, Chain of Thought)34:37 Agentic Harnesses & Loop Workflows38:40 Do LLMs Reason? (The Jacobian Conjecture)41:40 Real-World Impact of AI on Software Engineering46:01 The 3 Pillars of AI: Compute, Algorithms, Data49:25 Limits of Silicon Compute & Moore’s Law51:10 Algorithmic Gains vs Compute Scaling56:10 US vs China AI Competition & Sanctions01:12:40 Semiconductor Blockade Workarounds01:17:40 Historical Context of Neural Networks01:23:30 Local AI Models, Quantization & Privacy01:32:40 Data Center Bottlenecks & Memory Supply Chain01:39:00 The AI Financial Bubble & Circular Financing01:42:20 Current AI Limitations & Bubble Risk01:48:40 Audience Q&A01:58:35 Wrap-up & Sign-off

NVIDIA has become one of the great corporate success stories of the AI boom.

Its GPUs power much of the infrastructure behind today’s frontier AI models. Revenue has exploded. Profitability has exploded. Its market capitalization has reached almost incomprehensible levels.

And because NVIDIA sells the “shovels” during the AI gold rush, the conventional wisdom seems pretty straightforward:

Even if the AI bubble eventually bursts, NVIDIA wins.

After all, somebody still has to sell the picks and shovels.

I’m not convinced.

In fact, I think there is a scenario in which NVIDIA becomes one of the biggest casualties of the next phase of the AI revolution.

Not because its technology suddenly becomes bad.

But because the economics of AI could fundamentally change.

NVIDIA’s Moat Depends on One Big Assumption

The bull case for NVIDIA ultimately rests on a simple proposition:

AI has an essential dependency on NVIDIA GPUs.

Today, that proposition looks pretty damn convincing.

Frontier models require enormous amounts of computing power. Companies like OpenAI and Anthropic have traditionally trained their models using massive clusters of NVIDIA GPUs inside enormous data centers.

And NVIDIA’s data-center business is now overwhelmingly important to the company.

The logic therefore seems almost circular:

AI gets bigger → AI needs more compute → more compute requires NVIDIA GPUs → NVIDIA makes more money.

But what happens if the amount of compute required to produce useful AI falls dramatically?

What happens if frontier models become increasingly commoditized?

And, perhaps most importantly:

What happens if AI inference moves out of the data center and onto the devices sitting on our desks?

That’s where things get interesting.

The First Problem: Frontier AI Is Becoming Commoditized

One of the most interesting developments in AI isn’t happening in Silicon Valley.

It’s happening in China.

U.S. restrictions on advanced NVIDIA chips have forced Chinese AI companies to become extraordinarily creative with limited computing resources. They’ve developed alternative hardware and software stacks while finding ways to train increasingly capable models with less compute.

The result is a strange paradox.

The harder the United States tried to restrict China’s access to advanced AI hardware, the stronger the incentive became for Chinese companies to figure out how to build AI without it.

And we’re now seeing highly capable open-weight models emerge that can compete surprisingly well with leading proprietary systems.

The important point isn’t whether one particular Chinese model is better than Claude or ChatGPT.

The important point is what happens when the model itself stops being scarce.

If someone can download a highly capable frontier-class model for free, the economic value begins moving somewhere else.

The model becomes a commodity.

And once the model becomes a commodity, the question changes from:

“Who has the best AI model?”

to:

“Where should we host all of this AI?”

That distinction could be enormously important for NVIDIA.

The AI Revolution Has Two Different Problems

There’s a distinction that often gets lost in the AI discussion:

Training is not the same thing as inference.

Training is the process of creating the model.

Inference is what happens every time you actually use it.

Every time you ask ChatGPT a question, summarize a document, generate an image, write some code, or run an AI agent, you’re performing inference.

And I think inference could become NVIDIA’s Achilles’ heel.

Why?

Because inference has a very different economic profile from training.

For inference, the bottleneck isn’t always raw computational power.

It can be memory.

Consider a hypothetical near-frontier model with hundreds of billions of parameters.

A mixture-of-experts architecture might only activate a relatively small portion of those parameters for any individual token. The actual computation required can therefore be surprisingly manageable.

The problem is that the entire model still needs to reside somewhere in memory.

That’s where things get interesting.

What If Your Mac Can Run Frontier AI?

Imagine you want to run Deep Seek V4 Flash, a roughly 284-billion-parameter model locally.

You might need around 90–100 GB of memory to hold the model.

NVIDIA’s obvious solution is to use an expensive data-center GPU with enormous amounts of high-speed VRAM.

And if the model gets even larger?

Add more GPUs.

Connect them using NVIDIA’s proprietary high-speed interconnect technology.

Add networking equipment.

Add racks.

Add cooling.

Add power.

Add highly paid engineers to operate everything.

This is an extraordinary technological achievement.

But it is also extraordinarily expensive.

Now consider a different approach.

What if you could put enough memory and processing power into a consumer computer to run the same model locally?

Modern systems increasingly make this possible.

Apple’s unified-memory architecture is particularly interesting because CPU and GPU resources can share a large pool of memory rather than relying on separate pools of system RAM and VRAM.

That architecture isn’t necessarily going to beat a giant NVIDIA data center cluster at raw performance.

But that’s not necessarily the point.

The question is:

Do you need the giant cluster in the first place?

If a consumer machine can run a sufficiently capable model locally, the economics start looking very different.

You don’t need a hyperscale data center.

You don’t need to pay for cloud inference every time you ask a question.

You don’t need to send your private data across the internet.

You don’t even necessarily need an internet connection.

And perhaps most importantly:

You don’t need to rent NVIDIA GPUs by the token.

The Economics of Local AI Could Be Brutal

This is the part I find most interesting.

Cloud AI has a fundamental cost structure.

Someone has to buy the GPUs.

Someone has to build the data center.

Someone has to pay for electricity.

Someone has to provide cooling.

Someone has to operate the network.

And someone has to earn a return on all of that capital.

If AI inference happens on your own hardware, much of that cost disappears from the cloud provider’s balance sheet.

You already own the computer.

You already pay for the electricity.

You already have the hardware sitting on your desk.

The marginal cost of running another inference can therefore be dramatically lower.

That’s a very different economic model.

And if AI models continue getting more efficient and more capable, the incentive to push inference toward the edge becomes stronger.

This is why I don’t think local AI is merely a hobbyist phenomenon.

It could eventually become an economic necessity.

NVIDIA’s Attempt to Move Downstream

To be fair, NVIDIA isn’t stupid.

Jensen Huang and the rest of the company can see what’s happening.

NVIDIA has already begun pushing into consumer-oriented AI hardware, including systems designed to bring substantial AI compute and memory closer to the end user.

But there’s a problem.

NVIDIA is entering a battlefield where other companies have spent decades fighting.

Designing a powerful data-center GPU is one thing.

Building an entire consumer computing platform is another.

The consumer market is dominated by companies with expertise across the entire stack.

They design the silicon.

They build the computers.

They control the operating system.

They control the developer ecosystem.

They control the software distribution platforms.

And ultimately, they control the interface through which billions of consumers experience technology.

That’s a very different kind of moat.

The Next AI Moat May Not Be a GPU

This is where I think the AI conversation gets particularly interesting.

The companies best positioned for the next phase of AI may not necessarily be the companies selling the most powerful accelerators.

They may be the companies that control the entire edge-computing ecosystem.

In the United States, Apple is an obvious example.

Apple controls the chip architecture.

It controls the hardware.

It controls the operating system.

It controls the software ecosystem.

It controls the distribution channel.

And it has hundreds of millions of devices already sitting in consumers’ pockets, homes and offices.

In China, Huawei comes closer to this kind of vertical integration.

That could become incredibly valuable if AI shifts from being something you access remotely to something that’s embedded everywhere.

NVIDIA Probably Isn’t Going Away

Now, before anyone accuses me of predicting the imminent collapse of NVIDIA, let me be clear.

I don’t think NVIDIA is going to suddenly croak.

There will probably be enormous demand for NVIDIA GPUs for years.

Training the most advanced frontier models will remain computationally intensive.

Large enterprises will continue using centralized AI infrastructure.

Hyperscalers will continue building gigantic data centers.

And NVIDIA has an enormous software ecosystem and technological lead.

The point isn’t that NVIDIA becomes worthless.

The point is that its addressable market and competitive moat may change.

NVIDIA could eventually find itself in a position somewhat analogous to IBM.

IBM didn’t disappear.

It remained a powerful technology company.

But the computing world changed around it.

The mainframe became a specialized niche rather than the center of the entire computing universe.

Something similar could happen to NVIDIA.

The Real AI Revolution May Be About Decentralization

The conventional AI story is essentially:

Bigger models → more GPUs → bigger data centers → more NVIDIA revenue.

But there is another possible trajectory:

Better algorithms → smaller models → cheaper inference → local AI → less dependence on centralized GPU infrastructure.

If that second scenario plays out, the economics of the AI industry could look radically different five or ten years from now.

And that’s why I think investors should be careful about extrapolating NVIDIA’s current dominance indefinitely into the future.

NVIDIA’s extraordinary growth is real.

Its technology is real.

Its competitive advantages are real.

But none of those things guarantee that today’s AI infrastructure will remain tomorrow’s AI infrastructure.

And that’s the distinction I think the market may be missing.

The Biggest Risk to NVIDIA May Be AI Getting Too Good

There’s a delicious irony here.

The thing that could eventually threaten NVIDIA’s dominance might actually be the success of AI itself.

If AI models remain enormous, expensive and computationally hungry, NVIDIA probably continues to print money.

But if researchers figure out how to make models dramatically more efficient...

If open-weight models become good enough...

If inference becomes increasingly localized...

If consumer hardware gains enormous amounts of memory...

If AI becomes embedded directly into PCs, phones and other edge devices...

Then the AI industry may gradually require less centralized infrastructure.

And that could undermine the very economic structure that made NVIDIA so dominant.

So when I look at NVIDIA today, I don’t see a company that’s doomed tomorrow.

I see something potentially more interesting:

A company standing at the peak of an economic model that may eventually be disrupted by the technology it’s helping create.

And if that happens, NVIDIA won’t necessarily lose because someone built a better GPU.

It could lose because the world simply doesn’t need as many giant GPU data centers anymore.

That’s a much more dangerous threat to a moat.

And personally, I wouldn’t bet that NVIDIA’s moat is strong enough to justify its current valuation.

Not even close.

A few weeks ago my family took a road trip to Maine.

Over the course of several days I drove nearly 500 miles through half a dozen states before finally arriving at Acadia National Park. The scenery was spectacular. Rocky coastlines, endless forests, lobster shacks every few miles, it was exactly the kind of trip that reminds you just how beautiful America can be.

But it wasn’t Acadia that stuck with me.

It was everything I saw along the drive.

Nearly every picturesque town had the same pattern. There would be a charming historic downtown filled with boutiques, coffee shops, antique stores, and restaurants.

Then, just outside town, often hidden behind a hill or tucked away in the woods, there would be an enormous trailer park.

Many looked rough.

Potholes. Aging homes squeezed together.

And they were packed.

In some towns it honestly felt like more people lived in the trailer park than in the postcard-worthy downtown everyone came to visit.

I also couldn’t help noticing something else.

There seem to be far more people living in RVs, camper vans, cars, and tent encampments than I remember seeing just a decade ago.

That left me asking a simple question.

Why?

The United States isn’t a tiny island running out of land. We possess enormous natural resources, incredible engineering capability, and enough wealth to build housing for everyone.

So why has something as fundamental as shelter become so difficult to afford?

After getting home I spent several days reading about housing economics.

Ironically, I didn’t discover some evil conspiracy.

What I found was something almost worse.

A housing crisis created by millions of perfectly rational people making decisions that collectively produce a terrible outcome.

The Gold Rush Nobody Talks About

Housing isn’t just shelter anymore.

It’s become one of America’s favorite investment vehicles.

For institutional investors, residential housing offers something incredibly attractive:

* Demand never disappears.

* Rent can usually be increased.

* Property appreciates over time.

Some of the largest investment firms now own enormous portfolios of homes. Others control entire sections of the housing pipeline, from financing and insurance to construction and property management.

The economics are compelling.

Buy houses.

Reduce the supply available to ordinary families.

Collect rent.

Watch the value of the remaining inventory rise.

It’s a remarkably effective business model.

But the story doesn’t stop with Wall Street.

Millions of ordinary Americans have reached the exact same conclusion.

Maybe they rent out a basement.

Maybe they own a vacation property.

Maybe they have two or three rental homes.

Individually these seem like perfectly reasonable financial decisions.

Collectively?

They’re all competing for the same finite supply of housing.

It reminds me of the famous scene from A Beautiful Mind.

Where every guy at a bar rushes toward the same opportunity.

Instead of maximizing everyone’s success, they simply get in each other’s way.

Housing demand is relatively fixed.

People always need somewhere to live.

When too much investment capital floods into that market, the result isn’t endless profits.

It’s scarcity.

Interest Rates Broke the Market

Government policy didn’t exactly help.

During the pandemic, interest rates were pushed to historic lows.

Mortgages suddenly became incredibly affordable.

People rushed to buy homes.

Then inflation surged.

To fight inflation, interest rates climbed dramatically.

That created what economists call the lock-in effect.

Millions of homeowners now have mortgages around 2–3%.

Selling their current home means replacing that mortgage with one closer to 7%.

Why would anyone voluntarily do that?

So they don’t.

Existing homes stay off the market.

Inventory shrinks.

Prices stay elevated.

Meanwhile, new buyers face expensive mortgages, rising insurance premiums, and higher property taxes.

Everyone becomes stuck.

The market freezes.

We Quietly Changed What a “Normal” Home Looks Like

There’s another factor that doesn’t get discussed enough.

Our expectations.

Many Americans now consider a 2,500-square-foot single-family home to be normal.

Historically...

It isn’t.

The average American home during the 1950s was around 900 square feet.

Families were often larger.

Homes typically had one bathroom.

No central air.

Few luxury features.

Yet millions of families lived perfectly functional lives.

Somewhere along the way we collectively decided that every family deserved a home two or three times larger than what previous generations considered perfectly adequate.

Builders simply followed the money.

Larger homes generate larger profits.

Local zoning regulations often reinforce that trend by making it difficult or outright illegal to build smaller starter homes.

The result?

We continuously build housing that fewer people can actually afford.

The Great Housing Contradiction

Perhaps the biggest irony is that most homeowners genuinely support affordable housing.

At least...

Until someone proposes building it nearby.

Every additional home built increases supply.

Increasing supply places downward pressure on prices.

Lower prices reduce the value of existing homes.

For roughly two-thirds of American households, their home represents their largest financial asset.

So homeowners find themselves trapped in a conflict of interest.

They support affordable housing.

Just not next door.

Economists call this a collective action problem.

Everyone agrees there’s a shortage.

Almost nobody wants to bear the cost of solving it.

Nobody Planned This

This was perhaps the most surprising conclusion I reached.

I would almost feel better if there were a secret cabal deliberately engineering the housing crisis.

Reality appears much less dramatic.

The housing shortage is the unintended consequence of millions of people making individually rational decisions.

Investors want returns.

Builders want profits.

Homeowners want their equity protected.

Governments respond to short-term crises instead of long-term planning.

Every incentive makes sense on its own.

Together they create something deeply dysfunctional.

Who Pays the Price?

The people least able to absorb higher housing costs.

Young adults trying to purchase their first home.

Retirees living on fixed incomes.

Families struggling through illness.

People already one paycheck away from financial disaster.

Housing inflation doesn’t simply make life inconvenient.

It delays families.

Reduces birth rates.

Increases stress.

Expands homelessness.

Makes communities less stable.

Housing isn’t merely another asset class.

It’s the foundation on which nearly every other part of society rests.

So... What Can We Actually Do?

I’m usually skeptical of simplistic solutions to complex problems.

But this feels like one of the rare issues where a few policy changes could actually make a meaningful difference.

First, we should continue limiting large-scale investor ownership of existing residential housing.

Homes should primarily exist to house people not simply function as financial instruments.

Second, communities should make it dramatically easier to build smaller homes.

Not everyone needs or wants a 3,000-square-foot house.

Smaller homes are faster to build, require fewer materials, cost less to maintain, and provide a realistic entry point for first-time buyers.

Finally, perhaps we all need to rethink what success looks like.

A modest home that provides safety, stability, and financial breathing room may ultimately deliver a happier life than chasing the biggest house the bank is willing to finance.

The housing crisis wasn’t created overnight.

It won’t be solved overnight either.

But recognizing that this isn’t simply the fault of one villain or one political party is probably the first step.

Sometimes the greatest problems in society aren’t created by evil people.

They’re created by ordinary people, each acting rationally in their own self-interest.

And when enough of those incentives point in the wrong direction...

We all end up paying the price.

What if the future is increasingly divided between people who own capital and people who sell their labor? And what if you have no savings, no assets, and maybe even a negative net worth? Is it already too late?

Hello world.

I’m an unemployed former Big Tech software engineer with 25 years of experience in the technology industry.

Involuntary early retirement has given me something I didn’t have much of during my working years: time to think.

And one idea I’ve been thinking about a lot lately is this:

What happens to people who don’t own anything?

Not metaphorically.

I mean people who don’t own meaningful financial assets. No significant investment portfolio. No business. No real estate. No capital generating income.

People whose entire financial existence depends on selling their time and labor.

Because I worry that we’re moving toward a world where that distinction matters more than ever.

And if you’re starting from $0, how exactly are you supposed to escape?

The Rise of the K-Shaped Economy

The United States increasingly feels like a K-shaped economy.

The upper leg of the K represents people who own capital.

Stocks. Businesses. Real estate. Intellectual property. Technology.

And increasingly, AI and robotics.

The lower leg represents the much larger group of people who primarily survive by selling their labor.

Historically, labor has been the primary way most people generated income.

But technology is changing the equation.

AI and automation have the potential to perform an increasing amount of cognitive and physical work. At the same time, capital owners can potentially benefit from the productivity generated by those technologies.

If you own the machines, the software, the businesses, or the investments that benefit from increased productivity, you participate in the upside.

If you only sell your labor, you may find yourself competing against increasingly powerful machines.

That’s the basic fear behind the K-shaped economy.

And if this trend continues long enough, the two legs of the K could move further and further apart.

Social mobility could become increasingly difficult.

The people who already own assets could accumulate even more.

And the people who own nothing could find themselves permanently dependent on wages.

In other words, a permanent underclass.

It sounds dystopian.

But history has seen versions of this before.

Feudal societies were not exactly known for their upward mobility.

And while I don’t know if we’re heading toward some kind of techno-feudalism, I do think it’s worth taking the possibility seriously.

Because if you believe that capital ownership will become increasingly important, then the obvious question becomes:

How do you become a capital owner if you have no money?

What If You’re Starting With $0?

This is where things get difficult.

If you already have $1 million invested, financial independence is largely a math problem.

If you have $500,000, you have a significant head start.

But what if you have $0?

What if you have credit card debt?

What if you have student loans?

What if you have a negative net worth?

How do you go from $0 to financial independence?

I think the first thing you need to do is reject one of the biggest lies on the internet.

Stop Looking for Easy Money

The internet is absolutely drowning in financial advice.

And much of it revolves around the idea that you can find some magical shortcut.

Maybe it’s a speculative investment that will supposedly return 1,000% per year.

Maybe it’s an NFT.

Maybe it’s an AI-powered business that will generate $100,000 in monthly recurring revenue while you sleep.

Maybe it’s a passive-income system where you work four hours a week from a beach in Bali.

The problem is that most of these ideas are fantasy.

Passive income is rarely truly passive.

Publishing a $20 ebook doesn’t automatically make you rich.

AI doesn’t magically transform a bad business into a profitable one.

And speculative investments that promise ridiculous returns are usually just gambling with extra steps.

The uncomfortable truth is that financial independence is difficult.

For most people, it takes years of consistent effort.

There is no silver bullet.

And that’s actually good news.

Because if there were a magical shortcut to becoming wealthy, everyone would already be doing it.

The path to financial independence is much more boring.

But boring can work.

Step One: Embrace Frugality

If you’re starting with $0, your first objective shouldn’t be financial independence.

It should be financial stability.

You need to create some breathing room.

That starts with understanding where your money actually goes.

How much do you earn?

How much do you spend?

How much debt do you have?

What are your essential expenses?

What can you eliminate?

The goal isn’t necessarily to live like a monk.

Extreme frugality might work for some people, but it isn’t sustainable for everyone.

The key is finding your own sustainable level of frugality.

Spend less than you earn.

Then save the difference.

Build an emergency fund.

Pay down high-interest debt.

And eventually start investing.

This isn’t sexy.

Nobody is going to sell a million-dollar online course teaching you how to spend less than you earn.

But it’s foundational.

If you spend every dollar you make, it doesn’t matter how much you earn.

You have no capital.

And without capital, you can’t become a capital owner.

Step Two: Create Real Value

This is where I think you can potentially accelerate the process.

Create value.

The basic formula is incredibly simple:

Find a real problem.

Learn how to solve it.

Help people.

Get paid.

The world is full of problems.

Problems that need engineers.

They need marketers.

They need salespeople.

They need managers.

They need designers.

They need people who can build things.

They need people who can communicate.

They need people who can make complicated things simple.

The more difficult and valuable the problem you can solve, the more economic value you can potentially capture.

And that means developing valuable skills.

You don’t necessarily need to become the best person in the world at something.

You need to become good enough at solving a problem that people are willing to pay you for your expertise.

That income can come from a traditional job.

It can come from freelancing.

It can come from consulting.

It can come from a business.

Ideally, it can eventually come from multiple sources.

But I think there’s an important distinction here.

You don’t want your entire financial future to depend on a single employer.

If you can, build an income engine that you control.

Create something you own.

A business.

A product.

A service.

A digital asset.

Something that can eventually generate income without every dollar being directly tied to another hour of your life.

The AI Opportunity

This is where I think the AI revolution becomes interesting.

AI is absolutely terrifying in some ways.

But it also dramatically lowers the cost of creating things.

You can build software faster.

You can research faster.

You can create content faster.

You can reach customers faster.

You can automate parts of a business that previously required entire teams.

For the first time, an individual with a laptop and a relatively small amount of capital can potentially do things that once required a large organization.

That’s a massive opportunity.

But here’s the catch.

AI doesn’t eliminate the need to create value.

It makes creating value faster.

You still need to solve a problem that somebody actually cares about.

You still need customers.

You still need distribution.

You still need to execute.

AI is a tool.

It’s not a money-printing machine.

And the people who benefit most from AI may be the people who use it to solve real problems rather than simply generating endless amounts of AI slop.

The opportunity is there.

But you have to actually do something.

Stop Consuming. Start Building.

This might be the most important part of this entire discussion.

You need to start doing.

It’s incredibly easy to spend your entire life consuming information.

Watch another YouTube video.

Read another article.

Listen to another podcast.

Buy another course.

Research another business idea.

Wait for the perfect opportunity.

And then do absolutely nothing.

I know this because I’m guilty of it too.

But at some point, you have to stop preparing.

You have to stop consuming.

You have to stop waiting for permission.

And you have to start building.

Because time doesn’t wait.

If the world really is moving toward a more unequal, capital-intensive economy, then the window for building your own economic independence may not be infinite.

I don’t know if we have five years.

I don’t know if we have ten years.

Maybe I’m completely wrong.

But if I’m right, I don’t want to spend those years doom-scrolling about the problem.

I’d rather spend them trying to build something.

Step Three: Make Your Money Work for You

Eventually, if you manage to increase your income and live below your means, you should start accumulating capital.

This is where investing comes in.

The goal is to take the money you earn from your labor and convert it into ownership.

You work.

You earn.

You save.

You invest.

And over time, your assets start working alongside you.

That could mean diversified index funds.

It could mean real estate.

It could mean owning a business.

It could mean other productive assets that you understand and believe have a reasonable chance of generating long-term returns.

The exact asset isn’t the point.

The point is ownership.

You’re trying to transition from being someone who only earns money through labor into someone who also owns productive assets.

And this is where compounding starts to become your friend.

At first, your investments might generate almost nothing.

Then they generate a little.

Then a little more.

Eventually, if you accumulate enough assets, the returns from your capital can become meaningful.

And at some point, you may reach the magical threshold where your assets can cover your living expenses.

That’s financial independence.

The Difference Between Good Debt and Bad Debt

Debt complicates this equation.

Not all debt is necessarily the same.

There is debt used to acquire productive assets or grow a business.

And there is debt used to buy things that lose value.

One potentially builds wealth.

The other potentially destroys it.

I’m not a financial advisor, and this is absolutely not personalized financial advice.

I’m just talking about what I’ve personally observed and experienced.

But I think it’s important to ask yourself a simple question before taking on debt:

Will this debt help me acquire something that is likely to generate future value?

Or am I simply borrowing money to consume something today?

Cars.

Status symbols.

Lifestyle upgrades.

Man toys.

All of these things can be enjoyable.

But they don’t necessarily make you financially independent.

If you’re starting from $0, every dollar matters.

And ideally, you want more of your money flowing toward things that can potentially produce future returns.

The Real Escape Plan

So, net net, I don’t think escaping the permanent underclass comes from finding a magical passive-income hack.

For the vast majority of people, there is no silver bullet.

The path is much more boring.

Live below your means.

Create real value.

Develop valuable skills.

Increase your income.

Build something you own.

Invest your savings.

Acquire productive assets.

And then do it again.

And again.

And again.

If you start with $0, your first goal isn’t to become a millionaire.

Your first goal is to get to $1.

Then $100.

Then $1,000.

Then $10,000.

You build an emergency fund.

You eliminate bad debt.

You increase your income.

You acquire skills.

You create value.

You invest.

And slowly, your financial trajectory begins to change.

The journey from $0 to financial independence is not going to be easy.

But it doesn’t have to be impossible.

And I genuinely believe that if even a small number of people listening to this actually put these principles into practice, they can build real financial independence.

They can gain more control over their lives.

And maybe, just maybe, they can avoid becoming trapped in a permanent underclass.

Because ultimately, the most important thing isn’t becoming rich.

It’s owning enough of your life that you aren’t completely dependent on someone else for your survival.

That’s the real freedom I’m talking about.

And that’s all I have to say about that.

Hope it helps.

Welcome to Asian Dad Energy.

We’re all just trying to figure this thing out.

One existential crisis at a time.

Hello world.

I’m an unemployed ex Big Tech software engineer with 25 years of experience in the technology industry.

And lately, I’ve been looking at the AI industry and thinking:

Is it just me, or is this bubble looking extra bubbly?

Because something feels different.

The AI industry is still burning through enormous amounts of money. The companies at the center of the AI boom continue to require staggering amounts of capital to build data centers, buy GPUs, train models, and keep everything running.

But suddenly, the tone seems to be changing.

We’re seeing some of the most insanely valued companies in history preparing to go public. We’re hearing calls for government support. And we’re seeing AI executives who spent years predicting an imminent AI driven jobs apocalypse suddenly sounding a little more... cautious.

Hmm.

That’s interesting.

To me, this looks a lot like peak bubble behavior.

It reminds me of what happens near the end of every major financial mania. Everyone starts looking for the next investor willing to buy into the dream before the music stops.

Or, as we like to call them in the financial world:

Bag holders.

But why is this happening now?

I think there are several things happening beneath the surface that are starting to expose a fundamental problem with the current AI boom.

And before the AI true believers come after me with pitchforks and flaming GPUs, let me be clear.

I believe AI is going to be incredibly important.

I just don’t believe we have Artificial General Intelligence.

Not even close.

We Don’t Have AGI. We Have Very Expensive Probabilistic Parrots.

Yes, AI has gotten dramatically better.

We have agentic systems. We have tool integrations. We have models that can write code, analyze documents, generate images, conduct research, and occasionally pretend to be a competent junior employee.

But fundamentally, today’s large language models are still probabilistic systems predicting what comes next based on patterns learned from enormous amounts of data.

They can do remarkable things.

But they still struggle with consistency, reasoning, context, hallucinations, and knowing when they don’t know something.

And because of that, I’m skeptical that today’s AI is suddenly going to invent the next Warp Drive and increase global productivity by 10,000 percent.

Claude is not going to wake up tomorrow and announce:

“Good morning, humans. I have solved faster than light travel. Also, I fixed the economy.”

Sorry.

But there is one thing AI could potentially do extremely well.

It could replace human labor.

And I think that’s the gigantic bet hiding underneath the entire AI boom.

The AI Industry Has Made a Trillion Dollar Bet on Human Labor

Think about the economics.

The AI industry has attracted and consumed enormous amounts of capital.

And whether we’re talking about investor money, corporate spending, or debt financing, the numbers are staggering.

The basic premise behind much of this investment is that AI will eventually generate enormous profits by automating human work.

Especially white collar work.

And that’s the only economic story that really makes sense to me.

Because if you are spending hundreds of billions, or potentially trillions, building the infrastructure required to run AI, eventually you need to make that money back.

And you can’t do that by selling a $20 ChatGPT subscription to every person on Earth.

You need something much bigger.

You need to capture a meaningful percentage of the economic value currently generated by human workers.

And that’s why, for years, we’ve heard predictions from some of the biggest names in AI about massive numbers of white collar jobs being automated.

Software engineers.

Lawyers.

Accountants.

Customer service representatives.

Consultants.

Researchers.

Basically anyone who spends their day sitting in front of a computer.

The logic is straightforward.

If AI can replace millions of expensive human workers, the companies providing that AI can potentially capture a gigantic amount of economic value.

And if you believe the more extreme AI predictions, we’re talking about tens of millions of workers eventually being replaced.

That’s a massive opportunity.

Except...

There’s a problem.

It’s not happening fast enough.

The AI Productivity Revolution Is Taking Longer Than Expected

For all the talk about AI replacing human workers, we’re not seeing anything remotely close to the scale necessary to justify the industry’s enormous financial commitments.

We’re certainly not seeing millions upon millions of white collar workers being replaced every year.

And my own experience as a software engineer has given me a front row seat to the problem.

AI can be incredibly useful.

But getting useful work out of AI is not as simple as typing:

“Hey Claude, please build my billion dollar software company.”

Believe me.

I’ve tried.

The problem is that getting AI to produce consistently high quality work still requires a surprising amount of human intelligence.

You have to manage context.

You have to understand the limitations of the model.

You have to work around gaps in the training data.

You have to check its output.

You have to catch hallucinations.

You have to design workflows.

And when the AI inevitably does something completely insane, you have to figure out why.

In other words, AI doesn’t necessarily eliminate human work.

Sometimes it just changes the kind of human work you’re doing.

And this isn’t just a problem in software engineering.

We’re seeing similar challenges in other areas that were supposedly easy targets for automation.

Customer service, for example, has long been considered one of the obvious use cases for AI.

But when AI agents make mistakes, misunderstand customers, or confidently give completely incorrect answers, companies have a problem.

There have already been cases where AI automation initiatives had to be rolled back and human workers brought back into the loop.

Oops.

Turns out customers don’t particularly enjoy being gaslit by a chatbot.

Who knew?

The bottom line is that AI simply isn’t replacing human workers at the scale the industry’s financial model appears to require.

And I think the AI industry is starting to realize this.

Which brings us to another problem.

The Open Source AI Problem

The American AI industry has been built around enormous closed models.

ChatGPT.

Claude.

Gemini.

These companies control the models, the infrastructure, the data, and the computing resources.

And the plan, at least in theory, is pretty familiar.

Spend an insane amount of money.

Build the best technology.

Gain market dominance.

Kill the competition.

Then raise prices and enjoy enormous profits.

Silicon Valley has used this playbook many times before.

But there is one big problem.

The rest of the world is not sitting around waiting for America to establish an AI monopoly.

Open source AI models have gotten incredibly good.

And companies outside the United States, particularly in China, have made remarkable progress developing powerful models with significantly fewer resources.

These models can be downloaded.

They can be modified.

They can be run on your own infrastructure.

And increasingly, they are becoming good enough for many real world use cases.

That’s a huge problem for the AI industry’s dream of monopoly profits.

Because if a company can download a capable open source model and run it locally for a fraction of the cost of paying an American AI company every time an employee asks a chatbot to write an email...

Well.

That’s not exactly great news for the people trying to build a trillion dollar AI toll booth.

And this brings me to another trend that I think is even more important.

The Rise of Local AI

You don’t necessarily need a giant data center to run AI anymore.

With techniques like quantization and distillation, massive frontier models can be compressed into smaller models that can run on increasingly affordable hardware.

Your desktop.

Your home server.

Your laptop.

Your own private infrastructure.

And this has two enormous advantages.

First, you don’t have to keep paying a Big Tech AI company every time you want to use the model.

Second, your data doesn’t have to leave your computer.

For businesses and individuals who care about privacy, that’s a pretty big deal.

And as local models become more capable, something else happens.

The value of premium AI models starts to decline.

Why pay $100 a month for the world’s most powerful AI model if a local model running on your own hardware can handle 95 percent of what you actually need?

It’s the same problem that open source software created for proprietary software companies.

If the free alternative is good enough, the premium product has to work very, very hard to justify its price.

And that brings us to the fundamental problem.

The AI Industry Needs Productivity Gains. Fast.

The AI industry has spent an enormous amount of money based on the assumption that AI will eventually generate enormous economic returns.

But eventually isn’t good enough.

The debt has to be serviced today.

The data centers have to be paid for today.

The GPUs have to be purchased today.

The employees have to be paid today.

The electricity bill, unfortunately, does not accept payment in future AGI promises.

So the industry needs massive productivity gains.

And it needs them soon.

But what we’re seeing instead is a technology that is incredibly useful in some situations, moderately useful in others, and occasionally produces something that makes you stare at your monitor for five minutes wondering how a machine with a trillion parameters managed to screw up something a reasonably intelligent eight year old could have done correctly.

That’s not AGI.

That’s Tuesday.

The technology will improve.

I’m confident of that.

But the question isn’t whether AI will eventually transform the economy.

I think it will.

The question is:

Will it transform the economy quickly enough to justify the enormous amount of money being spent on it today?

That’s a very different question.

I Think the AI Bubble Will Pop

Let me be clear.

I don’t think AI is a scam.

I don’t think AI is useless.

And I don’t think AI is going away.

I think AI is going to be transformative.

Just like the railroad.

Just like the internet.

But both of those technologies experienced enormous speculative bubbles.

The technology was real.

The revolution was real.

The financial valuations were not.

And I think we could be heading toward something similar with AI.

The technology may ultimately change the world.

But that doesn’t mean every company building AI infrastructure today is going to become the next trillion dollar company.

And it certainly doesn’t mean every AI stock is going to make you rich.

In fact, I think the opposite could happen.

The AI industry has made an enormous leveraged bet that AI will rapidly replace human labor and generate massive profits.

But if AI isn’t ready to replace workers at the necessary scale, while open source and local models simultaneously push prices down, the economics become increasingly difficult.

And that’s when bubbles start to get interesting.

Because eventually someone has to pay the bill.

My One Piece of Advice

So here’s my one piece of advice to you.

Be very careful.

I expect AI companies will become increasingly desperate to raise capital.

And when companies desperately need money, they tend to become extremely creative about how they get it.

I wouldn’t be surprised if we see wildly overvalued IPOs, increasingly aggressive marketing, and even more spectacular promises about what AI is supposedly going to accomplish five years from now.

The goal will be to keep the machine running.

To keep the money flowing.

To convince investors that the biggest breakthrough in human history is just around the corner.

And there will be plenty of people willing to buy the dream.

Don’t be that person.

Because when the music stops, the people who built the machine will probably be the ones who walked away with the money.

The people who bought the dream at the top?

Well...

They’ll be the ones holding the bag.

Don’t let that person be you.

Because here’s the funny thing about bubbles.

The technology can be real.

The revolution can be real.

The future can be real.

And you can still lose your shirt investing in it.

That’s the part a lot of people seem to forget.

And that’s why, while I remain extremely bullish on the long term potential of AI, I am becoming increasingly bearish on the idea that today’s AI valuations and spending spree are sustainable.

The AI revolution may very well change the world.

But I have a feeling we’re going to have to get through one heck of a financial hangover first.

And that’s all I have to say about that.

Until next time.

Asian Dad Energy

One of the strangest things about getting laid off from Big Tech is realizing that, for the first time in decades, I actually have time.

And as strange as this new chapter has been, I’ve noticed something surprisingly wonderful.

Time has slowed down.

Not literally, of course. The Earth is still spinning at roughly the same speed. My clocks haven’t suddenly become defective. Monday still becomes Tuesday whether I like it or not.

But my perception of time has changed dramatically.

And honestly?

It feels a little bit like I’ve been given a life extension for free.

Where Did All the Time Go?

When I was working, time seemed to fly.

Days disappeared.

Weeks blurred together.

Months would pass, and I’d suddenly realize that an entire season had come and gone. I’d look back and think, Wait. That was six months ago? It feels like it happened three weeks ago.

The older I got, the faster it seemed to happen.

I remember being a kid and feeling like summer vacation lasted forever.

Now, somehow, I’ll blink and it’s Thanksgiving.

I’ll blink again and it’s Christmas.

I’ll blink one more time and I’m wondering why the grocery store already has Valentine’s Day decorations.

What happened?

Why does time seem to accelerate as we get older?

I never really thought about it when I was working. I was too busy.

There was always another meeting.

Another deadline.

Another project.

Another email.

Another fire to put out.

I didn’t have time to stop and ask why I didn’t have time.

Now that I have more time, I finally got curious.

And after doing some reading and thinking about my own experiences, I came across a few explanations that made a lot of sense.

The Aging Brain

The first explanation is probably the least surprising.

We’re getting older.

Our brains change as we age, and those changes may affect how we perceive the passage of time.

One way I’ve come to think about this is through the analogy of a video game.

Imagine playing a first person shooter when your computer is capable of rendering 120 frames per second.

Everything feels incredibly smooth.

Now imagine that, as the computer gets older, it can only process 60 frames per second.

The game is still running at the same speed in the real world, but you’re receiving fewer visual frames.

The experience feels different.

Some research into the perception of time suggests that something similar may happen in the aging brain. As our neural networks change, the brain’s processing of information can change as well. The details are considerably more complicated than my video game analogy, but the basic idea is that the way our brains process and encode experiences changes as we age.

And this may contribute to our subjective experience of time.

But I think there’s another factor that’s even more interesting.

The Problem With Autopilot

Think back to childhood.

Almost everything was new.

Your first day of school.

Your first time riding a bicycle.

Your first trip on an airplane.

Your first video game console.

Your first crush.

Your first time getting in trouble for doing something incredibly stupid.

When you’re a child, your brain is constantly encountering experiences it hasn’t seen before.

As we get older, that changes.

We become experts at navigating the world.

We know how to drive to work.

We know how to make coffee.

We know how to check email.

We know how to sit through meetings.

We know how to do our jobs.

We know how to drive home.

And then we do it again tomorrow.

And the day after that.

And the day after that.

This is one of the great advantages of having an experienced brain. We don’t need to consciously process every little detail of our lives.

Our brains can recognize patterns and automate familiar behaviors.

That’s incredibly useful.

But I suspect there’s a downside.

When you’re operating on autopilot, you’re not creating as many distinct memories.

Think about a typical commute.

You drive the same roads you’ve driven hundreds of times.

You pass the same buildings.

You stop at the same traffic lights.

You arrive at work.

You might remember the commute as a whole, but you probably can’t tell me what you saw at 8:17 AM on Tuesday three weeks ago.

Your brain didn’t consider that information important enough to preserve.

Now imagine doing that for years.

Same commute.

Same desk.

Same meetings.

Same projects.

Same routines.

Eventually, you look back and realize that five years have somehow disappeared.

The days were full of activity.

But your memory contains relatively few distinct markers separating one day from another.

And when you look backward, those years can feel incredibly short.

This might explain one of the strangest paradoxes of getting older:

You have more years behind you, but those years can feel like they’re passing faster.

Then We Added Social Media

As if living on autopilot wasn’t enough, we now have another problem.

Digital overstimulation.

For many of us, when the workday ends, we don’t actually stop.

We pick up our phones.

We open social media.

We scroll.

And scroll.

And scroll.

One video becomes another.

One post becomes another.

One outrage becomes another.

One argument becomes another.

And before we know it, an hour has disappeared.

The irony is that this content is incredibly stimulating, but the experience itself often leaves very little behind.

Think about what humans experienced for most of our existence.

There was a lot of boredom.

A lot of boredom.

You might spend hours walking somewhere.

Working in a field.

Gathering food.

Making something by hand.

Sitting around a fire.

Waiting.

Waiting some more.

Modern humans have largely eliminated this kind of boredom.

Instead, we have created an endless stream of content specifically engineered to capture our attention.

And there’s something interesting about this.

Our brains have to decide what information is important enough to remember.

But what happens when we’re exposed to thousands of stimulating pieces of information every day?

Everything is urgent.

Everything is shocking.

Everything is outrageous.

Everything is designed to trigger some kind of emotional reaction.

Eventually, nothing is special.

Your brain becomes overwhelmed by the sheer volume of information.

And the result may be that relatively little of it becomes a meaningful, lasting memory.

You spent an hour scrolling.

But what do you remember?

Maybe nothing.

And yet that hour is gone forever.

This is where I think the combination becomes particularly dangerous.

Repetitive routines during the day create fewer memorable experiences.

Digital overstimulation during our free time creates an endless stream of forgettable experiences.

And then we wonder why life feels like it’s flying by.

So How Do We Slow It Down?

Here’s the interesting part.

After getting laid off, my perception of time changed dramatically.

I don’t think it’s because unemployment magically alters the laws of physics.

It’s probably because my lifestyle changed.

I started doing things differently.

And I think some of those changes are things that almost anyone can try.

1. Switch Things Up

The first thing I’ve found helpful is introducing novelty into my life.

Nothing dramatic.

You don’t need to quit your job and become a professional skydiver.

Sometimes it’s as simple as taking a different route to the store.

Going to a different grocery store.

Learning something new.

Changing the order of your daily activities.

I have a bunch of different hobbies and projects.

Journaling.

Software development.

Drone piloting.

Coaching.

Gardening.

And I’ve noticed that when I change what I do from day to day, the days feel longer.

I’m not necessarily doing more.

I’m just doing different things.

The brain has to pay attention.

And when the brain pays attention, it creates more distinct experiences.

Those experiences become memories.

And when I look back on the week, it feels like a week actually happened.

Not just one generic Tuesday that somehow got copied and pasted seven times.

2. Be Where You Are

The second thing I’ve found helpful is focusing intensely on the present moment.

This can be difficult.

Our minds are constantly trying to escape the present.

We’re thinking about something that happened yesterday.

We’re worrying about something happening tomorrow.

We’re mentally composing an email while someone is talking to us.

We’re sitting at dinner while scrolling through our phones.

We’re physically somewhere.

But mentally, we’re somewhere else.

I’ve found that activities requiring complete attention can dramatically change my perception of time.

One example is my daily 15 minute meditation.

When I’m meditating, I have to pay attention to my breathing.

My posture.

My thoughts.

My mental imagery.

And something strange happens.

Fifteen minutes feels like a long time.

Not in a bad way.

It feels like I’ve actually experienced those fifteen minutes.

Another example is swimming.

I recently started taking swimming lessons.

This is a big deal for me because I had a pretty bad experience with water as a child, and as a result, I’ve spent most of my life avoiding learning how to swim.

Now I’m trying to overcome that.

And let me tell you something.

When you’re in the deep end of a pool, you’re trying to float, your face is underwater, you’re blowing air out of your nose, and your brain is screaming, This is a terrible idea!

You are very much in the present moment.

There is no thinking about your email.

No worrying about tomorrow’s meeting.

No doomscrolling.

Just you, the water, and the immediate question of whether you’re about to embarrass yourself in front of the swimming instructor.

And here’s the weird part.

Those moments seem to last forever.

But they also become incredibly memorable.

I can remember specific moments from my swimming lessons days later.

Which makes me wonder if a certain amount of fear and discomfort might actually be necessary for a satisfying life.

Not constant terror, obviously.

But maybe we need to occasionally do things that scare us.

Things that force us out of autopilot.

Things that make us pay attention.

Because those are the moments we remember.

3. Get Bored Again

The final thing I’ve done is probably the hardest.

I’ve dramatically reduced my consumption of digital content.

Especially social media.

Yes, I realize the irony.

I’m telling you to reduce social media consumption through a piece of content that will probably be distributed to you through social media.

I get it.

But I can only tell you what I’ve experienced.

Doomscrolling was eating an enormous amount of my free time.

And when I stopped, something unexpected happened.

I became bored.

At first, this felt terrible.

Then it started feeling wonderful.

I realized that boredom wasn’t actually the enemy.

Boredom gave my brain room to breathe.

Without a constant stream of content competing for my attention, I started noticing things again.

I started paying more attention to what I was doing.

I started having more distinct experiences.

And, most importantly, I started remembering more of my days.

My life didn’t necessarily become more exciting.

But it became more memorable.

And that’s an important distinction.

Maybe We Don’t Need More Time

I started this whole journey thinking that I wanted more time.

But now I’m starting to wonder if that’s actually the problem.

Maybe we don’t need more time.

Maybe we need to experience more of the time we already have.

We can’t stop the clock.

We can’t slow the Earth down.

And we certainly can’t negotiate with the calendar.

But perhaps we can change our perception of the time we’re given.

We can introduce novelty.

We can break our routines.

We can pay attention.

We can tolerate boredom.

We can put down the phone.

We can do things that scare us.

We can be present for the mundane moments instead of constantly trying to escape them.

Because when I think about it, the real tragedy isn’t necessarily that life is short.

It’s that we can spend so much of it barely noticing that we’re alive.

Since losing my job, I’ve started to feel like my days have become longer.

My weeks feel more distinct.

My memories feel richer.

And when I look back, I can actually remember what I did.

It almost feels like I’ve been given extra life for free.

Maybe that’s the real secret.

Maybe slowing down time doesn’t mean making the clock move slower.

Maybe it means making more of the time we have count.

And if that’s true, then perhaps the first step is surprisingly simple.

Put down the phone.

Try something new.

Let yourself get bored.

Pay attention.

And for just a little while...

Be where you are.

Hello World!

Last week, my family and I spent several wonderful days exploring New York’s Finger Lakes.

There wasn’t anything particularly extraordinary about the trip. We went sightseeing. We ate good food. We laughed. We wandered around. We took far too many pictures that will probably never leave our phones.

But somewhere in the middle of it all, while watching my kids run around and seeing everyone genuinely happy, I was reminded of something that I think many of us spend years forgetting.

Time is our most valuable resource.

Not money.

Not status.

Not promotions.

Time.

Once it’s gone, it is gone forever.

There Will Always Be Another Meeting

Modern life has a funny way of convincing us that everything is urgent.

Another meeting.

Another deadline.

Another sprint.

Another quarter.

Another performance review.

There is always one more project that absolutely must get finished.

The problem is that while work can always generate another task, life doesn’t generate another childhood.

Your son is only twelve once.

Your daughter only wants to hold your hand for a surprisingly short number of years.

Your parents only have so many healthy summers left.

Those opportunities don’t get rescheduled.

They simply disappear.

The Lesson I Learned After Being Laid Off

Getting laid off after twenty five years in the technology industry changed far more than my employment status.

It changed how I value my time.

For most of my career, I believed what many professionals believe.

Work hard.

Do a good job.

Be dependable.

Earn promotions.

Climb the ladder.

None of those things are inherently bad. Work gives us purpose. It pays our bills. It provides structure. It allows us to care for the people we love.

But somewhere along the way, many of us quietly allow work to become the center of our identity.

Then one day the company restructures.

Management changes.

Budgets get cut.

Artificial intelligence reshapes the business.

Or someone you’ve never met decides your position no longer exists.

Just like that, years of loyalty are reduced to a brief HR meeting and a severance package.

The company moves on.

Eventually, everyone does.

What Actually Lasts

That realization can feel depressing at first.

It can even make the universe seem strangely indifferent.

But I think there is another way to look at it.

If careers are temporary, then maybe we should stop expecting them to provide permanent meaning.

Because when our lives are over, nobody is going to gather around our hospital bed to admire our LinkedIn profile.

Nobody is going to remember that one presentation you finished at two in the morning.

Nobody will care how many meetings you attended.

Instead, people remember something much simpler.

The laughter around the dinner table.

The road trips.

The vacations that almost didn’t happen because everyone was “too busy.”

The conversations that lasted late into the night.

The traditions that only your family understood.

The times you showed up when someone needed you.

Those become the stories that get told long after we’re gone.

The Real Return on Investment

As someone interested in financial independence, I spend a lot of time thinking about investing.

Stocks.

Real estate.

Cash flow.

Retirement simulations.

Compound interest.

Those things matter.

But there is another investment that compounds in a very different way.

Experiences.

A weekend camping trip.

A family vacation.

Teaching your child to fish.

Watching a sunset together.

Sharing an ordinary dinner without everyone staring at their phones.

Unlike financial assets, these experiences appreciate in a way that can’t be measured on a spreadsheet.

Years later, they become treasured memories.

Sometimes they become family stories that get passed down for generations.

That is a return no investment portfolio can match.

Redefining Success

I don’t think success is about rejecting work.

We all need to earn a living.

We all have responsibilities.

But perhaps success isn’t maximizing every dollar.

Perhaps success is maximizing the moments that money makes possible.

Financial independence isn’t valuable because it lets you stop working.

It’s valuable because it gives you more control over your time.

And time is the one resource that every billionaire, every CEO, every janitor, and every retiree receives in exactly the same way.

None of us knows how much remains.

Protect What Matters Most

If there is one lesson I hope my layoff has taught me, it is this.

Protect your time with the people you love.

Guard it just as fiercely as you guard your savings account.

Invest in experiences, not just assets.

Take the trip.

Go to the family reunion.

Call your parents.

Eat dinner together.

Watch the sunset.

The emails will still be there tomorrow.

The meetings will still be scheduled next week.

The corporate ladder will still exist.

But today’s memories can only be created today.

At the end of our lives, our greatest legacy won’t be our job title.

It won’t be the size of our investment portfolio.

It won’t be the number of promotions we earned.

Our legacy will be the happiness we created, the love we shared, and the memories that continue to live in the hearts of the people we cared about.

That, I think, is a life well lived.

Over the Fourth of July weekend, my dad, my son, and I went on one of our annual boys club fishing trips.

Between catching countless panfish, my dad brought up a topic that instantly transported me back to my teenage years.

He told me that I needed to do everything possible to get my son into a prestigious Ivy League university.

To him, this was obvious.

To me, it was deeply unsettling.

I spent most of the conversation trying to explain that artificial intelligence is fundamentally changing the economics of higher education. A degree from an elite university simply does not offer the same value proposition that it did thirty years ago.

Unfortunately, that argument went nowhere.

Instead, it reminded me of just how much pressure I experienced growing up.

Like many Asian kids, I was told that admission into a top university would determine the entire course of my life. My childhood became an endless cycle of SAT preparation, Advanced Placement classes, extracurricular activities, and constant competition.

The message was simple.

Get into a top university and success would follow.

Fail, and your future would be ruined.

Even today, decades later, thinking about college admissions still raises my blood pressure.

As a father, I now find myself asking a question that my parents never had to consider.

What is the purpose of a university in the age of AI?

The University Was Never Just One Thing

When people think about universities, they usually imagine classrooms, professors, lectures, exams, and diplomas.

But universities have always been several different institutions bundled together.

They conduct research.

They train workers.

They certify credentials.

They provide networking opportunities.

They help young adults develop socially.

For decades, this bundled model worked remarkably well because every one of these functions reinforced the others.

Graduates earned valuable credentials.

Employers trusted those credentials.

Students accepted enormous tuition costs because those credentials led to high paying white collar careers.

The system made economic sense.

At least it used to.

The Cracks Started Before AI

Even before large language models appeared, higher education was already showing signs of stress.

Universities competed for students by building luxury dormitories, massive recreation centers, and professional quality athletic facilities.

Tuition exploded.

Student loan debt exploded.

Education increasingly shifted away from intellectual development and toward vocational training.

Instead of asking students how to think, universities increasingly focused on preparing students for specific careers.

Then AI arrived.

AI Breaks The Educational Model

Artificial intelligence does not simply improve education.

It undermines many of the assumptions that higher education has relied upon for generations.

AI can explain existing knowledge more effectively than many lecturers.

AI can tutor students individually.

AI can write convincing essays.

AI can solve homework assignments.

AI can pass many college examinations.

This creates uncomfortable questions for me.

If AI teaches the lecture, why attend the lecture?

If AI writes the essay, what exactly is the essay measuring?

If AI passes the exam, what does the diploma actually certify?

The college term paper perfectly illustrates this problem.

When I was in school, writing a major paper required weeks of research, organization, revision, and critical thinking.

The paper itself was never the valuable part.

The value came from the thinking required to produce it.

Today, large language models can generate that same final product within minutes.

The artifact still exists.

The learning process does not.

Once that happens, the assignment no longer measures what it was designed to measure.

Universities Were Really Measuring Human Thinking

For generations, universities served as society’s measurement system for cognitive professions.

A degree signaled that someone possessed enough knowledge and reasoning ability to perform complex white collar work.

But AI changes that equation.

Many of the cognitive tasks that universities prepare students to perform are rapidly becoming automated.

If those jobs disappear, then much of the traditional university model loses its economic foundation.

Higher Education Will Fragment

I do not believe universities will disappear.

I believe they will break apart into specialized institutions.

Research institutes may become independent organizations funded by governments, private companies, or nonprofit organizations.

Technical credentialing may shift toward affordable online providers that continuously update practical skills rather than requiring four year degrees.

Communities focused on networking and social development may evolve entirely outside traditional campuses.

Most importantly, I believe a new category of institution will emerge.

Schools whose primary mission is teaching people how to think.

Teaching Humans To Think

This may sound strange at first.

Isn’t that what universities already do?

Increasingly, I do not think so.

When I talk about thinking, I mean reasoning.

Judgment.

Agency.

Taste.

Ethics.

Persuasion.

Understanding human motivations.

Making decisions under uncertainty.

These are the capabilities that remain extraordinarily valuable in an economy increasingly dominated by artificial intelligence.

Future education should not ban AI.

It should teach students how to collaborate with AI while maintaining independent judgment.

Students should learn how to verify evidence.

Challenge AI generated conclusions.

Recognize hallucinations.

Understand the limits of machine intelligence.

AI should become a thinking partner.

Never a thinking replacement.

Assessment would also need to change.

Instead of take home essays generated by language models, students may demonstrate their reasoning through live discussions, debates, collaborative problem solving, and real time decision making.

Perhaps professors themselves evolve into mentors rather than lecturers.

People whose greatest contribution is not transferring information, but sharpening judgment.

Ironically, liberal arts subjects that many universities have spent decades marginalizing, including philosophy, history, mathematics, political theory, and physics, may become some of the most economically valuable disciplines because they teach people how to think instead of simply training them for a specific job.

The University After AI

I am not convinced that artificial intelligence will replace every form of human work.

As long as AI remains a powerful tool rather than true artificial general intelligence, society will still require a relatively small class of professionals capable of solving novel problems, exercising judgment, and making difficult decisions.

Those people will create new companies.

Invent new products.

Lead institutions.

Navigate uncertainty.

The education system that produces those people will look very different from the universities we know today.

It will place wisdom above memorization.

Judgment above credentials.

Thinking above information.

As a father, I hope those institutions exist by the time my son reaches adulthood.

Because I suspect those are the schools that will matter most.

The future belongs not to the people who know the most.

It belongs to the people who can think the best.