When Intelligence Becomes Cheap, What Happens to Humanity?


We survived machines that replaced our muscles. But are we ready for machines that replace our minds?

There was a time when I was searching for inner peace. Today, I find myself losing that peace thinking about Artificial Intelligence.

I have been using ChatGPT since its launch. I watched it evolve from something resembling a personal secretary into a programmer, researcher, analyst, and now an increasingly capable problem-solver.

Every few months, something that looked impossible becomes ordinary.

And strangely, instead of feeling excited about the possibilities, I sometimes wonder: Where is humanity heading?

This Revolution Is Different

We have seen revolutions before.

The Industrial Revolution replaced physical labour. Computers automated calculations and repetitive tasks. The internet transformed how we accessed information.

But none of them possessed intelligence or independent reasoning comparable to what AI is beginning to demonstrate.

They challenged how we worked. AI is beginning to challenge what makes our work valuable.

For centuries, our greatest advantage over other living beings has been our ability to think, reason, imagine, and invent.

Even among humans, education and intellectual skills have often determined economic opportunities. The educated had advantages over those without formal education, although intelligence was never the exclusive property of the educated.

And now, we are making those very capabilities available to everyone, almost instantly.

What happens when intelligence itself becomes a commodity?

The Old Escape Route Was Learning

When I was in college, I remember people in their forties attending computer institutes.

They were learning new skills to survive a changing world.

That was the beauty of earlier technological revolutions. When your skills became outdated, you could learn something new and rebuild your career.

A civil engineer could graduate at 22, build a career around civil engineering, and retire as a civil engineer at 60.

The tools changed. The profession remained.

But imagine graduating today, spending years mastering a skill, only to discover that AI can perform much of it before you establish your career.

You learn something else. AI catches up again.

You reinvent yourself. Another model arrives.

Yesterday, learning was the solution to disruption. Tomorrow, learning itself may become a race against disruption.

Innovation With an Expiry Date

As an entrepreneur, this troubles me even more.

You identify a gap. You research. You innovate. You build a product.

And just when you are ready to launch, a new AI model introduces the very capability you spent months developing.

Your innovation hasn’t failed. It has simply become unnecessary.

We once built products hoping they would last for decades.

Now, some innovations may have a shelf life shorter than the time required to build them.

When thinking becomes cheap, inventions become easier. But staying relevant becomes harder.

Of course, opportunities will continue to emerge. Not every profession or innovation will disappear.

But can we still build a lifelong career around a single expertise? Or will we spend our entire working lives reinventing ourselves, never knowing when the next reinvention will become necessary?

From Career Anxiety to an Existential Question

This is no longer just about jobs or salaries.

For generations, we told our children: Study well. Develop your intelligence. Learn a skill. Build a career. Secure your future.

What do we tell them now?

Learn something AI cannot do?

And what happens when AI learns that too?

Perhaps the biggest challenge ahead isn’t unemployment. It is the possibility of losing the connection between human intelligence, effort, achievement, and purpose.

If machines can think, create, and solve problems better than us, what will make us feel valuable?

I am not against AI. I use it every day. I see its extraordinary potential, and I know there will be opportunities.

But I also see a future where the shelf life of knowledge keeps shrinking, where experience may lose value faster than we accumulate it, and where staying relevant becomes a lifelong marathon with no finish line.

We spent centuries building machines to free ourselves from physical labour.

Now we are building machines that may free us from intellectual labour.

But what if the freedom we are creating becomes the very thing that makes us question our purpose?

Maybe the next great human challenge will not be learning how to become more intelligent.

Maybe it will be learning how to live meaningfully in a world where intelligence is no longer our greatest advantage.

And perhaps, after all these revolutions, we will return to where we started.

Searching for inner peace.

AI Stole My Cheese. And It May Steal It Again in Six Months.


I have been in technology and business for 26 years.

I started when creating a website itself was a skill. Then tools simplified it. PHP changed development. Frameworks reduced development time. Open source changed how we built products. Then came cloud, SaaS and APIs.

Every few years, somebody moved my cheese.

But AI feels different.

AI didn’t just steal my cheese. It seems capable of stealing the next cheese before I even decide where to keep it.

I have been using AI from its early days and watched it move from generic answers to usable content, code, reasoning and now agents that can actually perform tasks.

And I can clearly see gaps in today’s agents.

They struggle with some workflows. They need supervision. Enterprise integrations are messy. Exceptions confuse them.

The entrepreneur in me immediately thinks: “There is a business here.”

Then another voice asks:

“Will this problem still exist six months from now?”

That is something I have never experienced at this intensity in my 26 years of business.

Everyone Is Asking the Same Question

Talk to employees: Will my job survive?

Talk to entrepreneurs: What should I build?

Talk to software companies: What happens when AI can build this itself?

There are plenty of answers—learn AI, reskill, build agents, become AI-first.

But frankly, much of it still feels like writing in the air.

Nobody really knows where the capability line will be two years from now.

That made me realise I may have been asking the wrong question.

Instead of:

“What can I build that AI cannot replace?”

Maybe I should ask:

“What becomes more valuable as AI becomes more capable?”

Don’t Build Around AI’s Weakness

If I build a business around something AI cannot do today, my business depends on AI remaining bad at it.

That is a dangerous moat.

But if I own the customer problem—the workflow, integrations, domain knowledge, exceptions, relationships and operating process—AI becoming better can actually make my business better.

My cost of solving the problem comes down.

That completely changes the equation.

Don’t make AI’s limitation your moat. Make AI’s improvement your leverage.

Maybe I Was Trying to Plant the Wrong Thing

For years, I wanted to build something that lasts.

Something I could plant today and still see standing twenty years later.

AI made me wonder whether that is possible anymore.

Then my own journey gave me an answer.

HTML changed. Development tools changed. PHP changed. Frameworks changed. Infrastructure changed. Cloud changed things again. Now AI is changing almost everything.

But businesses still have customers.

Buildings still need managing. Companies still need moving data between systems. Money still needs collecting. People still need problems solved.

And suddenly it became obvious:

The problem was the tree. Technology was only its leaves.

Leaves are supposed to change.

What Do I Plant Now?

I don’t know where AI will be five years from now.

I don’t think anybody really does.

But I don’t need to find something AI will never change.

I need to find a problem worth owning even if the way we solve it changes five times.

A temporary AI gap might last six months.

Use it.

It brings customers. Customers bring workflows. Workflows bring knowledge. Knowledge creates systems, relationships, distribution and trust.

Those may survive the next model release.

Maybe creating a legacy in the AI era isn’t about building something that never changes.

Maybe it is about building something that knows how to change without losing the problem it exists to solve.

After 26 years of technology repeatedly moving my cheese, perhaps that is the lesson:

AI will keep moving my cheese. My job is not to guard the cheese. It is to own the dairy.