Originality Is Overrated (Even for AI)

“The secret to creativity is knowing how to hide your sources.”

— Albert Einstein

A few weeks ago, a friend and I were debating the future of AI. Not the general hype cycle, but a question rooted in its future capability: is AI becoming a genuine thinker, or is it just an extraordinarily fast doer?

The distinction matters. It shapes how you use AI as a tool, and more importantly, it forces a question people are genuinely wrestling with: what does it mean to be inherently human when machines become more capable on what feels like a weekly cadence?

The conversation got really interesting when we started talking about agentic forums like OpenClaw (a.k.a Moltbot, a.k.a ClawdCode), places where people were genuinely unsettled because AI responses sounded too human. Eerily fluid. Emotionally aware. People were worried about what that meant.

But here’s the thing: of course it sounds human. It was trained on human data. Every essay, every conversation, every published thought. Fed back to us in a mirror we built ourselves.

What I haven’t seen is original thought. Not once did either of us point to something AI had produced and say, “I’ve never encountered that idea before.” Sophisticated? Yes. Well-structured? Absolutely. Novel? That’s a different game entirely.

If AI is a doer, it’s the greatest synthesis machine ever built. It reads everything, processes everything, recombines faster than any human could. Powerful, but not new. Borrowed wisdom at unprecedented scale.

If AI is a thinker, we’re dealing with something fundamentally different.

“Taste” has become the word people reach for. The thing that supposedly separates us from the machines. I’m not sure anyone really knows what it means yet. It’s a word that can say a lot or a little. Everyone thinks they have it. Probably very few do.

But my conversation got me thinking about something more specific than taste. It’s not about what separates good from great. It’s about what makes a thought genuinely original in the first place.

Original thought has a mythology problem. We treat it like a lightning strike. Some genius wakes up, gets hit with a radical idea, and the world changes.

Cue: Newton and the apple. Archimedes in the bath. Einstein daydreaming on a train.

But those are stories we tell after the fact. The reality is far less cinematic.

Original thought is built, not born. There’s a sequence to it:

Step 1: You develop the capability to think clearly at all. Most people don’t make it past this step.

Step 2: You learn to think principally: from bedrock, not borrowed assumptions.

Step 3: Only after enough exposure (call it 10,000 hours, life experience, whatever resonates), enough cross-pollination across domains and experiences, do your thought patterns start producing something that feels novel.

Even then, the raw materials were always borrowed. The combination is what’s yours.

This is where AI seems to hit its ceiling. It clears the first two steps effortlessly. It thinks clearly. It reasons from principles. But it has no life. No career crisis that forced a reckoning. No immigrant parents who shaped how you see resourcefulness. No quarter-life meltdown that rewired your relationship with ambition. No friend conversations that quietly reframe how you see the world.

AI borrows brilliantly. But it has nothing personal to pour into the barrel of original thought.

Borrowed ideas age like fine wine. That’s an underappreciated fact.

A physicist discovers a principle. An engineer applies it to bridges. A business leader adapts it to supply chains. A psychologist finds it in human behavior. Each person refines it, stress-tests it under new conditions, adds depth the original thinker never imagined.

Newton’s laws didn’t stay in physics. They migrated to economics, biology, and philosophy, getting richer and more useful with each translation. That’s not dilution. That’s maturation. And every person who touches the bottle adds something AI can’t: the residue of a life lived.

Ray Kroc didn’t invent McDonald’s. The McDonald brothers had already perfected the “Speedee Service System”: a burger made in 30 seconds. But the real genius behind McDonald’s growth wasn’t Kroc or the brothers. It was Harry Sonneborn, a former Tastee-Freez executive who approached Kroc with a simple reframe: stop thinking like a restaurant company, start thinking like a real estate company. Own the land, lease it to franchisees, and let the burgers pay the rent.

Sonneborn famously told Kroc: “You’re not in the burger business. You’re in the real estate business.”

Could AI have analyzed McDonald’s unit economics and flagged the real estate opportunity? Maybe. But Sonneborn didn’t find it through spreadsheets. He found it because he’d spent years in the franchise world, watching which operators thrived and which didn’t. The insight came from mileage, not math.

Pep Guardiola borrowed “Total Football” from Johan Cruyff, his mentor at Barcelona. Cruyff inherited the philosophy from Rinus Michels at Ajax, who refined ideas that traced back to Gusztáv Sebes and the great Hungarian teams of the 1950s. The lineage stretches back decades.

What Pep did was understand the philosophy so deeply he could adapt it across different leagues, different players, different eras. Barcelona → Bayern Munich → Manchester City. Same principles: positional play, pressing, ball control. Completely different application each time.

Could AI have mapped Cruyff’s system to a different formation? Sure. Could it have felt the pressure of a dressing room full of egos in a foreign country and known which principles to bend and which to protect? That judgment came from standing in the room, not studying it.

The best ideas aren’t consumed fresh. They’re passed from hand to hand, each person adding something to the barrel: a new context, a stress test, a different application. By the time you pour the glass, you’re tasting generations of refinement. That refinement requires lived experience, something that hasn’t been trained into a model quite yet.

For months after I started Mental Wealth, I had a quiet worry. These models weren’t mine. Munger said them. Naval said them. Others lived them. Who was I to share ideas I didn’t invent?

Twelve posts dissolved that worry through the act of writing itself. Each edition has forced me to dig into an idea, pressure-test it against real experience, and explain it in a way that lands.

And here’s what I found: the gap between knowing about something and knowing how to use it is where the real edge lives. AI can explain inversion better than I can. It can define it faster, cite more sources, list more applications. What it can’t do is tell you what it felt like to use inversion to pull yourself out of a fog.

I didn’t invent inversion. But applying it to a personally lived career transition? That synthesis was mine. It was mine because I lived it, not because I thought of it first.

That’s what AI can’t replicate. Not the framework. The weight behind the application.

If even the most powerful synthesis machine ever built can’t shortcut the need for lived experience, then you definitely don’t need to pressure yourself to be original.

Once you let go of that pressure, you can stop performing and start learning. You’re not trying to impress people with how clever you are. You’re trying to make better decisions using frameworks that have already been stress-tested by people smarter than you. AI becomes your jet fuel, not your replacement.

You start building faster. Instead of reinventing the wheel, you ask: Who’s already solved this? What can I borrow? How do I adapt it to my context?

Understanding borrowed ideas across multiple domains often leads to insights that feel original. When you combine a psychology principle with a business framework and apply it to a relationship, the synthesis might be genuinely new, even if the ingredients aren’t.

You didn’t get there by trying to be clever. You got there by going deep. And depth requires living, not just reading.

Curate ruthlessly. Follow people who think clearly. Read books that have lasted decades, not just whatever’s trending this month. The ideas that survive time are the ones worth internalizing.

Understand deeply. Don’t just learn what a model says. Ask why it works. Ask where it breaks. Ask how you’d explain it to someone who’s never encountered it.

Apply broadly. Take a principle from biology and ask how it shows up in business. Take a mental model from investing and ask how it clarifies a personal decision. The more domains you stretch an idea across, the richer your understanding becomes.

Live fully. This is the one AI can’t do for you. The conversations, the failures, the career pivots, the Sunday morning coffee where nothing exciting happens but something clicks. That’s the raw material that turns borrowed frameworks into personal wisdom.

The more you practice cross-domain thinking, the more connections you see. Those connections become your fingerprint. The one thing no model can replicate.

The conversation with my friend was never a debate. It was curiosity rooted in mutual interest. I’ve always been fascinated by human psychology. He’s drawn to business and unlocking the next opportunity. Together, those threads led to something refreshing, a conversation I don’t think AI is ready to have. Maybe ever.

What we were really circling was a simple question: what’s innately human? What are the attributes that make us relatable? Where does taste actually come in? The chat gave me clarity on what makes human thought irreplaceable. Not invention. Not novelty. The lived experience that transforms borrowed ideas into something personal, tested, and real.

Newton didn’t invent gravity — he explained it. Einstein didn’t invent relativity from scratch. He saw what others missed. Kroc didn’t invent the hamburger. He saw the real estate play. Pep didn’t invent Total Football. He refined it across three decades and four leagues.

None of them started from zero. All of them added something only they could: the weight of their own experience.

Mental Wealth is my version of decanting. I’m borrowing ideas that have been aging for decades, sometimes centuries, and trying to pour them into something you can actually use. The flavor is richer because of everyone who touched the bottle before me.

And if you take what I’ve shared and apply it to your life, you’re adding to the vintage. That’s how wisdom compounds. That’s what no algorithm can shortcut.

Originality is overrated. Understanding is underrated.

The wine gets better each time it changes hands. Don’t be afraid to pour yourself a glass.