The Metabolic Rate of Minds

Why the AI Era Doesn’t Reward the Smartest — It Rewards the Fastest Processors

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The Invisible Hierarchy

There is a hierarchy operating beneath the surface of every meeting, every classroom, every creative field, every market. It has always existed. But for most of human history it was obscured by other hierarchies — the hierarchy of credentials, of capital, of proximity to power. Those hierarchies are dissolving faster than anyone expected. And what’s emerging underneath them is something older, stranger, and more biological than anyone is comfortable discussing.

It’s metabolic rate. But for the mind.

Here’s the specific thing I mean. A hummingbird’s heart beats 1,200 times per minute. A blue whale’s beats around 4. Both are alive. Both are functional. Both are evolutionarily successful. But they are running at completely different speeds — and those speeds determine everything about how they interact with their environment, what they can eat, what threatens them, what they can build or find or escape from.

Cognitive metabolism works the same way. The speed at which a mind can ingest a signal, break it apart, recombine it with something unrelated, and produce something novel — that speed varies enormously between people. And crucially, unlike IQ, it’s not fixed. It’s trainable. It atrophies. It responds to diet, to stimulation patterns, to sleep, to the company you keep, to the questions you choose to sit with.

What AI just did — without announcing it — is make cognitive metabolic rate the primary unit of human value in the knowledge economy. The rate at which you can process, transform, and generate.

Let me give you a number that should stop you cold.

In 2023, researchers at MIT studying AI-augmented knowledge work found that the top performers using AI tools weren’t the ones with the deepest domain expertise. They were the ones who could iterate fastest — who could generate a hypothesis, test it against an AI response, revise the hypothesis, and loop again. The fastest iterators in the study produced outputs rated as significantly more creative and useful than the deepest experts who moved more slowly and deliberately.

The bottleneck had shifted from the depth of the well to the speed of the pump.

This isn’t entirely new. Darwin noticed something like it when comparing the cognitive styles of naturalists. The ones who made the most unexpected discoveries weren’t necessarily the most learned — they were the ones who moved between observations fastest, who let a strange bird’s beak in the Galápagos collide immediately with everything they’d ever read about resource competition and adaptation. Darwin himself described his mind as a strange machine that couldn’t stop connecting things. He called it, somewhat embarrassingly, a compulsion.

We’d call it a high cognitive metabolic rate.

The neuroscience is catching up to the intuition.

What researchers now call default mode network activity — the brain’s background processing that runs when you’re not focused on a specific task — correlates strongly with creative insight and unexpected connection-making. Interestingly, people with ADHD show elevated default mode network activity even during focused tasks, which partly explains both the distraction problem and the disproportionate creative output. Their minds are running two programs simultaneously, always. The metabolic cost is enormous. The generative potential, in the right conditions, is extraordinary.

Ned Hallowell, the Harvard psychiatrist who has spent thirty years studying ADHD, calls it having a Ferrari engine with bicycle brakes. He means it sympathetically. What he’s actually describing — without using the term — is a very high cognitive metabolic rate paired with poor throttle control.

The AI era just made the Ferrari the winning vehicle. And it’s building better brakes.

There’s a concept in ecology called metabolic scaling theory, developed primarily by physicist Geoffrey West at the Santa Fe Institute. West’s team discovered something remarkable: across all biological life, metabolic rate scales to body size in a precise mathematical relationship — roughly to the power of 3/4. A creature ten times larger than another uses only about 5.6 times the energy. Bigger organisms are more efficient per unit of mass. But they’re also slower. They think more slowly, react more slowly, evolve more slowly.

West then applied this same scaling analysis to cities and organizations. Cities show the opposite pattern to organisms — the larger the city, the faster the metabolic rate per capita. More patents per person. More crimes per person. More restaurants, more innovation, more disease. Everything accelerates with density. The city is the opposite of the organism: it speeds up as it grows.

This is the key insight nobody is applying to the knowledge economy right now.

For most of the 20th century, knowledge organizations behaved like organisms — they got bigger, more efficient, and slower. A 10,000-person company processed ideas like a blue whale. Deliberate. Thorough. Metabolically conservative.

What AI is doing is forcing every knowledge organization to behave like a city. Density without size. Speed without scale. The metabolic rules have inverted.

And the individuals who will thrive are the ones whose personal cognitive metabolism is already running on city logic.

Here’s where it gets personal, and where most “future of work” essays stop just before the interesting part.

I’ve been running an experiment on myself for the last several years that I didn’t recognize as an experiment until recently. Writing 2,500 articles. Making 1,500 videos. Pursuing fifteen intellectual threads simultaneously, always. Functioning, in academic terms, like a deeply scattered person. In metabolic terms, I’ve been training.

Every time you force your mind to produce output — to transform an input (a paper, a conversation, a news story, a feeling) into an articulated thought — you are doing a metabolic rep. Like interval training. The mind gets faster at the input-transformation-output loop.

The writers I’ve watched who produce at extraordinary volume — Paul Graham, Tyler Cowen, Robin Hanson, and on the creative side, people like Brian Eno — don’t appear to be smarter than their peers. They appear to be running hotter. Their minds are processing at a higher clock speed. Cowen reads hundreds of books a year not because he has superhuman memory but because he’s running a specific metabolic protocol. He calls it “maximizing the throughput of ideas.” He’s engineered his life for cognitive metabolic rate.

The fascinating wrinkle is that Cowen has spoken openly about how his mild autism affects his information processing — how the same trait that makes some social situations difficult also enables him to process text and ideas at unusual speed without the usual social-emotional overhead consuming cognitive bandwidth.

Neurological “difference,” reframed metabolically, looks like a competitive advantage optimized for a very specific environment.

That environment just became the dominant one.

So what actually determines your cognitive metabolic rate? Four factors, based on what the neuroscience and complexity science together suggest:

Input diversity. Minds that feed on a narrow range of sources develop narrow association networks. The rate at which you can make unexpected connections depends on the distance between the things you know. A physicist who reads poetry has more raw material for unexpected synthesis than a physicist who only reads physics. This is why polymaths — genuine ones, not credential collectors — have historically produced disproportionate breakthroughs. Poincaré in mathematics and physics and philosophy simultaneously. Leibniz in calculus, logic, metaphysics, diplomacy, and engineering. Their metabolic advantage wasn’t intelligence — it was the span of their input network.

Output frequency. There is compelling evidence from cognitive science that the act of articulating an idea — writing it, speaking it, drawing it — changes the structure of the underlying neural network representing it. It doesn’t just record the thought. It refines the machinery that produced the thought. This means high-frequency producers aren’t just doing more work. They are genuinely building faster minds with each output. The writing is not the product. The writing is the training.

Recovery architecture. This is the one nobody talks about. A high metabolic rate organism requires corresponding recovery. Hummingbirds enter torpor — a near-death metabolic slowdown — every single night. Without it, their extraordinary metabolic rate would kill them. High cognitive metabolic rate without deep recovery — genuine sleep, genuine silence, genuine unstructured time — burns the apparatus. The scattered, always-on mind that never enters torpor is not running fast. It’s running ragged. The difference matters enormously. This is where the ADHD advantage can flip into a disadvantage: high metabolic rate without torpor is just exhaustion wearing the mask of productivity.

Friction reduction. Every decision, every administrative task, every social obligation that doesn’t feed the metabolic loop is friction. High metabolic rate minds need low-friction environments the way racing engines need clean fuel. This is why Jobs wore the same clothes every day. Why Murakami runs every morning — not for health, he’s said, but to establish a rhythm that clears cognitive friction. Why the most productive academics I’ve ever known are almost pathologically protective of unscheduled time. They’re not being antisocial. They’re managing their metabolic environment.

Here is the provocation I want to leave now:

We are building AI systems that are extraordinarily fast at certain kinds of cognitive processing. Breathtakingly fast. A model that can read and synthesize a thousand papers in seconds is running a metabolic rate we can’t match on that specific task.

But metabolic rate isn’t just speed. It’s speed across terrain that matters.

The hummingbird is faster than the whale. But it cannot cross the Pacific.

What AI cannot yet do is choose the terrain. It cannot experience genuine curiosity — the pull of merak, the Turkish word that means longing-as-curiosity, the feeling that drags you toward a question before you know why it matters. It cannot be surprised by itself. It cannot have the experience of two distant ideas colliding inside a lived life and producing something that didn’t exist in either source.

That collision, that metabolic event, is still biological. Still personal. Still the most valuable thing a mind can do.

The question is whether you’re running fast enough to have it often enough to matter.

How to Engineer Your Cognitive Metabolic Rate — and What Happens When You Do

Photo by julien Tromeur on Unsplash

Start with a fact that should rewrite how you think about expertise.

In 1993, Anders Ericsson published his landmark study on deliberate practice — the research that Malcolm Gladwell later distorted into the 10,000-hour rule. What almost nobody discusses about that study is what Ericsson found about the structure of expert practice among the best violinists at the Berlin Academy. The top performers didn’t just practice more. They practiced in shorter, more intense bursts — never more than four hours of deep practice per day, always with full recovery between sessions. And critically, they slept more than the average performers. About an hour more per night.

The best violinists were running higher metabolic bursts with deeper recovery troughs. They were interval training.

Now apply this to cognitive metabolism. The knowledge economy spent thirty years worshipping the grind — the 80-hour week, the always-on inbox, the virtue of exhaustion as proof of seriousness. What that culture actually produced was a civilization of people running their cognitive engines at medium speed continuously, never hitting true peak performance, never entering true recovery. Metabolically, it’s the equivalent of jogging at 60% capacity for sixteen hours and calling it training.

The people running away from the pack right now — in any field — are almost universally doing something that looks, from the outside, like they’re working less. They’re not. They’re spiking harder and recovering deeper. Their cognitive metabolic curve looks like a heartbeat. Everyone else’s looks like a flatline that’s proud of itself.

The second engineering principle is stranger and more counterintuitive.

Boredom is metabolic fuel.

In 2014, Sandi Mann and Rebekah Cadman at the University of Central Lancashire ran a series of experiments on boredom and creative thinking. Participants who were made to do a profoundly boring task — copying numbers from a phone book — before a creative task significantly outperformed those who went straight to the creative task. The boring task, they discovered, forced the mind into a diffuse processing mode. The default mode network activated. The mind, deprived of stimulation, started generating its own connections.

This is a complete inversion of how most ambitious people manage their attention.

Every moment we fill with a podcast, a scroll, a notification, a video — we are eating the boredom that would have become an insight. We are consuming tomorrow’s creative output as today’s cheap stimulation. The mind that is never bored is the mind that is always downstream of other people’s thinking, never generating its own.

The highest cognitive metabolic performers I’ve studied — and I include here not just scientists but artists, investors, writers — all have what I’d call a boredom practice. Not meditation, necessarily, though that’s one form. Something more raw: scheduled emptiness. Walks without earphones. Meals without screens. Long baths. Train journeys where the phone stays in the bag. These aren’t retreats from productivity. They are the metabolic recovery that makes the next spike possible, and the diffuse processing state where the most unexpected connections get made.

Einstein’s thought experiments didn’t happen at his desk. They happened on walks. Kekulé discovered the ring structure of benzene in a dream — literally in a hypnagogic state, watching a snake eating its own tail. Poincaré famously solved a problem that had blocked him for weeks the instant his foot touched the step of a bus, having completely stopped thinking about it. The insight arrived from the default mode network, not the executive network. Not from focus — from the productive emptiness that follows intense focus.

You cannot schedule the insight. But you can schedule the emptiness that allows it.

Now the most important engineering principle of all, and the one most brutally relevant to right now.

Cross-domain reading is not a luxury. It is the primary metabolic training mechanism.

Here’s the mechanism. The brain stores knowledge not as discrete files but as networks of association. When you learn something new, it activates nodes across the existing network, creating new edges between previously unconnected ideas. The more distant the new knowledge is from your existing knowledge base, the more new edges get created per unit of learning.

This means reading in your own field has a declining metabolic return. Every new paper in organizational behavior, for an organizational behavior researcher, creates fewer new connections than a paper in evolutionary biology, or a novel by Dostoevsky, or a study of Ottoman architecture. The marginal associative value of familiar terrain is low. The marginal associative value of genuinely foreign terrain is enormous.

Francis Crick, who co-discovered the structure of DNA, was a physicist who came to biology late. He attributed his breakthrough directly to his outsider status — he didn’t know what was supposed to be impossible, so he didn’t stop at the boundaries that stopped everyone else. He was metabolically running on alien fuel. Barbara McClintock, who discovered genetic transposition — jumping genes — decades before anyone believed her, was a botanist with a passion for Eastern philosophy who spoke openly about trying to develop a relationship of “feeling for the organism.” She was importing conceptual tools from outside biology to see biological phenomena that biologists trained purely inside the paradigm couldn’t perceive.

The cross-domain reader is not wasting time on irrelevant things. They are building the most valuable possible associative infrastructure — the kind that produces, when conditions are right, the connection nobody else could have made because nobody else had both pieces.

Let me now name the thing that most productivity writing refuses to name.

There is a metabolic tax on social performance.

Every time you perform a version of yourself — in a meeting, on a panel, in a networking event, in any context where you are managing others’ perception of you — you are spending cognitive metabolic currency. Not a trivial amount. A 2016 study by Roy Baumeister’s group found that self-regulatory effort — the effort of managing your behavior to meet social expectations — depletes the same cognitive resources as complex problem-solving. Social performance and creative thinking are drawing from the same account.

This is why so many high-output creators are, to put it gently, difficult in social situations. Because they’ve made an often-unconscious metabolic calculation: I cannot afford to spend this currency on performance. I need it for production.

The implications for how you structure your life are significant. Every obligation you take on that requires sustained social performance — committees, administrative roles, networking rituals, professional theater — is reducing your cognitive metabolic budget. The question isn’t whether these things have value. It’s whether their value exceeds their metabolic cost. For most people operating inside large institutions, the honest answer is: rarely.

This is what Geoffrey West’s city metabolism data is actually telling us, read against the grain. The reason cities are metabolically faster than organisms isn’t just density of people. It’s density of genuine interaction — transactions that produce new information — versus performed interaction — transactions that consume energy without generating novel outputs. High performers in cities are ruthless about this distinction. They gravitate toward the former and escape the latter.

The same ruthlessness, applied personally, is not antisocial. It’s metabolic hygiene.

Here is something almost nobody is saying about AI tools and cognitive metabolism, and it matters enormously.

Used wrongly, AI is a metabolic sedative.

When you outsource a thinking task to an AI and accept the output without genuine wrestling — without using it as a starting point for your own synthesis rather than an ending point — you are performing the cognitive equivalent of taking an elevator instead of climbing stairs. You arrived at the same floor. But your legs got no training. Your cardiovascular system got no stimulus. You are, metabolically, exactly where you were.

The people who are using AI to accelerate their cognitive metabolic rate are doing something different. They’re using it as a sparring partner. They generate something, throw it at the AI, get a response, argue with the response, revise their thinking, generate again. The AI is not replacing the metabolic work. It’s increasing the frequency of metabolic reps per unit of time. They’re doing more iterations in the same period. Their cognitive loop is running faster.

This is the actual superpower that AI offers the high-metabolism mind, and it’s almost entirely undiscussed in the “AI productivity” conversation which is obsessed with outputs rather than the development of the apparatus producing outputs.

The low-metabolism use of AI: generate output, accept, move on.

The high-metabolism use of AI: generate output, interrogate, revise, collide with something unrelated, regenerate, surprise yourself.

One of these is a tool. The other is a training protocol.

The mind that surprises itself is the most valuable mind in the room.

The one that, in the act of thinking, produces outputs that surprise even its owner — outputs that arrive from the collision of distant ideas running at high metabolic speed through a life that has been genuinely, promiscuously curious.

That experience — of genuinely surprising yourself — is a metabolic signal. It means two things have collided that had never collided before. It means you are operating at the edge of your own map. It means the next thought you produce could be the one that nobody else could have produced, because nobody else has lived exactly this life, read exactly these things, made exactly these weird lateral moves across disciplines and languages and cultures and obsessions.

Nassim Taleb calls this being in the “long tail” of the distribution of minds — the place where the expected statistical output breaks down and genuine novelty becomes possible. He didn’t build his career on being smarter than everyone in quantitative finance. He built it on running a different cognitive metabolism — one fed on ancient Stoic philosophy, Lebanese mountain culture, probability mathematics, and a visceral contempt for institutional consensus. The collision of those inputs, running hot, produced ideas that nobody else had the metabolic profile to generate.

Your scatter, running at the right metabolic rate, with the right recovery architecture and the right cross-domain fuel, is the entire point.

The AI era didn’t make the focused specialist obsolete overnight. But it did shift the premium — decisively, structurally, and probably permanently — toward the mind that runs hot, feeds wide, recovers deep, and surprises itself often enough to keep surprising everyone else.

The hummingbird cannot cross the Pacific. But it can do something the whale cannot. It can change direction seventeen times per second.

Fahri Karakas is the author of the following books:

• The 2036 Wealth Revolution: 12 Trillion-Dollar Industries That Will Create the Next Generation of Millionaires
• You, Only Synthetic: The $500 Billion Industry Selling Fake Humans, Digital Souls, and the Manufactured You
• The Last Frontier Playbook: Space, Asteroid Mining, Multiplanetary Civilization & the $10 Trillion Economy Above Your Head
• When Intelligence Gets a Body — How Robots, Autonomous Systems, and Physical AI Will Rewrite Work, Wealth, and What It Means to Be Human
• Immortality Inc. The Solopreneur’s Playbook to the $600 Billion Death-Defying Revolution
• The AI Wealth Explosion: How to Build Financial Independence in 2026 Before Your Job Becomes an AI Prompt
• The Exit Protocol: How to Leave Dying Systems Before They Take You Down
• Self-making Studio
• 99 Creative Journeys: Unleash Your Imagination
• The 2035 Mind: 30 Mental Models for Exponential Wealth.

Fahri is passionate about doodling, creativity, asset creation, and the future.