The Fire We Carry
The quiet rewiring of the human mind
Every transformation in human history begins with a tool we barely understand how to hold.
When one of my sons learned to build a fire (more like a bonfire) he was very excited. He wasn’t excited because he needed to use this skill all day every day — it was because he wanted to learn. He’d speak to his friends, experiment, watch a video, gather kindling, arrange it in a teepee or layer sticks and logs the way he discovered how. Everything was technically correct.
It wouldn’t light.
When he was younger, he tried over and over initially. Adjusted the spacing. Blew on the embers. Got smoke but no flame. After twenty minutes he looked at me, frustrated, and I crouched down beside him and did what my father had done with me — moved two sticks, added a handful of dry leaves or an old newspaper in a spot that shouldn’t have mattered, and waited. I remember the first time I lit a fire with my father like it was yesterday, even though it is now decades later.
The fire caught.
“How did you know to do that?” he asked.
I didn’t, exactly. My hands knew. Many years of campfires, burned fingers, failed attempts, and the particular way air moves through wood when the gap is right. Knowledge that lives in the body, not the brain. The kind you can’t look up.
He could have asked an AI for the optimal fire-starting configuration. He would have gotten a better answer than mine — faster, more precise, with citations. But he wouldn’t have learned what I learned crouching beside my father: that fire is a conversation, not a formula. That the wood talks back if you listen. That some knowledge only forms through failure, patience, and heat.
Something about that moment with my kid also stayed with me.
Not because my son couldn’t start the fire. That part was normal. Every generation has to learn certain things the hard way.
What lingered was a different question: what kinds of knowledge will still require that kind of learning — the friction, the failure, the heat — in a world where intelligent systems can answer almost anything instantly?
Over the past year I’ve been noticing subtle changes in how thinking itself happens around me — in my work, in my conversations, and even in the way my children interact with technology. At first it felt like a productivity shift. But the more I paid attention, the more it seemed like something deeper: a change in the architecture of cognition.
Over the next several essays I want to explore that shift a bit. Not from the perspective of AI capability, but from the perspective of human agency. What happens when intelligence becomes something we interact with rather than something we carry entirely inside our own heads?
We’ll look at why technology may quietly reshape cognition, why organizations may need to intentionally unlearn certain forms of expertise, and why the most valuable human skills may be migrating toward judgment, direction, and meaning.
But to understand where we may be going, it helps to start with something much older.
Fire.
The Wrong Historical Analogy
When people try to understand the moment we’re living through, they reach for the Industrial Revolution.
Factories replaced muscle. Machines reorganized labor. Cities reshaped economies.
But the Industrial Revolution didn’t fundamentally alter the structure of human cognition. Workers thought the same way after the power loom as before it — they just thought about different things.
A better analogy may be much older.
Fire.
Richard Wrangham’s research argues that the control of fire — and particularly cooking — may have altered caloric efficiency in ways that contributed to supporting the energetic demands of the expanding human brain, though the hypothesis remains one part of a multivariate picture.1 Fire extended the day, reorganized social interaction around the hearth, and may have literally enabled the cognitive capacity that distinguishes us from other primates.
Fire wasn’t merely a tool. It became an environmental condition. It changed what the brain could become.
Artificial intelligence may be becoming one as well.
For most of history, tools extended human capability. The hammer extended force. The telescope extended sight. The printing press extended knowledge. AI may be the first widely available tool that directly participates in complex cognitive tasks such as reasoning, synthesis, and planning — which is another way of saying it may be the first tool that extends thought itself.
That difference matters. Because when the environment around thinking changes, the brain does not remain the same.
The Brain Optimizes for Efficiency
Cognitive science has consistently shown that humans shift mental work into the environment when reliable tools exist. Psychologists call this cognitive offloading — the delegation of mental operations to external systems such as devices, written notes, or other people.2
This is not a weakness. It’s one of humanity’s great strengths.
Humans are uniquely good at constructing cognitive ecosystems. We store knowledge in books. We store navigation in maps. We store arithmetic in machines. Each time we do this, something subtle happens.
The brain reorganizes.
Neural systems that are heavily used strengthen. Systems that are rarely used gradually diminish. The brain is not a museum that preserves everything it once held. It’s an optimization engine that allocates resources toward whatever the environment demands.
As I explored in The Doing Was the Knowing, the doing is where expertise lives. The verbs — curate, reason, update, act — are the mechanism through which humans develop judgment. The brain doesn’t just use those operations. It becomes those operations through repeated practice. Strip the verbs and you don’t lose efficiency. You lose the architecture that made competence possible.
The London Taxi Driver Lesson
One of the clearest demonstrations comes from research on London taxi drivers.
For decades, drivers seeking a license had to master “The Knowledge” — a detailed mental map of roughly 25,000 streets and thousands of landmarks. Neuroscientists studying these drivers discovered that experienced cabbies had significantly enlarged posterior hippocampi, a brain region associated with spatial navigation and memory.3
Years of navigation training physically reshaped the brain. The posterior hippocampus grew. The anterior shrank. The longer someone had been driving, the more pronounced both effects became.
Later studies revealed the complement. When navigation is habitually outsourced to GPS, reliance on hippocampal-dependent spatial strategies decreases and self-guided spatial memory performance declines — and the longitudinal data suggests GPS use caused the decline, not the other way around. Whether this produces lasting structural change is not yet settled.4 The brain reallocates resources. Practice builds structure. Delegation dissolves it.
I think about this every time I watch my daughter navigate. She’s growing up in a world where the blue dot does the wayfinding. She’ll never be lost the way I was lost — truly, disoriently, productively lost — wandering streets in a foreign city (or your own neighborhood...) with a paper map and the growing panic that I’d misread the scale. That panic taught me something GPS never will: what it feels like when the territory exceeds the map.
Something I plan to explore in more detail soon: information answers what is. Knowledge answers what does it mean, and what should I do. The taxi driver who memorized 25,000 streets didn’t just have information about London. They had knowledge of it — embodied, contextual, alive in their hippocampus. The GPS holds the same information. It holds none of the knowledge.
AI Offloads Something Different
Previous technologies mostly externalized memory, navigation, or calculation.
Artificial intelligence interacts with a deeper layer. Reasoning. Planning. Interpretation. Synthesis.
For the first time in history, large portions of knowledge work itself can be partially externalized. Controlled experiments at Harvard Business School and MIT have shown that generative AI assistance significantly alters how professionals approach complex tasks — often increasing productivity while simultaneously changing how cognitive effort is distributed across planning, drafting, and evaluation phases.5 The effects are not uniform — in some settings, less experienced workers benefit most, while top performers show mixed results (at least for the earlier form of AIs, 2026 is likely going to be the year of top performer impact).
The system changes. The thinking changes with it.
We already operate beneath our own awareness — the brain constructing the feeling of deciding after the decision is made, the Dorsolateral Prefrontal Cortex (DLPFC) writing a story about agency that arrives 200 milliseconds late to a party that started without it. We were already strangers to our own cognition. Now we’re building systems that interact with that cognition in ways we can’t fully trace.
My son’s fire eventually burned for multiple hours. He sat by it, poking the logs the way boys have poked fires for thousands of years. At some point he said, “I get it now.”
He didn’t mean the fire-starting technique. He meant the thing you can’t explain — the relationship with material, the patience, the listening. The knowledge that forms only through contact.
What happens when AI mediates more and more of that contact?
What Migrates, What Atrophies
Whenever technology absorbs a capability, that capability doesn’t disappear. It migrates. Arithmetic migrated to conceptual mathematics. Photography migrated to composition. Human value shifts upward — less execution, more judgment; less production, more intention. I’ve started thinking of this as the Agency Gradient, and we’ll explore it more deeply later in this series.
But the deeper question isn’t whether AI makes people more productive. It’s what forms of thinking we stop practicing. Neural circuits strengthen with use and weaken with disuse.6 If humans stop reasoning independently, reasoning processes may increasingly occur in interaction with external systems rather than entirely within individual cognition. That isn’t dystopian speculation. It’s how brains work.
A new literacy is emerging: the ability to direct intelligence rather than merely produce it. To frame questions. To evaluate reasoning. To maintain agency in systems that generate answers faster than you can think.
The Fire We Carry
Fire allowed humans to cook food, survive harsh climates, and gather after dark. It also burned cities.
That’s the deal with every powerful thing.
Anthropologists believe fire reshaped the human brain gradually — through centuries of altered diet, extended days, and the social structures that formed around the hearth. The tool became an environmental condition. And the brain, as we’ve seen, adapts to its environment. It strengthens what it uses. It lets go of what it doesn’t need anymore.
This is what makes AI different from every tool that came before it.
The hammer extended force. The printing press extended knowledge. GPS extended navigation — and as we saw with the London cabbies, the brain quietly reorganized in response. But AI isn’t extending a single capability. It’s reaching into the whole stack: reasoning, synthesis, planning, judgment. The cognitive work that used to define what it meant to be competent at something.
Which brings me back to my son and the fire.
He could have looked it up. He would have gotten a better answer than anything I gave him — faster, cleaner, more precise. But he would have skipped something I didn’t know how to name until I watched him sitting quietly by the embers afterward, ash on his jeans, with that particular stillness that comes when something difficult has finally yielded to you.
That stillness isn’t satisfaction. It’s the feeling of a new capability forming inside you. The kind that only comes from staying in contact with a hard thing long enough for it to change you.
The question at the center of everything I’ve been writing about AI is this: if the brain reorganizes around what the environment demands — and AI is rapidly changing what the environment demands — what happens to the knowing that requires struggle to form?
Not information. Not answers. The deeper kind.
The kind that lives in the hands.
I don’t think we’ve seriously asked that question yet. And I think how we answer it — individually, in our schools, in our organizations — will shape what kind of minds we carry into whatever comes next.
The question is not whether the flame exists.
The question is who learns to carry it wisely.
And whether we’ll still have the hands — calloused, practiced, burned, and healed — to hold it at all.
Part of an ongoing exploration of human agency in the age of intelligent systems.
Further Reading
The Doing Was the Knowing — On CRUD, the verb layer, and what happens to expertise when agents take over the operations.
Let the Robot Wars Begin! — On compiled intent, agency erosion, and who owns the verbs in 2026.
Your brain is changing from AI right now - TranscendingX #90: Michael J. Jabbour with Uri Schneider. Full podcast below:
Footnotes
Richard Wrangham’s Catching Fire argues that the control of fire — specifically cooking — may have been one of several evolutionary developments that contributed to the expansion of the human brain, though the timing and relative importance of cooking versus other factors remain debated. Cooking increases caloric yield from food by 30-50%, providing the energetic surplus needed to support metabolically expensive brain tissue. The implication is profound: a tool changed the biological substrate of thought itself. Wrangham, R. (2009). Catching Fire: How Cooking Made Us Human. Harvard University Press.
Cognitive offloading — the delegation of mental operations to external tools and systems — is a well-documented feature of human cognition, not a failure of it. Humans are uniquely skilled at constructing “cognitive ecosystems” that distribute mental work across brains, bodies, and environments. The question AI raises is whether offloading reasoning produces the same benign redistribution as offloading memory. Risko, E. F., & Gilbert, S. J. (2016). “Cognitive Offloading.” Trends in Cognitive Sciences, 20(9), 676-688.
The landmark study of London taxi drivers showed that acquiring “The Knowledge” — the mental map of 25,000 streets — produced measurable structural changes in the posterior hippocampus. The finding demonstrated that intensive cognitive training physically reshapes the adult brain. Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S. J., & Frith, C. D. (2000). “Navigation-related structural change in the hippocampi of taxi drivers.” Proceedings of the National Academy of Sciences, 97(8), 4398-4403.
Subsequent research demonstrated the inverse: habitual GPS use is associated with reduced reliance on hippocampal-dependent spatial strategies and poorer self-guided spatial memory performance; structural claims require more evidence. The brain reallocates resources away from spatial navigation when the task is reliably handled by external systems. Dahmani, L., & Bohbot, V. D. (2020). Habitual use of GPS negatively impacts spatial memory during self-guided navigation. Scientific Reports.
Research from Harvard Business School and MIT on AI-assisted knowledge work found that consultants using GPT-4 completed tasks 25% faster and produced 40% higher quality output — but also showed altered patterns of cognitive engagement, with less time spent on planning and more on evaluation. The productivity gain was real. The question of what cognitive patterns changed is still being measured. Dell’Acqua, F., et al. (2023). “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality.” Harvard Business School Working Paper.
Hebbian plasticity — often summarized as “neurons that fire together wire together” — describes the basic mechanism by which experience shapes neural architecture. Circuits that are frequently activated strengthen their connections; circuits that fall into disuse weaken. This is not metaphor. It is the physical basis of learning, memory, and cognitive capacity. Hebb, D. O. (1949). The Organization of Behavior. Wiley & Sons. For modern reviews: Magee, J. C., & Grienberger, C. (2020). “Synaptic Plasticity Forms and Functions.” Annual Review of Neuroscience, 43, 95-117.
Looking forward to more in the series!