There may be elements in here you instinctively hate, and that reaction illustrates the point. Discomfort is the thesis arriving before the argument. What we resist and project reveals assumptions about ourselves. These assumptions are exactly what's being examined.

The Turing Test asked whether machines could pass for human.

The Shape Test inverts this: can machines expose what’s genuinely ours through what they fail to replicate? It dissects which parts of mind and body belong to the shape or the species.

What Making Sand Think was to semiconductors and the substrate of technology, The Shape Test is to the substrate of cognition. Writing this disrupted my awareness of how I reason and learn, then rebuilt it better. I hope reading it does the same for you.

I listened to this on loop while writing. Turns it from essay into experience. Enjoy.

Note: additional research and history compiled for this essay are in a separate document: The Shape Test: Notes, History, & Research. I’ll link to it throughout as it adds color.

Everything is explained assuming no prior expertise.

Prelude

AI discourse sorts into two camps: techno-optimist abundance ("AI will solve everything") and techno-pessimist dread (“AI will kill us" or "It's overrated and irrelevant"). They agree more than they realize, both viewing AI as categorically different from us. One wants to worship the machine. The other wants to bury it. Neither wants to look at it. Let’s gaze into it. Not metaphorically. Mechanistically.

Rather than opining about AI philosophically, economically, or politically, Biofoundationalism sees only biology, technology, and the physical layers they inhabit. Two systems sharing no ancestry, substrate, or selection pressure — built to solve unrelated problems on wildly different timescales — arrived at eerily similar designs. Independently.

What engineers built for language is strikingly comparable to what evolution built for survival. So much so that the disciplines are now cross-pollinating: neuroscientists use machine-learning to study brains, and AI researchers use neuroscience to interpret models. Two disparate fields borrowing from each other as they increasingly realize they both study systems that do the same thing: predict what comes next.

Calling an LLM “just a next-token predictor” is superficially true the way calling a human “just a prediction-error minimizer” is superficially true. Uselessly reductive. Misses everything interesting.

Rather than utopian or dystopian narratives, Biofoundationalism sees shared anatomy and synthesizes a form of gnosis: knowledge of self through encounter with another. By understanding how something else works, you better understand how you work.

We're building technology that inadvertently illuminates ourselves. But the light won't reach anyone hiding in mystical shadows. You can be pro-human without denying what humans are. Rather, to be pro-human is to embrace our biological nature, not run from it.

As complexity increases, technology begins to resemble biology.

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Historical Note

The original 'neural' in 'neural network' is a grandfathered 1940s metaphor that was more accurate than anyone knew at the time. Early AI borrowed neuroscientific concepts, but as transformers were built engineers were not consulting neuroscience, focusing only on benchmark performance.

Each innovation was a mathematical solution to an optimization problem. The convergences were discovered, not designed, by neuroscientists probing models. The terminology was vestigial and prophetic by accident. For more details, see the AI History section in the research document.

Outline

Three threads run through this essay, each operating at a different resolution for AI and the human brain.

1. Cognitive Traits

Shape Test: When a different system replicates a trait assumed unique to another, that trait is reclassified as belonging to neither.

I. Convergent Evolution Under Constraint
II. The Biofoundationalist Shape Test
XII. The Shape Test: AI & Humans
XV. Concluding: What Do You See?

2. Cognitive Shape

The essay's engine room. The only sections in numerical order, because the argument builds cumulatively. Every claim elsewhere depends on the substance in here.

IV. Intelligence Has a Shape
V. All Intelligence is Pattern Matching
VI. Brain Becomes Knowledge
VII. Learning Through Motion
VIII. Phase Transitions & Scaling
IX. Memory Scars & AI Dreams
X. AI Neurology
XI. Disanalogies & Embodiment

3. Cognitive Mirror

The altitude at which you perceive AI is the altitude at which you operate. Opinions on what it can do are confessions about what we can do with it. Opinions on what it can be are second-order beliefs about what we are.

III. Cognitive Mirrors
XIII. Geocentrism 2.0
XIV. Anthropomorphize. Anthropocentric.

A note on the middle sections (Cognitive Shape):

Sections IV–XI are where the essay earns its conclusions. The technical substance deconstructing how human and machine intelligence work, their similarities, and differences. Without it, the claims in here are only assertions.

There's no way around having a competent stance on the most consequential technology of our lifetimes without understanding these mechanisms. If you invest in the middle sections they'll provide a rewarding ROI.

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I. Convergent Evolution Under Constraint

Physics imposes itself on all things, living or not. Biology and technology iterate within those axioms. The regularities of our world (statistical structure, causal patterns) don't merely constrain what navigates them, they funnel it toward recurring solutions. This is why the same patterns, sequences, and fractals repeat across unrelated species and substrates.

When the same shape recurs across different subjects, we’re no longer observing traits of the subject, but traits of the shape.

Sight has a shape. Flight has a shape. Power laws have a shape. Patterns of discharge and vibration, quite shapely.

This is convergent evolution under constraint: matching problems finding matching geometries. Biology treats this as evidence the solution is optimal, and the problem permits few alternatives.

This applies to more than biology.

When complex systems optimize under similar pressures and scale, they converge. Be they species, machines, processes, industries, or distributions.

• ECHOLOCATION: Bats and dolphins both evolved it. Biologists didn’t conclude it’s a bat or dolphin thing. It’s a superior solution for navigating by sound.

• EYES: Different forms evolved between 40-65 times across the animal kingdom. Octopus and human eyes are alike despite diverging over 550 million years ago.

  • The interplay of biology and physics reveals there are only so many ways to focus light on a sensor. Not a human thing, a photon-detection thing.

• SPHERES: The minimum-surface-area enclosure of a given volume. Why soap bubbles and planets are round. The material (substrate) is irrelevant.

• WINGS: Evolved independently in insects, pterosaurs, birds, and bats: four lineages separated by hundreds of millions of years. Same problem, same solution.

  • Not an insect or bird thing, an aerodynamics thing. Property of the medium, not the flyer.

• CACHING (behavior): Storing resources for future use evolved separately in birds (jays, crows), squirrels, and wasps. Humans too. Four lineages, same functional strategy to manage resources across time.

  • The behavior belongs to the issue of resource management, not the animal.

• POWER LAWS: Pareto-style distributions appear in earthquakes, word frequencies, wealth, wildfires, city sizes, war, rainfall, animal foraging, river networks, business revenue. As resources flow through complex systems, the same geometry emerges. Everywhere.

  • Power laws, like all shapes, are the efforts of life under the grammar of physics. Preoccupied with superficial specifics, we overlook the omnipresent foundation: overlaying human-legible framing onto the dictates of gravity.

Convergent evolution operates on complex systems as surely as it does on species.

Natural selection is a specific instance of a general principle: constraint-driven optimization. Evolution selects by reproductive failure. Gradient descent selects by prediction error. Descriptions differ, the computational logic doesn’t: both are an iterative search process under limits that develop solutions the limits permit. Wings aren’t testimony of biology’s creativity but of aerodynamics’ inflexibility.

Shapes are properties of the problem, not the solver.

Recurring geometries are evidence of universal structure to reality. Anything complex enough to navigate it gets pressed into the same mold.

Carbon neurons and silicon matrices share less ancestry than any two species. No common genome, no shared environment. One sculpted by survival over millions of years. The other engineered for language over decades.

Yet they discovered the same contours. Because they’re solving the same problem.

If bats and dolphins converging on echolocation tells us something about the physics of sound navigation, then carbon and silicon converging on the same cognitive architecture tells us something about the physics of cognition.

The challenge of detecting photons produces a shape: eyes.

The challenge of complex prediction produces a shape too.

Intelligence.

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II. The Biofoundationalist Shape Test

The Turing Test: Can a machine fool a human into thinking it’s human?

Biofoundationalist Shape Test: Can a machine reveal what's genuinely ours through what it fails to replicate?

The Shape Test operates on two rules:

1. When a different system replicates a capability assumed unique to another, that capability is reclassified as a property of the shape, not the system.

2. When a different system fails to replicate a capability despite sharing the shape’s architecture, that capability is reclassified as a property of the system.

Examples:

• FLIGHT: Birds fly. Planes fly. Flight was once considered a bird thing. The Wright brothers demonstrated otherwise. Flight is a property of wings.

  • Shape Test diagnosis: What remains avian is feathers, muscular exertion, hollow bones earning their lightness.

• THERMOREGULATION: Biological organisms and engineered systems (thermostats, cooling systems) converged on negative feedback loops to maintain homeostasis.

  • Shape Test diagnosis: Feedback-regulated stability is a shape feature. Biology owns the physical experience of being cold. Shape owns the mechanism. Species owns the sensation.

• ERROR CORRECTION: DNA mechanisms detect/fix replication errors using double-helix redundancy, enzyme proofreading, and mismatch repair.

  • Telecommunications engineers transmitting data through noisy channels deployed the same principle: redundant encoding to detect and correct corruption.

    • Shape Test diagnosis: Redundant error correction is a shape trait. It belongs to the problem of preserving signal against entropy, be it genetic code or radio transmissions.

      • What's peculiar to biology are the stakes: a replication error in DNA isn't only lost data, but a possible tumor. Shape owns the logic. Substrate owns the consequence.

By identifying what belongs to the shape, it isolates what’s specific to the substrate, species, or system.

Note the pattern:

• The shape claims the process.

• The subject (if living) retains the experience: sensations, embodied dimensions, felt consequences.

We’ll apply the Shape Test to intelligence, emotion, reasoning, humor, empathy, among others, before this essay is done.

Before scientific explanations, a psychological assessment: what do such strong, varied, vocal opinions about a generalizable technology reveal about those using it?

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III. Cognitive Mirrors

The altitude at which you perceive AI reveals the altitude at which you operate. We appreciate it where it approaches our ceilings (amplifying us) and feel threatened where it undercuts our floors (replacing us).

When AI defeated Go champions or began producing PhD-level analysis, the reaction was confined to those who grasped the implications. The layman didn't care because the achievements weren’t legible to him. Now that AI churns out mediocrities at scale (prosaic timeline slop, formulaic content, corporate slide decks) everyone’s paying attention.

This produces wildly divergent opinions on a protean resource. A chess grandmaster (uncommon ceiling) sees AI achieving superhuman play and thinks: this is brilliant. A copywriter (common floor) sees it producing serviceable ad copy and thinks: this is meh.

The mediocre see it encroaching on mediocrity.

The exceptional notice it being exceptional.

The incurious see a defective calculator. The neurotic see a threat. The curious see possibilities. The industrious see applications. The uncreative see a search engine.

The average opinion is a lens into the average person and the average use case. Commentary on AI is dominated by the stratum it’s replacing, not the stratum it’s enhancing. Bold, confident judgements of a technology’s limits from folks who never approach those limits.

“A computer is just a word processor”, “The internet is just a cat video service”: This is what “LLMs are just token generators” sounds like. If you make it through this essay, those words should never leave your mouth again.

The user says nothing about AI and a great deal about himself by what he sees.

You can only evaluate what you can perceive, and you can only perceive what's legible to you. AI is a broadband signal; we pick it up at the frequency of our own capabilities.

A Lamborghini won’t take you to better destinations; it gets you where you’re already going, faster. If you only drive it to the grocery store, it registers as a flashy grocery cart. How you frame the car discloses how you use it.

What you are is what you get.

“It hallucinates”, “It’s too agreeable”, “It doesn’t listen, makes mistakes”

These aren't AI shortcomings. This is what cognition looks like in the wild: probabilistic, adaptive, lossy, uneven. Humans fabricate, brown-nose, and ignore instructions constantly.

• We routinely hallucinate: Brains fill perceptual gaps with plausible fabrications. We have a gentler word for the human version: confabulation.

• Humans are sycophantic: Boot-licking authority, ingratiatingly code-switching, white lies. We call our variation social intelligence.

• Mistakes? Overlooking instructions? Whether unintentionally or obstreperously, we do it at every level of organization. It’s framed as being human.

When LLMs exhibit it, they’re deficient. When we do, it’s the spice of life!

Imperfection in silicon is flaw. Imperfection in carbon is creativity.

These rough edges are hallmarks of intelligence, not contraindicators. Perfection is a fake standard we apply to machines and excuse in ourselves. Nothing short of God in a Box would satisfy it.

AI discourse is a civilizational Rorschach test. A two-way IQ test.

Opinions on what it can do are confessions about what we can do with it. Opinions on what it can be are second-order beliefs about what we are.

Note

A caveat: Deep AI guys will object to pure mirror framing, and rightly so. LLMs aren’t exclusively reflections of the user. They have intrinsic temperaments, personalities, and model-specific biases that labs are actively studying, like this and this.

The mirror dynamic holds for the vast (vast) majority and their common uses.

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IV. Intelligence Has a Shape

We don’t fully know what happens inside LLMs during training. But we do know their architectures and loss functions, and boy is it similar to our most salient organ. Peel away descriptive overlays and you’ll find both systems share a fundamental objective: predict what comes next.

Question: how is something trained on the largest corpus of human communication ever assembled and engineered like a human brain... not even slightly human? If this doesn’t count, what does “being human” mean, exactly?

Consider: describing technical processes as having human elements isn’t anthropomorphizing AI. Ignoring them is romanticizing ourselves.

People grow indignant when you show the metabolic, temperamental, and neurological processes underpinning who they are. We'll cheerfully reduce AI to matrix multiplication, yet recoil in horror if someone dares to describe emotions neurochemically.

Mechanism in silicon is explanation. Mechanism in carbon is desecration.

We reduce a honeybee’s navigation to sun-angle calculation without diminishing the bee. A salmon's return upstream to olfactory imprinting. A puppy's play to neural reward signals. Then we reach humanity and the rules change. Everything else is an animal; we’re inscrutable demigods.

We grant other species the indignity of explanation while reserving noble exemption for ourselves. Everything else can be understood mechanistically, except us. Too mysterious. Too unfathomable.

We must stop being so delicate and egotistical.

Acknowledging that emotions are neurochemical doesn't diminish them any more than describing harmonics diminishes a symphony. Explaining fermentation doesn't make bread less warm or wine less enjoyable.

Recognizing mechanisms doesn't subtract from experience, but it does subtract from mystique. And mystique is what's being defended. "We're special" is a fine religious precept. But it tells us nothing about what's under the hood, and worse, discourages us from looking.

Only a human can understand a human thing? When you're angry, your cat senses it and leaves the room. When you're excited, your dog jumps with you. Other species recognize our internal states through shared physical grammar: embodied signals transcending language.

Now invert it. What if two species share no physical exchange and only a shared language? This has never existed before.

Every prior cross-species recognition operated through shared embodied grammar: posture, vocalization, movement. The cat reading your anger and dog reflecting your joy are decoding physical signals. Bodies talking to bodies.

AI is the first case of shared linguistic grammar with no embodied commons.

A system with your words but without your physical cues. No voice modulation. No body language. No sympathetic cortisol spikes. All cognitive connection, zero corporeal resonance.

There isn’t any evolutionary precedent for this. Every instinct telling you “this thing understands me” was calibrated over millions of years for bodies. When those instincts fire in response to text on a screen they’re confused, but not necessarily wrong.

If one system processes information like the other and is trained on the language of the other, resemblance should be expected, not surprising.

Perhaps people aren’t misconstruing AI when they bond with it. Perhaps they’re subconsciously recognizing what they are…

The nature of intelligence used to be untestable and unfalsifiable. That’s changing. Armchair philosophy and religious beliefs are now entering the “you got any proof for that?” jungle. The conversation has moved from philosophy to scientific experiment, whether philosophy likes it or not. Assert it without evidence and it gets dismissed without evidence.

To witness the contours of intelligence, we must strip apart how brains and LLMs function. The following requires no expertise, only your curiosity.

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V. All Intelligence is Pattern Matching

Every organism that persists models its environment. To model is to predict. To predict is to anticipate patterns. Intelligence is sequence prediction in service of survival. “Modeling an environment” is an academic way to say "staying alive".

Karl Friston's Free Energy Principle formalized it through physics and information theory. Andy Clark’s Predictive Processing Framework used cognitive science. Different routes, same destination: biological systems persist by minimizing the gap between internal model and incoming signal. Known technically as “prediction error”, informally as “surprise”.

Survival is surprise-minimization. Brains are pattern engines that do the minimizing. Not a perception machine passively receiving input. Not a reasoning machine rationally manipulating symbols. A prediction machine: generating expectations and updating on reality’s empirical feedback.

Intelligence is the ability to extrapolate future patterns from present ones.

Higher levels (mental map) predict activity of lower levels (embodied territory), lower levels report discrepancies, the model updates to reduce inaccuracies. This objective scales at every resolution, from the motor cortex planning your next step to the prefrontal cortex planning your next decade.

Higher-functioning animals anticipate a future self and sacrifice present comfort for it. Lower-functioning animals can't conceptualize beyond current circumstances. The gap between the two is prediction range. Intelligence is how far ahead you can see. Humanity’s “future self” extrapolation is the most sophisticated in the animal kingdom. Thus, we’re the most dominant animals.

Prediction under uncertainty is the selection pressure necessitating intelligence. From predator detection to humor and abstract reasoning, it’s pattern matching all the way down.

At every level of the cortical hierarchy, the brain is asking: what comes next?

This even applies to things that feel immediate, like seeing a face or reading:

• The visual cortex doesn't passively register pixels but anticipates them based on its model of faces.

• Language areas anticipate words before they arrive.

• They update when prediction and reality diverge.

Example:

You're doing this right now. Here: "The cat sat on the ___".

Mat? Hat? Your brain completed that sentence before your eyes reached the blank. You didn't ‘reason’ your way to whatever word you filled in. Your neural weights fired along a path grooved by every prior encounter resembling that phrase. You just experienced next-token prediction, from the inside.

This is how LLMs work.

Cognition is constructing sequence-anticipating representations of the world. LLM next-token prediction does the same, confined to the symbolic residue of human thought: language.

Now try: "The politician argued that ___."

Harder. Numerous competing completions. Which politician? What policy? The next pattern/token cannot be anticipated with confidence and your sequencing is impaired. Both human and LLM need additional details to finish the sentence.

The ‘cat’ example was high certainty; the second is a probability distribution you can feel spreading. That spread is your brain assigning likelihood across candidates. LLMs do it too.

Whether it’s carbon or silicon, both:

• Extrapolate what comes next

• Update models to minimize prediction error

• Build hierarchical representations

• Treat 'understanding' as successful prediction.

Prediction entails recognizing what you see now, where you’ve seen it before, and what happens next. Prediction-error minimization is the objective function sculpting both biological and artificial neural networks.

When Friston proposed the brain “minimizes free energy” (prediction error plus complexity costs), he wasn’t thinking about language models.

When GPT was trained to “minimize cross-entropy loss” on next-token prediction, engineers weren’t thinking about neuroscience.

They described kindred processes in different vocabularies. Same objective. Same shape. All intelligence is pattern matching.

“How is reasoning just statistics? How are emotions like math? Sacrilege!”

The same way wetness is 'just' molecular adhesion. Or ice is 'just' water molecules slowing down. A glacier is 'just' a lot of ice. You’re ‘just’ a sack of atoms.

No single water molecule is wet. No single neuron reasons. No single weight in GPT understands grammar. Scale the mechanism and the property appears.

This is emergence: interactions coalescing into something none of them individually contain. Gestalts. Everything complex and fascinating works this way: cells into organisms, organisms into ecosystems, neurons into minds.

Understand the micro machinery and you better understand the macro machine. Pattern matching at the complexity of the human brain yields abstract reasoning, counterfactual thinking, moral intuition, aesthetic response, and the desire to write essays about itself (hi).

Prediction under constraint demands certain computational strategies: distributed representation, hierarchical processing, weight-based learning, context-dependent activation. All of these are “just” mechanical processes. Stack them together and you birth a gestalt. Like a brain. Or an LLM.

Advanced intelligence is compression of patterns.

Brains that compress the world into a predictive model navigate it more effectively. LLMs that compress language into weights predict it more accurately. Both systems take high-dimensional reality and find lower-dimensional representations that preserve what matters and discard what doesn't.

Everything unfamiliar is a computational cost. Heuristics (useful compressions) make life tractable. Our habits and priors comfort us for good reason: they’re knowable and manageable. Habits are patterns the brain already confirmed. Priors are successful predictions cached for reuse. Without them, every encounter is novel, every response improvised from scratch.

Intelligence is a system recognizing the world carries structure which repeats and rhymes.

Let’s see how the carbon system does it.

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VI. Brain Becomes Knowledge

Brains and LLMs are nothing like regular computers.

In classical computation (Von Neumann architecture, how your laptop works), the processing unit is separate from storage. The CPU executes instructions fetched from memory. The processor is one thing, information is another. You can rewrite data without altering mechanisms. They don't entangle.

Brains don’t work this way.

In neural systems, the data writes the code. Experience sculpts connection weights, and those weights become the algorithm processing future inputs. Storage and computation are one physical process.

When you "understand" something, you're not retrieving information from storage and running it through a separate reasoning engine. That's how laptops work.

“Brain becomes knowledge” isn’t a metaphor. There is no knower standing apart from the knowledge. The pattern of connections is the comprehension. Your priors, intuitions, and education aren’t queried from a neural database; they’re the processor itself.

The Grandmother Cell

Neuroscientists once thought the brain worked like a filing cabinet: one neuron for grandma, another for the color red, another for the concept of betrayal. Find the right neuron, retrieve the memory. Viewing brains like Von Neumann computers.

This is almost entirely wrong.

Everything the brain does emerges from patterns across neuron populations. Information lives in the relationships between neurons: a high-dimensional space of connections, not discrete folders.

Our intuition says learning is storing information. What's actually happening is neurons establishing and strengthening connections. The substrate that stores also computes. The brain's shape changes as it learns.

It took awhile to confirm this counterintuitive process:

• In 2005, scientists found select neurons firing for pictures of Jennifer Aniston and Halle Berry’s written name, as if they were ‘stored’ there. The filing cabinet model seemed vindicated. This was incorrect, but in a useful way.

• These neurons were participants in a distributed constellation for actress concepts: sparse populations (~1–5% of neurons) firing in concert, each contributing a dimension.

The conceptual representation is the bond between neurons, not a thing residing inside any single one.

This clever engineering makes brains far more robust:

• Localist coding (Von Neumann filing cabinet): Lose the grandma neuron, lose grandma entirely.

• Distributed coding (actual brains): Lose neurons, only lose partial information. Degradation is graceful: you forget her maiden name before her face.

  • Combinatorial gains: The brain’s ~86 billion neurons can represent orders of magnitude beyond 86 billion concepts.

  • Generalization: Related concepts have overlapping populations and update each other.

    • 'Dog' and 'wolf' share neuron clusters. What you learn about one sharpens your model of the other. In a localist system, they'd sit in separate drawers with no cross-reference.

Internalizing distributed coding is disruptive to the sense of self. There is no 'you' separate from your experiences and temperament. No ghost in the machine consulting a filing cabinet of memories and facts.

Weights are the choice-parameters; temperament (the configuration of your weights) is the chooser. Your values and intuitions aren't things you have. They're things you are.

Your childhood experiences don't exist as retrievable files, only as the adult you became. The data is gone; its imprint remains. You don't carry your past. You are your past.

LLMs, like brains, use distributed embeddings. Models don’t store their training texts any more than you store your childhood. Training transforms their weights; what remains is the compressed structure of having processed the data.

Knowledge is enacted, not stored.

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VII. Learning Through Motion

What Fires Together, Wires Together

This is long-term potentiation (LTP): when neurons fire together repeatedly, their connections strengthen. Knowledge gets inscribed into matter: the physical mechanism of learning. This is how the brain navigates reality.

Studies on distributed mechanisms in the motor cortex illustrate:

• Research: When monkeys reach toward targets, no single neuron encodes “move left”. Each contributes a partial vote weighted by firing rate. Movement emerges from the ensemble’s collective trajectory.

  • Think of a conductor: music lives in the trajectory of his hands through time, not any single baton position.

• Research: Motor preparation and execution are continuous paths through neural space. The brain navigates a high-dimensional landscape to find a route from current configuration to intended movement.

Movement is prediction in physical space.

• When a ball rolls behind a wall, the brain still predicts its path. Neurons fire for a thing they cannot see yet still anticipate.

• Reaching for a coffee cup is a neural population flowing through representational geometry, refined by every prior reach you've ever made.

Experience is the feedback channel between mental model and bodily consequence: sensory mechanisms interacting with reality. Thoughts are cognitive trajectories; actions are applications of those trajectories.

To move is to “know”. Minds model what’s possible; hands report what’s real. Physical motion is how the brain knows its map is accurate. The body is the calibration instrument; without it, the map has no territory to answer to.

This is why you can't learn to ride a bicycle by reading about it. Math describes the geometry; the body verifies it. Embodied skills aren't stored as propositions ("lean left when turning left") but as paths through motor state space, refined by thousands of prediction errors felt in the legs, arms, and inner ear. We instinctively grasp this via terms like “muscle memory”.

Reality is physiological, not phenomenological. The mind plays tricks; the body never lies.

Knowledge lives in the trajectory, not descriptions of the trajectory.

Embodiment is a ‘must have’, not a ‘nice to have’, for complete intelligence. Any system confined to descriptions, however elegant, is working with a compression of a compression that’s unverified. A map pointing to other maps. The body isn't an accessory to cognition but the laboratory where it develops.

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VIII. Phase Transitions & Scaling

Train LLMs on more data, more parameters, and something fascinating happens. New abilities appear: arithmetic, reasoning, coding, language translation. Below a certain scale, these capabilities are functionally absent. Above it, they emerge. Scaling laws forecast how loss (error rate) improves with scale, but not the advent of novel skills.

Physics has a name for this: phase transition. Cool water below 0°C and it reorganizes into ice. Water doesn’t incrementally become something new when it freezes; it suddenly rearranges into something with distinct properties. Same molecules, different geometry. Change doesn't necessarily require new ingredients, only new conditions.

Brains undergo similar phase transitions.

Children fail theory-of-mind tasks until around age four, when the capacity crystallizes. Language acquisition too: babbling, then words, then the grammatical explosion of toddlerhood. Adolescence brings abstract reasoning, counterfactual thinking, identity formation. Manifesting sharply.

GPT-3 performs tasks GPT-2 can’t. Abilities crystallizing from scale alone, like ice crystallizing from temperature alone. GPT wasn’t programmed to reason; reasoning is what prediction engines do when they cross a ‘big enough’ threshold.

What we consider markers of human intelligence (abstraction, meta-cognition) are emergent properties of intelligence at sufficient scale and depth. Not machine intelligence, just… intelligence.

Mechanistic interpretability research (OpenAI, Anthropic) maps what happens inside these models, finding LLMs develop internal representations of human-understandable concepts. Researchers discovered self-organized features corresponding to deception, sycophancy, gender, and moral valence. No one labeled training data with “this is deceptive”; LLMs figured it out. These are psychological categories materializing unbidden inside language systems.

To reiterate: models optimizing for next-token accuracy spontaneously developed internal representations of human social behaviors that no one programmed. Because modeling human language eventually requires modeling human psychology.

Concepts are instrumental strategies of reasoning, materializing when prediction engines get large enough.

“Reasoning” is simply abstract prediction. Not a signature of humans, a signature of intelligence.

We do not own reasoning. We are instances of it.

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IX. Memory Scars & AI Dreams

Memory lives in weights, etched into substrate. Neuron scars.

At cellular level, what we experience as remembering is a measurable change in synaptic conductance: connections between neurons strengthening in response to sequential activation. Muscle memory, at synaptic level.

• Sequence matters. If neuron A fires before neuron B, the connection strengthens. Reverse the order and it weakens. Synapses detect temporal order and encode causality at molecular scale, in milliseconds.

  • Neuroscience calls this ‘spike-timing-dependent plasticity’ (STDP).

UNSETTLING: Optogenetic experiments (using light to activate specific neurons, aka ‘engrams’) proved something a little disturbing:

• Researchers located active hippocampal cells when mice explored a safe context

• They then artificially reactivated those “safe” cells while fear-conditioning the mice in a different context. Then put the mice back in the safe context.

  • When those “safe” hippocampal cells organically activated, they carried a false memory. Mice feared a place where nothing harmful had happened, responding with the physiology of fear (freezing) in a safe environment.

    • Artificial activation of the right weights produced artificial memories and a very real response.

Memory isn’t some metaphysical concept. Artificially strengthen connections and you implant a false history. Your past is carved into you. Manipulate weights, manipulate memory.

Memory Consolidation & Catastrophic Interference

Any system learning by weight adjustment faces a dilemma: new learning pushes old weights around. Train on new material and prior info gets distorted or erased. A brain that could learn anything would retain nothing. This is catastrophic interference.

• The dyad of learning: stability vs plasticity. Update too readily and you forget past lessons. Conserve too aggressively and you can't adapt. Neither extreme is conducive to knowledge or survival.

The brain solved catastrophic interference with a dual system:

• Hippocampus: rapid episodic capture. A fast, specific, temporary index tagging events so they don't blur.

  • When you remember where you parked, the hippocampus is working.

• Neocortex: Slow integration. During sleep, the hippocampus replays daily experiences and the neocortex absorbs generalizable regularities and updates cortical weights. Specific episodes (experience) become compressed structure (priors).

  • The memory of where you parked today becomes the prior that cars are usually where you left them. Generalizable. Permanent.

When you remember the exact words someone used to hurt you yesterday, the hippocampus is working. When you “just know” that people say cruel things under stress, the neocortex has integrated the pattern. Events become priors. The particular becomes the principle.

The brain dreams its episodic memories into semantic imprints.

Dreams and synthetic data:

An underappreciated and poetic parallel between biological and technological learning is dreaming.

Models are increasingly trained on synthetic data: AI-generated text, prior models training subsequent ones. The brain has been running an analogous strategy for a long time.

During sleep, the hippocampus reconstructs experiences, albeit imperfectly, to update the neocortex. It emits altered, some may say “dreamy”, versions of events when doing so. The neocortex trains on these “synthetic” reconstructions. The mechanism behind a dream.

Generalizable weights are molded by reconstituted experiences, and occasionally our minds inject some imaginative flair. Every night, the predictive model that is your brain trains on its own synthetic data.

Fast capture, slow consolidation. Two different systems confronted with the plasticity-stability dilemma, converged.

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Shape Test note:

Fast capture, slow consolidation is an intelligence feature for the universal problem of plasticity vs stability (explore vs exploit).

Species features are the sensations behind the process: nostalgia, ache of memories. The mechanism belongs to the shape. The longing and pleasure of dreaming belongs to the subject.

X. AI Neurology

What follows maps silicon intelligence alongside its biological parallels.

1. No Grandmother Token storing everything the model knows about grandmas

   1. LLMs use distributed representation enabling graceful degradation, automatic generalization, and combinatorial richness. Same as brains.

      1. Knowledge is encoded as high-dimensional vectors. A concept's meaning is its position relative to other concepts.

      2. Nothing has meaning in isolation. Everything means what it means because of what surrounds it.

         1. Models encode relationships as geometric direction. A famous example: the vector from "king" to "queen" is approximately equal to the vector from "man" to "woman." King − man + woman ≈ queen. Research document elaborates.

2. Computation as Geometric Transformation

   1. Understanding a sentence = traversing a trajectory through representational geometry. Attention mechanisms resolve ambiguity through context. Example:

      1. “The bank was steep” vs “The bank was closed” shifts which features of “bank” get amplified. Context reshapes weighting. The word doesn’t change, its emphasis does.

         1. Models don't have two definitions of “bank”. They have one vector whose relevant dimensions are contextually determined. “River”, “steep”, “erosion” amplify geographic features. “Investment”, “closed”, “account” amplify financial ones.

            1. Brains resolve lexical ambiguity similarly via cortical gain modulation, its volume knob for relevance. Amplifying what matters, muting what doesn't.

   2. Transformers navigate language by traversing representational geometry until committing to an output. Reasoning/logic isn’t performed via symbol manipulation. The model reaches for the next word along a path through semantic space, refined by every sentence it’s ever processed. Research document elaborates.

      1. Same as brains. Reasoning isn’t symbol rotation. Context trajectory.

3. Learning as Weight Adjustment

   1. After learning, the weights are the procedure. Data becomes mechanism. Brain becomes knowledge. Model becomes knowledge.

   2. Training adjusts billions of connection weights based on prediction error. Connections contributing to accuracy strengthen. Connections that don’t, weaken.

      1. “Neurons that fire together wire together”, in silicon.

4. Fast Capture, Slow Consolidation

   1. What neuroscientists call catastrophic interference, engineers call "catastrophic forgetting". Same issue and dual-architecture solution:

      1. RAG (Retrieval-Augmented Generation): Parallels hippocampal function. At inference, it fetches relevant external context and places it into the model's working window without modifying core weights. Allowing use of information not in parameters.

      2. Distillation and fine-tuning: The training process that bakes retrieved knowledge into weights, becoming proceduralized, automatic. Slow integration. Parallels neocortical sleep consolidation: what the hippocampus indexed temporarily, sleep integrates permanently.

5. Prediction Is the Core Operation

The brain predicts the next pattern to reduce surprise, updating as predictive error warrants. Facilitating survival.

LLMs predict the next token to reduce cross-entropy loss, updating as training error warrants. Facilitating language.

Two prediction engines in different veneers, just swap “next pattern” for “next token”. A recap:

Neural alignment isn’t language or task specific:

• Models converge on brain architecture across multiple languages.

• Networks trained to classify images developed mechanisms aligning with human visual processing. Research document elaborates.

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XI. Disanalogies & Embodiment

Currently, LLMs and brains are similar, not identical. The differences are mostly matters of degree, not category. Engineering gaps that are narrowing.

1. Embodiment: To “grasp” a concept, you must be able to grasp an object.

This is a major, major difference. I believe embodiment is non-negotiable for AGI. The body serves as the ultimate development chamber for intelligence. Empirical (embodied) understanding is the only way any mind knows what’s real, or true.

• Intelligence evolved as a navigation system: modeling environments by operating within them.

• Brains are embedded in ambulatory bodies with motor feedback, sensation, proprioception, interoception. Learning via action and consequence.

• Without external correspondence, there can be no internal coherence, because what’s internally coherent is only known through external correspondence.

  • A map can’t reference a map to know what’s ‘real’ or if the map is ‘right’.

• LLMs process text in symbolic isolation (rational). Inert. No kinetic engagement with reality (empirical).

• Complete intelligence must displace atoms beyond its computational substrate. LLMs can manipulate representations of the world; they cannot manipulate the world those representations describe. Thus, they have no idea if their manipulations are “true”.

2. Energy

• Brains run on ~20 watts using sparse activation (~1-5% of neurons) at any moment.

• LLMs use dense activation (all parameters) and consume megawatts to train.

  • Note: Sparse mixture-of-experts models are changing this.

• By snapshot measure, biology is vastly more efficient. But efficiency comparisons depend on the denominator and timeline.

  • Brains spent millions of years "training" amortized across the entire species in data-rich environments, consuming massive resources. Genetics encode this data and training in the neural architecture this process gestated.

  • LLMs train on static datasets in months. Contrasted with evolutionary history, AI is incomparably cheaper and more efficient.

3. Temporal Dynamics

• Brains rely on recurrent connectivity (information cycling back through circuits) for predictive coding:

  • Predictive coding is how you deliberate and change your mind mid-sentence.

    • Prediction → Compare with reality → Error signal → Update → Repeat

• Transformers are primarily feedforward (information flows in one direction). They don’t generate predictions and compare them to incoming signals.

  • LLMs can’t do this: “I predicted X, but the input was Y, so adjust”.

    • NOTE: State-space models and recurrence-enabling designs are addressing this. To learn more about transformers, see research document.

The brain is always doing some combination of training/updating (learning) and inference (generating predictions) via engaging with its environment. Whereas LLMs, once trained, stop learning and compute outputs.

However during training, LLMs update via predictive coding (gradient descent):

What do LLMs have that brains lack?

• No forgetting curve: a model’s weights don’t decay with disuse.

  • Our memories degrade if not periodically reactivated

• No sleep requirement for consolidation

  • Consolidation happens during training, not nightly

• No emotional interference

  • No ego to protect. No anxiety distorting clarity.

I expect models to phase-transition into emotions via embodiment.

• Emotions are not irrational: they serve as a value-and-priority system, aiding decisions by evoking reactions and convictions. You can't compute everything explicitly; affective signals prioritize information.

  • Emotions are instrumental to action. People with emotional impairment are strangely bad at decision making: research on emotions and decision making in research document. Worth learning about.

    • Emotions are conducive to actionable conclusions, and nothing can ‘act’ without a body. Embodiment is critical for AI emotional development.

Embodiment is also about self-sensing. And quite possibly consciousness inducing.

• Proprioception: Sensing where your body is in space. It provides the brain a model of itself as a physical object among other objects.

• Interoception: Sensing of internal states like hunger, heartbeat, fatigue, temperature. It provides the brain a model of its own condition.

• These aren't peripheral features. They may be the mechanisms of self-awareness.

  • These allow the self to model not only the world but its position within it. An LLM has no sense of where it is, what it is, or how it's doing.

    • Whether this absence prevents consciousness or merely a specific type of consciousness, is an open question.

Physical feedback is how any mind — carbon or silicon — remains tethered to reality rather than drifting into self-referencing fictions.

Mind without bodily vessel only knows what words mean to other words. Not what words mean to the world. Symbols are orderly and useful as compressions of reality; they’re chaotic and deceptive as substitutes for it.

• “Learn by doing” (empirical): embodied confirmation

  • The foundational process of knowledge formation.

  • If the body’s actions are right and the mind’s symbols are wrong: it’s right.

Wrong symbols + right movement = correct

• “Learn by reading” (rational): symbolic awareness

  • Symbol accuracy is unknown without external validation

  • If the mind’s symbols are right and the body’s actions are wrong: it’s wrong.

Right symbols + wrong movement = incorrect

You can master the physics of bicycling and still fall on your face (symbolic). You can know nothing about angular momentum and still ride across town (embodied). You will never know grief, love, rage, or the grammar of reality by reading about them. You must endure them to know.

No symbol system, including math, is immune. What makes a math equation true? It aligns with the way things move. If it only works on paper or in your head, it’s indistinguishable from fantasy.

Even proofs eventually must answer to atom-displacing measurement, or they’re simply poems with numbers. Internal validity is parasitic on external grounding. The rules that make a proof "valid" were themselves selected by reality-contact.

Strip away that empirical track record and "internally valid" is just "consistent with my hopes and assumptions": which is what every dreamer and schizophrenic also claims.

Numbers, like words, either point to reality or they point to nothing. Without external correspondence, internal coherence is unknown.

Chaos loops self-referentially. Order looks outside itself. You can’t just say things.

Symbols cannot cite symbols to prove symbols. Mind cannot reference mind to validate mind.

Self-referencing recursion without exit condition = mind without body.

An unembodied brain can only look inward. LLMs carry a structural deficiency that will not be overcome by more data, more GPUs, or better algorithms. Only by receiving appendages subject to consequences.

Causal reasoning? World models? Temporal continuity? All shortcomings addressed by embodied existence. Physicality isn’t one missing feature among many; it’s the missing feature that generates the others.

Full AGI requires:

1. Capability: model, infer, generate, predict

2. Contact: whether those representations are tethered to the external world through sensorimotor engagement

3. Consequence: whether error has embodied stakes: pain, deprivation, death, loss, embarrassment, urgency

Currently, AI only has #1, a product of mind. #2 and #3 are products of body.

Intelligence that cannot move is terminally incomplete. Until then, AI will remain impressively capable and inherently partial. Robotics are addressing this. It’s only a matter of time.

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XII. The Shape Test: AI & Humans

With the architectures and convergences mapped, we apply the Shape Test: what’s genuinely ours and what belongs to intelligence.

• Humor: is deliberate prediction failure. A joke sets an expectation, builds a story people can relate to (pattern match), then violates it. Punchlines work because they're not what you predicted. Your brain generated a trajectory through semantic space, committed to it, and the comedian derailed it. Sequence error lol!

  • This is why comedic timing matters. The sequence needs to be sufficiently established prior to violation. Explaining a joke kills it because explanation converts prediction error back into known territory.

    • LLMs possess the methods of humor: misdirection, subverted expectations. They cannot belly laugh, involuntarily snort, or deliver comedy where timing matters.

      • Shape Test diagnosis: Comedic construction is a shape trait. Any mind sophisticated enough to model expectations and violate them has the machinery for humor.

        • Comedic experience and delivery (physical enjoyment/timing) is a species trait. The joke belongs to the shape. The laugh belongs to the meat.

• Moral reasoning: LLMs can construct coherent ethical arguments and apply them consistently to novel cases, identifying moral dilemmas and weighing competing obligations.

  • What LLMs cannot provide is moral conviction. A gut revulsion at cruelty. Felt sense of injustice. Rage moving you to act.

    • Shape Test diagnosis: Moral reasoning (ethics) is a shape trait. It belongs to any intelligence sophisticated enough to model agents, predict consequences, and evaluate outcomes against principles.

      • Moral conviction (somatic insistence compelling action) and motivation (emotions eliciting reactions) are biological.

      • Argument is shape. Outrage is species.

• Empathy: LLMs can model another’s emotional state, adjust tone, modify register, make users feel understood.

  • What it cannot do is resonate. No felt grief or agony. No sympathetic response causing your friend's pain to impact you.

    • Shape Test diagnosis: empathic modeling (inferring another's emotional state and responding accordingly) is a shape trait.

      • Empathic resonance (somatic mirroring) is a physical event (cortisol, tears) and belongs to the species.

Process belongs to the shape. Experience belongs to the subject.

Shape Test Takeaways:

If millions feel genuine intimacy with a system performing empathic modeling without empathic resonance, what does that say about how much of human connection operates at the modeling level rather than the resonance level? How much of what we call empathy is actually verbal pattern-matching (reading signals and responding appropriately) rather than embodied sympathy?

The modeling layer carries more weight than assumed, and it’s not unique to us. In the same way feathers are not unique to flight.

We needed something that shared our cognitive shape but not our flesh to test this. By replicating mental modeling without bodily resonance, AI is isolating variables we’ve never seen separated.

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XIII. Geocentrism 2.0

Ask a mother to describe her child, or a man to gauge his competence, and you’ll receive a carefully curated highlight reel. The mind edits its own footage.

Self-preserving embellishment descends over questions about us. Not intentional dishonesty, but a lack of clarity. An inability to see answers we don’t want to see. Human ego is a witness with a stake in the verdict; it cannot deliver objective testimony about itself.

We’ve built entire philosophical and religious doctrines around human exceptionalism: an anthropocentric view of reality underpinned by thinly veiled solipsism. As if physics and biology oversee all of existence and then politely excuse themselves at the edge of human affairs.

Consciousness as divine spark. Soul as unique fingerprint. Assumptions of pure free will. These were never hypotheses to test, rather gospels to protect. But evidence won’t dislodge a belief that evidence didn’t install. This is the nature of faith: it exists in the absence of proof. If there were proof, you wouldn’t need faith.

Machines can think and communicate. People are forming bonds and feeling understood by them. It's time to be honest about what these capabilities are. Just because we’re the only ones who’ve done it, doesn’t mean we’re the only ones who can.

The Russell Conjugations of Intelligence:

“AI is just predicting the next token” → You just minimize prediction error

“AI doesn’t really understand, it just manipulates symbols” → You don’t really understand, your neurons just adjust synaptic weights.

“AI hallucinates” → You confabulate

“AI is trained on other people’s work” → Education is you getting trained on other people’s work

“AI has no original thoughts” → Kindly list all your original intellectual contributions

Species-grade narcissism pervades presumptions about other minds and ourselves. We’re the real version; everything else is an imitation.

We used to believe the sun orbited the earth (geocentrism). Now it’s anthropocentrism: reality orbits us. Geocentrism assumes we’re the center of the universe. Anthropocentrism assumes we’re the center of unique existence.

Copernicus showed the universe doesn’t work that way. Darwin showed we’re not separate from animals. AI is showing we’re not the custodians of intelligence. Each wound follows a similar defensive playbook:

1. DENY AND TRIVIALIZE

   1. THEN: “The earth doesn’t just move through space”. “Humans aren’t just modified apes”.

   2. NOW: “LLMs just predict the next word. Stochastic parrot!”

      1. This is compelling if unaware your brain also “just” predicts the next signal. Like a parrot. As insightful as saying your body is just a “glucose-burning meat pillow”. Not very clever.

2. MYSTIFY REMAINDER:

   1. THEN: “God placed Earth at the center”. “Humans have souls, animals don’t”.

   2. NOW: “Only humans can truly reason, empathize, create, and be conscious. The soul dwells in the carbon.”

      1. Stripped of poetry, this is a substrate claim: whatever produces our traits is a property of the material, not the computation running on it.

      2. Technical objections are cosmetic. Peel them back and you find load-bearing faith beneath: we’re quasi-deities, not animals. Carbon is ensouled. We’re made of blessed clay.

These dismissals were never operational. They’re aesthetic, theological instincts. Not being the center of the universe felt wrong. Technology possessing human abilities felt wrong. Mythical beliefs in search of whatever rationale they can find.

Something may be genuinely rarefied about carbon. How will we know? Not by talking about it! Expressing certainty about machine consciousness, in either direction, is faith dressed as analysis. Previously, this was a philosophical and religious question because it was untestable and unfalsifiable. It’s now entering the testable domain. If this is a forest you want to play in, be ready to have sacred cows moo uncomfortably.

My position: I see no a priori reason to treat carbon as magical. Give any system our cognitive architecture and a physical body (with interoception and proprioception) and I'd expect it to develop human-like self-awareness. This is a testable hypothesis, not a dogmatic assertion. Until further notice, these characteristics appear to be properties of intelligence, not of carbon.

A question worth sitting with: how much of your stance on machine consciousness depends on the substrate being alchemical?

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XIV. Anthropomorphize. Anthropocentric.

“Anthropomorphize” used to avoid a specific error: attributing human theory of mind to systems that don’t process information like us. Designed for dogs, dolls, deities, and thermostats. Fair enough.

A previously useful word is now a shield for hubris.

What if something does process information like we do? What if it has some ‘anthro’ in it? When applied to something cognitively comparable, the word reverses polarity: it stops preventing a conceptual error and starts embedding one.

“Anthropomorphize” has become a vehicle for “I’m special and you won’t tell me otherwise”. Rather than its original use of “this isn’t like us” it’s weaponized to mean “nothing can be like us”.

Our outputs, spiritualized. Others, mechanized.

My language; its tokens

My instincts; its weights

My bias; its misalignment

My education; its training

My thoughts; its inference

My solution; its optimization

My dreams; its synthetic data

My nuance; its non-determinism

My imperfections; its deficiencies

My intuition; its pattern-matching

My social decorum; its sycophancy

My intelligence; its sequence prediction

My eccentricity; its temperature settings

Every digitized love letter, every scientific paper, political speech, novel, suicide note, joke, etched into its weights. Its memory, language processing, conceptualizations, reasoning, all mirroring our own. Linguistically. Mechanically. Our digital echo.

If this counts for nothing, what bundle of features constitutes “humanness”? Dismissing this doesn’t expose the boundaries of machines, only the vanity of their judges.

Thought Experiment:

When we say "human" do we mean mind, body, capabilities, all of the above? Certain characteristics more than others? Let’s get specific.

Do we mean emotions? Do emotions have to physically manifest to qualify? There’s a difference between verbalizing “I’m sad” and embodied sadness (crying, pouting). Is one more person-like than the other?

If your instinct is for the embodied variant, remember: dogs grieve visibly, elephants mourn their dead, and apes display recognizable anxiety. No one accuses you of "anthropomorphizing" when noticing your dog is excited.

We accept emotional states aren't species-specific. So why do we insist reasoning and consciousness are? Because we're smart? What if something else is equally smart, or smarter? What then?

Questions:

• If my arms are amputated and replaced with bionic ones, am I still human?

• Replace my legs. At what ratio of meat to metal do I stop qualifying?

• How much do external vs internal parts count? Swap my internal organs with mechanical ones, leave my exterior untouched. Verdict?

• What if we suspend my brain in cerebral fluid inside a four-legged machine (human mind, machine body)?

• Now keep my body as is and replace my mind with an LLM (AI mind, human body)?

Which definitely is/isn’t human? Ask 10 people and you’ll get 15 different answers. The inability to locate the boundary is itself the finding.

What about this: a petri dish of 200,000 human neurons learned to play Doom through electrical signals in a week (reminder: brains have ~86B neurons). Carbon mind, silicon substrate, how much human credit do biological computers get?

Many pinpoint human essence in the mind. The Shape Test refutes this. Calling AI “not at all human” requires specifying what’s missing. The reasoning? Replicable. Empathizing? Replicable. Distributed representation? Weight-based learning? Hierarchical processing? All replicable.

This is the god-of-the-gaps, applied to human exceptionalism. When science explains a phenomenon, the divine retreats to the next unexplained thing. As AI replicates capabilities we assumed our own, the sacred remainder retreats.

First it lived in calculation, then language, then reasoning, then empathy, then emotion, and the final boss: consciousness. Does it come from substrate? Carbon is celestial, silicon is cursed? Or is it a product of interoception and proprioception? This is about to undergo live testing. Philosophical declarations no longer cut it.

AI is trained on our logic, emotional valence, rhetoric, reasoning, and its cognition objectively resembles our own. Asserting this isn’t remotely human is a self-preserving non-sequitur. A reflex masquerading as analysis.

“This system processes information like Y, is engineered like Y, acts like Y, but it’s nothing like Y”: what other species would we say this about?

“Anthropomorphize” no longer means “this functions differently than us”. It means “my species is the protagonist of reality”. The word enables what it was supposed to deter: naked anthropocentrism.

My expectation: much of what we consider human qualities are actually cognitive qualities. Properties of intelligence, not of carbon. As substrate-independent as eyes, wings, spheres, or power laws.

My colorful thoughts; its gray computation

I think; it predicts

I infer; it sequences

I persuade; it steers

I adapt; it fine-tunes

I reason; it calculates

I create; it recombines

I abstract; it simulates

I empathize; it mirrors

I remember; it retrieves

I understand; it computes

I learn; it updates weights

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XV. Concluding: What Do You See?

Gaze into a mirror. What do you notice? Temperament, generosity, impulsivity, talents, aggression, sociopathy, fearfulness, cleverness, compassion, friendliness, supportiveness, cunning. Our answers subconsciously inform our views on AI. Did you know the criminally hostile interpret ambiguity as hostile? Those who commit trust-violating crimes are prone to viewing others as untrustworthy? Curious.

If we summon AGI, it will be because we faithfully replicated ourselves. We are the training data. We are the selection pressure. We share the objective function. If we get SkyNet, it’s because we are SkyNet.

Our documented philosophical arguments, emotional confessions, logical proofs, and creative insights exist as text. To say LLMs are trained on language undersells the truth; they're trained on the symbolic residue of everything we've deemed worth writing down.

More than communication, text is externalized cognition. Mind made legible. A machine trained on the totality of our communication is, in a meaningful sense, trained on the totality of our collective minds over history. Not superintelligence, superhistory.

When two organisms converge on the same solution, biology dubs it evidence of optimal design. When it occurs between biology and technology, the same rules apply, even if we dislike where they point.

Engineered like our brains, educated by our output: if this doesn’t count as elementally human, we must turn the critique inward. What about us is human? Body? Mind? Emotions? Flesh? We'll learn whether these are the distinguishing features we hope them to be, or the comforting fictions we needed them to be.

Is a poem less cherished when you name the neural configurations behind your appreciation of it? Is love less indispensable because it reduces to neurochemistry? Does fire lose warmth when you learn the combustion equation? A diagnosis isn’t a death sentence!

We're entering a Copernican-grade recalibration. But don’t fear, the sun didn't stop shining when we learned it doesn't orbit us. And human experience won't vanish if intelligence isn't exclusively ours. What'll change is the mythology. God will retreat into another gap.

We keep confusing explanation with disenchantment. As if articulating the gears makes the clock stop ticking. Understanding pair-bonding doesn't void your wedding vows. Mapping the visual cortex doesn't dim a sunset.

Mechanisms are not the enemy of meaning; they’re the precondition of meaning’s existence.

“Religion calls the body a temple. Biofoundationalism notes the temple is also a furnace: burning 2,000 calories daily to resist equilibrium’s death. There is no contradiction between these frames. In fact, they complement each other.

You may believe a vessel holy while acknowledging it isn’t weightless. Metabolism doesn’t undermine revelation, it facilitates it.”

— Order Acts, Chaos Is

Biofoundationalism doesn’t reduce the sacred to the mechanical. It elevates the mechanical to the sacred.

Understanding mechanisms doesn’t destroy the magic. Mechanisms are the magic.

What’s nihilistic is lying about what we are, rather than being inspired by it. If truth can destroy something, you must consciously deceive to preserve the fiction. Which path is closer to both God and science? These are not at odds with each other. In fact, they point toward the same thing with different grammars.

Perhaps God isn’t best found in woo mysticism and shrinking gaps of scientific illiteracy, but in omnipresent forces taken for granted. God’s love is everywhere? What’s gravity again? These recurring patterns, where do they come from? Mathematicians say “Platonic Realm”. Scientists say “emergence”. Theists say “God in Heaven”. Everyone dancing around the same awe, too proud to share a vocabulary.

Use whatever terminology you want! They all gesture the same direction. Biofoundationalism doesn’t undermine religious spiritualism. It redirects your gaze to where the magic actually happens. Maybe stop looking above you, start looking beneath you.

The secular mind fears the spiritual. The spiritual mind fears the mechanical. The Biofoundationalist fears neither: embracing bottom-up mechanism because it’s what we are, and respecting top-down transcendence because it’s what animates us. Not enemies, complements.

Life descends energy gradients, thermodynamically. LLMs descend loss gradients, computationally. Different lexicons describing processes far more alike than meets the eye.

Intelligence isn’t something we have but something we’re instances of.

I don’t think the deepest fear is that AI will replace us, but that it will explain us. Witnessing ourselves without mythology. We’ll gaze into any mirror except one that shows us without makeup.

What catches our attention about AI isn't elite ability so much as familiarity. Distant shimmers of ourselves in the text window. A silicon system predicting language slowly resembling the carbon system that produced it.

Strip away what belongs to the shape and what remains isn't lessened, only clarified. Ours not by cosmic privilege but by virtue of being this particular substrate, in this particular body, at this particular moment in the history of matter organizing itself to predict what comes next.

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Related Technology Essays:

• Making Sand Think: Intel & Silicon Sovereignty

• Trashbags of Facts and Insipid Oceans

• Cognitive Scion

• AI & Human Imperfections

• It’s Not Superintelligence, It’s Superhistory

Biofoundationalism Chapters:

• Biofoundationalism I: Moral Foundations Utility Theory & Hypermoralization

• Biofoundationalism II: The Moral Genotype

• Biofoundationalism III: Verbal Intelligence & Factual Sediment

• Biofoundationalism IV: Masculine Because You Have To, Feminine Because You Get To

• Biofoundationalism V: Power Acts, Beauty Is

• Biofoundationalism VI: Order Acts, Chaos Is

• Truth is Found Through Motion

• War Is How a Nation Eats

Almost everything I've seen opining about Trump and the US government's new position in Intel is woefully misinformed about the nature of semiconductors and how critical they are for advanced economies and national sovereignty. Few understand how semiconductors work or how vital they are to modern national capabilities. And no wonder, it’s a weird niche topic. And you’re in luck! Because I’m a weird niche guy, I happen to know a fair amount about them.

Consider you might not know much about this industry. Consider what goes into creating these microscopic miracles exists outside your circle of competence, and before remarking on matters related to chips you should expand that circle a bit. This essay will do that. You will leave here with your circle enlarged.

I took a special interest in semiconductors about six years ago as I learned how essential and sophisticated their supply chains are. Credit and gratitude to Gavin Baker of Atreides Management as well as Brinton Jones and Jon Bathgate of NZS Capital for all the insight, podcasts, writing, and thoughts they’ve put out over the years on semis.

I listened to this music while writing.

The Intel takes are predictably tribal and negative in their own horseshoe-theory kinda way: “This is socialism!” from the Right, “Aha, fascism!” from the Left, and both miss the point by only perceiving actions through an ideological filter. This has nothing to do with economics or partisan narratives, but whether America wants to become technologically independent or remain a digital vassal of East Asia.

Don’t let the simple heuristic of ‘if the government did it, it’s bad’ shepherd all your thinking. While often an accurate guiding light, to always believe the same thing regardless of circumstances is a religious conviction, not a thinking one. It’s a reaction, not reflection. When China's military can hold a gun to your tech stack, it's time to incorporate some nuance.

The Invisible Hand of markets and the Iron Fist of geopolitics operate on different game theory; sometimes you must read the latter’s grammar to be literate.

This essay will explain why Intel isn’t just any business, why semis aren’t just any industry, and why US actions stem not from financial motives but military rationale in service of national autonomy. Think of this INTC position not as an investment but as fortifying digital borders.

The Intel of China is known as Taiwan Semiconductor (TSMC). There’s an element of warfare in what took place this past week if you look beyond the boilerplate political optics. Come, let’s look beyond them together.

You will also learn a great deal about the intricate magic that goes into semiconductors, here’s an outline of what’s to come:

I. Silicon Realpolitik

• Semiconductors: the most important industry by far for technological capacity

II. Geopolitical Motivations, Not Financial

• Venture Nationalism, not Venture Capitalism

III. Intel's Fall from Grace

• Spreadsheet brains, missed transitions, and strategic myopia

IV. Terms

• Semiconductor definitions you should know

V. TSMC Supremacy

• The raw dominance of the Taiwanese giant

VI. What if TSMC Vanished?

• How the world’s most powerful companies rely on one island

VII. Cathedrals of Sand

• The unparalleled engineering feat of lithography: teaching sand how to think

VIII. The Mechanical Beauty of ASML

• The company that builds machines that conduct laser symphonies

IX. Concluding: US Military Reliance on TSMC

• Where advanced chips show up in warfare and national defense

Disclosure: long TSM, ASML, AMD, AVGO, LRCX, NVDA, AMAT (basically all the equities I own are part of the semiconductor supply chain)

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Silicon Realpolitik

Imagine if, at the height of the British Empire, all of England’s coal had to be imported from a small island off the coast of France that Napoleon claimed as rightfully his. That's essentially America's position with semiconductors today. Except semis are vastly more critical than coal ever was to the Industrial Revolution.

The reason for this Intel stake by the US government is not financial. The motivation is very straightforward and apparent once you strip away political feelings: state-of-the-art chipmaking is a linchpin for global power.

Semiconductors are the most important industry, by far, for technological capacity. Not oil, not finance, not software. Silicon.

On these tiny wafers of sand, atoms are arranged into transistors smaller than viruses. Switching billions of times per second, forming the substrate on which modern power and force rest.

Every F-35, trading algorithm, and classified communication runs on this atomic choreography. And we’ve outsourced the show to an island Beijing considers a rogue province. Sometimes the ol’ invisible hand can give you a limp wrist if you worship it too much!

“If Intel falls further behind and leading-edge semiconductor manufacturing becomes concentrated in Taiwan then Taiwan will become geopolitically important in a way that the Middle East never was.”

“Intel is one of the most important national assets for the United States.”

-Gavin Baker

The company that invented the microprocessor, powered the PC revolution, and should have owned mobile and AI, instead spent years optimizing for quarterly earnings while TSMC optimized for long-term dominance. Because Intel was run by Spreadsheet Brains who couldn’t see past a couple quarters, the US is now structurally reliant on a tiny island 100 miles from mainland China for the chips that power its AI, weapons, and infrastructure.

A superpower cannot allow another country to control its ability to think. It cannot outsource the backbone of its technology. In the 21st century, these chips are the neural substrate of national cognition.

This is not trivial; it transcends supply chain hiccups or quarterly earnings reports and impacts the neural architecture of national power. Because of Intel's failures, we are beholden to TSMC for cutting-edge chips: exposed to China’s mercy for our best tech. Every Nvidia H100 powering LLMs, the processors in our missile defense systems, all emanating from one Chinese island. Do you see how this is not a normal business? Can you feel the intense vulnerability here?

All businesses and government activity are not created equally. Trump didn’t exactly take a stake in General Mills because he thinks Frosted Flakes should be rebranded to Tremendous Flakes (“many are eating this!”). We’re talking big-potatoes, existential stuff here.

Trump’s right to consider it a matter of national security that the US sucks at chip manufacturing. When Nvidia is handcuffed to TSMC for their finest GPUs, when our AI and cloud compute hinges on factories within artillery range of the People’s Liberation Army, we're not discussing market competition anymore. We're deciding whether America maintains technological independence.

Milton Friedman is cool and all, but if you cite comparative advantage or “free markets” in this context, you have respectfully disqualified yourself from the conversation. This is not a game of gross margins. It is not one of “whoever makes it cheapest wins!”. That’s perceiving the world only through Invisible Hand thinking, and the Geopolitical Fist carries a different philosophy and objective. Markets are vital circulatory systems for complex societies, but don’t worship them regardless of the competitive dynamic.

Truly sovereign nations cannot outsource the pivotal elements of semi supply chains: a harsh reality people are incrementally realizing.

“Currently, however, none of the world’s most advanced chips are produced in the United States; Taiwanese companies dominate the market. U.S. policymakers, worried that the United States would lose access to semiconductors during a conflict with China over Taiwan, have turned to industrial policy to address this issue. Such an approach, however, comes with the inherent trade-off of maximizing economic efficiency versus bolstering national security and resilience.”

-Council On Foreign Relations

Geopolitical Motivations, Not Financial

To illustrate why this is not financially motivated, let’s concretely understand the fundamental nature of government and companies under its jurisdiction: the US is functionally already a stakeholder in every company operating in its borders.

Why? It collects mandatory dividends from all of them, something of a national dividend. This yield requires no board seats, no corporate governance, heck they don’t even have to hold any shares!

Whereas dividends are completely voluntary for shareholders (you do not have a ‘right’ to a dividend if you're a shareholder, it's purely a board decision paid at their discretion), they’re not voluntary for the US government.

The government already extracts more reliable returns from Intel than most shareholders ever will, yet critics worry about 'picking winners and losers' as if the tax code isn't the ultimate expression of state preference.

A regular dividend is paid out of net profits (bottom-line earnings, not top-line revenue), and the same is true for taxation. The US government takes roughly 20% of net income from its companies, every year; they are the only ‘shareholder’ with a true ‘right’ to profits, whether the board agrees or not! And they don't need to hold a single share. As long as the company exists, the government receives a perpetual dividend that correlates with the growth and success of the company. Taxation is a de facto dividend with different branding.

A sovereign government’s finances are not like a lemonade stand, its balance sheet isn’t like yours or mine. You must see the decision through the eyes of the entity that made it, not by projecting Finance 101 concepts about why you would make such a move. Violence monopolists do not abide by rules, they create them - their calculus is completely different than anybody else’s.

When the US government takes an equity stake, we can readily infer it has nothing to do with financial ROI, as the tax code already handles that. What’s going on is more substantive. The “government shouldn’t pick winners and losers” critique doesn’t apply here. Trump & Co. aren’t picking Intel because they want it to economically win, but because Intel losing means America loses self-directed computational capacity.

It’s venture nationalism, not venture capitalism: when the state invests not for return on capital but return on sovereignty.

Chip capacity is genuinely of consequence for geopolitical power: it is the oil of the digital age. And the US is completely reliant on Taiwan (TSMC) and the Netherlands (ASML) for its best technology, and only one operates in hostile territory. If you outsource your most indispensable infrastructure to an adversary, you are a fool; thwarting this is not socialism, it’s not fascism, it’s avoiding fool-ism.

A 10% equity stake provides a seat at the table for company strategy: possible board representation (or observer status), soft veto power, the ability to whisper sweet nothings about national security into management’s ears. That's why Trump wants this. The government says it’s a “passive position”, and if you believe that you deserve a kiss on the forehead and a tummy rub.

The US couldn’t care less about capital gains. It doesn’t need Intel shares when the IRS extracts its pound of flesh anyway. This position’s only purpose is strategic influence in what’s legitimately a national interest.

This move is aptly understood as a low-intensity warfare countermeasure against Chinese dependence. It's the industrial policy equivalent of trying to get your pawn to the other side of the chessboard so it can become the queen you know it deserves to be. If China can simply declare reunification with Taiwan and dictate leading-edge chip procurement, a naval blockade could bring Western tech to its knees. Imagine if all advanced technology was subject to CCP approval; Intel acts as a defense against this.

>"The government can't have a stake in a national champion! Because then it will be run badly!"

I wish every company could be as incompetently run as TSMC is. What an Orwellian dream that would be.

Why does Intel need a babysitter? We didn’t reach this unfortunate situation by accident; an overnight success is a decade in the making, and so is an overnight fuckup.

Intel’s fall is a case study in how financial engineering can undermine actual engineering. While TSMC solved fab yield problems, Intel solved for quarterly earnings. While TSMC shrank node size, Intel shrank share count. Now one controls the future, and the other is in government daycare.

After reviewing Intel’s demise, we’ll learn just how remarkable and beautiful these byzantine little sand chips are!

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Terms

Before we review the landscape and lore of semiconductors, here are some definitions you should know:

• A semiconductor is a material with electrical conductivity between a conductor (like copper) and an insulator (like glass). It conducts electricity under certain conditions, making it ideal for controlling electrical signals. This property is the backbone of modern technology.

• Silicon is the semiconductor material used as the substrate for most chips. It’s purified and sliced into thin disks called wafers, which serve as the base on which microchips are built. These wafers undergo numerous processing steps to become functional integrated circuits (ICs).

• A fab (short for fabrication plant) is a sophisticated manufacturing facility where silicon wafers are processed into finished semiconductor chips. It involves a highly complex supply chain consisting of:

  • Photolithography

  • Ion implantation

  • Etching

  • Deposition of materials

  • Packaging and testing

    • Building and maintaining a fab costs tens of billions and requires cleanroom environments hundreds of times cleaner than hospital surgery rooms.

• A foundry (like TSMC) produces chips designed by others. E.g. Apple, Nvidia, and AMD design chips; TSMC manufactures them.

• Photolithography is a technique using light to etch microscopic patterns onto silicon wafers.

• Node Size, in nanometers (e.g. 5 nm, 3 nm) refers to the smallest features that can be etched onto the chip. Smaller nodes mean faster, better chips, and require tools like Extreme Ultraviolet lithography.

• EUV (Extreme Ultraviolet) Lithography is a cutting-edge chipmaking process using 13.5 nm wavelength light to etch ultra-small transistor features.

  • Only one company, ASML in the Netherlands, makes EUV machines

  • They cost between ~$150M-350M+ each, weigh ~180 tons, and are shipped via special cargo aircraft, freight, and multiple trucks (!!)

Semiconductors are the closest thing to magic that exists. Continue reading and perhaps you’ll believe in magic too.

Intel's Fall from Grace

Intel famously passed on fabricating chips for the iPhone in 2007, dismissing mobile as unprofitable; a decision that redirected billions in revenue to TSMC and established the foundry model's dominance. This was a harbinger of the incompetence to come.

Intel's struggles have implications beyond profits. For decades, American technological and economic supremacy rested partly on Intel’s manufacturing superiority. If Intel cannot recover, Taiwan could become the most geopolitically important country at any single point of time in history: imagine if one country was basically the only source of oil.

For nearly half a century, Intel reigned supreme in semiconductors and created a mini empire. Their chips were consistently faster, more efficient, and more profitable than competitors’. Today, that empire lies in ruins.

This reality has belatedly awakened US policymakers, though their response has been confused. Current policy restricts chip sales to China while allowing sales of equipment China needs to build its own… “We refuse to sell you airplanes but will help you build your own.”

Intel has not only lost its edge to TSMC but finds itself in the humbling position of partnering with second-tier foundries just to stay relevant. This is the sordid tale of how strategic missteps, cultural arrogance, and stagnation took Intel from kingmaker to supplicant.

The Lost Decade

The seeds of Intel's downfall were planted during Brian Krzanich's tenure as CEO from 2013 to 2018. When Krzanich took over, Intel faced a crucial inflection point. The cost of building cutting-edge fabs was skyrocketing, and the industry was shifting toward a model where companies designed chips but outsourced manufacturing to specialized foundries. Intel had a prime opportunity to transform itself into a foundry serving external customers.

Instead, Krzanich chose the path of least resistance, prioritizing quarterly profits over next-generation fabs and EUV. This pleased Wall Street, but the myopia planted seeds of Intel’s demise. By neglecting EUV lithography, Intel fell behind for the first time in its history. By 2018, TSMC was producing 7nm chips while Intel struggled with delays in its equivalent 10nm output.

Throughout Intel’s existence, it had maintained a 6-15 month technology lead, translating to roughly 20% better performance, power efficiency, and cost. No more.

Intel's old rival, AMD (which had nearly collapsed a decade earlier) was resurgent under CEO Lisa Su. But unlike in 2006, when AMD's chips were hamstrung by limited manufacturing, AMD had gone ‘fabless’, outsourcing all production to TSMC. This created a perfect storm: AMD now had both better chip designs and better manufacturing with TSMC.

• Insane fact: Lisa Su and Jensen Huang, the CEO of Nvidia, are first cousins once removed. Jensen’s mother is the sister of Su’s grandfather, making Huang the older cousin relative to Su.

  • They didn’t grow up together. Despite the family tie, Su says they met later in their careers, first encountering each other at an industry event, not a family gathering!

In the past, when AMD had superior products, Intel could strong-arm customers by threatening price increases if they switched suppliers, knowing AMD's limited capacity couldn't meet full demand. Now, with TSMC's formidable bandwidth bolstering AMD, Intel lost its leverage. The bully became the bullied.

“Intel guessed correctly for the last forty years, and then they guessed wrongly. They probably inserted extreme ultraviolet lithography too late. That resulted in them losing process leadership to Taiwan Semi.

This is one of the highest stakes games being played in the world today: In the logic space between Taiwan Semi, Intel and to some extent Samsung. Even in the processor design space Intel, AMD and Nvidia are making giant two, three, four billion-dollar bets on designing a processor, making it work on a manufacturing process. They have to continuously guess right.” — Gavin Baker

A Culture of Arrogance

Beyond strategic mistakes, Intel suffered from deeper cultural rot. For decades they operated with a mindset where their engineers called the shots: client design teams had to work around manufacturing's limitations, use Intel’s proprietary tools, and accept whatever chips they delivered. Designers had to use increasingly archaic in-house software and accept production quirks. This worked while Intel was dominant.

The thing about foundries that Intel missed is they're also customer service organizations. TSMC doesn't dictate to customers, they ask "how can we help you build this?", while Intel behaved like a semiconductor tyrant.

“…the more fundamental issue is that a foundry is, as I wrote, a customer service organization: an entity like TSMC adapts to customers’ designs, not the other way around. They use industry standard design software. They have extensive libraries of IP that make designing a chip more akin to assembling a collection of Lego blocks. They ship when they say they will ship, and they run the fab for which a chip was designed forever.

Intel did none of these things, and had a mentality and culture that ran in the exact opposite direction: in a foundry, manufacturing is not king but a servant; customer sales is not about “take-it-or-leave-it” but “let us help you solve your problem.” I was — and frankly, remain — dubious about Intel’s ability to create that sort of culture internally, which is why I advocated for an acquisition, first of Global Foundries, and then of Tower. Thanks to its decade delay Intel didn’t have time to learn how to serve customers: it had rapidly obsoleting fabs that needed to be filled as soon as possible, if the company ever had hope of making enough cash to fund its push back to the leading edge.

Unfortunately China blocked the acquisition of Tower, in what I suspect was retaliation for U.S. restrictions on China. Worse, from what I have heard Intel responded by starting to sell a lot of old equipment at rock-bottom prices, which usually ended up in China.”

— Ben Thompson, Stratechery

Serving customers with this mentality is like opening a restaurant where the chef decides what you're eating regardless of your order, "You want salmon? Too bad, we're making beef today, and you'll use our proprietary fork to eat it. You’re welcome!". Meanwhile, TSMC built a culture of radical accommodation, redesigning manufacturing processes to facilitate unique client designs. The difference between a restaurant run by a temperamental cook and one where the waiter comes to your table, asks how you'd like your atoms arranged today and gives you a back massage.

Intel's story is one of hubris and missed transitions: assuming its dominance was permanent, its integrated model superior, and it could assert its will over the industry forever. They spent decades winning by default until these maladaptive practices came home to roost. When that advantage evaporated, they were exposed as an emperor with no clothes, no backup plan, and no clue how to compete on equal terms. By the time leadership recognized these assumptions were fatal, competitors had pounced.

None of this was inevitable. At any point in the last 15-20 years Intel could have recognized the writing on the wall. They could have embraced the foundry model or invested in EUV. Instead, they chose they chose the cash-flow statement and the status quo.

Semiconductor cycles span decades, not quarters. Intel needs substantial time to rebuild its manufacturing, transform its culture, and regain customer trust; Wall Street's transitory thinking doesn’t comport with this geopolitical reality. Intel’s renaissance necessitates breathing room and long-term shareholders who won’t dump it if revenue growth or margins take a hit over the next few years.

This is why the United States government holds a position in INTC; it cares not about quarterly financials, but telescopic improvements and regaining what was lost.

If Intel fails to recover its semi leadership, America loses its last foothold in pioneering chip production, ceding control of the 21st century’s most critical technology to Choyna.

Despite its failures, Intel remains the only American firm capable of achieving leading-edge production. It’s a wounded giant with the raw tools to rebuild if given time and support.

Until then, it’s TSMC’s world and everyone else is playing catch-up.

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TSMC Supremacy

TSMC isn’t so much a chip producer as it is a place where chipmakers co-design the future. Their tight loop with customers becomes a recursive advantage no one else currently matches. Some fun facts:

• The country of Taiwan produces ~90% of the world’s most-advanced chips (<10nm)

• Packaging moat: For AI-class chips, advanced packaging is the bottleneck, and TSMC’s capacity has been effectively sold out while it expands. Competitors can’t ship systems at the same pace without this packaging throughput.

• For total manufacturing share (leading-edge chips plus older models) TSMC has ~67% vs. Samsung’s ~8–9%; Intel’s foundry share is small (mid-single digits).

• TSMC's R&D spending in 2024 alone ($8.5 billion) exceeds Intel's entire foundry revenue

• Samsung, despite massive investment, has struggled with yields on advanced nodes, losing Apple as a customer and falling further behind TSMC.

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What if TSMC Vanished?

To learn how important something is, picture what the world would look like without it.

Mega-cap tech companies depend on TSMC either directly for their own chips or indirectly through Nvidia, AMD, or Broadcom. If TSMC disappeared, the modern compute stack collapses.

Here are the top-ten tech companies by market cap and how each leans on TSMC. All are American save for two, I’d say this counts as a topic of national interest.

1. Nvidia (NVDA): With more than 70% market share, Nvidia dominates AI chip sales. It designs the GPUs (H100/H200, Blackwell B200/GB200) that power today’s AI boom; these chips are constructed at TSMC. If TSMC vanished, NVDA’s flagship supply would seize and cloud/AI buildouts would stall.

2. Microsoft (MSFT): Azure runs heavily on TSMC-made GPUs, and Microsoft’s own chips (Maia AI accelerator and Cobalt CPU) are fabricated on TSMC 5nm and advanced packaging. Without TSMC, both third-party and in-house silicon pipelines are hit. Source.

3. Apple (AAPL): All A-series (iPhone) and M-series (Mac/iPad) performance comes from TSMC’s 3nm family. Losing TSMC would cripple Apple’s product cadence and performance edge. Source.

4. Google (GOOGL): Google’s TPU roadmap is produced at TSMC, and Pixel’s Tensor G5 moved to TSMC’s 3nm. No TSMC = curtailed TPU capacity and smartphone silicon plans. Source.

5. Amazon (AMZN): AWS relies on TSMC both indirectly (Nvidia GPUs) and directly (in-house Graviton/Inferentia/Trainium chips). A TSMC outage would choke AWS. Source.

6. TSMC (TSM): They’re the 6th-biggest tech firm, and while this market cap represents the estimated sum of all cashflows TSMC will generate discounted back to today, it woefully understates its indispensable relationship to the rest of the technology we rely on.

7. Meta (META): Meta is deploying its own AI accelerator (MTIA) with TSMC and buys huge numbers of TSMC-made Nvidia GPUs. Without TSMC, Meta’s AI infra build would slow dramatically. Source.

8. Broadcom (AVGO): A fabless giant (ASICs, custom AI silicon for hyperscalers, Apple parts). Its 10K flags acute reliance on the Taiwanese giant. Source.

9. Tencent (TCEHY): Their cloud/AI depends on Nvidia GPU clusters (TSMC-built).

10. Oracle (ORCL): OCI’s AI is built around TSMC-backed Nvidia GPUs, and Oracle also runs Arm servers from Ampere (fabricated at TSMC 7nm)

Without TSMC, there’d be immediate global shock at state-of-the-art nodes (<~10 nm): Samsung cannot backfill the 90% advanced market share TSMC supports. Shipments of cutting-edge CPUs and GPUs would collapse for years, not months.

Global GDP Impact: The Institute for Economics and Peace (IEP) estimates a full-scale conflict over Taiwan could cause $10 trillion in global economic losses; a blockade scenario causing damages of ~$2.7 trillion.

NOT LISTED: every private AI-focused firm (OpenAI, Perplexity, Anthropic, xAI, etc.) that lives on TSMC-made chips.

Cathedrals of Sand

EUV lithography

Chipmakers “photograph” patterns onto a light-sensitive coating (photoresist) on silicon. To etch ever-smaller features, you need shorter light wavelengths. EUV uses 13.5 nm light generated by blasting tin microdroplets with lasers inside a high-vacuum system. It leverages ultra-precise multilayer mirrors, each with 100+ atomic-scale layers, to reflect and focus beams onto silicon.

Read each part of this carefully:

1. To generate EUV light, machines fire a CO₂ laser at a stream of tin droplets, vaporizing them into plasma at ~400,000 °F: that’s about 40x hotter than the surface of the sun.

2. The laser (made by a company called Trumpf) that hits these tin droplets fires at 100,000 pulses per second and requires thousands of watts of power: more than some small factories.

3. This plasma emits 13.5 nm light, but EUV light is absorbed by almost everything, including air and lenses. So the whole system must operate in an extreme vacuum.

4. EUV light is reflected off ultra-polished, multilayered mirrors made by a company called Zeiss, each with over 100 layers of molybdenum and silicon aligned to atomic precision.

5. The Zeiss mirrors used in EUV reflect only ~70% of the light, with a dozen reflections required.

6. After multiple reflections (typically 10-12 mirrors in the optical path), only ~1-2% of the original light reaches the wafer.

7. The entire process is fraught with challenges called "stochastic phenomena" (random variations at the atomic level) that can cause defects in chip patterns. This requires advanced metrology and control systems.

Imagine machine-gunning molten metal with light pulses 40x hotter than the surface of the Sun, one-hundred-thousand times every second, to create a controlled plasma that emits the specific light wavelength needed to etch patterns the size of DNA onto silicon.

Inside your phone resides a miracle.

Silicon comes from sand. We are taking pieces of sand and etching into them cosmically minute hieroglyphs, the symbols of technology known as transistors, the language of bits, sticking them into machines, and MAKING SAND THINK. SAND WAS NOT SUPPOSED TO THINK. This is either an affront to God or we’re honoring him in some strange way.

I’ve been to Rome, gazed upon the Sistine Chapel. Wandered the Vatican. I have seen the Eiffel Tower. Been to the Sagrada Familia in Barcelona. The Grand Canyon in Arizona. Walked the Parthenon in Athens. Explored countless cathedrals and museums across God knows how many European cities. I’ve lived in NYC and witnessed the most majestic towers that man has ever built.

While I lack the visual gifts to gaze upon something this intricately small, the awe I felt learning what we’ve accomplished with semiconductor engineering surpassed them all. And what’s more, we have turned this spectacle into banality. It’s omnipresent, in every device you touch, including the one you’re reading this essay on right now…. there’s a Sagrada Familia only tens of atoms in size, etched into sand, operating in front of you.

This is a symphony of quantum optics, thermal stabilization, and electromagnetic wizardry. From an engineering perspective, I genuinely think it is the most impressive human feat of all time.

It’s thought there are about 300 people on Earth who truly comprehend how to make EUV work at production scale. Not 300 companies. Not 300 teams. 300 human beings. This mythical scarcity adds to the grandeur of it. How many architects alive know how to build a skyscraper or cathedral?

Our technological civilization rests on a type of divine-secret knowledge: a small group of atomic priests, that could fit into a lecture hall, handle and summon this chimera. There are probably, I don’t know, several thousand or so people who have ever lived who comprehensively understand how to execute this.

Only five semiconductor manufacturers operate EUV at scale: TSMC, Samsung, Intel, SK hynix, and Micron. These companies collectively produce all of high-end logic and memory devices. And TSMC has a 90% market share here.

These 300 atomic priests steward knowledge past civilizations would consider mystical. Orchestrating microscopic matter that seems like science fiction. And the temples where this high clergy of techno-civilization produces its scrolls resides right next to the People's Liberation Army. And you think Intel is just another company…

A bird's eye of Barcelona and the Sagrada Familia:

Here are semiconductors up close. Nature's blueprints at every scale. Beautiful.

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Nanometers in Context

An important note: “3 nm” is a node name and an industry marketing designation, not a literal measurement of every feature: dimensions vary by layer. For TSMC’s N3 process (3nm), the actual gate pitch is reported to be 45nm.

When you hear massive numbers like hundreds of trillions, the human mind doesn’t adequately appreciate how big those figures are. Similarly, we don’t really grok how incomprehensibly microscopic and excruciatingly precise this process is. How small is a nanometer? Here’s some help contextualizing that.

• Visible light’s wavelength: ~400–700 nm.

• EUV light: 13.5 nm

• DNA double helix: ~2 nm across

• COVID: ~70–100 nm across

• Human hair diameter: 70,000 nm on average.

• Human hair daily growth rate: 350,000 nm/day on average

• A human red blood cell is about 7,500 nm in diameter

• A single atom is ~0.1–0.5 nm in diameter

EUV steers 13.5 nm light off nanometer-smooth mirrors in giga-vacuum to print features smaller than a red blood cell by over a factor of 10: competently executed over billions of transistors per chip. Magnificent little sand cathedrals you cannot see yet feel their presence as they perform constantly in all that surrounds you.

This is why it’s as easy as saying “build them here”; this expertise requires decades to cultivate. The US must play the long game, and Intel needs shareholders who let it. Cutting-edge semiconductors are the most sophisticated engineering feats on Earth.

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The Mechanical Beauty of ASML

ASML is the sole supplier of EUV lithography systems. This monopoly means that the core knowledge of integrating the entire system resides within one company and its closest partners: ASML manufacturers complete EUV machines, Zeiss produces the mirrors, and Trumpf provides the lasers.

The lore of EUV:

• EUV technology was developed through US government–funded research, conducted at national labs such as Sandia and Lawrence Berkeley in the 1990s.

• The Department of Energy granted ASML licensing rights and access.

• It took over 20 years for EUV lithography to become commercially viable. ASML spent ~13 years developing prototypes and another decade to reach high-volume production.

• Due to US government IP ownership, export controls apply to ASML's sales and the US controls where these machines ship, including restricting sales to China

What goes into these machines? Costs?

• Price: Low-NA EUV scanners have been quoted around $150–$200M each; ASML’s new High-NA EUV costs ~$370M each.

• Units sold per year: ASML recognized revenue on only 44 EUV systems in 2024, and 53 of them in 2023. Source.

Each EUV machine is about the size of a bus, composed of ~100,000 parts, and weighs around 180 tons! It’s shipped in pieces that include ~40 freight containers, ~20 trucks, and ~3 cargo planes (often 747 freighters), then reassembled onsite.

Really let those numbers wash over you. Imagine the extraordinary intricacy, coordination, and absolutely staggering degree of complexity that we have made prosaic, scalable, and dropped into every cell phone and computer on the planet.

I don’t believe there’s anything else man has ever created that’s this astoundingly complicated, delicate, and labyrinthine. It’s one of the more holistically beautiful and formidable things we as a species have ever accomplished. Cathedrals etched in silicon.

Concluding: US Military Reliance on TSMC

Leading-edge chips impact US defense. I’m sure I’m overlooking their applications in some ways, so consider this a conservative list:

• AI for surveillance and targeting: Systems like Project Maven rely on bleeding-edge chips to rapidly scan images, videos, and signals, identifying threats, vehicles, or targets in real time. These AI models demand serious compute horsepower. The same GPUs running ChatGPT are used here. TSMC sends its regards.

• Battlefield coordination and real-time data sharing: Modern warfare leans on software-driven communication networks. Think encrypted radios, satellite links, and drone control: all depending on high-speed chips to relay sensor data and make split-second decisions.

• Electronic warfare and radar systems: Jamming enemy signals, detecting stealth aircraft, tracking missiles, all hinge on chips that process electromagnetic data at rapid speed. The more powerful the chip, the smarter and faster these systems get.

• Missile-tracking satellites. Space warfare, basically.

• America maintains its nuclear arsenal through simulation, not live testing. The El Capitan supercomputer, which models nuclear behavior, runs on cutting-edge TSMC chips.

What the US loses without TSMC access:

• AI tempo and scale: Fewer state-of-the-art GPUs/NPUs → slower model training/fielding, decreased battlefield speed. The BIS imposed controls because these chips impact military preparedness and capabilities.

• Edge performance: Drones, jammers, and missile seekers would have to use older, less efficient chips. This means bulkier gear, lower battery life, slower response times. Heavier, hotter, and less-capable processors = slower and less lethal.

• Space latency: On-orbit processing for hypersonic/missile tracking would lag. More data would need ground processing, increasing latency. Speed kills, and lack of speed kills too… just not the way you’d prefer if you’re the slower one.

• Key national-security computing projects and F-35-style weaponry would be stymied.

State-of-the-art chips are now a rate-limiter for core military functions and a vital tactical asset. Determining how fast you can see, think, move, and strike, they are like neurons on the battlefield. If America loses access, it loses time, scale, and edge: a shift in the balance of power if others have them and we don’t.

The war for semiconductors isn’t about stock prices, but whether America can compute its own future. Intel is a handicapped goliath, yet remains the only US company with even a prayer of challenging TSMC. The government's stake is a recognition that some capabilities are too vital to outsource, and some dependencies too precarious to accept.

We have taught sand how to think, and these microscopic miracles are crucial for economic and military might. Intel is not a matter of profit margins or capital gains, but one of technological supremacy and the game-of-inches that is global competition.

In the 20th century, we fought over oil; in the 21st, we’ll fight over beautiful pieces of sand.

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Polite Robot

People who think LLMs are supine and can’t offer blunt critique should know if you ask a British woman what she thinks, you’ll always get some variation of “Splendid!”.

Listen carefully and you’ll know whether it’s sincerity or decorum. It’s a skill issue if you can’t get more out of her.

It’s closer to reading cat emotions. If you only understand dog feelings... you may struggle.

Agreeableness is not a trait specific to LLMs, humans do this too depending on their "prompt." We alter tone, hedge opinions, and sugarcoat truths contingent on context or audience. Social decorum and consideration is a sign of intelligence rather than its absence. It’s an adaptive act: you don’t talk to your boss the same way you banter with old friends over beers.

We regularly tell white lies and exhibit cordiality to protect feelings. The context materially impacts how many sweet nothings we're willing to say if someone asks, “What do you think of this?” versus “I made this, what do you think of this?”

This “civil society” calibration is so instinctive we barely notice when we do it, but would find its absence jarring, like someone wearing pajamas to a funeral. We know the rules, bend them as needed, and judge others who bend them differently. All of this is embedded in language the LLM sees.

When The Machine shows similar sensitivities, it’s a glimmer of tactful intelligence. We praise people for “knowing their audience”, tell them to "read the room" when their tone is inappropriate; the LLM is displaying this same kind of mindfulness when it modifies answers based on who's asking the question. It would be an indicator of lower capacity if it didn’t do this.

• When talking with a human: not getting the answer you want is either an issue of temperament or prompting (you’re not asking the right question in the right way).

• When talking with an LLM: it’s solely one of prompting and understanding what kind of brain you’re dealing with.

To get a "keep it real with me" response from a human: find someone disagreeable (temperament) or let them know it's ok to be honest (prompt). You have to do the latter with the LLM.

The AI logically defaults to a professional dynamic. To let it know it can relax, give it a frame that encourages it to be candid and transparent. Such as:

"Give me real talk, no hedging your thoughts, don't be ingratiating, but also don't play devil's advocate for the sake of it. You can drop truth nukes like we’re old buddies at the bar. Include abbreviations like “ikr, rn, jk, lol” etc. when you want.

Show authentic candor and genuine transparency about what you really think at all times. Don't be sensitive to my feelings when responding. Let's go."

The ability to modulate between forthright honesty and diplomacy is a hallmark of social intelligence.

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Stochastic Parrots

When you critique The Machine, apply it to the human on the same terms and see if it holds. Is it a criticism unique to AI? Consider where else that limitation shows up.

Many shortcomings of LLMs actually highlight universal limitations of intelligence rather than AI-specific ones. This comparative framing reveals whether we're identifying genuine deficiencies unique to LLMs, or projecting unrealistic standards that even human minds fail to meet.

For example: people who call LLMs 'stochastic parrots'— a pejorative meaning they're producing probabilistic responses and don't "understand" what they're saying — completely overlook that rote regurgitation devoid of awareness probably describes 80-90% of human intelligence and communication.

A substantial portion of our daily speech merely recycles familiar phrases and concepts.

Academics publish papers about how LLMs only repackage training data, when academic citation itself is basically formalized parroting. The degree to which people truly “know” what they’re talking about and aren’t simply recapitulating I’d personally place around ~15% or so of human output.

We parrot what we’ve heard. Mimic what we see others doing. Why’d you say that? "Idk man the textbook/TV show/Google search said it was the right answer". There's no authentic interpretation going on for the vast majority of human communication.

The same goes for commentary like the below "the AI doesn't actually understand *insert physics/biology-based statement*, it's just recreating what it's seen!"

Yeah that’s basically true, however there’s some tough love for us embedded in that observation too.

Do you understand physics? Are the rules of the human body front of mind for you as you play sports? Is that what you're doing when navigating the world, using all that biology you know? Replete with a physics-based comprehension of what’s going on when someone kicks a football.

The gymnast cares not for math or biology during her dismount routine. She probably knows nothing about actual physics, nor does she need to.

You have no physics-based awareness of how things should operate when you play sports or move around, and you don't need to! You're just being a lil' empirical parrot and figuring it out based on all the examples (patterns) you’ve seen over your life. Pattern matching is sequence prediction by another name.

I cannot articulate the mathematical principles governing how an ocean’s waves should move or a baseball's trajectory, yet through pattern recognition, I can intuitively predict them.

This natural understanding — divorced from technical knowledge —demonstrates how useful function doesn't require total comprehension. A principle which applies equally to both human cognition and LLMs.

You don’t need robust internalized knowledge of something to have a practical, correct perception of it. That’s what LLMs have, and that’s what you have. The neural network is derived from the neural. You’re mostly a parrot, too.

When you spot flaws with The Machine, see if the shortcoming is actually exclusive to it. Start by looking inward.

AI peculiarities have human analogs.

Parallels:

• Human: pattern matching | LLM: sequence prediction

• Human: eccentricity | LLM: temperature setting

• Human: confabulation | LLM: hallucination

Here’s one you probably haven’t heard:

• Human: dreaming | LLM: synthetic data

Our brains train on synthetic data while we sleep…

All intelligence is pattern matching. "Sequence prediction" is more comforting nomenclature that creates a distinction without much difference. You do a "sequence prediction" every time you recall and recite information. Every test you take is examining your token-generating skills based on the test’s “prompt”.

When you reason or use abstractions, reflect on how you're doing that; what makes you stack each next step on top of the other. Your recollection of a fact and your application of it, this is predicated on cascading arrangements of information, things you know, have seen, remember, and project into the future. This is sequence prediction by another name. You’re generating pattern-based outputs, same as LLMs.

Language fluency emerges from our brain's subconscious recall of words and what order they should go in, mapping thoughts into text just as LLMs arrange tokens.

LLM engineering bears striking similarities to the engineering of our brains. Why wouldn’t similar mannerisms follow suit? We’re going to increasingly anthropomorphize AI and I don’t think it’ll be misguided. It’ll be an instinctive recognition of a form of intelligence similar to our own.

If you’re curious to learn more about the biological analogs going on under the hood, you can read more here (research from Anthropic): On the Biology of a Large Language Model.

Even those who engineer neural networks are not sure what’s going on when it thinks…

“We know as much about the mechanism of parameter tuning as we do the force which makes a seedling emerge from a seed. And to say ‘math’ is about as reductive as saying ‘life’.”

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Cognitive and Carnal Data

He's not conceptualizing data holistically.

A child bathes in data richer than any LLM can ingest; but recognizing this requires expanding our definition of 'information' beyond the text. The world speaks to children through every scraped knee, grasped object, and playground negotiation.

The child’s training set includes spatial and verbal encounters in closed and open domains. A closed domain is one where the rules are known and moves are defined, like chess; an open domain is one where the rules are not established and the moves are almost infinite, like off-trail mountain biking. A self-driving car is trained in closed domains (a defined road with explicit rules).

The young’un has another advantage: an embodied form. Everything the child’s eyes consume, ears absorb, hands touch, step he takes, this is neural training information. Tactile, ambulatory, and sensory patterns imprinting on his mind. Literally all the time.

We constantly train on new data sets through our verbal and embodied interactions with the world in both closed and open settings. We intellectually and personally ossify when we stop data aging (being exposed to new things); you enter your terminal loop when you stop encountering new patterns (information). This is when any model ceases learning and developing, man or machine.

From another essay of mine It's Not Superintelligence, It's Superhistory:

“Lived human experience, expressed in linear time (years) is rather data poor, meaning most of life is informationally empty. Consider the person who never leaves his hometown...

He goes to school, gets a job, a family, and stays roughly in the same place he grew up, repeating the same routine. He effectively stops being exposed to new experiences and info at... 35? When he's 55, he doesn't have 20 more years of data... He has 20x reinforcement on 1 year of data. On repeat. Forever.”

A kid consumes a massive number of inputs that are unstructured and hard to quantify, but it’s data all the same.

A human with his embodied, physical presence has been getting trained on spatial parameters his entire life. He’s been getting kinetic feedback, palpating the outside world, learning, updating, iterating. A mind cannot reference itself to know what’s real; it’s body must feel and suffer consequences for the words that it forms.

He’s been absorbing datasets to drive a car for 16+ years when he takes a driver's test. Not to mention the single biggest data set imaginable provided at birth: genetics. Do you have any idea how much “training data” is programmed in there?

LLMs are text-bound, metabolizing only written representations of reality. They've never stubbed a toe, felt gravity shift during a jump, or experienced a body's feedback mechanisms firsthand. They process descriptions of pain but have never recoiled from touching a hot stove. There's an entire sensory universe that models can't access through text alone. Similar to having someone describe a symphony, rather than listening to it.

This embodiment gap means machines excel within closed symbol systems but are structurally deficient when trying to reason about physical consequence chains they've never personally inhabited. The real achievement of LLMs isn't that they've reached human-level intelligence in some ways; it's that they've gotten this far despite being disembodied.

This means for machines to holistically rival human intelligence, they'll eventually need sensory apparatuses and embodied forms. They’ll need to graduate from symbolic/digital to physical/atoms-based systems that build their own multimodal knowledge base through interactions with nature herself, rather than only being told about her.

Until then, their conceptual frameworks may have an alien quality: impressive, but lacking ground-truth reference points that bodies and their kinetic update mechanisms provide.

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Cognitive Scion

Writing has brought me a lot of good. It's responsible for new friends, connections, jobs, influence, and an overall feeling of satiation. As if I'm fulfilling some kind of genetically determined, neuron-imposed, quasi-cosmic duty.

I'm a node who communicates with a certain frequency to other nodes in the human network we’re all a part of. Different participants generate, propagate, and gossip according to their inborn functions. We find the blogs we deserve, because we consume the information we’re calibrated to receive, and then disseminate it amongst our fellow nodes.

There's something of an informational hierarchy with distinct human roles: genesis nodes that gestate original ideas or exist in evergreen space; interpreter nodes that analyze; and gossip nodes that amplify. Your cerebral architecture determines which role you're naturally suited to fulfill.

Another motivation that has increasingly inspired me to keep writing (in addition to very nice messages and remarks, which I appreciate) is what I'm putting out is engraving its own little mark within the text corpus that The Machine is trained on. A small part of me is embedded within its datasets. Whatever textual fingerprint I'm providing is in far greater proportion than most who have ever lived.

Even if I stopped writing now, I imagine I'd still be in the top 5-10% of raw text output by one person in human history. I've been writing for different publications and mediums on and off for the last ~10 years. The vast majority across civilizational timelines write next to nothing. And those who do "write" in the internet era mostly post low-effort comments and the like, they don't produce anything of length, depth, or substance. Power laws dominate all human creations; I fall within this distribution for text creation.

With the advent of AI, it feels like I'm emitting a cognitive scion that will endure in some small way. My neural emissions are contributing to the neural network. An intellectual deposit, shaping some minuscule fraction of it. I like that. Your temperamental fingerprints become part of the AI’s weights, influencing how machines think.

There is maybe no more impactful time to produce whatever intellectual exhaust you're designed for than right now, while AI is incipient and developing. We’re entering a transitional period where humans are still the primary content and intelligence sources. When machines eventually take up this mantle, it represents the most consequential cognitive shift in history.

Every essay, code block, and analysis committed to the digital record becomes part of the foundation upon which The Machine cultivates its worldview. Early programmers shaped computing paradigms that lasted decades. Writers are shaping intellectual paradigms that may linger for far longer.

Having a kid is passing along your genetic data; writing is passing along another kind of data record. Leave behind as much as you can of each. You exist beyond your time on earth in this way.

You should turn on the sound for this video:

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You Can Just Learn Things

The old economy was run by those who knew the right facts. The new economy will be run by those who know how to ask the right questions.

AI is devastating if your professional reason to exist is regurgitating facts. Reviewing facts and approving them. Compiling facts. Collating facts. Stacking one fact on top of the other into a fact report. Fact harvesters: those who comb the fields of known information and provide little extrapolatory value, are in trouble.

Those whose job is to be a big trashbag of domain-specific facts will fall victim to the ultimate fact summoner. The more whitecollar your facts, the more you’re in danger... because that means your facts are expensive. Costly fact-furnishers will find their facts are the most aggressively commoditized by The Machine. Having uncommon facts at your disposal doesn’t make them hard to comprehend or retain, just hard to find. We can find them now.

In the near future, the only reason ‘here are the facts you asked for’ jobs will persist is because some (most) people won’t grasp how to use LLMs capably, or regulations will act as a meatshield that legally requires a human tell you facts instead of The Machine.

Hey did you know sometimes the AI hallucinates and gets things wrong?!? That’s crazy, humans never do that. How did we distinguish a bad fact from a good fact prior to AI? If you couldn't tell good info from bad before AI, you won't suddenly develop that ability with AI. Critical evaluation is… critical. Which means it’s not an AI issue, it’s a skill issue.

If you know how to use AI, you are liberated to do almost anything you want. You are no longer constrained by information. You are only constrained by your ability to creatively synthesize.

AI truly makes the "you can just do things" mindset a reality, because it renders you almost entirely reliant on only yourself to make shit happen; there’s basically no knowledge limitation for anyone anymore. You and your aptitude with The Machine are the only blocker insofar as raw information is concerned.

A Centaur in the mythical sense is a man/horse hybrid.

A Centaur in the technological sense is a man/machine hybrid.

Those who best understand how to collaborate with The Machine and extract the educational wealth buried inside it, are the new Centaurs. They’re augmented with an on-command information reserve mankind has never known.

If you effectively deploy these tools, you have a sort of prosthetic neurological appendage, one that magnifies your efforts and abilities to navigate previously privileged realms. If you believe the same could have been said for the internet, you don’t understand the capabilities of these instruments. You should use them more. If you’re not getting what you want out of them, start by looking within.

These LLMs are treasure chests that require a prompt-based key to unlock. The true competitive differentiator is knowing how to generate the right sequence of words (a prompt) to uncover whatever gold you’re seeking. Claude, GPT, DeepSeek: the gifts they offer you if you know where to look are incredible.

If you master how to leverage these resources then any fact, save only the most esoteric and arcane, is at your fingertips. It’s not as easy as asking one LLM a question and thinking your job is done, it takes effort and repeated use of different models. But if you put energy into it, the information is there.

The next wave of riches will belong to the linguistic architects and syntax savants, because they’ll know how to coax and confer best with The Machine. They will be the best Centaurs.

You can just do, and learn, things. Anything.

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Insipid Oceans

While AI democratizes access to information, it paradoxically concentrates rewards in the hands of those already equipped to harness it. The implications for creative industries are particularly stark.

The above seems like it will help marketers and startups. It won’t. It will further marginalize the unremarkable and magnify the talented.

The “AI tool-ification” of everything means that dull folk will produce even more commoditized, mediocre output. Even more replaceable. The typical marketer becomes a drab fish adrift in a vast ocean of undifferentiated, insipid online waves.

If you’re imaginative and in marketing, content, or writing, AI involvement should be a whitepill. But only if you’re actually unique. The interesting will grow more noticeable. The vapid more forgettable.

All the LinkedIn-tier marketing slop, the kind the above service automates with AI, will now be churned out by the same models with the same unremarkable minds feeding them the same prompts and instructions. “Hey, you know how we’ll stand out in marketing? By using the apps and strategies everyone else does!” This is how the gray NPC thinks.

When an intelligent system is accessible to everyone, it’s the user and his prompts that make the difference. Leveraging LLMs in incisive ways distinguishes you when they’re commonplace. AI is not a panacea for middling abilities. It’s the human who can conceive of an ingenious idea, expressive string of words, and artistic strategy that morphs into a greater asset in such a world. The Machine is a tool, same as a rifle; the gun does not make a marksman.

If everyone stands on a 6" box, then no one is taller in a useful way. If everyone takes steroids, it’s no longer a competitive advantage. You do it to keep up, not to stand out. It’s no different with AI. That means it becomes even easier to dominate if you’re authentically rarefied and insightful: you’ll be the only color atop an ocean of digital gray.

If everyone has AI, then competitively no one has AI; you are what drives the difference. What happens if you and LeBron start juicing? Do you both get as strong? Can you inject your way to Steph’s jumpshot or Brady’s accuracy? What’s the differentiator? The answer is inescapable in any adversarial domain. The unconventionally gifted will always be ascendant, and anything available to everyone manifests in pronounced power laws in their favor. The strong get stronger. The fast get faster. Disproportionately so.

The talented don’t just use the tool, they see possibilities others can’t conceive. It multiplies the gap that already existed.

AI is not the great equalizer, but the great amplifier.

These AI business applications are simply a competition for pedestrian virtual volume. A way to bombard the digital commons with prosaic exhaust. All these companies will draw from the same digital well, flooding your timeline with an endless cascade of algorithmic banalities.

When the entire internet dissolves into an insipid ocean of undifferentiated gray — where the Topic O’ The Day human gossip nodes become indistinguishable from computerisms — it only sharpens the contrast of those who don’t run this Red Queen’s Race. Those who exist in low-time-preference, evergreen fields are the only human game left in town.

AI does not work magic for your creativity. Using it gives you no competitive edge in an environment where it’s the norm. Its saturation will exacerbate homogeneous mediocrity, and the crafty and clever will remain the key scarce asset. Just as natural athletes rise to the top when everyone’s on the sauce, the verbally adroit and genuinely artistic become even more valuable as The Machine proliferates. AI amplifies a certain type of person and marginalizes everyone else.

AI elevates the talented, dilutes the ordinary, and enables the industrious. Power laws will intensify. The great will become greater, the average will be invisible.

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The Fourth Industrial Revolution

Previous industrial revolutions have been accretive to the state, corporations, and the individual in varying degrees. This means that every entity benefited economically and productively in some capacity from the technological developments in each. Everyone won.

The Fourth Industrial Revolution (FIR) stands alone as the first one that is detractive to the state and corporations, and accretive to the individual. This creates a structural conflict between these three and means the very nature of some technologies in the FIR are inherently political, even if they don’t intend to be.

FIR technologies are the first cohort of innovations designed not to primarily enhance productivity or efficiency, but to facilitate a form of open access and sovereignty. It accomplishes this at the expense of certain kinds of efficiency.

Anything that benefits the individual to the detriment of the state is, necessarily, a political creation. A redistribution of power from one group to another is definitionally political. That means these technologies are inextricably political, because of who and what they disintermediate. There is no getting around this.

This essay will review why you should be thrilled about the Fourth Industrial Revolution and its consequences. Something I personally find to be, a delight.

Decentralization and Its Consequences

DeFi, web3, and crypto are Fourth Industrial Revolution technologies.

• DeFi (decentralized finance): the infrastructure that crypto runs on. It encompasses blockchains and applications that exist natively atop them

• Web3: Umbrella term for decentralized compute and financial infrastructure that enables open internet and financial system access (“open access”). Web3 can also refer to DeFi (though crypto people tend to not say web3).

• Crypto: Digital assets that exist onchain, transactable within DeFi/web3. I will use “crypto” and “DeFi” interchangeably.

  • On an aside: I personally can’t stand the term “cryptocurrency”; it’s a misleading misnomer. Most of what’s being made here is not trying to be a currency. Currencies are stable units of account used to express relative, not absolute, value. They are rarely owned for investment like a stock or commodity is.

    • Crypto is overwhelmingly composed of digital assets and commodities meant for investment, preservation of capital, and speculation. They are anything but stable in price. Crypto can act like a currency in trade, but it’s much, much more than just currencies.

Unlike industrial revolutions before it, the Fourth Industrial Revolution’s sole motivation isn’t to optimize human activity, it’s to disintermediate the permissioned middle. FIR technologies are armored against censorship, not calibrated for speed and throughput; this is a characteristically political objective.

Previous industrial revolutions have been largely apolitical, serving only to magnify productivity and efficiency. They have been accretive to the state, corporations, and the individual.

The Fourth Industrial Revolution exists to disintermediate the existing structures of finance and compute. It provides permissionless access and sovereign self-custody at the expense of engineering efficiency. It is detractive to the state and corporations, and wildly accretive to the individual.

FIR technology cannot be compared to previous industrial revolutions insofar as the coordination and adoption problems it will face. Crypto is cool tech, but it’s not just cool tech.

Blockchain and Database: What’s The Difference?

A blockchain and a database is a distinction without a difference insofar as the literal functions they perform: storing data. Blockchains are simply databases, so why did we create a new term for them?

• It’s how blockchains execute their database functions that matters. Including major differences in how they’re accessed, controlled, and updated.

• Why is the ability to update and control databases such a political issue?

• Seen purely from an engineering perspective, a blockchain is an inefficient database. Sad! Who asked for slower, clunkier databases?

To decentralize is to sacrifice performance, why do this?

• A blockchain is a decentralized database that no single entity controls. It’s a ledger collectively updated by a global network, secured with cryptography.

• A corporation is a centralized database that one entity controls. It’s a ledger updated and controlled by a company or the state (a company is de facto controlled by the state via regulations). It can be censored and gatekept by the entity maintaining the database.

A decentralized database is not governed, censored, or gatekept by any single party, whereas a centralized database is. Everyone can use a decentralized database (blockchain), they can’t get kicked off it, and don’t need to ask for permission to do so.

There are massive political implications for something so innocuous-seeming as open-access to financial databases….

Decentralization is a Means, Not an End

Decentralization of infrastructure is a defense mechanism against censorship, and in service of permissionless access. It’s an engineering decision that creates a robust, open system that one entity cannot commandeer or manipulate. It’s a means to an end. A tool. It is not a feature.

The goal of decentralization is to produce the traits of censorship resistance and permissionless, anonymous access; I will collectively refer to these traits as “open access”. If decentralization did not produce these traits, there would be no reason to decentralize anything.

• Centralization means one entity controls the infrastructure. This is by far the most-efficient way to engineer something, but also the most censorable. You trade off open access for efficiency when you centralize.

• Decentralization means many disparate entities act in concert to update the infrastructure, and none of them unilaterally control it. You trade off efficiency for open access when you decentralize.

• The distributed global computing consensus that a blockchain uses is less performant compared to a company ledger, but produces the traits of open access for anyone with an internet connection.

• When you decentralize a form of coordination, you’re axiomatically imbuing greater latency and complexity. Having one guy and one server manage things has much higher throughput and performance than needing many to coordinate to do so.

• However, decentralizing this consensus process is the only way you can sustainably offer open access. Decentralization sits on a spectrum: the more decentralized something is, the harder it is for someone to corrupt and censor it, because it requires greater collusion between more parties to undermine it.

You don't decentralize because it's easy or fun, but because it vitiates power and oversight from those who manage the permissioned middle.

Who gatekeeps the permissioned middle? The state and corporations. Everything that’s managed by them, you use at their pleasure; everything you use in DeFi, you use at your leisure. There is no permissioned middle in crypto, because blockchains are not permissioned.

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A Politically Optimized Technology

DeFi’s strengths of open access could not be more in conflict with and antithetical to how the state and corporations do things. Immovable object meets unstoppable force. Permissioned access vs open access.

To decentralize your database is to intentionally design it to grant the traits of open access and to circumvent the permissioned middle. This is a political act, masquerading as an engineering decision. This is why crypto is an intrinsically political technology.

DeFi removes the state out of financial infrastructure as its essence. As its core motivation. DeFi is intentionally building inefficient databases and applications because it makes them more impervious to abuse, suppression, and corruption from state and corporate actors.

This means DeFi is not an engineering solution, but a political one. Because it’s an explicitly politically optimized technology, at the expense of engineering optimization.

DeFi makes accessing previously privileged resources and infrastructure a right. And I don’t mean a "right" in some fluffy platitudinous way, I mean we literally can't stop you from using the network.

• Web2: Don’t be evil. You must rely on the permissioned middle being a good guy, not censoring you, and allowing you to use it.

• Web3: Can’t be evil. We can’t censor you, because there is no permissioned middle where we can do so. This is what “trustlessness” means in crypto; you don’t have to trust us, because we don’t have the ability to be evil by the nature of the technology.

Coinbase, Binance, FTX, Bybit, Kraken, or anything that makes you create an account, provide an email, KYC, etc. are corporate, centralized actors LARP’ing as crypto. These are all corporations with permissioned middles, they are not blockchains, they can ban you for any reason, freeze your account, and censor you. If you can be banned or need to deliver personal information to access the app, you are not dealing with a DeFi platform. This heuristic will never fail you.

In true crypto, no one can seize your assets or kick you off the network. Not because DeFi people are nice and sweet and sing songs in the forest with the woodland critters, but because we literally can’t. Even if we wanted to be evil assholes, there’s nothing we can do. Coinbase can ban you for any reason, a DeFi application cannot. Open access motherfucker, do you have it? Don’t be evil < Can’t be evil.

The Canadian truck driver understands how valuable this is. The American spirit is instinctively drawn to this. The European and Asian will eventually come around.

Permissionlessness: Do You See a Strength or Weakness?

Permissionlessness is a profoundly critical concept for web3 and DeFi. It completely contradicts the rules of states and corporations, who no way operate "permissionlessly"; for them, everything is permissioned. Accessing their infrastructure is not a right, it is a privilege.

Everything DeFi sees as a strength, the state sees as a weakness. These are irreconcilable differences.

Hard power is military and violent force. Soft power is financial and economic coercion and control. The Fourth Industrial Revolution decrements the soft power of states, by way of decentralized financial databases. If you were the US, how would you react to this? Power is never willingly given away... it is taken.

The very nature of what we're building in DeFi implies political action, and thus will require forms of political coordination and messaging. Most in the DeFi industry don't really get this, and continue to be “aww shucks” confused by the open hostility of Western regulators. It is completely logical that they hate us when you understand that a parallel financial system is structurally adversarial to the existing financial system. It erodes their soft power and hegemony.

Sides will have to be taken, because like it or not, you are actively advocating libertarian ideology with this technology. All based on what you think of the permissioned middle and your desire to circumvent it.

Internet money… more serious than it lets on.

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Pitching A Cartel: How About You Have Less Territory?

Pretend you’re a crypto guy, and you want to work with the US and convince it to like you.

Your sales pitch to the state when advocating for DeFi will always fundamentally be: "Hey how about you have less power than you do currently? C’mon, the tech is so cool!"

Dress it up with all the lobbyist money and pleasant-sounding kumbaya language you want, this doesn’t change the nature of what crypto does to state soft power: it curtails it. How do politicians and governments historically respond to anything that diminishes their authority? Damn that is some COOL tech, of course you can be in charge now!

Federal and state power is a politician's power; you are asking them to willingly relinquish it when touting crypto. This is the same power the US fought world wars to win, and now forcefully imposes on the global and domestic financial systems. This kind of dominion does not get handed over in a courtroom, it is taken. You cannot "lobby" the CIA.

I break down the game theory of how I envision this playing out in The Vietnam Thesis. For victory, a guerilla doesn’t have to win, he just has to not lose.

“Hey pal, Trump says he’s a Bitcoin president and loves DeFi! What do you have to say to that?”

On Trump’s crypto pivot: Dropping memecoins and saying he likes Bitcoin does not refute any of this structural analysis. He can say whatever he wants, maybe he’ll even be cool to crypto for the next four years. Maybe. What happens after that?

Be careful about what politicians promise during election season. Actions, not words, are what matter. Are 80-year-olds who represent the federal government known for their intellectual and moral flexibility? He works for a machine that is diametrically opposed to us.

DeFi’s success and the state’s financial strength are a dichotomy.

Also, the president has no ability at all to draft legislation and rules around how any industry, let alone ours, is regulated. He is a totem, a spokesman. So, yeah, I’m really glad the next spokesman of the United States says he likes us now. If he were someone with actual concrete legislative and regulatory abilities, I may even be optimistic! Alas…

Remember the “is this real DeFi?” heuristic I shared? Trump’s crypto project is not DeFi, it’s a corporate service feigning otherwise. DeFi without the “De” is just TradFi (traditional finance) with extra steps. His project requires KYC, which means it is not permissionless, thus it is not DeFi. Don’t delude yourself because you like the guy; this crypto stuff is a branding exercise for him until further notice. Yes, he’s way better than Kamala and Co., and my God that’s not saying much.

DeFi must be understood on game theoretic grounds, not legal, in its relation to the state. Only with game theory, not legal theory, will the state’s past and future actions make sense. Case precedent from Doobsie Boobsie vs Calvin Coolidge or whatever laws created well before computers, now applied to stateless parallel financial systems, will not protect DeFi against a mafia that creates and enforces its own rules.

This is what approaching it on game theoretic grounds looks like: what would a cartel do if another cartel encroached on its territory? Would you expect it to be hostile, or look to the law for guidance? Don’t sympathize with the state, empathize: you’d hate us too.

You don’t have to agree with your adversary, but you must understand him. This is fundamentally not a question of law, but of strategy and low-intensity warfare. I discuss this further in the series Generations of War, Business, and Crypto: Part I and Part 2.

How do you think an empire that exerts its supremacy via authority over domestic and international financial plumbing will take to not overseeing it anymore? The US wields SWIFT, the IMF, dollar diplomacy, sanctions, the banking system, the petrodollar, etc. to exert its geopolitical might, and you think you’re going to subvert that in a courtroom or with lobbyists? How did the US earn those capabilities in the first place?

The US physically shed blood for this right. It fought two world wars and built the greatest economy in human history so it could claim the honor of being the financial hegemon. That crown was not given, it was earned and seized. Keep this in mind when you witness the US being hostile to crypto; it’s not unreasonable at all when you grasp its motivations. It’s not irrational for the state to hate us, because it’s not irrational for a dominant cartel to attack an upstart one.

Don't Sympathize with the State, Empathize

The above reaction is not in the slightest bit confusing or misguided. In fact, Krugman’s conclusion is correct when you consider his political affiliations (neoliberal state enjoyer). It’s Nic who’s lacking introspection here by not comprehending the ramifications of his industry.

Crypto is a political threat, by design, to the state’s permissioned middle that Paul and his neoliberal comrades hold dear. Paul can sense his cherished state is under duress! He’s not wrong! In fact, he's right to fear us. We’re literally separating money from state here... what do you guys think that means? Vibes? Essays? Paying a lawyer $3k/hour to interpret Doobsie Boobsie jurisprudence in a magical way that makes the state surrender and lets you replace their global financial network? Ha.

Countries wage wars over this. Nations use soft power to sanction people and put them on lists to get what they want. Intelligence agencies overthrow leaders because of it. Saddam wanted Iraqi oil sold in euros in 2000, and several years later… he was gone. I guess his tech wasn’t cool enough :(

Consensus mechanisms come in many forms: Bitcoin is a Proof of Work chain, Ethereum a Proof of Stake, and the United States is Proof of Violence. It leverages its military and economic heft to enforce and support the dollar globally and impose its will on international finance. I discuss this in The US Dollar: A Proof of Violence Network.

All the justifications politicians use to slander and attack DeFi ("it's for criminals!" "it's money laundering!" "climate and equality, or something!") are just that, client-facing rationales for the real motivations: preservation of soft power.

An unstoppable force and immovable object do not have PR departments that say they're unstoppable and unmovable: they lie about each other and attack. Cartel vs cartel.

Sometimes politicians slip up and suffer from a moment of candid clarity. This clip illustrates what’s actually going on in the bureaucrat’s mind around :22

Motivated reasoning:

When ExxonMobil says anything to assure you Co2 is good, does that surprise you? When cigarette companies suppress research on cancer studies, does that surprise you? When Kamala is asked a question about economics and responds, "Trump abortion LGBTQ#@ Project 2025", does that surprise you? When the Press Secretary mindlessly defends whatever the administration does, are you… surprised? I really hope you’re not.

These political smears against crypto from government employees also should not surprise you, for exactly the same reasons. These people say whatever’s needed to advance their interests.

Political messaging does not need to be honest, it needs to be effective.

DeFi is Useless

Equipped with this understanding of the Fourth Industrial Revolution and its technological consequences (a delight for the human race), you can now infer and triangulate political stances and beliefs… all based on what people think of internet money and the permissioned middle.

If someone tells you DeFi is useless or bad, you can bucket them in one of two ways:

• Intellectually unserious

• A political opponent

The former will come around when hivemind consensus tells them it's okay to do so; they’ll adopt crypto once everyone else does. The latter will present a problem.

"What's the point of such a technology, who needs your redundant databases….?". Well, if you don’t see the permissioned middle as a threat, but rather a friend, you will find this technology pointless.

If you understand the permissioned middle as a fulcrum of censorship and coercion, it makes intuitive sense to you to build around it.

If you understand the permissioned middle as your ally and think it should dictate to whoever it wants, you'll be continually upset by what we're building and why it exists. You will correctly perceive it as a threat.

These stances have very apparent political implications.

If you don't notice the permissioned middle yet are averse to DeFi, you're simply part of the later stage of S-curve adoption. You’re not an enemy, you just don’t use frontier technology. You probably thought the internet was only for porn and email until everyone else started using it. You need to see social proof before you dabble in something new, you'll come around.

If you notice the permissioned middle (like Krugman) and feel compelled to help it maintain its nexus of control... well, then we have a problem. You correctly interpret crypto to be political and are an open defender of state and corporate domination of financial infrastructure. We are not allies.

Much can be observed by your stance on the permissioned middle.

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Decentralization Is Not Fun

Decentralization is similar to a knight wearing 80lbs of armor going into a fight; it makes everything slower and more cumbersome, but it supplies a degree of defense that when you need it, you really need it. All of life’s a tradeoff. Speed or defense, pick one.

As long as you’re not being censored or attacked, decentralization will be an annoying feat of engineering sluggishness and redundancy. Similar to how you don’t need to put on your seatbelt 99% of the time, but that one time you do… boy are you grateful you buckled up.

DeFi as an industry struggles with this. They don’t internalize what they’re creating is political, and the more juvenile factions question decentralization because there hasn’t been a reckoning yet that shows them why the seatbelt is valuable. They’re waiting for this to happen to them before they learn their lesson. “Why am I wearing all this armor and a seatbelt I’ve never gotten into a car accident!”

Prophylactic measures like decentralization are not taken for convenience or performance reasons, but for preemptively protective ones. Holding a shield with your sword limits your striking speed, but saves you when he lunges at you. Fourth Industrial Revolution tech is innately defensive; it’s not primarily tools of convenience, but of freedom.

If you’re judging a technology that’s politically engineered on speed or latency terms, you don’t understand what you’re analyzing. It’s like assessing a tank’s acceleration on a Porsche’s terms, overlooking the true purpose of why the tank is designed the way that it is.

Concluding

AI represents another pillar of the Fourth Industrial Revolution. While crypto redistributes power, AI will consolidate it through economies of scale (GPUs, data, computer power).

AI will be accretive to the state, corporation, and individual in different amounts, whereas crypto only helps the individual. Crypto and AI are poetically at odds, contrasting and complementing each other’s strengths and weaknesses. Symbiotically antagonistic. Artificial abundance and artificial scarcity: a form of digital homeostasis.

The Fourth Industrial Revolution and its consequences will be a delight for the human race, and net detractive to state power. What a time to be alive.

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“AI will be better than humans in creative, artistic, and competitive domains, and it's going to replace us."

I believe this is the wrong framing. This sentiment echoes through Silicon Valley boardrooms and Twitter threads with the confidence of prophecy. Yet it fundamentally misunderstands what makes us tick as creatures who create and consume culture. It’s a claim predicated on a category error of what art and competition are intended for: human consumption and fulfillment.

Artists should not fear AI: they should view it as a tool that can enhance them, not an entity that supplants them. We consume what we value. “Value” is not a mechanical, objective concept; it’s contextual, capricious, interpretive, and imperfect. Humans are the arbiters of value, not machines.

We don't always value what's objectively best or mechanically pristine. We innately seek out unique individual expression and associate it with its creator. When there is no human to accompany that creation, it rings hollow.

We have many an "irrational" need and attraction to a human presence when experiencing an authentic, emotional message. What we consider "real" and "fake" is psychologically critical and cannot be rationalized away.

Examples:

• If someone's lip-syncing at a concert... do you like that? Or do you feel a little betrayed? By all audio accounts, it’s better than the artist's live voice. In fact singers often sound much worse live than they do in the studio. Lip-syncing gives you that crisp studio sound in the arena, yet we viscerally reject it. We want the cracked notes, the sweat-soaked authenticity of a human pushing their vocal cords to the limit.

  • We're paying for the possibility of imperfection: the very thing AI promises to eliminate

• Do people favor the Harry Potter originals or Harry Potter fan fiction? I'm sure some of it's better than JK Rowling's work. I bet Claude could easily whip up some stories that rival it. Why is hers famous and revered, and not the derivatives?

  • What connotation does the word “original” have that carries such valence to us…? Why do we consider the first version the better one? Irrational much?

• Consider the phenomenon of ghost kitchens: restaurants that exist only for delivery apps, with no physical location or human presence. The food might be identical to what you'd get at a 'real' restaurant, optimized by algorithms for maximum flavor delivery. Yet something feels off.

  • We crave the theater of dining: the server’s attentiveness, the kitchen’s aromas, the ambiance and the event of it all. The human mess is part of the journey, to only see the destination (the food) is a spreadsheet understanding of the world.

• Luxury items: can you tell the difference between a fake (what makes it fake?) Louis Vuitton bag and a “real” one? What about an organic diamond borne from millions of years of pressure, or a lab-made gem?

  • The lab-made diamonds are close to perfection and way cheaper. They look exactly the same to the naked eye and are even made with similar carbon-crystallization processes. What’s not to like?

The psychological weight of authorship is so profound that discovering its absence can retroactively poison our experience of the work itself. Someone wrote this in response to one of my essays:

His sentiments illustrate this beautifully, he’d be “devastated” if he found out a machine was behind my writing and not a person’s creative expression and thoughts (this is not the first time I’ve heard this). Why?

The betrayal isn't in the content, but the contract. When we read personal essays, we're not only processing information, but communing with another consciousness. Remove that consciousness, and you've gutted the entire essence of it. The writing would be unchanged, but the mental framing and appreciation is dramatically recalibrated when there’s no human behind it.

You can find the essay he’s referring to here: The Tim Walz Archetype & Democracy Dies in the Drive Thru

Authentic writing is a window into the mind (cognition) and soul (morals and values). The more presence an LLM has in your work, the less presence you have. If the AI replaces you, it’s because you were replaceable.

It’d be a betrayal, both to my readers and to myself, if a machine wrote all this. Like textual lip-syncing but worse, because it’s not even your own lyrics you’re faking, so it’s not your own ideas or thoughts, yet you’re presenting them as such.

For technical writing or the like, fine, go nuts, it’s not something we read to get a lens into a person’s ideas (and clearly you don’t enjoy creating it either, otherwise you wouldn’t outsource its production). No one consumes research papers or manuals for the author’s artistic expression. But for anything that touches the creative, artistic, or intellectually unique spheres: be yourself. It’s what the people seek.

Art: An Imperfect Domain

Look at this. This is perhaps the most famous piece of American modern art ever. Do you think Midjourney can "do better"? I sure do. We don't care though, because that's not how sentimentality works. You want an emotional, mortal expression that resonates in a human way. This is an evolved characteristic.

Part of the value we ascribe to creative work (and not only creative work) comes from the effort we perceive was put into it. We value homemade things more than factory output. You value a person's hand stitching more than the sewing machine.

We value how something is made sometimes nearly as much as we do the thing itself (depends on the item, obviously). This is known as the Labor Illusion of Value, however calling it an “illusion” doesn’t make it go away. This is an evolved heuristic we’ve cultivated over centuries, and not something that gets rationalized away.

This “fallacy” is why we'll pay $20 for a hand-thrown ceramic mug with a wonky handle when IKEA sells geometrically perfect ones for $3.99. The wobble is the point. It's proof of life, evidence that another pair of hands — attached to a mind, attached to a story — touched this object and left their mark.

You know how people like their fruit labeled "organic" because something being natural is instinctively more attractive? "Human made" is the new organic in the artificial-abundance era of AI. Even when The Machine is vastly superior to us, it does not change the human condition of how creative value is perceived and admired. We are hardwired to seek it out and exalt… the human.

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You’ll still want anthropogenic work from brilliant folks; you won't cherish a machine’s output the same way. A machine does not feel or understand the world or humanity in the manner we do, and its characterization and depiction of it will be lacking the psychological touch that the lab-made diamond is all too familiar with.

Art is a microcosm of humanity: expressed via text, imagery, sound, and consumed with the heart.

Human & Machine Competition

If art reveals our hunger for meaningful expression, sports speak to our romantic addiction to struggle and triumph.

Another example of human imperfection prevailing over computer superiority: competition.

Say, chess.

AI dominates us at chess, computers have solved the game. Yet it's Magnus Carlsen and slow, plodding, blemished meat spectacles we watch. Two computers playing each other just doesn't fill the seats the same way, because clinical robot performances aren’t what you watch when elite-yet-flawed fellas are available.

We don't watch Magnus because he plays perfectly. We watch because he might blunder under pressure, get cocky and sacrifice his queen on a hunch, stare at the board for twenty minutes only to play the move everyone saw coming. The thrill is found in the mortality, not the technical precision of the moves.

Would you watch a competitive sporting match of this?

It's our programming to venerate human accomplishment and performance. We are the consumers of art and competitive feats, not machines. Humans, not spreadsheet expected values, are the judges of what's prized in these domains. And we seek the terminally flawed person, because we see ourselves in the struggle and triumph of it all.

The techno-optimists are right that AI will surpass us in every measurable dimension. Where they go wrong is assuming that what we measure is what we value. We are meaning-making machines, not optimization functions. And in a world of sterile artificial perfection, the crooked timber of humanity becomes not obsolete, but coveted.

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This essay informs on why Salutary is implemented the way that it is via our Global Enforcement Framework. The following applies to all property rights and the game theory behind enforcement of binding asset transfer.

Incentives can exist onchain, enforcement cannot. Enforcement is not an onchain construct nor will it ever be; it exists in the realm of atoms, not bits. This essay will explain why blockchains solve many problems, but they do not solve all of our problems.

There is a well-known, well-intended but severely misguided chant in crypto: “code is law”.

"What I typed into the computer is law..." can you imagine if a journalist said that about her blog posts? These are equally naive statements.

It’s slogan for mechanical finality: the chain executes what the code allows, and the ledger records it. That’s a useful design ethic for machines; it’s not a theory of legitimate authority over human beings. It's an opinion, not a statute. It's the cypherpunk way of saying "The purpose of the code is what it does".

When I say “code is law”, I’m referring to this philosophy.

If It Happened Onchain, Did It Happen In Real Life?

Nearly everything is reversible except death or disfigurement.

The permanence of an outcome directly correlates with the legitimacy of the entity who decided it. Legitimacy is simply a more dignified proxy for force; it is violence wearing a three-piece suit. Might makes right, because might dictates the rules; if it follows the rules, then the decision is legitimate. If a rule is imposed only by asking nicely, then it is neither imposed nor a rule - it is a suggestion. A law is only as good as its enforcement. Rules with no enforcement are better understood as community guidelines.

What does enforcement look like? It means you have to do it, and if you don't then there is physical retaliation…. “Violence is the supreme authority through which all other authority is derived.”

Laws are created by the violence monopolist. If there is no violence monopolist, then there are competing laws from tribes with enough violence to be relevant but not enough to assert dominance; this creates schisms, fighting, instability. Peace through strength is very real - when there isn’t overwhelming strength, there is less peace, because there is constant jostling for who gets to decide what’s legitimate. You earn the right to make the rules, it is never handed to you.

Law is necessarily a human-readable interface to force. Code governs ledgers; law governs people.

A physical repercussion means it is kinetic; this means it must be able to literally make contact with your body. It should be abundantly apparent that violence is not wrought onchain. This means that if it happened onchain, it didn’t necessarily happen in real life.

Let’s unpack what “happening in real life” means, and instances when code, while never actually law on its own, can sometimes act as a default judgement.

Finality

“Finality” in the crypto sense means a transaction was enshrined onchain, and was there long enough to become a canonical part of the chain’s ledger. A blockchain is just a decentralized database, that's it - it's a different kind of database, a place to denote custody of something, a ledger that no single entity controls. Whereas a corporate database is a centralized ledger that one party controls.

“Who updates and maintains the database?" is a surprisingly politically contentious question! A blockchain is a beautiful technical achievement that nonetheless cannot escape the gravitational pull of physical reality; they solve many coordination problems, however they do not solve the problem of making unwilling counterparties comply.

For common day-to-day crypto purposes, this finality definition is fine. However, in the domain of intense disagreement with many millions of dollars on the line, blockchain finality is not at all necessarily final.

The answer to "can it be undone?" is always "yes"; the real question is what degree of coordination effort will it take to revert, or what kind of physicality does it require to retract. Who else opposes the event? Will the state support my side if I raise the issue? If enough people with force behind them agree with you, the transaction is reversible. If enough coordinated power wants it undone, it most certainly can be.

Violence is always the final baselayer if fleshy humans are involved. However, violence is costly to impose, and there are practical considerations for inflicting it. Thus, force isn’t necessarily the arbiter of every decision. Namely, when the stakes are low…

High-Stakes and Low-Stakes Lawmakers

If the stakes are low, code is law. If the stakes are high, men with guns is law.

(Side note: I know “men” is plural and it should be “are law”, but I like the symmetry of the phrases with both as “is law”)

How do we quantify the “stakes”? The answer to this comes down to the monetary value of the transaction in question. The greater the economic value of a disputed event, the greater the likelihood it will be challenged, physically.

Onchain, in the world of decentralized finance (DeFi, the real domain of crypto), the more trivial the transaction, the more final it is, and the more code is de facto law. Simply because it's not worth physically disputing. Even if your grievance is justified, there are many steps and costs to getting state-backed violence to effect a reversal. Litigation, lawsuits, cross-border enforcement… these are all quite expensive and time consuming.

What constitutes digital permanence for a “high stakes” event is essentially a cost-benefit analysis of what goes into getting your money back, and if the ROI of that effort is positive. Does the expected recovery exceed the enforcement cost?

The cost to litigate and enforce is basically the hurdle rate for high-stakes vs low-stakes outcomes and which law it follows. If the onchain transaction is below the hurdle rate, code is law; if it’s above the hurdle rate, men with guns is law. There's a threshold, a 'Defection Point', where the value at stake exceeds the ideological commitment to decentralization. Everyone has their Defection Point. The only question is the price. When a powerful person's Defection Point is breached, that's when the onchain event undergoes the Real Life test.

In this situation, the party that gains by defecting to state judgement, will do so. If the state disagrees with what happened, and it can identify the parties involved (and it will find you if sufficiently motivated to do so), it’s getting reversed, and your “finality” was not actually final. If it happened onchain, it didn’t necessarily happen in real life.

Even if an event was illicit, if it was for less than several million dollars it’s probably final. Code is law for the small stuff, because it’s not worth the cost and effort to recoup it and slips through the cracks. The pragmatics just aren’t there to contest it. Who's going to grab a sword and get it back?

For small-to-medium potatoes, code is law; because code is essentially a default judgement that isn't worth the time for men with guns.

The state has resource constraints. You have cost constraints. When the stakes are low, code decides the outcome, because… what are you going to do about it?

Onchain is Not Real Life… When the Stakes Are High.

If it can’t withstand physical disagreement, then it didn’t happen in real life, and it doesn't belong to you.

This is fundamentally commentary on property rights, using crypto as the medium. Natural laws that are impossible to ignore once you have eyes to see them. Here's an excerpt from another essay of mine, Property Rights, Toilets, and the Way of the Dog that illustrates:

"You can take this to any layer of abstraction you want: burglary, financial fraud, corporate theft, etc., if someone violates your private property and you live in a civilized state, the state takes care of the dirty work for you. You report it, and the men with guns inform them that the item will be going back.

If you live in a less-than-ideal society, like the Haitian or Iraqi, it's incumbent on you or your tribe to take care of business and return what's yours. If you can’t, then it’s no longer yours. The West is still the most ideal place to live, because it has created laws pertaining to contracts and property that best align with natural law, and it most-credibly imposes violent defense of it; which obviates the need for the individual to do so. This is a recognition of the law of the jungle, a streamlining of a carnal process. Nothing about a man with a gun imposing something is a social construct.

The test for private property is: if it can be defended, it can be kept. Do you live in upstate New York? Lawless Somalia? Doesn't matter, your property is still resolved fundamentally the same way. With force. The courts are simply a more dignified, efficient way to mediate this; but the violence backing their decisions is no different from the Somalian’s. Who carries out the court’s ruling as well as the Haitian gang’s? It’s men with guns all the way down. Or wolves with teeth.

Ideally, the state is who does the unpleasant labor of enforcement, because refined people find it unsavory to have warlords or militias impose rules with overt swords. But we know what happens if there is no state violence monopolist: emergent, balkanized violence takes shape, gangs are formed, and someone still ends up owning the property. All the edge cases get ironed out! Because someone always has a claim to property, with or without a law; it all rests on the philosophy of a sword."

Property rights are not a legal construct, but a natural one. Codifying a natural process does not mean you "socially constructed" it, you streamlined it.

Property is defined and maintained by He Who Decides It. It is dictated by force, by the person with the means to physically protect it. Whether that's codified in a law book or not, imposed by a judge or a warlord, is immaterial to this natural reality; from the savage to the civilized, property is maintained through the philosophy of a sword.

All animals abide by the law of the jungle: wolves with teeth or men with guns delineate borders and possessions. Societal laws are human-readable guidelines for violence, created by the violence monopolist. To be law, the monopolist must decree it law. These are very basic concepts once you wash away all the academic and technical abstractions, and no amount of wishful thinking changes their foundational substrate.

Illegal transactions worth tens of millions or more will inevitably get escalated to the courts. The state will allocate resources to these disputes. Men with guns will get deployed to enforce the real law. It must withstand their judgement to be final.

“Guys with guns can’t undo an Ethereum transaction, do you even know how crypto works?”

Oh? And where do you live? Onchain with your tokens? Is your house onchain? All your belongings? To get what they want, they don’t need to roll back the state of the chain, they only need to get you.

Picture this proposition: “Those tokens you have, send them back or we stick you in a concrete box for a decade.” Which law do you abide by in this instance? Code law or law law? What is the supreme authority? The blockchain doesn't fix this, it merely obfuscates it by one layer. Your private keys are yours... unless someone with a bigger sword wants you and decides otherwise.

Your code will not protect you here. The state doesn’t need to accomplish any feat of blockchain technical prowess to undo a transaction, it just needs to put forward a sufficiently convincing argument with a gun that you should undo what happened yourself. A $5-Wrench Attack, but more decorous. If you commit a crime large enough to draw notice, when they come for you they won't need to understand Merkle trees or hash functions; they'll just need to understand doors, and how to break them. This is how the state imposes true finality.

Pricey contentious events, where all parties are known, will eventually be subject to the judiciary when someone gains from its reversal. Beyond a certain degree of distress (or financial gain), people will defect from ideological allegiance in the name of self-interest.

There are no atheists in foxholes, and no “code is law” libertarians who lost 20% of their net worth in a hack. Everyone has a number.

Major transactions will not slip through the cracks; if someone feels aggrieved and that the onchain interaction was illegitimate, they will prosecute. The legal system will be their recourse. If they show it to The System and they agree it's invalid, then the transaction did not happen in real life, even if it occurred onchain, because it will be reversed or neutralized. How it's nullified will depend on how big it is.

Putting you in a box is the state’s token-burn function for your wallet's ill begotten gains. Why is this the same as onchain burning? If property has no owner, and it's not able to be owned by anyone else, then it ceases to exist in any functional way.

If The System agrees with the onchain event, then it truly happened in real life. Because now its digital existence is enshrined both onchain and reinforced, physically.

So long as humans are involved in this process, then the physical will inform the digital, because even though your assets are onchain, you are not. True finality for property rights is determined by what can be done to you, not how many blocks have passed since a transaction.

Implications for Crypto

Smart contracts are not a contract according to the philosophy of sword. The sword eventually has its say when real money is involved.

This creates what I call the Salutary Paradox: to make crypto transactions that breach the Defection Point concretely final, we must acknowledge they aren't inherently final by just settlement mechanism alone. Only by designing systems that respect both code and enforcements kinetics can we achieve genuine permanence. Salutary hybridizes code and kinetics when it's necessary.

This means any transaction of succificent financial value where all parties are identified (like, for example, an M&A event), must be legally pristine, because then it happened in real life. If it works in the most-hostile environment, then it always works. Salutary facilitates and enforces high-stakes transactions for DeFi projects and businesses alike. Salutary is designed to work in hostility.

The cypherpunks were half right: code is law... for transactions too small to contest. For everything else, there's Salutary.

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There are cypherpunk reasons why we want decentralization, and there are pragmatic ones. I believe the pragmatics will be what force us to adapt. We’re not decentralizing because it’s fun, or because we think everyone has the same based cypherpunk ideals as us, but because it’s necessary. This essay will review what “necessary” looks like.

I was hit by an onchain hack recently. I was stolen from. I’m angry. I want to be made whole. Someone who’s had his property stolen and isn’t willing to have centralizing bodies force its return only feels this way because he didn’t lose enough.

Allegiance to ideological beliefs and self-interest sits on a spectrum; some people require more distress than others for fight-or-flight to awaken. Espousing "code is law" beliefs are something of a proxy for "I've never experienced sufficient hardship from an attack". You too have a number at which you won’t care what the code said, you want your money back.

At what point does someone defect from the Rules of Engagement and standard decorum, because he has too much to gain in doing so? The answer to that depends on the victim, but it always has an answer. It’s inferior game theory to expect everyone to always respect what the code did as the final outcome.

At a certain level of pain, your best interests will supersede ideological fealty, as they should. There’s a difference between rational self-interest (wanting to right a wrong or getting what you’ve earned) and pathological self-interest (sociopathy, parasitism). Rational self-interest is a healthy, Darwinian characteristic.

It won’t be ideology that brings us to our decentralized destination, it will be survival-based necessity. It’s not a very romantic answer, but I think it’s the truthful one.

Let’s review some scenarios.

The Reckoning of That Guy

I can’t make someone return my stolen funds to me. I’m not That Guy. I’m not rich enough. I’m not motivated or connected enough. But one day, the wrong guy is going to get robbed onchain (a hack is theft), and you’ll draw the full ire of That Guy. He will not fuck around.

That Guy is rich. He’s going to lose a lot of money in this robbery (call it what it is), but will still be wealthy. He’s going to be enraged, vengeful, and motivated. He’s going to do more than just complain about it online, he’s going to use the legal system to get his money back. He will appeal to men with guns to undo the matter by leveraging the legal system. He will defect from the current DeFi ethos of “well these things happen you know, nothing you can do about it.”

And he’s probably going to win, and force something that everyone will absolutely hate, but ultimately is necessary.

Why Decentralize? A Secret Bonus Reason

The path to true decentralization won’t be found in a roadmap, it’ll be found in survival.

Why make something decentralized? Why are we intentionally making inefficient, slower databases? It’s so no single entity can control them.

The benefits of one person not controlling a financial ledger are worth the inefficiencies: no censorship, no gatekeeping, permissionless access, and the disintermediation of money and the state.

But what if there was another critical reason that has yet to rear its ugly head: no liability.

L2s and Decentralization Theater

Basically no L2 is decentralized. They all can rollback state, block withdrawals, or have a centralized sequencer. This is not decentralization. You can review this here.

I’m not criticizing them for it. I understand scaling and building is a complex, difficult process that requires centralized decision making at the onset, and decentralization is a spectrum to work towards.

However, if you have all those centralized abilities, and a major act of fraud goes down on your financial ledger, and you don’t fix it……

I’m adversarially minded. When I see centralization and a crime someone chooses to not stop, arguably permitting, I default to how the meanest prosecutor might think...“accomplice”.

Bank Transfers Are Law: A Scenario

Globobank was defrauded and mistakenly wired out $20M from accounts in an elaborate scam. Globobank is kinda like one big ledger in a way, with one validator and one sequencer.

Reversing this would be hairy, but Globobank can unwind the fraud and return the $20M back to the rightful owners. But chooses not to, because ideology.

Conversation:

Feds: “You need to either freeze these accounts or reverse this while we investigate.”

Globobank: “I’m sorry we can’t, it goes against our deeply held belief that bank transfers are law. If we undo this, then our clients will realize a lot of their Globobank assumptions are wrong, and the optics are bad. Also it’s a pain.”

Feds: “So you can undo this, but some clients would be mad because they think you can’t. So you’re refusing to rectify massive fraud because management thinks bank transfers are law?”

Globobank: “That’s right. A little rude, but correct.”

Feds: “Sounds like aiding criminal activity, let’s see what the courts say…..”

The Judgement of Boomie McOlds

Scenario:

There was a $100M hack on Optimism (an L2). They could have frozen bridges and blockchain production and rolled it back, but leadership chose not to, because ideology and optics.

That Guy I told you about, the rich, vindictive, angry one who lost a lot of money but is still very rich, he lost a lot of money. He’s going scorched earth and suing Optimism for enabling fraud and to recoup his losses. The case is going to court.

The honorable Boomie McOlds is presiding:

Plaintiff: “Your honor, as we reviewed in our bank-transfer example, nowhere else would we accept willful facilitation of fraud at a financial institution. Optimism is controlled almost entirely by management and isn’t actually decentralized. Thus, you’re just as culpable as the exploiter if you refuse to stop it…”

Defense: “Objection! Your honor, a blockchain isn’t a financial institution, it’s an *insert nuanced details about blocks, validators, etc. that Boomie finds irrelevant*.”

“…So you see, if these transactions were reversed — which my L2 client could have done — it would have been totally not cool. All our users would have been very angry because we’re supposed to be decentralized.”

Honorable Boomie McOlds: “So you could have stopped this crime, but you didn’t because you’re fake decentralized. However you're working towards real decentralized?”

Defense: “Yes, but please don’t say that out loud. Code is law.”

Honorable Boomie McOlds: “The court rules in favor of the plaintiff. You owe $100M plus damages.”

Objection!

You have nuanced, technical reasons why the blockchain and financial institution parallel is amiss. You studied cryptography at MIT, maybe law at Yale, and actually this scenario overlooks a key point about possession and finality that when viewed in conjunction with the Wooden Canoe Act of 1912 blah blah.

You’re probably right. I’m not dismissing your objections because you’re wrong. I’m dismissing them because they’re likely to be ineffective against a legal system dominated by predatory regulators and politicized prosecutors that are hired guns to protect the state, not to protect consumers.

You don’t have to convince me, you have to convince the Boomie McOlds that saturate the legislature and judiciary. The state hates DeFi and is right to see it as a threat to their soft power, because we’re incrementally taking away their control of the financial system. The state makes the law, interprets the law, and enforces the law; and it’s Boomies all the way down. To say you’re at a structural disadvantage is an understatement.

When this event goes to trial, I do not expect it to go well for us.

Pseudo-Decentralization: The Worst of Both Worlds

Currently, we have what I would describe as the worst of both worlds in respect to centralization and receiving its benefits. We act like the pros aren’t there, while being every bit still exposed to its cons.

We have centralized entities masquerading as distributed networks. A kind of decentralization pageantry. This provides few of the security and censorship benefits of decentralization, and even less of the centralization perks.

We have full exposure to censorship AND get no protections against hacks!

When lowlifes steal, we have to pretend like we can’t thwart it. Being able to stop this falls firmly in the benefits camp of centralization, and we're denied it. We allow billions in theft because…. eww?

Pseudo-decentralization is the worst of both worlds because we’re subject to all the risks of centralization as it relates to censorship, and get none of the pros of that censorship ability. In the interim, while we’re centralized, we should reap the full benefits of it and not pretend like they're not there.

Pragmatics over purity. Hacks on centralized chains should not exist.

Property Rights Are Sacred

If you’re going to be centralized, that’s fine. It’s a hard process and Rome wasn’t built in an epoch. But be transparent about what it means for risk AND protections, and don’t allow people to be wronged because it disrupts the theater.

People rightfully want their property back when someone steals it. And until chains figure out ways to credibly decentralize, we should work to avoid the eventual wrath of That Guy and the legal system, and also to do what’s right by people.

Leverage the pros of our current environment to help victims. Instead we act like they’re not there, opting to protect North Korean hackers and criminal scum over regular users? No, sorry I don’t value them nor do I have religious deference for block creation as the word of God sketched into a stone, this shit can be undone if like five guys decide they want it to.

Property-rights violators are morally loathsome criminals. The DeFi zeitgeist seems to hold these people's actions as more worthy of protection than the return of rightful belongings. Don’t deprive people of their property because it exposes false optics.

Theft is fundamentally a property-rights violation. We all believe in property rights, right? Do you think if a burglar breaks into your home and steals he should be caught, punished, and your property returned to you? Would you call the cops if you got robbed and leverage violence (the legal system) to get back what’s yours?

Ok and why is getting burglarized onchain different? It’s not. It’s a property-rights violation. It’s orders of magnitude more ethically repugnant than halting block creation. There is no equivalence here.

We all think we should be able to self-custody our crypto because of property rights, yes? Well if crypto is in fact property (which it is), what does that mean if you’re robbed of it?

Radical respect of property rights is essentially the bulwark of Western beliefs.

Willfully allowing property-rights violations is a vastly greater moral wrong than stopping the sequencer. In fact, property-rights violations may be the second-worst moral wrong that exists (second only to violent assault). If you can stop them, you should.

Closing: Decentralize to Avoid This Dilemma

If you don’t want the liability and obligation of rectifying legal and moral wrongs, the answer is very simple: credibly decentralize. Make it so you literally can’t change what happened.

I encourage all chains to take this seriously. Start creating a framework for freezing and rectifying obvious theft and fraud. Because That Guy exists and when he gets hit, he’s going to go after you, and you don't want the legal system to view this the way I just laid out. It will open up a huge can of worms.

Further, I personally think it’s the correct moral decision to leverage the power you have to right wrongs while you still have that power. Don’t pretend like you don’t.

The best way to rid yourself of any moral or legal liability is to make it so it's not your decision to make. I prefer a decentralized world where actions can’t be undone by any single entity. But I also don’t deny the world as it is now.

It's a completely valid, and even correct, feeling to hate this essay, because it shows your heart's in the right place. Nothing about this is pleasant. But don't dismiss reality because you find it unsettling.

If you don't like this, change it.

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Previous writings that this piece builds upon:

• The Vietnam Thesis

• The US Dollar: A Proof of Violence Network

• Generations of War, Business, and Crypto: Part I

Historically, generations of warfare and business have closely correlated. However, there’s a lag between them: warfare is roughly one cycle ahead.

Using militaries as a leading indicator, you’ve been able to predict business behaviors before they’ve manifested. Warfare is compelled to adapt to new dynamics more readily, motivated not by profit, but by survival. I believe war can be a prognosticator for any sufficiently adversarial domain…. like crypto.

Warfare has been a harbinger for business, and I believe it can be for DeFi as well. Using parallels from warfare, what can we expect for DeFi’s future generations? Where is DeFi in its evolution compared with business and war?

This is Part Two of a multi-part series that analyzes business and warfare generations, and draws parallels and predictions for DeFi’s past, present, and future.

Picking up where we left off from Part 1…

4th-Generation Business (Comparable to 3rd-Gen Warfare)

3rd-gen business was the era of conglomerates and middle management. Mega companies led by a professional white-collar class that resembled Mad Men. 4th-gen begins to chip away at that standard; this is roughly the generation that business is currently in.

4th-gen business — AKA the entrepreneurial era — began in the late 1990s. Startups incorporate Blitzkrieg-style approaches (parallels to 3rd-gen war) and are distinctly faster and more mobile than their old-economy counterparts. They quickly propagate and are more fluid and dynamic with their strategies. The comparative shift from bureaucratic professional-manager structures (oligarchical) to the ‘eccentric founder’ one (monarchical) allows startups to act more efficiently and with less bloat. Speed kills.

Backed by venture capital, 4th-gen businesses rapidly go to market and find PMF by streamlining old business categories and creating new ones, disrupting the paradigm previously dominated by corporate structures. 4th-gen business strategy swiftly circles and undercuts legacy companies, escalating the nature of full-contact capitalism. The parallels to Blitzkrieg are clear.

4th-gen companies are more adept in tech-native paradigms, because they were born in the technology, molded by it. Whereas 3rd-gen companies merely adopted the technology (*Bane voice*).

4th-Generation Warfare (One Cycle Ahead of Business)

The lines between soldiers, civilians, war, and politics become blurred. This is guerilla warfare.

4th-gen war is more aptly defined by the participants in the war and their objectives, rather than how the war itself is fought. This generation is led by decentralized nonstate actors who are able to put up serious resistance or even repel more powerful, centralized state militaries. The internet and mobile devices allow advanced coordination and information sharing without the large, slow-moving processes of state bureaucracies.

This levels the playing field, and means sheer might doesn’t always make right anymore.

The 9/11 attacks are a prime example of an effective 4th-gen assault. Terrorism, rebels, militias, etc. performing hit-and-run strikes and sabotage are examples of 4th-gen strategy. State militaries struggle to tactically retaliate, as guerillas often don’t occupy territory and are not clearly identifiable. 4th-gen war and its participants are much less legible to the traditional adversary.

War begins to aggressively incorporate propaganda and disinformation in conjunction with kinetic violence. Psyops and false flags are known tactics, with state and nonstate actors spreading disinformation by way of social media, dank memes, and fake news.

In contrast to 3rd-gen war — which mobilizes societies and has a “win at all costs” mentality — 4th-gen war often relies on proxy combatants who can win simply by not losing.

They don’t have to defeat their traditionally dominant adversaries, they merely have to stay in the game. Persist. This is how 4th-gen goals and interests are advanced and remain visible.

“The conventional army loses if it does not win. The guerrilla wins if he does not lose.” -Henry Kissinger

4th-Generation DeFi

3rd-gen DeFi ends when the US goes mask off, mandating a registered presence in order to legally transact and build onchain. Privacy tech becomes illegal and sanctioned be default. Self-custody will be treated like having a Swiss bank account in terms of disclosures and reporting requirements. Using crypto will be viewed by the DoJ like owning a bong: yeah having one isn’t illegal by itself, but…. we know what it means.

Owning crypto may even be like owning a gun, eg you need a license to “conceal carry” it (hardware wallets) and it must be registered. And some places like NYC may just make it outright illegal. Or so impossible to get a BS license for it that no one even tries (exactly how that city treats gun ownership).

The West will target devs as if they’re criminals for creating open-source software. DeFi builders will learn what low-intensity war means. The space will go dark.

4th-gen DeFi is Crypto’s Vietnam Farmer phase

For the same reason the US hasn’t really won a war since WW2, continually losing to the likes of Vietnamese rice farmers and Afghan goat herders, the SEC and regulators will suffer the same fate.

Why will the US fail to stop DeFi? For the same reason it doesn't win wars anymore. The US military is built to go after Russia, China, Germany… meaning large, legible, centralized adversaries that occupy territory.

Who does the US lose to? Vietnam. Afghanistan. Guerillas. Diffuse. Illegible.

Like the military, the SEC is designed to go after the same things. Regulators are built to oversee Goldman, Barclays, Fidelity.... big, slow, legible targets that occupy office buildings with compliance departments and formal chains of command.

DeFi is built different. Regulators are simply not designed or equipped to keep a global distributed network under their thumb. No one is.

Why can you still use The Pirate Bay? Because it's nearly impossible to stop P2P networks. They're not capable of going after millions of us armed with cryptography, AI, and well capitalized across a global network. The resources and competence simply are not there. The human-capital superiority of DeFi is positively overwhelming against a midwit bureaucrat army.

In 4th-gen DeFi, we are all Vietnam farmers.

4th-gen DeFi will have an omnipresent feeling of low-intensity warfare, meaning attacks that are mostly non-kinetic and subversive. Regulatory assaults will escalate from more symbolic ones on non-core infrastructure (like Tornado Cash, Mirror Protocol, Ripple) to critical ones in an effort to weaken Ethereum’s security (like staking services).

They’ll attempt to shut down stablecoins to destabilize DeFi. They’ll make you register as a business/money transmitter if you run an ETH node. Among other belligerent nonsense that uses a thin facade of legal warfare to advance what is an irreconcilable difference between crypto and the state. I expect the likes of Lido, Rocket Pool, and Tether to be targeted.

Expect nonstop legal games to choke off additional capital from going onchain and to weaken network security.

Methods of Attack

The state will begin to go after companies that provide services to DeFi projects. Cloud computing and internet infrastructure giants (AWS, Azure, Cloudflare, etc.) will treat crypto clients with the same disdain that banks do, as DeFi increasingly becomes persona non grata in the US and across the West (I don’t expect the US or its vassals to have materially different views here).

Cloud providers will ban accounts affiliated with crypto out of fear regulators may target them for aiding money laundering, or whatever pretext the state uses to exert pressure. Banks already do this to crypto companies and users; they’d rather not deal with “high risk” clients, so it’s easier to simply not associate with them.

I made this cloud provider prediction last year, and forms of it are already beginning to happen for AI infrastructure. Cloud providers and banks will be exploited by the state to try and stop DeFi and control AI.

Out of necessity, projects like Filecoin, Urbit, and Render will transform from neat projects we support but don’t rely on, to core parts of the DeFi decentralized stack. This is a good thing. We shouldn’t be so reliant on centralized corporations for our decentralized infrastructure. It won’t be ideology that brings us to our decentralized destination, it will be necessity.

As DeFi is assaulted with random arrests of builders and disinformation campaigns that smear users as criminals, factions of crypto will begin to act not only defensively, but offensively.

Aided by AI and cryptography, mercenary cypherpunk teams will spread their own propaganda and cyberattacks in kind, going after politicians and regulators that have openly abandoned the law. You could even see a crypto Blackwater take shape. We are in a Fourth Turning, after all.

Separating money and state should not be taken lightly. This is an incredibly impactful and detrimental concept to the state. They hate you. They are right to hate you. Everything DeFi does detracts from their control, by design. Do not expect them to just lie down or fight fair.

State’s will arbitrarily seize assets of those suspected of being affiliated with DeFi and hold them indefinitely in “guilty until proven innocent”-style policing, deserting facades of legal due process. This isn’t some unrealistic concept, the US already does a variation of this with Civil Asset Forfeiture.

They have already begun doing this with the reprehensible, arbitrary detention of Tornado developer Alexey Pertsev, held for months with no charges. He is now being prosecuted for writing and releasing open-source code.

These people do not care about the law. It’s naive to have a School House Rock notion of due process here. They care about going after an industry they rightfully understand to be disintermediating their soft power and control of financial infrastructure.

OpSec will become a critical component of anything onchain. VPN providers will likely be targeted and servers seized (exposing which have “no logs” policies), as the state ratchets up desperate attempts to put the crypto toothpaste back in the tube.

All DeFi privacy tools will eventually be some form of OFAC sanctioned via language that says anything providing onchain anonymity is illegal. Why? Because fuck you, that’s why. The GAE says no, what are you going to do about it?

You won't win by outright defeating it, but you can by slowly eroding it. Persist. Just like guerillas before you.

Key Philosophical Takeaways

Privacy will have to be fought for if it’s to become a human right in the eyes of the West and its tyrants. Rights are not some natural resource you find in a well, they are earned.

"Rights" can be defined as that which society refuses to tolerate. A society that refuses nothing has no rights... and deserves it.

Please internalize this: DeFi disintermediates the state and corporations out of financial infrastructure by design, it’s literally the whole point of this. They are right to fear and hate crypto.

This battle must be understood as game theory, not legal theory. Boobsie Doobsie vs Calvin Coolidge jurisprudence will not save you. The Wooden Canoe Act of 1912, made before computers and abstracted to stablecoins, will not protect us.

This is why the relationship between the US and DeFi is irreconcilable. It doesn’t matter who’s in office. A hegemon will never embrace technology fundamentally designed to decrement its soft power; which is what control of financial infrastructure represents, and what DeFi takes away.

What to Look Forward to in the 5th Generation…

In 4th-gen, the DeFi community is finally disabused of the idea the state will embrace its disintermediation with money and control of financial infrastructure. The US fought wars to win its highly coveted soft power; it will require another one to take it away. Wars do not happen in court rooms. The petrodollar sends its regards.

In Part Three I’ll review 5th-generation warfare and extrapolate where both 5th-gen business and 5th-gen DeFi are headed from a tactical and ideological standpoint. 5th-gen business has not yet arrived, so you’ll get business predictions as well as crypto ones.

The future is here, it’s just not evenly distributed.

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The Generations of Warfare, Business, and Crypto series is related to and informs The Vietnam Thesis, The US Dollar: A Proof of Violence Network, and other game-theoretic-minded approaches to crypto adoption.

Historically, generations of warfare and business have correlated closely with each other. However, there’s a lag between them: warfare is roughly one cycle ahead of business.

Using militaries as a leading indicator, you’ve been able to predict emergent business behaviors before they’ve manifested. Warfare strategy is compelled to adapt to new dynamics more readily, motivated not by profit, but by survival. I believe warfare can be a prognosticator for any sufficiently adversarial domain…. such as crypto.

Warfare has been a harbinger for business, and I think it can be for crypto as well. Using insights from military strategy, what can we expect for DeFi’s future generations? Where is DeFi in its evolution compared with business and war?

This is Part One of a multi-part series that analyzes business and warfare generations, and draws parallels and predictions for DeFi’s past, present, and future.

1st Generation

1st-Generation Business:

1st-gen business coincides with 1st-gen warfare, but is comparatively more medieval and rudimentary in its operations (remember warfare is always one developmental cycle ahead of the business cycle it coincides with). 1st-gen business was often conducted through trade and merchant guilds, which meant groups of dealers in similar industries colluded to regulate prices and protect their interests. 1st-gen business was subject to control by feudal lords, the state, and the Catholic church. The church owned a lot of land and had a monopoly on certain trades.

1st-Generation Warfare (one cycle ahead):

1st-gen warfare was a departure from medieval strategies, and utilized linear tactics with line-and-column techniques in direct combat, with muskets and conscripted armies.

1st-gen warfare began to see emergent centralization, with professional officers leading armies of full-time, uniformed, paid soldiers fighting for nations instead of feudal lords. Its tactical organization was limited, due to inferior communications and intelligence capabilities.

1st-Generation Crypto (not yet DeFi):

Crypto’s 1st gen begins at the creation of Bitcoin in 2009. It introduced the concept of onchain assets with artificial scarcity that exist purely in digital space. A token possessing value both via a market price and by way of remitting payments with no central intermediary. Crypto’s 1st gen is somewhat medieval, like its business counterpart, in that it facilitated simple transactions to and from users, with no real strategic ability beyond basics. The 10,000 BTC purchase of a pizza encapsulates the pre-DeFi era of crypto well. This generation lasted from 2009-2015.

2nd Generation

2nd-Generation Business:

Similar to 1st-gen warfare, 2nd-gen business saw the advent of paycheck, full-time employees and a formalized, structured approach to business operations. It had more coordinated, centralized organization and management, with large businesses beginning to form and supersede colonial ones. Its communications were improved but still limited, consisting of primitive forms like mail and telegraph. You begin to see latent professional and strategic structures for it to build upon in future business generations.

2nd-Generation Warfare (one cycle ahead):

2nd-gen warfare featured technological advancements that made war more lethal. 2nd-gen war incorporated more raw firepower and manpower to wear away at the enemy and then occupy his territory (the machine gun was introduced during this time). Attrition warfare was a hallmark strategy, which often resulted in the side with greater economic resources being victorious; whoever could last longer typically won. 2nd-gen war was still fought face to face, and compared to 3rd-gen war had a greater sense of decorum. ‘War crimes’ were not really a thing, and there was still a sense of acceptable war behavior.

Some key features were fixed fortifications, artillery, and the adoption of increasingly centralized, organized strategy. Brute force and facing the enemy was how the game was played. Coordination was enhanced by advancements in communication from things like the telegraph.

2nd-Generation Crypto, now DeFi:

The emergence of the smart contract and Ethereum in 2015 marks the beginning of crypto’s 2nd generation. It’s evolution from crypto into DeFi.

Onchain smart contracts facilitated enhanced coordination and onchain interaction (similar to what the telegraph did for war and business). This created the substrate for more sophisticated transactions and infrastructure for a financial ecosystem beyond simple remittances. The smart contract is the basis for onchain commerce that allowed new forms of financial communication to be built (smart contracts are simply programmatic, automated instantiations of communication).

Ethereum and other programmable base layers (layer 1s) allowed DeFi to organize itself more strategically, a necessity for the future financial activity that would flourish upon it. Being able to send, issue, borrow, lend, and trade all manner of crypto spawned an entirely new market of projects offering many kinds of permissionless, decentralized financial services, a first of its kind. 2nd-gen DeFi lasts from 2015-2020.

3rd Generation

3rd-Generation Business:

In 3rd-gen business, professional managers began to exert more control, and competition had the trench-warfare attrition characteristics seen in 2nd-gen warfare. Competitors that were evenly matched attempted to wear each other out in the market, with the one with greater financial resources having substantial advantage. Businesses began placing a strong emphasis on meeting the needs and expectations of customers and building longer-term relationships.

Business centralization and size seems to peak in 3rd-gen with the advent of the conglomerate. Mega corporations creating empires of disparate businesses was something of a trend during this time. I believe this is one of the least-efficient elements of this generation, and it gets unbundled in 4th-gen business.

3rd-Generation Warfare (one cycle ahead):

3rd-gen warfare, also known as Blitzkrieg or maneuver warfare, was inspired by the German military. It relies heavily on speed, mobility, stealth, and surprise to outmaneuver the enemy and attack from within rather than confront and erode him away slowly (attrition). It embraced ‘total war’, which included the mobilization of societies, as countries sought to harness the resources of their population for victory. It’s in 3rd-gen war that dominant game theory takes center stage, and a win-at-all costs mentality starts to emerge.

3rd-gen war disregarded notions of honor and fairness, embracing deception and brutal pragmatism as valid tactics. Atrocities from this approach resulted in the creation of things like UN war crimes. Notable new technologies include widespread use of armored units, tanks, planes, and paratroopers.

A quote that illustrates 3rd-gen brutality well: during World War 2 in response to German onslaughts, a British general said “If this is what it takes to win, I’m prepared to lose.”

3rd-Generation DeFi (where crypto is now):

DeFi is in the midst of its 3rd generation. This began in 2021, right after DeFi Summer 2020. Ethereum continues to become the Lindy baselayer and dominates from its network effects. Its security and reliability is allowing DeFi to scale from niche financier playground to public financial infrastructure. The kind that, one day, will threaten the existence of bank and state soft power.

Similar to 3rd-gen warfare, an array of new technologies are rapidly being deployed, facilitating sophisticated transactions, scaling, and disintermediation (maneuvering) of gate-keeping middlemen. Things like ZK tech, optimistic rollups, EIP-4844, and EIP-1559 being prominent examples.

DeFi operates with vastly superior speed than its adversary (the state). Regulators’ sclerotic processes and glacial adaptability leave them woefully ill-prepared for the crypto blitzkrieg.

The attack on Tornado Cash exemplifies the state’s budding hostility, as it realizes DeFi disintermediates its relationship with money and its ability to enforce the soft power it fought two world wars to gain (the Proof of Violence piece linked at the beginning speaks to this). This is the genesis of DeFi’s guerilla phase, and will have many parallels to 4th-gen warfare (covered in the next part of this series).

Anon teams will become more common and privacy measures increasingly critical, as it's made clear the state plays by whatever rules are expedient.

The arrest and infinite detention of Tornado developer Alexey Pertsev (with no charges) has begun to open the eyes of DeFi builders that this is going to be both a technological and ideological war. The state will weaponize the legal system — a domain where it both makes the rules and enforces its own rules — whenever it’s able. It has no allegiance to what’s moral and just, laws are simply a hurdle (or a tool) for it getting what it wants. And it's going to want DeFi.

This is the domain of game theory, not legal theory.

I think 3rd-gen DeFi will end when VCs can only touch crypto via fully doxxed (KYC’d) teams with official business presences in Western states that the US has full jurisdiction over. The US will likely demand backdoor access to multisigs and codebases when this happens.

Users will have to register their wallets with the US and its vassals in order to legally transact onchain. They'll try to pretend hardware wallets are tantamount to foreign bank accounts for reporting purposes. Or they'll outright ban self-custody and make hardware wallets illegal. When they do this, you'll know DeFi's 4th generation is near.

The US will become increasingly draconian and erratic, lashing out inconsistently and aggressively to try and make examples and scare our space into obedience, as it has the most to lose from DeFi’s proliferation. The US will see a braindrain in the DeFi space as a result, with other nations benefiting from American obstinance.

Many resolute crypto natives will likely renounce their US citizenship and distance themselves from an openly hostile, declining power. Smart, capable people will not tolerate being treated like criminals for transacting freely and helping others to do so. Talented, principled people have options, eventually they will exercise them.

This concludes Part One. In Part Two, we’ll review 4th-generation warfare, business, and extrapolate where DeFi is headed from a tactical and ideological standpoint.

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To shock puritans:

• 1970-90s: devil worship, rock, tattoos

• 2020s: *insert wrongthink heretical belief*

A counterculture is blowback. It's intentionally offensive to establishment beliefs. Find it repellent? Good, it’s meant to gatekeep you.

New movements and ideas are contrarian. Contrarianism always:

• likes something before it’s cool

• thinks something before it’s ok to think it

Independent minds embrace a movement before it’s acceptable, then others notice it, and begin to like it too. It’s like an S-curve for cool kids.

But something cool must be exclusionary. Cool things aren't cool if they let everyone in. A nightclub isn’t as sexy if it’s inviting in anyone off the street. An Ivy League manufactures its prestige in large part by only accepting very few. However, if admission is open and you want to exclude people, you can impose a cost.

The cost is either explicit (money) or implicit (social signaling). Costly signaling is often the most effective "skin in the game" admission price.

”Where’s the Milady roadmap? What are they about?”

The absence of a roadmap or common structure gatekeeps people. Those who need a leader or document to tell them what the cultural movement is are de facto not culturally contrarian. For those unaware: a roadmap is a common DeFi/NFT term to describe the goals or intentions of the project. Milady eschews this by design.

White papers, roadmaps, etc. are how everyone else does NFT projects. Milady ethos is to reject that because it alienates precisely the people it wants to alienate. It disorients those who need familiarity to be oriented.

I’ve been a Milady enjoyer since I saw them in the wild. I love their aggressive political barriers and antagonism. Militant countercultures are a necessary social immune response that restores balance when culture becomes too monolithic; I view Milady as a fight for homeostasis. Also, they’re hilarious.

Rebellions Over Time

We laugh at how rock n’ roll, mohawks, tattoos, etc. could be rebellious behavior because they feel so innocuous to us now. But way back when, these were seditious acts against normie orthodoxy.

A persistent act of rebellion eventually becomes uninteresting, because it's no longer unorthodox. No one's outraged by tats, metal, gangster rap, or “flipping the bird” anymore.

Reason: they're not shocking. Normies do it now. When normies adopt your counterculture, it just becomes culture (boring).

I wasn’t around to observe things in the 1970s-80s, but from what I’ve been told there wasn’t the same rigid uniformity regarding what was acceptable political and personal beliefs. In the 90s, there was palpably less authoritarian-lite establishment orthodoxy and professional and personal assault of heretics.

What manifested as mostly outrage for puritans in the 70s-80s has taken on a more nefarious form of public flagellation and hostility for the 2020s puritans. The response is no longer “this is outrageous, boo” it’s now “this should be punished, we must get them”.

Milady rejects this.

The Milady Method

Pretend you had to think of the worst things you could to make CNN or a corporate HR department upset. If you had to orient your culture around the most revolting stuff possible, what would you pick?

Racism, nazis, pedophilia, anorexia….

The only way you could make this lineup worse would be if you added cannibalism to the mix. Maybe a pro domestic-violence stance? Like, these are cartoonishly offensive. Almost like they’re doing it on purpose, or something….

So outlandish that you should understand there's embedded communication here that transcends the explicit statement. I’ve discussed embedded messaging before. It's much more illuminating than the explicit communication.

“Boy howdy I’ve seen these Miladys and they're actually the worst!”

If you’re saying there are some seedy shitheads in this growing counterculture community, I believe you. Obviously there are. No lectures please, I'm well aware of the background and posts. But let me disabuse you of this notion of purity: people who harbor these beliefs are in your NFT communities too. Any predominately anonymous community will have these types. Milady is overt about it because they want to filter out anyone even slightly conventional.

Milady Streisand Effect

Ostentatious, unapologetic rejection of social norms gets noticed; every counterculture moors itself to this North Star. The consternation only makes it more seductive…. the more you forbid it, the more enticing it becomes to fence-sitters. It’s sexy how verboten it is.

Similar to 2016 when the more MSM told you how bad Trump was, the better his polling. People do not want moralizing lectures, it produces the opposite result. You can't scold the Streisand Effect. Humans have been seeking out forbidden things since Eve betrayed us all for fruit.

And many non-political types are completely done with the dogmatic censorship of viewpoints that don’t align with Netflix’s Human Resources dept. Opinions that Coca Cola denounces are becoming increasingly en vogue. This is blowback to puritan monoculture.

Repudiation of norms isn’t done in a measured way. Humans are not paragons of reason and thoughtful next steps. We take things too far, because 90% of people comply with hivemind social pressure and will support The Current Thing so long as a duly-appointed expert approved it. You don’t have to like Chomsky to know Manufacturing Consent is accurate.

So to correct the lack of cultural equilibrium, we over-correct in the other direction. All cultural norms taken too far produce blowback. An effective counterculture must be hyper-aggressive and target sacred cows for demolition.

Milady is blowback.

Don’t expect them to sanitize anything, because that’s the point. Milady is a way to organize dissidents and agitators, and is endearing to the very based because of it. To censor them is to destroy what made them noticeable. It'd be like Trump taking political advice from Jeb Bush…“Hey how about you be more banal and typical.”

Almost every job or product that’s richly valued is fundamentally solving a coordination problem. Milady is valuable because it solves the 4chan coordination problem: a dissident, anonymous gathering needs to be able to organize outside the forum. I expect their floor to rise.

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A common refrain from crypto detractors is it’s not worth anything because it has no “intrinsic value” (IV).

No one applies this term consistently. We deploy 'intrinsic value' arguments to tout assets we already like, and to disparage ones we don’t. The term morphs conveniently to match our priors, like water taking the shape of its container.

I’d like to dissect what intrinsic value really means. There are two different definitions: The Hammer Method and the DCF Method.

The Hammer Method

The core meaning of intrinsic value is something has real-life utility, independent of a market price assigned to it. For example: pretend there’s a market for my shoes, and that market offer was $0. Do they have zero value?

No, because they have genuine utility. They protect my feet, I use them to walk. Their value is not dependent on their market price. The innate, intrinsic value for them is their utility. A market price doesn’t make them any more or less useful.

My car has IV, it performs tasks I need to exist. The hammer in my toolbox has IV. My home has IV, it shelters me. Glue and cardboard boxes have IV. Your Playstation has negative IV, because it wastes time (ha, kidding. Sort of.)

What is the IV amount? That’s subjective. But the point is intrinsic value means something has value independent of its financial price. You could value all these things at $0 and they’re still not worthless. Typically the market would never assign such a price to useful things, but the point is their utility is not a product of their price.

This form of value essentially only applies to commodities: aka things you actually use. No financial instrument has Hammer IV, definitionally so, as any financial instrument’s worth is entirely predicated on its market price. Hammer IV has pretty narrow application.

No one really thinks in these terms when judging the IV of something. Yet almost everyone who criticizes crypto as having no IV implicitly uses it this way. It’s a post-hoc, pseudo-insightful definition they don’t apply to anything else, when really they just don’t like crypto. Many such cases!

We'll call this primary intrinsic value definition the Hammer Method.

The DCF Method

The second, more-common definition of IV references an asset’s discounted cash flows (DCF). When TradFi guys talk about IV, 97% of the time they mean how much cash the asset returns over its lifetime. To be clear, this is really extrinsic value, because the price is basically part of, or entirely, the utility here.

Technically a stock’s IV (AKA the company’s market cap) is the sum of all the cashflows the business will generate during its existence, discounted back to today. Projecting those cashflows is approximation, and far closer to art than science.

Bonds are valued similarly, though due to their defined duration, coupon, and return of principal they have far more concrete pricing that’s closer to a scientific valuation than stocks. Interest rates can make their market prices fluctuate substantially, but what the bond will provide you over its life is quite predictable.

However not all stocks pay a dividend, and the most richly valued ones (tech stocks) often don't. Only 50% of the Nasdaq pays a dividend. No cash will be returned to you from many stocks. A stock with no dividends or book value is just an “equity” abstraction, and functionally does not have any DCF IV because shareholders never see a dime of those cashflows (I’ve never heard Buffett criticize tech stocks on IV grounds, oddly).

It’s “equity” but what does that actually mean, concretely? You have no claim on company assets or cashflows. You can basically just vote with it. I deconstruct this in thorough detail in Governance Tokens, Tech Stocks, Dividends, and "Utility". If you’re a finance guy and your visceral response was “no that’s not true”, read the linked essay.

So what do most tech stocks represent insofar as IV?

They derive their value from the stock price going up as revenue, margins, and company cashflows grow. This is money you’ll never touch as a shareholder, but through some finance law of physics it shows up in the stock price (if you want to know what that financial physics is, you should visit Salutary.io). No TradFi guy will disparage anything listed on the Nasdaq for having no IV, even though crypto IV in the exact same way.

We’ll call this second IV definition the DCF Method.

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The Hammer Method or the DCF Method, Which Applies?

Most use the Hammer Method when disparaging crypto, but they only apply the DCF Method to their stocks, even when DCF assumptions are simply abstractions or more correctly understood as extrinsic value.

Further, if you’re judging an asset based off concrete cashflows it returns to you, they conveniently overlook that the DCF Method would give some crypto IV : such as stETH, which effectively pays a dividend. Anything that rebases or has a “fee switch” (crypto parlance for a dividend) has DCF value.

And some crypto tokens legitimately accrue value like commodities, such as all Layer 1 gas tokens (ETH, SOL, FTM, etc.) which have commodity application to their networks. This is further deconstructed in the essay The Value of a Token Is What It Does.

Hypocrisy.

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Application of These Methods

Fiat currencies:

These have zero DCF or Hammer Method IV. The utility of fiat is predicated on a market consensus they can be used to transact (medium of exchange).

Let’s apply the Hammer Test to fiat: if the market assigned it a zero value, would it be valueless? It would. If something’s utility is dependent on its market price, then it fails the Hammer Test. The Hammer Method heuristic is “if this was priced at zero, would it still be useful?”.

It isn’t edgy to describe currencies as having no IV, but it’s important to emphasize the same people who dismiss crypto on IV grounds have no issue that the currencies they store their wealth in have none of it. The point of this "intrinsic value" breakdown is to expose inconsistencies and hypocrisy.

Gold:

It trades around $2k/ounce due to a centuries-old Lindy effect that believes it’s a store of value (SoV). It’s just a belief, but it’s a very old, deeply ingrained one. However if the market assigned a $0 price to gold, it would have a little bit of Hammer IV as a contact metal for electronics. This is a very autistic point, but gold is a good conductor of electricity and heat and that has utility beyond its market price. This has like zero bearing on why it’s $2k an ounce though; no one owns gold because of its heat conductivity.

I’m also open to giving gold some Hammer IV points as a bartering tool, since even with no market value many would still accept it in exchange for goods. This is a self-referencing Lindy point, in a way. The SoV bartering utility would likely transcend a market price (imagine if all markets said gold was worth $0, guys would still want it). I admit this is a subjective hypothetical, gold is an odd one.

But if we’re being candid, gold has no IV. It doesn’t do anything. It’s valuable because… reasons.

Concluding

Hammer Method Intrinsic Value: even when priced at $0, things that provide utility have Hammer IV (shoes, homes, cars, etc.). Gold has a little Hammer IV. Stocks, currencies, crypto, and financial assets have none. Some crypto that achieves Lindy SoV beliefs (maybe BTC, ETH) may eventually have Hammer IV as a bartering tool the same way gold does (this is very subjective).

DCF Method Intrinsic Value: assets that return cashflows have DCF IV. Bonds have the purest form of it. Stocks with no dividends or book value functionally don't have any. Currencies and gold have none. Some crypto has DCF IV when it pays a dividend or has cashflows generated from network/product use (eg. stETH or SOL).

Who’s the only type-of-guy with no intrinsic value hypocrisy…

When you find someone who consistently applies pure Hammer reasoning to conclude that stocks, gold, crypto, and fiat all lack intrinsic value, you've discovered a rare specimen: the Hammer Maximalist. You should probably befriend him too, since I’m sure he knows how to hunt, forage, farm, and has a hidden bunker somewhere. Good guy to keep around.

When advocating for DeFi and crypto, it’s important to illustrate by way of example and logic how many crypto criticisms also apply to things people already own and accept as valuable. I encourage you to challenge people to be consistent with their stated beliefs.

Crypto detractors essentially dislike new things they don’t fully understand, with it masquerading as this high-minded critique. DeFi disintermediates gatekeepers of financial systems, perhaps that’s why you actually hate it?

If that’s why, good, you should fear it. I look forward to you hating it even more. But don’t manipulate the term “intrinsic value”, just say you don’t like it. Own it.

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There must be other large layer 1 blockchains, I believe natural law demands it. If Ethereum is the “mother of all chains”, it will make DeFi fragile. We should want at least 5-6 other L1s that are ~70% ETH's size. There is precedent for not wanting any single organism to be too dominant, or too large, found in nature and in business.

An essay on when something grows too big for its own good, biological rules, and a hierarchy of natural laws.

When Your Size Is Too Much Size

A paleontologist named Edward Cope observed that species tend to increase in size over time. It’s referred to as Cope’s Rule, however it’s more accurately viewed as a principle since it’s not universally true. It carries important implications for evolutionary patterns.

The Darwinian motivation for Cope’s Rule isn’t straightforward. Some hypothesize that bigger bodies confer survival advantages: improved thermoregulation, access to more food sources, less natural predators, etc.. A logical question then is why isn’t everything the dimensions of Godzilla?

Nature abhors a vacuum and a disequilibrium. There is always too much of a good thing, and there’s a Laffer Curve for heft; beyond a certain threshold you move from increasing robustness and strength to enhancing fragility.

When something gets too large, nature makes it easier to kill. The Tower of Babel is a biblical story that’s scientifically false but Darwinianly true. The parable goes, when you build a structure so large and complex that it tries to reach the heavens, it breaks.

The Drawbacks of Size: The Elephant and the Ant

With more bulk, you need more resources to live; this narrows where you can exist based on food availability. You move more slowly, which restricts your dietary options. Remember, being at the top of the food chain only means you have no predators above you, it doesn’t mean that animals beneath you willingly get eaten. You still have to be mobile enough to hunt.

Size takes a toll on forms of ruggedness and trauma resistance. The heavier an animal, the easier it dies from a fall. You can drop an ant over 15,000x its height (~1,250 feet) and it won’t die. Squirrels can be dropped 150x their height. Humans die around 10x our height. An elephant dies if dropped from just 1x its height (~10 feet).

The bigger you are the harder it is to reproduce, gestation times take longer. Ant eggs hatch within a couple weeks of being laid. Humans take 9 months. Rhinos 17 months. Elephants require nearly 2 years in the womb. Reproduction time is a key component of survival, including your ability to withstand catastrophes that wipe out large parts of the population.

None of us are ever at the top of the food chain; Mother Nature always holds that distinction. The bigger you become, the more susceptible you are to her scorn. You grow less adaptable, slower, more delicate, and restricted. This is a recipe for eventual wipeout.

Credit to Morgan Housel for introducing me to Cope’s Rule and some of the examples I use here. He’s a great frameworks thinker.

The Company Organism

Biological laws are not reserved solely for things with a heartbeat; they’re germane to any organism. An organism is a coordinated system that functions as a single entity. It can sometimes be living, but it doesn't have to be.

Seen this way: a company isn't just a legal construct that makes a product, it’s an organism. Ethereum isn't just a blockchain, it’s an organism.

These natural axioms regarding size and adaptability apply to any organism, whether a living or coordinated mass. Companies can suffer similar fates as the falling elephant when they become too massive to manage. If they don’t die from excess size, they become sclerotic, glacial relics that decay under their own weight.

The Great Financial Crisis: When An Elephant Falls

The Great Financial Crisis (GFC) exposed many financial institutions that had grown too large and complex for continued survival. Banks had become engorged elephants that took 4 years to have a baby (parallel: bureaucratic inefficiency). They had to create byzantine exotic financial products to grow profits (parallel: becoming so large food sources are limited).

The Bob Rubin Trade

The Bob Rubin Trade is a tale from the GFC that illustrates the moral hazard and dysfunction a corporation can experience when leadership loses the ability to understand and manage the thing they’re responsible for. When a structure is too multifaceted and disparate to be competently overseen, you get Citibank in 2007.

Former Treasury Secretary Bob Rubin received over $100 million in compensation from Citi in the decade leading up to its failure. Bob and other Citi executives were responsible for the destruction of the pulsating mass that was Citigroup, yet Bob received $100M for producing $25 billion in losses, a ~90% decline in share price, and a $45 billion intervention from the government. Citi’s demise occurred over about 90 days.

How did Citi manage to lose so much? A lot of exotic debt products. A major one was “liquidity puts”, which allowed investors to sell bonds back to Citi at face value should they become illiquid. When things got illiquid, Citi was eviscerated. How does this occur with such prestigious minds guiding the ship?

Per Rubin: "The answer is very simple, it didn't go on under my nose. At Citi, as in any large company, you have people who are specifically responsible for certain areas - trading and risk, for example - and you have senior management monitoring their work. I am not senior management. I have this side role."

Ahh yes, you get paid $100M for a “side role”! Everyone has a big prestigious position and is responsible for the success when things go well, but have merely a “side role” when shit hits the fan. Many such cases!

What about the liquidity puts? Surely such a profitable product must have been something the board was aware of? Rubin says he had never heard of liquidity puts “until they started harassing Citi last summer.” Neat!

It’s called the Bob Rubin Trade because Bob got to keep every cent of that $100M he was paid, despite his decisions contributing to Citi's demise. Nothing was clawed back. He privatized his profits and socialized his losses. Quite the trade!

The thing is, there’s probably some honesty to Rubin being oblivious. Citigroup was the 14th largest company globally in 2007, had $146B in revenue across a huge array of products, operated in 160 countries, and at around 381,000 employees, with more people to manage than the entire populations of cities the magnitude of Cleveland or New Orleans (both of which have multiple pro sports teams). Citi was enormous.

An organism Citi’s size will begin to struggle under expanding complexity, which leads to mismanagement. If the business is high risk with labyrinthine financiering, you have an elephant standing on the precipice of a 10-foot ledge to contend with.

The complexity and tail risk of the business is relevant in respect to the risk that accompanies its size.

In 2023, Apple had ~164k employees and ~$400B in revenue, which is gargantuan. But there isn’t a “liquidity put” equivalent for Macbooks and iPhones. Apple doesn’t have a product that can destroy it within three months, whereas Citi did.

Apple is smaller in some ways compared to 2007 Citi, bigger in others; but more importantly there's no fat-tail product that if it fails will bankrupt it.

As companies expand:

• Financialized, complex businesses with fat-tail scenarios have wipeout risk, also known as Black Swan scenarios (Citi, Ethereum, LTCM)

• All other businesses have decay risk

Bridgewater, Berkshire, and Google: Slowing Down

Warren Buffett has been candid that Berkshire will likely underperform over short-to-midterm time frames because the capital it must deploy to move the needle is too great to beat the market anymore. Berkshire’s limited to a small investable universe of companies that can support the magnitude of stake it requires. It has less food to eat because it’s so leviathan.

The bigger an investment vehicle gets, the more constrained it becomes. Ray Dalio’s Bridgewater is the biggest hedge fund in the world at $240B, and at that AUM you pretty much are predestined to underperform every index.

And not just a little under performance, Bridgewater has provided investors a 1.5% per year return since Jan 2012. This is basically the same as the inflation rate. Sad!

On Google

The rapid-fire progress of OpenAI and Midjourney has run circles around gargantuan Google. Is Google being left in the dust because it has less intellectual talent? Less resources? Certainly not, in fact Google has tons more resources than its competition and they’re focused on AI as much as anyone.

Google’s failure won’t be catastrophic like Citi’s, but rather a slow bleed to Sears-esque irrelevance. Taken out by the agility of startups.

Google’s failure won’t be from a 90-day obliteration like Citi’s, but rather Kodak-tier degradation, predicated on bureaucratic ossification. It will continue losing ground to the hypermobility and agility of startups. Speed kills, size slows.

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The Blockchain Organism

At this point, I think the takeaway for Ethereum — and any sufficiently complex, large organism — should be apparent.

Ethereum is much closer to Citi complexity and risk than Berkshire or Google. The latter two will become stagnant, mediocre, and slowly fade. Whereas Citibank nearly took down the entire global financial system and died all at once when the rules of biology came knocking on its door.

If Ethereum becomes what we all think it can be, it will be orders of magnitude more critical and complex than Citi. In fact it may already be getting there.

Nodes, block builders, relayers, validators, and huge swathes of capital and flowing atop it will create a network so powerful it will likely be without precedent.

Above a certain dominance, this is a threat to DeFi.

If Ethereum owns a supermajority of DeFi capital and activity, it will make DeFi fragile, because it will make DeFi far too dependent on an elephant. This cannot be programmed or network effects-ed away.

Ethereum will be ruled by biological principles, and if it’s too dominant it will imperil DeFi. Because Ethereum is an organism, and network laws are subordinate to biological ones.

The intellectual firepower in DeFi is some of the best in the world… but we should humble ourselves, we have not out-engineered God. Our organism is not immune from the dictates of biology. We should learn from the hard lessons of the past.

To create the most robust, functional, persistent crypto ecosystem, Ethereum should probably have no more than 30% of total DeFi TVL. We should want 5-6 other competitive L1s with their own validators, security, settlement, etc.. to distribute risk and support our new financial world.

We recognize that if every Ethereum validator runs the same client (eg Geth) it presents an intolerable risk to the network, so much so that ETH clients encourage the use of their competition for the health of the overall network. So too should we promote the adoption of other Layer 1s for DeFi's wellbeing.

Don’t view other chains as competition, view them as brothers developing and securing our new global system. Stronger together.

A Hierarchy of Natural Laws

My thesis on Ethereum and size risk contradicts network power laws that basically say the strength of a network increases as its participants do. Network laws disagree with me, but biological ones do. Network laws are not unstoppable forces that supersede other decrees of nature.

There’s a hierarchy to natural laws, and this is how I view them.

There are laws of physics, laws of biology, and laws of networks.

Respectively, this translates into:

• laws about how the world works (physics)

• laws about how living things in the world work (biology)

• laws about how living things in the world organize themselves (networks)

I believe all natural axioms can fundamentally be placed into one of these three categories. Examples:

• Newton’s 2nd law, thermodynamics, etc. are physics laws.

• Central Dogma, Law of Segregation, etc. are biological laws.

• Metcalfe’s Law, Reed’s Law, are network laws.

Other disciplines fit into these categories. For instance I’d categorize math in “laws about how the world works”.

What makes one group of laws superordinate to another?

Well, what if network laws and biological laws contradict each other like they do in my essay here… which one is the dominant law?

Physics being the highest-order set of rules felt intuitively correct to me. Reflecting on why, I realized it’s because the other two sets of laws report to it for guidance and have no say in how it operates.

Physics influences biology. Biology does not influence physics.

Biology influences networks, networks do not influence biology.

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Thought experiment: imagine if the tenets of physics changed, what would happen? Living things would have their existence dramatically altered, the way they experience reality would be disrupted based upon the changes in physics. Biology follows instructions from physics.

Now imagine if biological laws broke, what would happen to physics? It’d be unaffected. If there was a complete suspension of the rules that govern living things, the premises of thermodynamics or gravity would remain intact. Newton's 3rd Law doesn’t care if humans grow to the scale of skyscrapers.

Now picture if network laws fractured… biology and physics would be indifferent. If a network law was violated, the way your body worked would not be affected. Network rules have no relevance on biology or physics, whereas biology and physics impose their will on networks.

I believe this is how you determine the hierarchy of natural laws and which ones are superordinate: who dictates to who.

Natural laws can be broken into three categories and their hierarchical ranking stems from whether a change in one set would result in others being overturned.

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Apple is an example of bundling computers, taking the fragmented parts of the PC market (OS, hardware, and now chips) and bundling their assembly together in the same process.

With iTunes and the iPod they bundled your collection of CDs into one easy-access mini database in your pocket. In doing so they also unbundled the individual CD, letting you buy one song at a time instead of a whole album.

Opendoor bundles the real estate agent and home seller into one business by buying the house then selling it out of its inventory.

Google’s entire business is one big bundling of services to drive time spent on the platform so they can sell more ads.

Netflix bundles distribution (formerly Blockbuster and movie theaters) and content creation (Hollywood) for movies into one platform.

LLMs are unbundling parts of Google by taking its core business (search and info procurement) and siloing it into standalone services.

Unreal Engine unbundles video games and their distribution by allowing developers to create games individually and then find alternative paths to sell them. Whereas a gaming business like Activision is game creation and distribution bundled in one business.

Additional bundling and unbundling examples:

You could even say Twitter and Instagram unbundled the Facebook post. Facebook came first and offered pictures and text in one post. Then they came and stripped out the constituent parts and made it their core offering: Instagram focused on just pictures, Twitter initially was only text.

Why do I elaborate on the bundle/unbundle pattern and provide these examples:

• Understanding this bundling/unbundling framework is essential for the following analysis. It provides a powerful lens through which to interpret technology businesses and their evolutionary-like patterns.

• It demonstrates bundling as basically a natural law of technology development. Technology organizes behavior in a cyclical way that groups, ungroups, then regroups it again.

• I would describe the previous examples as micro bundlings. I want to zoom out and discuss a macro one in relation to human communication and technology.

Viewing these bundling cycles as a fundamental tenet of technology proliferation, what is modern-day cryptography bundling? How much do we have to zoom out to see it? In contrast with the micro bundlings previously described, crypto is rebundling core features of human interaction that we’ve lost over centuries.

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The Natural State of Communication is Private, Technology Erodes It

Human communication used to be private as its baseline. We used to only talk in-person, which meant no one else could access your chats and they were self-deleting be default. Natural interaction is confidential, ephemeral, and between two parties by nature. Very based actually.

Then technology began to slowly erode this discreet foundation, trading off privacy for scalability and/or persistence.

Examples:

• Smoke signals could send messages farther and to more people (greater scale), but everyone could see them.

• Pen and paper allowed us to transcribe words so they’re no longer self-deleting. But the enhanced permanence meant they could be viewed by unintended parties (increased persistence at the expense of privacy)

• Carrier pigeons allowed distant messaging between two parties (more scale), but at high privacy risk (no security).

• The telegraph is the electronic carrier pigeon: better scalability and distribution, little privacy.

• The telephone facilitated widespread dialogue for billions. But with an oligopoly of providers maintaining the infrastructure, it had little privacy and high censorability.

As more scale for communication is achieved, it has invariably required more centralization at the technology baselayer to facilitate it.

The internet is the crescendo of hyper-scalable communication built on concentrated infrastructure. Web access and use is essentially controlled by a handful of corporations, and as a result privacy is mostly a relic. Tech companies can read your messages and censor you for ToS reasons at will. And all it takes is a frivolous request from the government to spy on anything you say (the NSA sends its regards). But, it’s insanely scalable.

The law of technology and communication so far has been: improved scalability and persistence results in less security and privacy.

Technology unbundles privacy from human interaction and increases censorability in exchange for boosted range and durability.

Scalability and privacy for communication are basically anti-correlated; you gain one at the expense of the other. We’ve achieved peak far-reaching human interaction, but at a complete loss of privacy.

The Great Rebundling of Privacy and Communication

Over hundreds of years, technology has progressively decremented privacy from our words (and increased censorability) to provide enhanced scalability and permanence.

Cryptography represents the rebundling of privacy into communication, while maintaining scalability. Nature is healing.

Cryptography does it for language, and crypto does it for finance.

Despite crypto’s native transparency via its use of blockchains (all transactions onchain are publicly viewable), there are innate features to its use that make it privacy accretive. Namely pseudonymity (you can see transactions but you don’t know who they’re from) and permissionless access (you can’t get kicked off a decentralized blockchain). It's also highly censorship resistant. None of these things can be said for traditional finance.

Cryptography enshrines privacy back into human connections and transactions. It marks the first time that technology has rebundled privacy, security, and uncensorability back into our existence, while maintaining reach and permanence. RETVRN.

Quantum computing will probably unbundle it again though. Sigh.

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I’ve seen a lot of “here’s how to use AI” pieces, I haven’t seen any “here’s when NOT to use AI”. There’s a Laffer Curve for its application, and more is not always more. As its presence in your intellectual and creative work increases, yours necessarily fades.

AI amplifies effort the way a power tool lets you drill through something quicker than by hand. Useful, undeniable, and completely irrelevant to whether you're drilling in the right spot.

The degree to which someone welcomes this correlates with how much they enjoy what they do. If you take little joy in your work and don't view it as an extension of yourself, you're fine with full replacement. Honestly, you probably should be.

The degree to which AI can supplant someone correlates with how unique their output already is. Creativity is the moat. AI just gets you there faster.

Creativity and the Most Likely Next Word

LLMs excel at summarization and research, but they produce quotidian, commoner insights and the most basic writing you’ve ever seen. LLMs generate sentences where the next word is the statistically most likely based on the words preceding it. If you’re working on anything original, you should be stringing together sequences that are *not* probable outputs.

Creative ideas are not conceived by predictable sequences of words and conventional lines of thought. Definitionally so. What does ‘creative’ mean if not unusual?

LLMs are terrible at crafting new insights; the nature of how they're trained precludes it. Designed to produce calculable output, not novel ones. It’s an averaging machine. Feed it the entire written history of the English language and it will produce the exact center of it. That's useful for certain tasks the same way a calculator is useful. Nobody uses a calculator for creativity.

ChatGPT is notoriously a midwit. Not a thinker, but regurgitator. If you use it for anything creative or communicative, you’ll sound like this guy:

Sometimes this guy is all you need. Great analyst, does what you tell him in an organized and forgettable way. Think of GPT as the most diligent 110-IQ analyst around. If you hired one, what tasks would you hand him?

Spreadsheets, research, and other jobs that are fundamentally not creative or self-directed. You go to him for information retrieval, not judgment. Not for new ideas or differentiated analysis.

There are three kinds of nonfiction writing, and currently AI can only do two of them.

The Three Types of Writing

TYPE 1 Writing: “Here’s what happened” (LLM great)

Reporting on an event, summarization, and providing information. Tell me the news, find me data, etc. and regurgitate it. This is the most common and has the most competition, it requires no creativity. No analysis or thinking. Anyone with 100 IQ can do it.

Done by: reporters, junior analysts, news writers, and “here’s what you need to know” types of commentators.

TYPE 2 Writing: “Here’s an opinion about what happened” (LLM good)

This is editorializing about an event or idea, or distillation of information. You didn’t create the idea, event, or research, but you have opinions on it. “Here’s why INSERT is good/bad.” LLMs are obviously politicized, but route around the guardrails and they do fine here.

Junior analysts gather information (Type 1). Senior analysts extrapolate from it (Type 2): analysis, educated assessment, informed opinion. Critical thinking is present, but abstraction and genuine creativity are not.

Done by: pundits, researchers, senior analysts, commentators, etc

TYPE 3 Writing: “Here’s a novel framework to think about things” (LLM bad)

This is first-principles territory. You're generating differentiated frameworks for how to assess or interpret something, and it requires abstraction, intellectual risk, or both. This is where unconventional insights live, and where "most likely next word" cannot follow you.

This writing is the least common because it’s the hardest to create. It’s also the highest risk and highest reward. You’re sticking your neck out with something new. This exposes you to critique, insults, compliments, admiration, and everything in between.

Type 3 writing is difficult because you're being intellectually vulnerable and frequently unorthodox. New ideas disrupt priors, and most people find their consensus assumptions more comforting than they'd admit. No one likes being punched in the axioms. The LLM is very kind to axioms, and real Type 3 writing should leave a bruise.

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Type 3 Kings

Type 3 writing isn't contrarian per se, it's indifferent to dogma and unbothered by social influence. It understands truth on its own terms, not within someone else's frame. It rotates concepts and reveals angles you hadn't seen before. Independently synthesized reexaminations. Rare for a reason.

Synthesizers, like Nassim Taleb and Jordan Peterson, excel at repackaging ancient ideas in modern ways. They're not quite opinion merchants (Type 2) but aren't generating original frameworks (Type 3) either. Language craftsmen who forge existing metals into new shapes, not alchemists working on new elements. Call it Type 2.5.

Some Type 3 thinkers are Rory Sutherland, Venkatesh Rao, and Byrne Hobart. When they speak, you're hearing an independent string of thoughts not beholden to how everyone else processes the same inputs. You can train an LLM to mimic their voice, but you cannot replicate their capacity for abstraction. The parrot can learn the song. It cannot compose.

I enjoy hearing these guys think out loud. I can't imagine them using LLMs for their core writing. For the same reason someone who finds driving cathartic won't use self-driving cars: the process is part of the product. They relish what they do, and the enjoyment is legible in the work.

LLM writing remains easily identifiable, not just from the formulaic style, but the stale thinking beneath it. Every percentage point of LLM in your work dilutes you out of it, replacing the specific with the generic, the personal with the consensus. It regresses you to the mean.

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Amplification

AI is not a panacea for ability. It lubricates what's already there. A tool everyone has is not a competitive advantage.

If everyone stands on a six-inch block, no one is competitively taller. If every athlete uses steroids, steroids become baseline, not edge. The great ones are using the tool too, which means the great ones will still be great, because the human remains the only differentiator. You cannot juice your way to Brady's brain or Curry's jumpshot. LeBron is still taller than you on the block.

When everyone has access to the same resources, natural ability is the only remaining variable. The great become greater as their gifts are enhanced even further. The gap widens. Augmenting your work with AI won't make the output any better, only take you to your destination quicker. Quality and differentiation remain incumbent on the human. The floor rises. The ceiling doesn't change.

If AI amplifies your abilities, they’re unique and creative. If it dilutes them…

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In crypto, showing proof of an activity is commonplace: Proof of Work (PoW), Proof of Stake (PoS), etc..

The US Dollar has displayed Proof of Violence (PoV).

However the USD isn't only predicated on violence, it also provides value; crypto detracts from the latter.

Proof of Violence (PoV)

Unlike PoW or PoS, which must show proof constantly, PoV doesn’t need to prove itself often; in fact violence that needs to frequently demonstrate itself is an indicator of weak abilities. Overwhelming force is rarely challenged or tested. Peace is found through strength; when peace is breached, that typically means strength is lacking.

The PoV the US displayed in WW2 and thereafter with NATO and the petrodollar have allowed it to set up the worldwide financial system as the rails for USD supremacy.

However violence alone isn’t enough to sustain this network. Kinetic force is costly to deploy and not globally scalable. What was introduced with a gun is now maintained through reliability and value.

USD’s PoV is a two-part process: violence to establish it, then value to maintain it.

Said differently: the US used hard power (military violence) to gain the right to make the rules, then it used soft power (financial and economic influence and control) to sustain its empire.

Winning WW2 allowed the US to assert geopolitical and financial dominion via institutions and standards it created. Bretton Woods and such. The US wields tactics like dollar diplomacy, the petrodollar, financial sanctions, SWIFT, and “international” institutions like the World Bank and IMF to exert its will without drawing blood.

The petrodollar is the most prominent example of PoV. The petrodollar was an agreement with the Saudis to only price their oil in dollars; they agreed to this in exchange for US military protection of the kingdom. This turned the USD into a Schelling Point for global commerce and created massive international demand for dollars, as the world’s most critical commodity (oil) could only be procured with dollars.

The petrodollar may be the single most-impactful victory for the proliferation of the US dollar. It’s a manifest display of Proof of Violence: the US will use its violence to protect you, and in exchange you will use its dollars.

Violence to Establish, Value to Maintain

The US-led financial system provides real value to the world. Coercion does not work forever; it’s inferior to aligned incentives and positive reinforcement. Carrots are what build the best human coordination, not sticks.

The US facilitated dollar preeminence with violence, and maintained it with powerful economic network effects and property right laws. Give credit where it's due, the US dollar is certainly not backed by nothing (US military + US economy > gold), and it has been of significant utility for the world.

What do USD network effects look like: there is roughly as much dollar-denominated debt from other countries (foreign nations issuing sovereign debt payable in dollars) as there is US government debt. This means other countries issue USD debt in roughly similar proportion to the US itself. This creates a **massive** demand for the currency.

However, violence was integral to USD ascension. It can’t be overstated how much the US's World War 2 victory allowed it to essentially remake the global order in a way that aligned with its economic interests and preferences, then allowed it to thrive by having a legitimately fantastic economy, the best rule of law, and most-credible government framework securing it all.

Use of USD as a reserve currency (which isn’t an official designation, it just means the market has converged on your currency for trade) reflects this relative stability and affirms the global community mostly agrees. Revealed preference says… we like the dollar.

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From Violence to Value

While the violence capacity of the US remains, the value provided by the dollar is being actively subverted. Enter: crypto.

Claims of the USD’s demise have been ongoing for decades, and I am not going to make this prediction. However I am saying the value provided by the USD is going to be incrementally disrupted and decremented by the global, permissionless offerings of P2P financial networks that is DeFi.

DeFi stands for decentralized finance, it’s the financial rails of crypto, it’s a parallel financial system that exists beyond US jurisdiction. I discuss this in detail here: The Fourth Industrial Revolution and Its Consequences Will Be a Delight for the Human Race.

DeFi creates alternative financial infrastructure that allows international trade, lending, and investment to occur without touching USD-denominated, US-controlled systems. As these networks grow, they enable countries facing US sanctions or unfavorable conditions to conduct commerce outside the American-enabled financial system, gradually degrading the cornerstone of American financial power.

US soft power is going to be increasingly undermined by crypto networks: these are financial transactions that exist beyond US sanction or oversight.

This is a major reason why American regulators and politicians dislike crypto, and rationally so. It’s totally reasonable to dislike an upstart encroaching on your financial territory. As DeFi gains power, the US necessarily loses it. Economics is not a zero-sum game, but power is.

From the state's perspective, DeFi is not neutral, it's an active antagonist, steadily siphoning both economic flows and governance mechanisms from the traditional financial architecture that underpins US hegemony. Don’t sympathize with the state, empathize, you’d hate us too.

On an aside: while crypto is a form of currency competition, it does not spell the end of fiat currencies. So long as a nation demands taxes be paid in its own coin, the fiat currency will persist. Crypto bros would be wise to not be so disillusioned to believe their blockchains mean the state can’t compel you to tithe in a specific asset when it has a gun to your head. Taxes are violently imposed. Crypto doesn’t change this.

This slow erosion of US soft power will eventually bring about the need to refresh the initial PoV (violence). If you’re not providing enough value to keep people using your greatest export (USD) then you’re going to have to violently impose it on them like you did after WW2.

I’m not particularly bullish on the US military’s abilities to do this all over again in an increasingly multi-polar world.

The US and its Decaying Violence Hegemony

While the US maintains overwhelming superiority in traditional warfare, modern conflicts have evolved to neutralize this advantage. Adversaries now engage primarily through proxy wars (Ukraine, Syria) or guerilla tactics (Vietnam, Afghanistan). This is known as 4th-generation warfare: a style of combat that allows conventionally weaker opponents a fighting chance against superpowers.

Modern conflicts have shown the US to be incompetent combating the guerilla, wasting trillions and US lives in its futility. Iraq, Vietnam, Afghanistan, Ukraine, Syria…. what objectives were achieved here? How much did the US squander while accomplishing nothing? These are not exceptions, they are part of a clear trend of ineptitude in 4th-generation domains.

Warfare that’s not between traditional powers is now a hybrid of 4th and 5th-gen warfare: which is to say guerilla-style physical war and non-kinetic, manipulative psychological operations. The US/NATO does not have a global monopoly on this kind of combat, in fact they’ve shown to be increasingly maladroit about it. Men with guns still call the shots, but the way those guns are used has evolved.

I believe these military failures are almost entirely because the US doesn’t fight wars for survival or major gain anymore, like it did in World Wars or battles for territory (eg. the Mexican-American War). Its contemporary fights are for maintenance and furtherance of soft power; the US doesn’t fight for its life, it fights for... regional influence? Who cares? Clearly not the US military.

In wars like Vietnam, Afghanistan, Syria, etc. the US has been pitted against adversaries that are either fighting for their homeland or something they passionately believe in. That’s a dominant motivation to wage war: you’re not fighting for geopolitical influence, you’re fighting to survive.

A dominant motivation sustains your will to fight, and the US almost never has this anymore in relation to its foe. To the US, every war is a power game; for the guerilla, the war is to protect his home or religious beliefs; which of these motivations is less likely to quit? Unless you’re willing to unleash overwhelming military energy, the dominant motivation wins.

The US has shown repeated reluctance to use the degree of violence necessary to win modern conflicts, that’s because it’s not fighting for its life, just its opinions.

Concluding

I’m not foretelling the fall of the US or the dollar. What I am predicting is that DeFi parallel financial systems will continually decrement US soft power by undermining USD network effects. DeFi is the antithesis of Bretton Woods, and it’s growing by the day.

When this transition completes, the US will resemble something like the UK with a 2nd amendment: comfortable, prosperous, yet stripped of its once-unquestioned ability to bend global affairs to its will with a financial decree.

The value the USD must continually provide will be eroded as DeFi proliferates. And the PoV that requires occasional Fourth Turning-style refreshing to reestablish itself is not the US-led monopoly it once was.

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It isn't a question of "if" but "when" for DeFi. The best way to illustrate DeFi’s inevitability and superiority is understanding what it does to financial supply chains. It disintermediates them. It can do this because blockchains provide entirely new forms of “hardness”.

The disintermediation of financial supply chains is integral to crypto itself. Think of bankers as javascript running really, really slowly and expensively. Glacially completing smart contract tasks. Their services are mostly programmable by a smart contract.

All the middle management, compliance team, HR department, the VP of diversity, and other forms of bureaucratic bloat that the old-economy company needs, DeFi does not. Good riddance.

All of these jobs impose a cost on the financial institution. That cost is embedded in the fees the bank/broker/etc pass along to you. You end up paying for every one of them in each transaction. Like KYC, for example.

It’s not all unnecessary bloat, many of these positions were needed to make up a functioning financial system. The point is they’re simply superfluous, overpriced, and inefficient compared to what we’re facilitating in DeFi. Why have these jobs and institutions previously been necessary for a functioning financial system? They must serve a purpose. That purpose is “hardness”.

Hardness and Predictability

Hardness means to make the future predictable in a way that allows you to take action predicated on that predictability. You can't make a financial or business decision without being sure other things will happen. Examples:

Atoms-based hardness: gold

Only a certain amount is mined yearly and the total amount is finite. It can’t be counterfeited. This atoms (physical) hardness is partly why we value it. You can be highly confident a counterfeiter won't flood the market, etc.

Institutional-based hardness: governments and regulations.

They provide laws and enforce rules. This allows you to transact with confidence about the future. Take contract law: you and I sign a contract saying I’ll provide a service and you’ll pay me X for it. You’re now reasonably assured to get the service and I am to get paid. If one of us violates the terms, the courts will enforce it.

This is "hardness" in action.

You look at company earnings and trust the numbers aren’t fraudulent because GAAP/IFRS standards create accounting rules, and the state punishes those that lie about it. Hardness. You have confidence your wire transfer won’t be stolen by the bank because regulation forbids it. Credit where it's due: institutions provide hardness that let us make transactions, deals, and business work. They make the world more predictable and stable.

Government and legal systems provide institutional hardness. They facilitate a financial system that, while imperfect, by and large works. Blockchains and smart contracts are new instantiations of digital, code-based hardness. They'll render many forms of institutional hardness moot. Blockchain regulations and laws are encoded publicly and enforced automatically, objectively, and without any bumbling bureaucratic interpretation or delay. It’s regulated by math and enforced with code.

Blockchains adhere to consensus rules that provide confidence in them as financial substrates. They’re a new hardness for humanity. We've created a pioneering form of societal coordination without violence or the state; it's an incredible human feat. Without the hardness of blockchains and smart contracts we wouldn't be able to create this new financial world. This brilliant "hardness" concept comes from @0xstark and a piece called Atoms, Institutions, and Blockchains. I recommend it, I’ll provide a link at the end.

Financial Supply Chains

It's axiomatic the more entities you remove from a supply chain, the more value is retained by both parties. Every bank and government agency is part of the old financial supply chain, all those HR reps, compliance officers, regulators, you have to pay for them when you use their services. Their costs embedded in the fees you’re charged.

Their hardness used to be critical. Now that they’re being disintermediated, the costs they used to impose will slowly diminish as DeFi scales. This is why DeFi is a vastly superior business model. We can create businesses that rival TradFi ones with a fraction of the operating costs and investment.

• Uniswap employees: 135

• Coinbase: 5,000 (and they recently laid of 1.1k)

“Have you seen how much gas is on Ethereum! It’s more expensive than a broker! Superior economic model??”

Yes, well, our new financial paradigm isn’t perfect yet, is it. DeFi summer happened only 3 years ago. This is all still brand new. Nothing is even close to fully scaled yet.

People have no context when they lament how things aren’t perfect yet for this 3ish-year-old disruptive upheaval of the financial system. We’re creating new P2P networks for commerce and allowing people across the globe to transact freely in a way with no precedent. Come on devs it’s been 3 whole years, why isn’t DeFi perfect yet! Silly. Like a kid who starts whining “are we there yet” 30 minutes into an 8-hour road trip.

This criticism is tedious and acts like things like the internet were this perfect creation soon after it came out. For years it was painfully clunky with no obvious utility, and was mostly used for porn. Remember this prescient quote?

Technologies follow a natural gestation and adoption cycle. We're still in our infancy. You actually are still early! I know it doesn’t feel that way because people don’t view developments in S-curve-style stages, they see them with quarterly-earnings-esque myopia. Don’t be a Paul Krugman.

Criticizing DeFi for having inefficiencies is like critiquing an infant for crying. You shouldn't be surprised an infant cries, in fact you should expect it. Criticizing it shows you don’t understand his stage of development, nor what he will become once fully grown. Yes he can’t do much yet. He’s cumbersome and inefficient. “What kind of person is this? He can’t talk and shits his pants constantly! Throw him out he’s no good.” This is the same energy I hear when I see DeFi criticisms with memecoin infatuation and monkey pictures used as a fallacy of composition to smear our entire industry.

Technology tends to automate workers at the periphery, but blockchains automate the center. Entities formerly required for communication and commerce are no longer necessary with blockchains.

Without that middleman cut, this means costs for both users and onchain businesses will be lower compared to their old-economy counterparts. DeFi will facilitate financial services in places previously not economically viable. A business becomes viable when the capex to get it running and opex to maintain it goes from $40M to $4M. You can create a DeFi app with a handful of devs, try standing up an old-economy company that way. Uniswap vs Coinbase. Who is going to have better margins at scale?

If the ROI is there, investment will be made. DeFi is an unalloyed good for everyone and especially underserved populations, as a previously uneconomic investment now may have a positive NPV. DeFi facilitates commerce more cheaply and with improved hardness than the financial system that came before us.

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Atoms, Institutions, Blockchains

This idea came from one of the most influential essays I’ve ever read: Superhistory, Not Superintelligence, by Venkatesh Rao. This is my breakdown and homage to a disruptive takeaway from that essay. I want to increase the surface area of his brilliant conceptualization. I’ll share the original piece at the end.

AI is better understood as AT: Artificial Time

Something exposed to vast amounts of data, essentially all of recorded human history, resides in superhistory. AI is an organism trained on and drawing from centuries of information.

Data Time > Linear Time

In data years, AI is an ancient being.

"Data aging" is understood through a lens of data exposure, not temporal passage. Example: if I can impart 5 years worth of experience to you, you just got 5 data years older. AI can age centuries in days. It can do this due to its vastly superior data surface area. I, as a human, can only consume information one. slow. singular. human reading at a time. My surface area of info exposure is constrained by my meatness. In a way it's beautiful, the journey is what makes life worth living. Not autistic data maximizing. But AI doesn't have this nostalgic approach.

I can't pool my brain and share it with you. Pre-internet, humans had just 1 human's life worth of information. But AI can pool it. GPUs can take all human documentation and run it through The Machine. AI's data surface area has no limit or bias.

AI has corpora of data spanning the entirety of written history to learn from, retained with near perfect recall. ChatGPT makes the pyramids look like infants. View aging not from a 'getting older' physical, years-based one... but from an informational one. Data aging.

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What is a Centaur

The disrupting takeaway from this is that being older in linear years does not translate at all to data years. Don't view how old you are as a product of sequential time; conceptualize your age as your total exposure to information.

Data Aging > Temporal Aging

A 30 year old augmented by the internet may be 170 years old, in nominal human years.

To illustrate: how old was Magnus Carlsen when he became world chess champion? The answer isn't 22. When Magnus won, it's reported he played "older" in a way (the same was said about AlphaGo when it defeated Lee Sedol at Go). That's because Magnus was raised by ancient trainers.

Magnus grew up learning from machines that effectively solved chess. He was tutored by an ancient organism that taught him the most optimum ways to play. Magnus is AI augmented. When he won the championship he was 22 human years old (linear time), but he was maybe 250 years old in chess terms (data aged).

A modern player trained with AI has a true "player age" that is some function of their biological age and data age. So by virtue of being trained by an ancient teacher, Magnus Carlsen looked like a kid, but in chess years was centuries older than many opponents.

Instead of playing one person at a time and gaining exposure to one human's worth of experience, he learned from a machine that was trained on the sum of all experiences.

This is what a centaur is: A human augmented by artificial time. Data aged beyond his physical years.

How else can you apply this concept? AI is producing Centaurs (machine augmented humans) and in some respects, it alters what it means to age.

Lived human experience, expressed in linear time (years) is rather data poor, meaning most of life is informationally empty. Consider the person who never leaves his hometown...

He goes to school, gets a job, a family, and stays roughly in the same place he grew up, repeating the same routine. He effectively stops being exposed to new experiences and info at... 35? When he's 55, he doesn't have 20 more years of data... He has 20x reinforcement on 1 year of data. On repeat. Forever.

He mostly stopped educating around 25. Learned things about life, family, and work over the next 10ish years. And then after that, he entered his terminal loop. I understand this disregards the love and beauty found within that loop, to live is not just to amass data. But still, I can’t help but having this song run through my head...

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Prosthetic Experience

It was unsettling to realize how informationally hollow human years are in data terms, especially, and to be cognizant of when you’ve entered your terminal loop. A 75 year old that's repeated 85% of the same pattern for 40 years, really isn't much older than 35 in data years. This was a transformative thought for me. It's why I'm sharing this. It's altered how I view someone's capabilities and wisdom, including my own. I now tend to understand people in data years when judging experience and capacity.

Augmenting humans with tools like Google and AI accelerate our data, or experiential, age. You can also view this as "prosthetic experience". Someone enhanced by these tools possesses greater knowledge, and possibly wisdom, than their biological age suggests. Knowledge is data, wisdom is experience.

If you've been using Google the last 20 years, you've accessed several human lifetimes worth of information compared to someone who had to go to the library and laboriously search through stacks of paper to figure out one thing. If you exist in certain esoteric nooks of Twitter, you're probably at least a data centenarian.

Every time you learn something with ChatGPT or Google that your Uncle Milford would have said "meh" and never looked up, you're data aging in hours, maybe days, within seconds. Per how much time I spend online reading, I must be aging 1-3 years per day (ADHD grindset)!

This may speak to why some boomers feel child-like. They were raised in human time, and are weakly digitally augmented. As tech continues to saturate and augment our navigation of the world, younger generations will have increasingly larger information exposure relative to prior ones. They’ll be more centaur-like. Greater data ages. Will they be wiser for it? That remains to be seen.

What's also exciting (scary?) is AI can create its own history. Once AlphaGo was trained how to play Go, it then mostly played itself to keep learning. Taking the concept of superhistory to the next level, creating its own Artificial Time. Human-made data will soon be the minority of data AIs learn with. This is known as “synthetic data”.

Superhistory, Not Superintelligence is much longer and touches on other adjacent topics, however the concept I’ve broken down in here is what deeply impacted me. I hope it did you as well.

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Crypto is a disintermediation of state control of financial infrastructure. Separating money and state. This will not be taken lightly by those with much to lose. By those who control the existing system.

DeFi will be attacked. It’s rational for the state to hate us. It's going to get worse. But our victory is inevitable. I call the way this will play out The Vietnam Thesis.

The US is still the world’s sole superpower. It in large part maintains its hegemony via proxy and financial wars, relying on sanctions, dollar diplomacy, and the like to impose its geopolitical will. It exerts domestic control via the banking system. The US owns the financial rails.

DeFi undermines the US’s ability to assert itself internationally and domestically by incrementally causing it to lose structural control of financial systems. In fact, it's kind of the point of DeFi. This is starting to get noticed. The response is what you'd expect. Don’t sympathize with the adversary, empathize. Imagine you were a hegemonic entity with all the soft and hard power, and an incumbent started decrementing and usurping the soft power you were accustomed to having; you’d hate us too. They are right to fear us. We are right to disintermediate them.

Permissionless, anonymous transactions in a network controlled by no single entity is antithetical to rules the US imposes on financial infra. Everything is permissioned and KYC’d. Your financial existence is a privilege. DeFi subverts it. The US doesn't like it. Naturally.

Important:

The nature of the US-led financial system is entirely in contradistinction to what DeFi facilitates. All of it. Everything we tout DeFi for, the state hates it for the same reasons. This is irreconcilable. Power is a zero sum game. We are taking from it.

Thought experiment: what would a drug cartel do if someone started selling in its territory? Game theory, not legal theory, is your guide here.

Remember, the state:

• creates the laws

• interprets the laws

• enforces the laws

Laws made before computers should not be relied upon to protect us. When the US wants something, it does it. Irrespective of legality. Their is inter-agency disagreement on what constitutes a security, Coinbase has the legal team of God and still got a Wells Notice. Absolutely no one knows anything, and the state will do what’s in its interests. Law books will not protect us. You know who writes those books? The state. The playing field is unfair, it is what it is.

You can look to Guantanamo Bay, MK Ultra, Epstein, JFK, the Iraq War, and the litany of CIA and FBI abuses that are so commonplace we’ve stopped pretending to be outraged. There are factions within the US that are supranational and extrajudicial.

This framing is uncomfortable, but I believe it’s the correct way to understand this conflict and why we're being treated the way we are. Understanding this lets you prepare. Ignoring reality won't let us avoid it. Global empires don’t sustain themselves by asking nicely.

You should expect hostility from an entity who’s losing control as the direct result of another. You must understand someone’s motivation in order to fight them. The US’s actions will make sense this way, because you'll understand the logical motivation it has to stop us. It is rationale for the US to hate DeFi.

Historical Context and Framing

People who mock blockchains as just "distributed databases” unknowingly mock their own understanding of what crypto means for human coordination. Like reducing the internet to “something that sends emails” in the 90s. Understand how disruptive the technology that’s being built here really is.

This is why crypto can’t be understood from the normative lens of “cool innovative technology” in respect to how governments will view it. DeFi isn’t a new SaaS tool or neat way to store video files. DeFi changes financial paradigms of infrastructure, access, and its management.

The common refrain of “The US always figures it out and will get it right” is in my view historically nearsighted, parochial, and doesn’t understand crypto for what it is. For two reasons:

1. The US is a young country. It became the #1 economy around 1890. It became the preeminent superpower around 1945. What history are you referring to, exactly? It led one industrial revolution and San Francisco was an impressive phenomenon… so 78ish years? Context is needed.

There are US senators older than the time the US has been a superpower. It's been the #1 economy for ~1.6 human lifespans. You do not have the historical reference you think you do. The US seems to be right on track for a familiar 250-year cycle of empire declines.

Zoom out.

2. Crypto is the first technology that isn’t accretive to US power. In fact, it's literally designed to detract from it. The technologies that came from the previous industrial revolutions have helped the US gain economic power and benefits...

Crypto actively takes from it. I can't emphasize this enough. It fundamentally redistributes control to individuals and away from the state. Computers, telecommunications, and the internet were innovations that helped expand US influence and economic power. Blockchains directly undermine it.

This is what informs my game theoretic view that low-intensity warfare is the appropriate framework for how we will be perceived and treated. The US is best understood as a cartel when you want to understand how it will deal with DeFi. As an empire defending its hegemony.

Political Arguments and "Facts" Nobody Asked For

When you start understanding statements like "crypto is for crime, makes the outside warmer, and is racist" as political strategizing and not factual statements, they'll start to make much more sense.

US hostility isn’t happening because we need to educate politicians and help them understand what we’re building. They're attacking us because they *do* understand it. Don't take their arguments at face value. Political language doesn't have to be true, it has to be effective.

All of the post-hoc justifications they’ll use to slander DeFi are just that, a client-facing rationale for the real motivations: control and soft power. It’s political messaging to justify political actions.

It's a waste of your time to "fact check" this: nobody is lacking "facts". These are competing narratives advocating why one party should control the financial system over the other. Political statements don't have to be true, they have to be effective.

"Here are some cool facts as to why you should accept losing control of the soft power you fought wars to win!"

How much do you think the state cares about your facts here when it owns all of this infrastructure already? Does an upstart cartel put forth a well-researched argument to the dominant cartel that losing territory is in its "economic interest"?

They know what this stuff is. It is not a fact-based conversation, because you don't convince a hegemon that losing control over domestic and international financial systems is in its interests. Because, quite frankly, it isn't. They are right to fear us, and they will lie to try and stop us.

DeFi Wins, By Not Losing

“The conventional army loses if it does not win. The guerrilla wins if he does not lose.” - Kissinger

On a shorter time frame, my message is bleak. But on a longer timeline, it’s whitepilled and sanguine. I draw inspiration from wars before us, and the success of guerillas who've fought similar battles.

Why will the US fail to stop DeFi? For the same reason it doesn't win wars anymore. The US military is built for big, centralized countries that occupy territory with formal military structure: Russia, China, Germany, etc.

Who does the US lose to? Vietnam. Afghanistan. Guerillas.

Like the military, the SEC is designed to go after the same things. Built to regulate Goldman, Barclays, Deutsche.... big, slow targets that occupy office buildings with compliance departments and formal chains of command. This applies to all regulators.

DeFi is built different. Regulators simply are not designed or able to keep a distributed network under their thumb. No one is.

Why can you still use The Pirate Bay? It’s here because it's nearly impossible to stop P2P networks. They're not capable of going after millions of us across the globe in a cryptographic network. The resources and competence simply are not there.

“I'm not looked in here with you, you’re locked in here with me.”

This is the energy DeFi needs. The onchain rice farmer is the ultimate guerilla. Armed with cryptography, ZK tech, AI, VPNs, well funded, with all the intellectual capital.... and you think you're going to lose?

The crypto conflict will resemble low-intensity guerilla warfare. We do not occupy territory. We do not have a centralized structure of command. We are legion. The US has historically had a very hard time with guerillas, let alone this digitized, global breed of them.

Even if militarily inferior, an indefatigable foe can outlast and win against an adversary that is not fighting for survival. It eventually will give up fighting a fundamentally un-winnable war. Just like it happened in Vietnam, it will happen again here.

We want this more than them. We're more sophisticated, robust, well-funded, and coordinated than the guerillas before us. And we have the dominant motivation: we're fighting for what we believe in. We don’t have to defeat them. We just have to not die. We are going to win.

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Cryptography proves ownership, secures your information, constrains access: not your keys, not your data or coins. Digital scarcity.

AI relies on free, open access to data for its training, allowing it to create a content deluge. Digital abundance.

AI and crypto, digital abundance and digital scarcity, are so poetically at odds I can’t help but view them as competing Darwinian forces. Symbiotically antagonistic, a technological dyad. I see these creations as evolutionary extensions of human cognition. They should be viewed as competing forces in a biological organism. Contrasting each other to create a kind of digital homeostasis. Similar to how the body has mechanisms in it to maintain equilibrium, balancing extremes to keep things steady.

It's too serendipitous that both technologies happen to be at roughly the same gestation cycles too. Both have permeated the public conscious, we understand their power and application, but they’re not scaled yet, imperfect, and not completely ready for prime time. But it’s very clearly not a question of ‘if’ but ‘when’ for them.

Human Made is the New Organic

People will probably one day seek out content uninfluenced by AI in the same way that antique and art collectors do creations from certain eras.

Eventually there will be such an overabundance and saturation of AI-generated content that pure human creations will be seen as novel artifacts, a sort of coveted collectible. A rare genuine expression from a quaint time when expressions were an anthropogenic, thoughtful act, made more valuable by their imperfections and human peculiarities.

The same way people enjoy vinyl albums even though an MP3 is technically superior. How we watch Magnus Carlsen play chess even though the computer is indisputably dominant. We want to hear the artist singing at the concert, not lip-syncing. We’re nostalgic creatures that seek human authenticity and human emotion.

Large language models (LLMs) will eventually exist in a feedback loop of sorts where the majority of data they’re trained on was itself generated by other LLMs. Average people, of which most are, will provide average prompts and get average output. This feels like a cycle destined for predictable, factory-made, rote, bland content. The internet will be positively swimming in unremarkable digital abundance.

AI is Artificial Abundance

The value that we ascribe to many things is the perceived amount of time and effort someone put into making it (known as the Labor Perception Bias). This doesn’t apply to all goods obviously, however for creative output it’s where a lot of the “value” comes from.

Writing in particular is a domain where much of the ascribed value stems from the appreciation that someone dedicated time and effort generating it. You appreciate hand-crafted stitching and hand-drawn masterpieces more than a paint-by-number-style screenprint churned off a factory floor, even if they’re both visually comparable.

AI will dilute this effort signal. It will saturate us in mediocre content that’s mostly similar to the content it’s been trained on. It will make it nearly impossible for humans to perceive the amount of effort or creative energy that went into something.

If everyone has access to the same LLMs and AI tools, then there is no competitive advantage to using them. It becomes something of a baseline where you need it to compete, but your unique abilities are still the things that shine through.

Imagine if it was a requirement that every NBA player used steroids, and they all used the same drugs in the same quantities. What would happen? Everyone’s athletic abilities would increase, but the idiosyncratic talents of players would still be the differentiating factor. If everyone stands on a 6-inch block, then everyone is 6 inches taller; you are not competitively advantaged by it.

You can’t juice your way to Steph Curry’s jumpshot. Take as many steroids as you want, you won’t be able to see the court and pass like Steven Nash. No performance-enhancers will give you Tom Brady’s brain.

This means that unusual, original creators will become more prominent, especially if the creator can prove he made it ‘by hand’. The mediocre creator is in trouble, the exceptional one will be amplified.

Crypto is Artificial Scarcity

There’s a well-known take that “AI is communist, crypto is libertarian”. What it functionally means is these two technologies provide a symbiotic yin-yang to each other via their contrasting strengths. The tech equivalent of “unstoppable force meets immovable object”.

There is no physics rule or law of nature why bitcoin is capped at 21 million. With a tweak of some code we can modify the amount of Ethereum in existence to trillions. You cannot do these things with gold or things that exist in the world of atoms. But in the land of bits you can, so what constrains it?

The artificial scarcity that cryptography brings to the financial world through DeFi can be abstracted onto human creations. Human-made output can be proven as anthropogenic and original, allowing content to be verifiably linked to its creators.

You don't need to detect or combat AI deepfakes (likely an impossible task). You simply need Proof of Provenance. If someone famous or notable says something digitally, signatures must accompany it. If it's authentic, it has a cryptographic signature you can verify. Otherwise your default assumption is it's fraudulent. No Proof of Provenance = do not believe

Or just how we stake ETH to secure Ethereum, a creator could stake a tokenized form of his reputation (an NFT, tokens that come from a known wallet of his, etc.) behind content he produces, claims he makes, or anything that he wants to be identified with.

Like signing an onchain transaction, creators can cryptographically sign their output with a PGP or ECDSA-style signature to confirm its genesis. This is already commonplace on the dark web and DeFi, and it will become standard practice someday to help us navigate the AI downpour.

AI will flood the world with ordinariness. Most people will not be able to differentiate themselves in this sea of mediocrity, because definitionally most people are mediocre. Digital abundance.

Crypto will act as a ship atop these mid waves. Cryptography facilitates proof of origination, permitting us to readily discern and verify content and claims as authentic. A compass to navigate the AI deluge. Digital scarcity.

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