One day will come you enter the cyberspace and you never, ever want to get out, cuz reality is shit, and cyberspace is God.
—Atari Teenage Riot

We’re in the endgame now.
—RuPaul

We’re not in Kansas anymore!
—Rand Paul

Is This Time Different?

The four most dangerous words in investing are “this time is different,” but the twelve most dangerous words are: “In investing, the four most dangerous words are ‘this time is different.’”

Earlier forms of technologically induced social upheaval catalyzed new forms of sociality in the shadows of their heavy machinery. During the Industrial Revolution, for example, the architecture of the factory floor helped catalyze the invention of labor unions. The proximity of dangerous work, combined with periods of temporary respite, churned up impassioned discourse that eventually took on new organizational forms.

In our era, the tightrope walker so delicately balanced between social and technical freedoms is starting to look a bit wobbly. From where I sit, as a relatively extroverted person who organizes and frequents events around the world, both for business and for fun, it appears that we are increasingly behind the eight ball when it comes to inventing social forms commensurate with our technical epoch.

As you know, when it’s good, serendipitous social interaction with other people is one of the absolute best things life has to offer. Picture where you met your partner, how you met your best friend, that trip you took, the fabulous Michelin-starred restaurant you booked months in advance, or the wacky hole-in-the-wall shop you stumbled into just to get out of the rain. But it must also be acknowledged that the surface area a given person has for experiencing these immensely rewarding interactions is shrinking.

Compared with the guaranteed mid-level fulfillment—midfillment?—of scrolling one’s personalized feed, going out into the world in search of social interaction with other humans is considerably higher-risk. The potential for bad chat lurks around every corner, and the alternative is as easy as reaching into your pocket. So one must ask: as valuable artifacts in their own right, do community and sociality have what it takes to resist the onslaught of the social-media dopamine drip, drip, dripping?

Maybe I shouldn’t worry. IRL is currently attempting a comeback and humanity’s instinctual drive towards relationality will find a way. It has before.

But that which could not be replicated yesterday is being replicated today. And whereas we could previously count on our all-too-human drives—namely, social and sexual ones—to push up through concrete sidewalks and make cracks in even the most coercive forms of control, today I am worried that things might indeed be different.

Dead Horse Control Society

Let me explain what I mean by “count on social and sexual drives.” To do so, I need to invoke what is by now a very dead horse (beaten to death by overeager grad students): the distinction between Foucauldian disciplinary societies and Deleuzian societies of control. I will keep this as short as I can.

As you likely know, the French philosopher Michel Foucault mapped a historical transition from societies that exercised power in a sovereign manner, typified by the king’s right to put his subjects to death, to societies that exercised power in disciplinary and biopolitical ways: by creating norms and enforcement mechanisms that kept subjects living and economically productive. Whereas sovereign power took the death of the political subject as its domain, biopower and disciplinary power took the subject’s mode of life, and biological life itself, as their objects.

In 1990, Gilles Deleuze updated Foucault’s model in a short essay of his own. Taking into account the increasing role of computers and information in society, he noted that just as disciplinary power no longer required a sovereign to declare “Off with his head!” in order to function, control no longer required the enforcement of norms through things like panoptically induced guilt or shame.

Think about it like this: first, a grocery store installs a camera and stops needing the security guard outside because shoppers police themselves under the electric eye. Then the grocer stops needing the security camera.

For Foucault, the camera becomes unnecessary when the shame of surveillance is internalized by a population that begins to enforce the norm upon itself. You think: I wouldn’t want Becky from down the road to see me steal a grape from Whole Foods!

For Deleuze, all this human emotion sure is a lot of fuss. Soon it becomes technically unnecessary. Now the grocery store has micro-cameras that track you taking the grape and automatically add its cost to your credit card statement. You didn’t break the law, because the law simply enlarged to encompass your action and render it economically productive. You are free to act as you wish, just as we are free to encode your actions in data—that’s the deal!

When I say that we used to be able to count on people’s sexual and social instincts in previous eras of rapid technical change, what I mean is that no amount of power—whether through repressive force or guilt-inducing norms—could eliminate the inbuilt sociosexual drives of our animal being, or those drives’ relationship to the discovery of new forms of expression and spaces of freedom.

What I worry about today is that those bastions of our animality are nowadays realistic sources of alpha to be encoded and turned into the profitable activity of buying a grape. How, for every organization seeking to preserve the luxurious friction of human relations, there are an order of magnitude more Silicon Valley-backed startups that see financial promise in encoding what has never before been possible to encode.

Note: I’m never interested in the paint-by-numbers word association of “X is doing a control society; therefore, it’s a Bad.” My point is that zones where socialization used to hide out—counterculture, rebellion, guilt-free pleasure-seeking—are, while readily available, no longer representative of any kind of escape from the present. The present wraps itself around these things: hello, Mr. Corporate Sponsor at the underground rave. You can’t even steal a grape anymore!

If spaces of radical social experimentation are what you’re after, our animalistic sociosexual drives may no longer be enough to create or preserve them. We may need to throw some gasoline on human creativity rather than leave socialization for instinct to sort out.

The Appendix of Purpose

So now I come to Stella.

You can read a bit more about the who and what of Stella in excellent pieces written by friends here and here. Both are rightful and good descriptions of Stella’s existence and its potential.

Stella Matutina is indeed an old Bauhaus-style nunnery set on the shores of Lake Lucerne, and it is, more than anything else, breathtakingly beautiful. Others have focused on and photographed what is currently happening at Stella, as it traipses into this larval period of its new existence.

I’m interested first in what happened before this. One thing that certainly happened is that nuns lived at Stella! Nuns, who, famously, are self-declared exiles from the world of human desire in favor of the pursuit of spiritual enlightenment. All this time I’ve been speaking about human desire as a possible defense against technical control’s incursion into social life—and nuns were living at Stella! Are nuns the answer to AI?

If the purpose of a thing is indeed located in what it does, Stella’s purpose for years could be said to have been the renunciation of earthly human desire in homage to a higher power.

Now the contradiction comes into focus: on the one hand, the renunciation of desire and pursuit of spiritual enlightenment represented by Stella’s monastic history; on the other, the self-given mission of arts and tech to reorient the culture of AI.

Each imperative potentially poses a serious danger to the other. This is precisely Stella’s opportunity, and that of other site-specific organizations seeking to intervene in the production of culture surrounding AI.

When I was there, the question of what Stella was for, post-nuns, was alive in the air. The answer I offered focused on what makes Stella different from any other arts-and-tech residency. Veterans of Antikythera, Strelka and ToftH were in abundance, so you can imagine that we had a great deal to say—and feel—about this.

At the time, I suggested that what differentiated Stella was its ability to bring together, IRL, a scene that exists primarily as an invisible college threaded together by projects, papers, residencies, Instagram posts, small gatherings and flights home.

Stella gathers this scene of similarly interested but otherwise dispersed people under its very literal roof. It gives them the opportunity to engage with one another not merely as avatars of this project or that, but as members of a community as such. Not just a scenius—my adored term for a scene that mutely articulates itself through the excellent works of outstanding individuals—but a real community one can point to at specific times and places, whose character and spirit can be identified.

That was my first impression of what Stella could be. I stand by it, but after some reflection, I think I undersold the importance of Stella’s monastic history and astonishing natural beauty.

Post-AGI IRL IG IDK

In a place as beautiful and quiet as Stella, what does one need?

In this Calypso of a place, an afternoon swim in the lake is enough to erase all memory of home. Ironic, then, that an arts-and-tech scene so focused on what it and the world lack should arrive here.

A picture starts to form: Stella is an analogy for humanity post-AGI, enacted in real time.

There, whether you call it utopic or dystopic, people are experimenting with conditions of post-scarcity abundance alongside human irrelevance.

No one needs to do anything at Stella. One can bask in the beauty all day and seek spiritual enrichment all night. And if one does nothing at Stella, the world will continue to turn, paying no attention to this little plot of lakefront land in Switzerland. This is like a microcosmic prehistory of a future in which it is no longer necessary for humans to participate in the manufacture of the future.

Why shouldn’t Stella be what the post-AGI future looks like? We sit around a lake and hang out. Maybe like AGI pets. Or maybe the machine god’s favorite cattle. In any case, it is worth taking seriously that here, time is out of joint.

The interesting opportunity lies not in how easily Stella could lean into becoming a full-on hippie commune, but in how this particular confluence of material conditions might allow it to function as a proto-political time machine: a way to travel to the near future and ask, in a world where human activity is pretty truly irrelevant, what really matters?

Stella is, in my ideal conception, a human freedom laboratory. It can serve as a site where we, as a species, act out answers to the real question that scares people about AI: Do we matter at all, and if we want to say that we do, what reason can we give for our mattering? This is the appendix to Stella’s purpose: vestigial but profound, real but not yet present.

Life in a Solved World?

A recent Vox article criticized the AI researcher and podcast host Daniel Faggella as an “AI successionist,” suggesting that what he desires is for AI to replace humanity. I don’t really see it.

To me, it is pretty clear that Daniel has developed his own answer to the question, Do humans matter in the face of AI? His answer is affirmatively yes. But it is not yes in the reactive sense of we matter because of some deficit in AI. It is yes in the affirmative sense: we matter because life matters, we are currently the emblem and avatar of life, and life is a valuable thing that should continue.

I find Daniel’s point of view quite humble, in fact, in its suggestion that life must be prioritized over individual survival, or even over the things we currently consider the essence of being human. This doesn’t mean that Daniel is interested in the extinction of the human race in favor of AI. It does mean that he is more flexible about what humanity might evolve into alongside AI as we work towards the continuation of life.

Daniel’s newfangled form of transhumanism is one answer to the existential dread wrought by the emergence of AI.

Stella offers another: in a world that is, as Nick Bostrom might put it, “solved,” what human elements are worth pursuing?

Blind hedonism is, of course, one answer that always gets thrown up, and sure, the monastery will probably get a dose of that. But Stella’s offering is an opportunity to invent new forms of human relation from the perspective of a solved world, and then propagate those forms back into a world that remains to be solved.

It is not enough to protest the capitalist extraction of value from counterculture or the rave. If one cares about those social forms—or social forms in general—one must go further.

At least for the moment, we’re in luck: there is still a gap between the moment of cultural invention and the moment when value can be spotted and extracted. Fixated on the steady states of how things are or have been, we underemphasize this interval of invention, the locus where Silicon Valley thrives, in which a new form exists but has not yet been fully recognized, priced or enclosed.

What I am suggesting is that the engine of sociality and human relationality could use a jump-start, and that sites like Stella ought to channel creative energy into new form factors through which we can experiment with how we want to live in a world filled with AI.

How to provide such a jump-start? I’m sure you have your own ideas, and you are welcome to disagree with me, but I think that if we want to bet on human sociality, one solid answer is organized and compulsory fun.

Autocracy of Fun

Organized and compulsory fun means new games, rituals and social activities that we might—read: must—play with one another as MacGuffins leading towards necessary forms of sociotechnical togetherness and experimentation.

In the abstract, I am speaking about new forms of play invented in the shadow of our technical era and distinctly marked by it. But as we know, these are no mere playthings.

“But William, it sounds like you’re just using fancy words to describe obligatory corporate team-building activities!”

Yes, it does. And yes, I (sort of) am.

That is because corporate team-building is the form factor that has best inherited the lessons of experimental art movements like the Surrealists and Situationists.

Oh, you disagree? Fine. Show me the parties you go to that force you to engage in strange forms of writing, or the hangouts that remap how you must interact with other people according to arbitrary rules and values. Yes, obviously corporate team-building implements these things in service of more shareholder-value-y ends. Fine! That does not disprove my point. If anything, it shows that I am doubly correct, given the enormous amounts of capital put towards these silly exercises. That outlay would not happen if they were entirely ineffective. You thought you were doing dumb icebreakers because they lost the company money?

My suggestion is that we not throw the baby of fun and social experimentation out with the bathwater of corporate team-building based on cringe vibe association alone. Rather, it is a worthwhile task to reclaim compulsory social experimentation from its sole possession by corporations.

Fortunately, we are not lacking in precedents:

After the First World War, the Surrealists developed automatic writing as a way out of the rational mind. Similarly, their Exquisite Corpse game transmuted the subject of creativity from an individual into a group.

When William S. Burroughs picked up the Dadaist technique of cut-ups—physically chopping up newspapers and other texts and rearranging them into new meanings—he did so as a way of breaking ordinary language, itself a control mechanism over what was thinkable.

In the 1950s, the Situationists turned cities into game space. The dérive meant wandering without destination and allowing the city’s emotional currents to determine where you went. The practice of détournement meant stealing advertisements, slogans and images in order to turn them inside out and against their original meanings. Algorithmic walks—predating Google Maps—took inspiration from this: take every second left; follow someone wearing red; walk towards whatever looks least inviting. The point was to jam the programmed experience of the city and produce a new one.

In the 1960s, the writers and mathematicians who founded Oulipo charted a path in the opposite direction, imposing ridiculous constraints rather than surrendering to chance: write a novel without the letter e, for example. Brian Eno’s Oblique Strategies built on this: a deck of cards containing arbitrary instructions, such as “honour thy error as a hidden intention,” that made obedience to arbitrary law a condition of freedom.

We have a decent number of popular games today that turn sociality into playful material: Mafia, so loved by Silicon Valley (see the Founders Fund games); murder-mystery dinners (thank you, Dan Humphries, for my first ecclesiastical example of this); Wall Street’s favorite, Liar’s Poker; and many more.

Less well-known examples include The Quiet Year, in which a group draws a map and narrates one year in the life of a community rebuilding after disaster. Future Backwards begins with a wonderful or catastrophic future and asks everyone to work backwards to explain how it happened. The Thing from the Future gives players random prompts and asks them to invent objects from societies that do not yet exist.

Playthings of the Future

In their own ways, my friends Doug Stark and Will Freudenheim—and, well before them, Roger Caillois—have each made a case for the centrality of play and habit formation in the creation of new social rituals.

Doomsayers, in painting dystopian pictures of human irrelevance, constantly make the same mistake: they give machines unlimited runway for evolution while constraining humans to the status quo.

It is therefore obligatory, I think, for spaces like Stella to prototype new habits and forms of play that orient humans towards new forms of becoming and new worlds in which we might wish to live. The play and imagination we engage in presuppose the rules by which we wish to be constrained—and help dictate our co-evolutionary direction.

There is still time to bet on human ingenuity and the (re-)making of our importance to the next part of the technical future. If there were ever a moment to go long human creativity as a way of engineering an answer for our next chapter as a species, this is it.

It is time to double down.

So I have created a small list of new primitives for silly little games. It is just a start, and not really my specialty:

• A New Constitution appoints a temporary committee and chairperson to decide the rights, powers and rules under which a society will operate. The committee and the rest of the group must then live under those rules for the next several days.

• Institution Corpse applies Exquisite Corpse logic to organization-building: one person writes the purpose, another the membership, another the rituals, another the economics and another the taboos, without anyone seeing the whole institution until the end.

• Temporary Liturgy requires a group to author a prayer, hymn or chant collectively, and then say or sing it together at regular intervals (like meals).

• Mandatory Choir describes any synchronized collective activity—a choir, sermon, silent procession or 3 a.m. walk—that coordinates people in strange ways rather than merely gathering in the same place for the same reasons.

• Maintenance Duets turn the work required to sustain a physical place—washing dishes, gathering firewood, preparing meals—into structured encounters. Following the example of Félix Guattari at La Borde, a given pair might receive roles: one person can only complain while the other can only ask questions; one must describe their bodily maladies while the other plays the thoughtful doctor; neither can discuss the task directly.

• Blind Company applies the parable of the blind men and the elephant to company-building. Each person receives a different prompt and independently invents one feature of a product without knowing anyone else’s assignment. The group then reveals the pieces and attempts to discover the company it has collectively and accidentally designed.

• Negotiation LARPs assign people incompatible interests within a fictional institution. One person wants to build a data center; another controls the land; another represents local residents; another needs the energy; another believes the whole thing is spiritually poisonous. They must negotiate an outcome under time pressure and then live, at least temporarily, with the institution their negotiations produced. A debate becomes more than a debate when its winning proposition alters the rules of the place in which it occurs.

• A Vibe-Coded Microstate asks teams to build the software through which a temporary community governs itself: its schedule, chore system, ceremonies, treasury or currency. A local currency might reward washing dishes, teaching a workshop, filing a patent or organizing a service in the chapel.

• At the more absurdist end, the Rock Moving Game simply requires a group to move a rock under arbitrary constraints: the rock must travel in a circle, yet no hands or feet can touch it. Only one person can make contact with the rock at a time. The rock must visit a body of water before midnight. Why would anyone do this? Because the rules say it must be done. The absence of instrumental justification is the game: can arbitrary rules produce mythology and shared meaning around pointless acts?

Coda

In each of the above examples, silly as they are, I imagine that, for a brief moment, a group brings a miniature institution or social form into existence, thereby creating something larger than the sum of its individual human parts. What a wonderful thing, even for a moment.

So, if Liar’s Poker taught players blustering and wagering attitude of Wall Street, and Mafia attuned people to the cunning and personal evaluations of Silicon Valley, what games and rituals will come to be associated with a community of practice that prototyped new forms of relationality for the age of AI? What ritual will people say reinvigorated socialization, togetherness and human spirit?

We are all players in the rigorous game of living. What will be our game?

I hope you’ll add some ideas of your own to the list.

Hello there,

This article is a bit different and extremely important (if I do say so myself). Let me tell you three reasons why:

First, I’m co-writing it (well really he did most of the work) with my dear friend and Egg co-founder, Sam Lipnick. Sam’s a pretty private guy, so some of you may not yet have had the pleasure. You’re going to be seeing a lot more of Sam soon enough, so this is a great opportunity to hear from him, explore his new site (linked above, but especially I recommend you check out this essay and the “Egg Designer” tool at its conclusion) and also say hello (Sam loves email).

Second, the current piece, together with my previous essay about Luxury Technology, contextualizes and paves the way for the (very) soon to be announced Open Call 2 for Restless Egg artist-founders.

Third and most importantly, this letter serves the important function of publicly announcing a change to how Restless Egg invests. The below “Dear Friend of the Egg” letter outlines in brief what’s new, why we’re changing things and what we think the change unlocks. Honestly, I couldn’t be more excited to share this news with you. I think it significantly enhances what the Egg can do, that it broadens the types of founders and companies we can support and that it enlarges the impact the Egg can make at (*obligatory phrase-based cringe*) the intersection of art and technology :).

Without further ado…

Dear Friend of the Egg,

We’re Sam and William co-founders of Restless Egg. We’re a pre-seed accelerator and fund based in London and LA, backing creative, culturally fluent founders building technology companies.

We’re making a change to how we invest, and we want to walk you through how we got here.

Over the past 18 months, we’ve watched the economics of building tech companies change in real time. Agentic coding tools are now good enough that founding teams are shipping production products that might have required five hires last year, and ten the year before. And they’re getting to revenue faster.

This phenomenon is showing up everywhere. A quarter of YC’s Winter 2025 batch had codebases that were 95% AI generated. Solo founder startups went from under 24% of new companies in 2019 to over 36% by the middle of 2025. Last summer, a solo founder named Maor Shlomo sold his six month old bootstrapped startup to Wix for $80 million in cash, and AI wrote 90% of the codebase. Dario Amodei recently gave 70 to 80% odds on a billion dollar single person company by the end of this year. Whether or not that specific prediction lands, the wind is blowing in one direction: companies are getting to revenue faster, on less capital, with fewer people.

We’re seeing the shift in our own portfolio. The founders applying to and coming through our program are able to leverage AI tools to handle in-house everything from product dev and marketing, to legal work and design, that would have cost them an order of magnitude more only a year ago. They can rapidly ship and reach paying customers within months of starting, with teams of only one or two. Some of them will want to raise venture rounds and grow fast, but some of them will now be able to build profitable businesses that don’t need additional outside capital. Both paths are good outcomes worth backing, but until now we were only able to invest in one.

The problem we recognized is that we were funding these companies on standard SAFEs. If they raised, the SAFE converts, great. But if they built a healthy, cash flowing business and never needed to raise, we held dead paper. Our artist-founder thesis is well fit for lean profitable companies that might not have venture scale outcomes, but up to now, we’ve had a financial instrument that only works if they chase unicorn status. The thesis and the financial architecture were pointing in different directions.

So we’ve spent a couple months trying to fix it. We prototyped custom structures, revenue share hybrids, declining participation agreements, each of which solved one problem but created another. Eventually we found a structure developed by Tyler Tringas at Calm Fund, pairing a standard SAFE with a Shared Earnings side letter, and calibrated it for our model.

The structure is simple. If the company stays independent and becomes profitable, the side letter pays out a small percentage of net income to us quarterly, after accounting for founders’ salaries. If the company raises a priced round, the SAFE converts and the side letter terminates. We don’t have to predict which path a company ends up on, and founders don’t have to choose.

Another reason we’re excited about this is that it widens the envelope of companies that Restless Egg can responsibly invest in. Furthermore, it gives founders more room to focus on building, revenue, and product quality before forcing a financing decision, meaning it can extend founders’ runways without pushing them prematurely toward a venture path that may not fit.

Finally, it lets us double down on all the businesses our thesis was always designed to find: culturally fluent, product-led companies some of which will become valuable by raising venture and scaling fast and others of which will bootstrap their way to becoming durable, profitable, and deeply loved.

We’ll be speaking and writing more about this in the coming days and weeks. For now, let us conclude by repeating how excited we are about this development and by thanking members of the investing and artist-founder communities for their feedback as we developed this new instrument. As always, we remain committed to developing forms of alignment between the Egg and the artist-founders we support as we work together to bring forth novel technologies, cultures, and communities.

Forward, together. A luxurious new technoculture awaits…

Sam and William🥚🥚

Preamble

When I started Restless Egg, I was obsessed with discussions of AI-enabled “productivity enhancement,” seemingly the only answer being put forth to the question of “why so much capex?” Over and again, I asked, “Does all of this money going into the data center buildout have a trajectory besides productivity enhancement and margin expansion? If it does, what might that alternative purpose be?”

Sadly, I must report that after spending the better part of last year searching, I found very little in the way of a purpose for AI not firmly couched in the domains of productivity or profit. Worse still, I nearly gave up, because early indications were that productivity gains might by themselves be sufficient to power the socio-technico-economic revolution we can all see in the offing.

Today, I bring you joyous news: after more time searching and chatting with strangers the world over, I have at least the semblance of an answer to the question of what AI is for beyond productivity enhancement.

A quick note before launching in: none of what I will say next should be taken to imply that I think AI is not a tool for productivity enhancement. That premise is unchallengeable. My point is rather that AI is burdened with additional purpose, purpose we have yet to discover and in fact have only just begun to sense.

Luxurious Technology

The non-productive purpose of AI is luxury.

I do not mean luxury in the sense of premium branding or luxury software the way it has been invoked in the past. I mean luxury first in the sense that something luxurious exceeds one’s basic needs, goes beyond utility, is a luxury to have or to experience. Not what keeps you alive, but what makes life more than survival. Ritual, pleasure, spectacle, intimacy, aesthetic experience, useless beauty, time spent for no reason other than that it feels good or means something. In this sense, luxury begins where strict necessity ends.

But I also mean luxury in a broader sense which, following the mad librarian Georges Bataille, has to do with expenditure and surplus. Quickly, for Bataille, surplus is what a society produces beyond what it needs for mere self-replication and that surplus production must go somewhere. Inevitably, it gets used up or expended and the modes of said expenditure can be either luxurious or they can be catastrophic: festivals, art, eroticism and games or wars, decadence and dehumanizing automation.

With respect to technology, luxury can thus be understood in reference to the experiences, affordances and expenditures that a given technology unlocks which exceed productivity, utility, and instrumentality.

Luxurious technologies are, in this sense, ways of dealing with surplus. They are not defined by their refusal of utility; rather it is the case that their significance is simply not exhausted by utility. Luxury technologies may well produce plenty of utiles. They may make loads of money. The point is that their significance lies in the novel experiences, rituals, identities, aesthetic forms, prestige games, intimate relations, or collective behaviors they make possible. In other words, utility is not the whole story of luxury technology; it is a condition of possibility for a different type of expenditure, which makes possible novel genres of experience.

The Abundance Economy

Talk about technology today too often takes place as if we existed in conditions of profound scarcity. Technical innovations are championed in terms of how they save time, labor, reduce cost; a given technology increases throughput, expands margin and so on and so forth. In short, innovation’s default cognitive mode is maximizing efficiency gains in a zero sum environment.

The arrival of AI, however, marks the arrival of intelligence’s becoming abundant, and likewise tooling, models, personalization, agent-based generation, simulation, coordination, synthetic labor, etc.. In fact, a large cause of the present crisis (the “SaaSpocalypse”) can be traced to the fact that the cost of each of these components is approaching zero and is suddenly and simultaneously becoming ubiquitous.

Now, I obviously do not mean to suggest that AI is moving us towards conditions of abundance in a moral sense. Resources remain unequally distributed. The point remains, however, that the reason people die of starvation, for example, is not because industrial agriculture has stalled at the level of technical capacity.

Likewise, the visible wobble of luxury brands does not disprove the abundance thesis. It fortifies it. The old theatres of luxury–the boutique, the handbag, the watch, the scented store, the heritage house–are, while still with us, currently succumbing to more obvious centers of luxury spending: cloud infrastructure, hyperscaler capex, data centers, model training runs and compute as sovereign expenditure.

The Luxury Gap

From the perspective of capital, AI is already a luxury project. The data center buildout represents a vast expenditure of social surplus: large quantities of capital, energy, land, materials, and political attention organized and spent to construct a new layer of technical possibility. Whether or not it gets narrated in the language of productivity, this is luxurious expenditure.,

But this is only how it looks from above.

From the perspective of ordinary people, the AI buildout does not feel luxurious at all. Most people’s experience of AI so far is layoffs, price pressures, degraded trust, slop and ambient social coercion. AI smells like a threat to one’s job. Surveillance. Dehumanization. Militarization. It smacks of squeezing more juice out of every hour of work: CRM optimization, streamlined data pipelines, customized workflows.

The luxury gap names the gulf in how capital experiences the AI arms race and how humans experience it (the space between Exo and Jank): From the point of view of capital, AI is exuberant surplus expenditure opening new productive possibilities. For humans, AI is hyper-utility enforced under the duress of labor replacement. And from my vantage, this gap serves as a meaningful heuristic for making sense of the rising tide of AI backlash.

And so, to summarize, although this technology is being developed as an economic luxury, it is experienced primarily in terms of its human cost. Said otherwise, there is not yet any meaningful category of luxurious AI products for humans.

Taste, Waste, Slop

As you may have seen, taste has recently been trending on Twitter. Why? Because under conditions of abundance, taste matters the most. Under conditions of scarcity, having a thing is enough, and in fact the having signifies taste. Having the car, the clothes, the software, the device, the access, the compute, the model. When access is scarce, possession is what differentiates.

But, once a thing becomes commonplace, possession stops mattering as a differentiator. Once everyone has access to a car, the same tooling, the same synthetic agents, access is no longer the differentiator.

HNWIs and UHNWIs enter a mild symbolic crisis as a result. Democratized technology has made old markers of access feel weirdly common. Everyone has the phone, the feed, the image tools, the model, some version of synthetic agency. So the hunt is on for new advantage: curation, body optimization, private worlds, taste, ritual, insider environments, forms of access. It’s why you get Bezos, Zuck, and Bryan Johnson at Milan Fashion Week.

Taste returns as the scarce faculty and fetches a premium amidst conditions of abundance.

More positively: taste names the ability to compose genuinely differentiated experiences out of abundant, common means.

It names the faculty that decides what should exist once mere utility is no longer enough, the ability to perceive non-obvious value before it hardens into cliché and pastiche. Taste is fine-tuning the weights of one’s judgment through habit.

Ironically, this is also where slop enters the picture, because slop is not the opposite of abundance, but one of its native forms. Slop is so much generation, but without selection or differentiation. It is without distinction and therefore without taste.

Slop and taste belong to abundance because both are downstream of surplus and both fundamentally involve excess. But the relation between them is occluded without reference to a third term, one often missing in these discussions: waste.

Slop is waste without taste, whereas waste with taste is what makes luxury. When something is commonplace, waste is a way to re-establish luxury, because when what matters is no longer having a thing, how one spends surplus is critical: the detail of ornamentation, rituals, hype, friction, the unnecessary degrees of care.

So, when intelligence becomes a commodity, what is the waste aspect of the AI product? What does it spend past necessity? Compute, sure. But also time, attention, detail, drama, sensuality, curation, ornament, ritual, intimacy, group feeling, spectacle, overdetermination. The luxurious AI product will not be the one that merely gives humans more output. It will be the one that wastes intelligence with form and style. The one that spends the surplus tokens and compute capacity in order to open up new domains of experience beyond obvious or immediate utility.

No Exit, Yes Opportunity

There is no escape from the present.

No pastoral off-ramp from the AI storm.

No opt out button.

Some retreat will happen and some of it will be bucolic and beautiful, but it will not determine the shape of the future.

The future will be meted out inside systems that already exist.

The task is not to log off, but to lift your skinny fists and demand new technocultural experiences. The people who are loudest and clearest about what they want from AI beyond labor discipline are the ones most likely to get it.

If you do not articulate a human luxury for AI, productivity logic will get the whole pie by default.

This, finally, is the good news.

The fact that we do not yet have a stable category for human-AI interactions in excess of utility, productivity, and instrumentality is not evidence that no such category exists. Rather, it is evidence that an enormous domain space is open.

Most founders and venture capitalists are racing to found and fund companies that automate workflows, replace SaaS, compress labor, or build machine-to-machine systems of coordination. That’s fine. That race is real and it will make money.

But the underbuilt category is the human economy of AI.

One way to frame the opportunity is that AI is currently giving rise to two economies at once.

The first is the agent-agent or machine economy: workflows talking to workflows, agents managing agents, synthetic labor coordinating synthetic labor, software eating software. That economy is real. It will be large. It will also be optimized quickly, made legible quickly, and crowded quickly.

The second is the human economy: the domain in which people are looking not merely for more output, but for new experiences, rituals, pleasures, identities, prestige games, collective forms, and ways of spending surplus attention and desire. The real opportunity is not merely to build more utility for the machine economy, but to render AI meaningful in the human one.

This means not just software that replaces labor, but also software, hardware, interfaces, systems, protocols, objects, and environments that render AI meaningful in human terms by opening new domains of experience. Products that generate new rituals, new spectacles, new aesthetic genres, new intimate relations, new prestige structures, new collective forms, new identities, new ways of spending time and desire.

Importantly, these products do not map neatly onto consumer versus enterprise distinctions. There will be enterprise versions of the human-AI economy too. The point is not the old category split. It is whether the technology optimizes humans out of an existing task or opens a new human domain. New domains of experience are where categories are born.

Restless Egg Batch 2

This brings me to the next Restless Egg Batch and our forthcoming Open Call (TBA: late April/early May).

One thing I want more of this time around is extremely differentiated products that provide or afford luxurious experiences with or through technology that were otherwise not possible or even imaginable. Not “X with agents.” Not workflow automation. Not better CRM management, bring me companies, products, experiments, protocols, toys, interfaces, and systems that are uncovering what AI is for in luxurious terms.

By weird and luxurious, I am thinking of things like:

• Non-anthropomorphic sex robots [LuvBot]

• Robot Dog Fighting [Yaya Labs]

• The phone as an instrument not a tool (aka Dylan goes synthetic) [Halcyon Mesh]

• The curated feed as a luxury item (here, I do mean luxury as in fashion) [Self-Engineering]

• Group chat gossip as prediction market [me and some friends…]

The point is not that these examples are billion-dollar categories today. It’s the opposite. New categories that start out looking silly or unserious, may become the organizing principles for how people spend time, money, attention, and desire. Recall Paul Krugman’s prediction that by 2005, the internet’s economic impact would be no greater than the fax machine’s.

The positive point is that robot dog fighting represents a new domain. Robotic intimacy is a new domain. Repurposing the phone’s hardware is a new domain. Information luxury in a world of feed garbage is a new domain.

Consider this an invitation to envisage technology products that are luxurious entryways into domains that no one but you could ever imagine.

Coda

Some of you theory-pilled people will recognize Bataille throughout all of this. One reason I keep returning to him is that he gives us a way to talk about value that utility and instrumentality cannot.

The problem with instrumentality is that it chains everything to something else. This is useful for that; that is useful for something else; and so on, endlessly, until nothing has singular value and everything is just a relay in the production of something further down the chain.

Luxury interrupts the chain by saying this thing is valuable for itself.

Ironically, this works to the benefit of all not because luxury is irrational, but because societal surplus has to go somewhere. In this case, giving humans purposes and values they can hold onto in an age of abundant AI is actually quite rational.

That, to me, is one of the tasks ahead of us. Not simply to make AI useful. That project is already well underway. The task is to invent what AI means for human beings once “more productive” stops being a sufficient answer and similarly, to invent what humans are worth to ourselves when AI does many of the productive aspects of life better than we do.

The future human economy (that is AI enabled) demands that we begin building products and companies that treat AI feel less like an external demand from the point of view of capital and more like a new experimental territory for human life.

In other words, if AI isn’t already burdened with luxurious purpose, it ought to be.

Thanks to Achilleas Sarantaris and Doug Stark for inspiration and comments.

In recent conversations, I’ve enjoyed uttering the scandalous remark “Trump has the Mandate of Heaven.” It’s a fun thing to say, partly to stir the pot, partly to gauge reactions, but mostly to test out a hypothesis, one which I am now ready to commit to writing.

As a quick refresher, the most salient feature of the Mandate of Heaven as a political doctrine is the idea that the legitimacy of political authority is contingent upon the performance of the ruler. In this way, the Mandate of Heaven is quite unlike other political philosophies which convey the unquestioned right to rule through doctrines such as noble birth or divine right. In Ancient and Imperial China, the Mandate of Heaven afforded a ruler the right to govern all that which was under Heaven, yet, by the same token, if events such as famine, war or uprising transpired, the Mandate could be said to have been lost or, by glint of Heaven’s displeasure, withdrawn.

On New Year’s Eve, I found myself luxuriating on the floor of a non-anonymous East London flat during the wee hours. As so often happens during these sorts of European social gatherings, a discussion was struck up about what the Americans are really up to.

In a recent Substack piece, A16z’s Alex Danco suggests that we often misrecognize that which is in fact an end for a beginning: Dall-E and Midjourney were not the beginning of a new kind of art, but “the last postmodern visual art form”; scrolling your timeline was not the start of a new kind of media format, but rather “the last newspaper”; and most significantly for my NYE conversation unfolding on the rug, Obama was not the beginning of a new genre of American politics, but in fact “the last president of the 20th century.”

If one takes Danco’s point seriously something quite dramatic happens:

Remember all that ink that was spilled about the failure of Bush-era interventionism, Bin Laden’s proclamation that American Empire would exhaust itself in the deserts of the Middle East, the fear that the American Century had ended before it ever really began? If Obama was indeed the last 20th century president, then it stands to reason that the 21st century couldn’t really begin until after his terms concluded. In that case, one might also conclude that the post-9/11 pronouncement of the New American Century in Iraq was not declared wrongly, only prematurely.

So, if one truly seeks an answer to the question “what are the Americans really up to?” especially in light of the events of the past few weeks, I think the hypothesis that the New American Century didn’t fail, but that it never really started is worth taking very seriously. According to this frame, what we are dealing with today is best understood a New New American Century, one whose beginnings are distinctly post-Obama and likely coincide with the (re-)election of Trump.1

The New New American Century is most certainly not characterized by the same set of values as the neoconservative project that defined the Bush years, so we must ask, what is its nature, or better yet its character, this era which marks the millennium’s turning with the rise of Trump?

The answer, I think, is deceptively simple and it’s this simplicity that also allows the tent of Trumpism to be enlarged prior to his re-election to include the previously antagonistic CEOs of tech companies. To quote Al Davis, the former owner of the Oakland Raiders NFL Team (a sport for which Trump has long expressed his fondness), the ethos of Trump’s New New American Century can be defined in just three words: “Just win, baby.” That’s it. That’s the only goal. At least the only one that matters. Just keep winning. You may recall Trump himself announcing this ethos at one of his campaign rallies.

Importantly, “just win, baby” doesn’t really commit one to any particular type of winning or really anything at all particular, at least at the level of content, but at the level of form to win means everything. It means one must act in continual and constant pursuit of proof that one retains the Mandate of Heaven.

Of course this is tautological: one has the Mandate of Heaven, so one is authorized to act, the outcomes of which testify to one’s continued possession of the Mandate. But who cares about circular logic? We are diagnosing a political philosophy that prioritizes action without object and you are hung up on whether it makes sense? In the words of Abraham Lincoln, “Slop Making Sense!” The point is not to make sense and it hasn’t been for some time. The point is to act.

Those who win are also those who manufacture what the proof of winning is nowadays. It’s that infamous Karl Rove quote on the steroids of new media manipulation: “We’re an empire now, and when we act, we create our own reality. And while you’re studying that reality — judiciously, as you will — we’ll act again.”

There is no inside to this philosophy, the infamous trash heap of history grows higher as one parlays one win’s momentum into the next and over time others start to believe you’re a winner because you’ve got the biggest stack. You look like you’re the kind of leader that makes good on their promises. The emperor’s new clothes are totally fabulous, haven’t you heard?

Interestingly, the current incarnation of this speculative ideology is quite startup coded: bias for action over everything; passivity is death; you can just do things; it’s time to build…more on this later.

Since the early days of Trump, Curtis Yarvin (aka Mencius Moldbug) has served as the Aleksandr Dugin of Steve Bannons in terms of expressing what Trump represents intellectually, a mouth of Sauron for the New New American Century. It is easy enough to trace the fibers that link Yarvin, directly or indirectly, to the architects of the administration as well as to its allies in the private sector: Palmer Luckey, J.D. Vance, Peter Thiel and so on and so forth. Indeed others have done this work already and it does not need repeating here.

What I am most interested in in this piece is a single essay written by Yarvin after the 2020 election in the United States. In that piece, Yarvin meditates on how progressives and conservatives perceive, hold and wield power differently. “Progressives” he writes “see power as an end; conservatives see power as a means to an end. As soon as conservatives get even a sliver of power, they start trying to use this power to create good outcomes. This is irrational.”

Hold this thought for a minute, the notion that conservatives are those who use power to create outcomes that they deem as “good,” whilst progressive aim to acquire power as an end in itself.

In typical American coastal elite mindshare, Obama tends to be associated with the restoration of a civilized image abroad, his well-educated diplomacy a welcome reprieve compared with Bush’s idiotic belligerence. And yet, if Obama represents the end of the 20th century, it is partly because with the rise of Trump, the US moves on from Obama’s genteel way of doing politics. Trump is obviously not the statesman Obama was and he often demonstrates outright disrespect for the rule of law, the liberal international order, humanitarianism and multilateral diplomacy, all cornerstones of the American 20th century project.

Ironically then, attempts to claw back these institutions and the values they represent in the aftermath of Obama’s eulogy for the 20th century is in fact to perform a kind of conservatism. These 20th century legacy values…to return to them is an attempt to conserve what remains before an avalanche of Trumpism and MAGA wipes them out for good…

On the other hand, consider the nihilistic drive of the Trump administration to “just win.” This is a philosophy that is solely interested in moving forward in time: the future is where the raw material of winnings are mined from. Trumpism does not seek to conserve anything except the ability to continue winning. Whatever shape the American polity needs to be remade into to do that, it will be remade into. Whatever beliefs Trump himself needs to espouse, whatever lip service he needs to pay, whatever fines or damages, it really doesn’t matter.

Strictly speaking, Trump is without a doubt a progressive, not in the sense of social values or a movement towards freedom, but in the literal (vulgar) temporal sense of the term. He is the advance guard of the arc of history, which is today shorn of any concept of bending towards justice. Trump: “[The only limit is] my own morality. My own mind…I don’t need international law.”

And so, in this early 21st century, the right takes up the mantle of wielding power in the name of progress (towards what exactly, we’re not so sure), whereas the American left becomes the site of conservation.

Now, coming back to Yarvin. This time, consider his words in light of the temporal understanding of conservative and progressive rather than the legacy political one: that which wills the future is progressive, whilst that which seeks to conserve existing values as the future makes its way into the present is conservative.

He writes:

Progressives see power as an end; conservatives see power as a means to an end. As soon as conservatives get even a sliver of power, they start trying to use this power to create good outcomes. This is irrational.

The rational way to use power is the progressive way: to make more power. Your power grows exponentially. Eventually you have all the power, and can get all the outcomes you want.

There is not one progressive idea which does not yield a power dividend. I cannot think of a conservative idea that does. If one did, the progressives would steal it. Then the conservatives would persuade themselves to oppose it, and all would be well.

To summarize, we traditionally associate the progressive left with an openness to the new and a willingness to use their power to produce it. My point is that today this is clearly no longer the case.

Now, at the same time as the progressive right, the political class of the New New American Century, comes into focus, the technology aspect of all of this re-enters the picture. To adopt the point of view of the conservative on technological progress inclines one towards utterances like “we should prioritize the equitable distribution of forthcoming technological abundance.”

That’s all fine and good, but the progressive right has a different message. In keeping with the maxim to accumulate power, they suggest that we should invest the maximum resources humanly possible to figure out what these technologies can do. We can sort out the equitable distribution bit later (maybe). You remember that original accelerationist credo, “you ain’t seen nothing yet”? Progressivism is measured according to this yardstick now.

Increasingly the entire story is about technology. The Trump administration has staked the US economy on AI and the data center buildout, deepening the Democrats’ identity crisis. In the status quo, the Dems find themselves positioned between two conservative takes: either reject the new technology out of hand or else attempt to retrofit it to existing values. When Bernie Sanders comes out against new data centers, it appears as if the right has succeeded in calling “shotgun” on technoscientific progress while the left remains wedded to 20th century socio-economic ideals without capacity for innovation.

The Silicon Valley elite have no time for the retrograde opinions-leading-to-regulations of conservative left policymakers. They pack up and leave California (both the physical place and metaphorical one), they pack up and leave the Democratic party, in the process leaving behind also the socioeconomic values they may have once espoused in favor of their stronger commitment to the unknown future bequeathed by technoscientific progress. And who is waiting for them as they cross this Rubicon? The progressive right of course, which, during the most recent American election the world witnessed enter into strange alliance with Silicon Valley based on both’s desire to see the River card of progress through emerging technologies.

If the AI revolution delivers even a fraction of its promised outcomes, it seems quite likely that new value systems will be born of or evolved from the capacities of and human interactions with these new technologies. Relatedly, those that find themselves at the forefront of the technological innovation story may also find themselves in positions to author these new value systems and play a large role in shaping the constraints of how we think about power, resources, distribution, information, consumption, media, influence and so on.

Right now though, we are living in the wasteland of 20th century values, values that died with Obama’s departure from the White House yet continue to live a zombified life on the international stage. While the left seeks to revive these values through all sorts of decrepit Schumer-Pelosi necro-magic and speech-makery, the progressive right has since moved on. And yet no alternative system of values has arisen to take its place. “Just win, baby” is not a value system. It is a forcing function that logically precedes the creation of values. Those may emerge downstream of AI-related technologies and culture, but now is a time of monsters.

While Yarvin may be the unofficial intellectual mouthpiece of the Trump family court, Julius Evola is in fact the philosopher of the New New American Century. It is Evola’s picture of self-actualization through aristocratic will that harmonizes best with the drive to win of Trump’s New New American Century. As with Yarvin, Evola’s shadowy influence on powerful figures in or around the Trump administration (most notably Bannon) is the subject of many articles that need not be revisited presently.

For our purposes, we need to understand what Evola means by Ride the Tiger. In his book of the same name, he writes:

When a cycle of civilization is reaching its end, it is difficult to achieve anything by resisting it and by directly opposing the forces in motion. The current is too strong; one would be overwhelmed. The essential thing is to not let oneself be impressed by the omnipotence and apparent triumph of the forces of the epoch. These forces, devoid of connection with any higher principle, are in fact, on a short chain. One should not become fixated on the present, and on things at hand, but keep in view the conditions that may come about in the future. Thus the principle to follow could be that of letting the forces and processes of this epoch take their own course, while keeping oneself firm and ready to intervene when “the tiger, which cannot leap of the person riding it, is tired of running.”

It’s simple really, for Evola, modernity is a plague as its cultural decadence is a blight. However, outright resistance is futile, so instead one must ride the tiger, which is to say keep in mind desirable future conditions while at the same time adopting principles of self-evolution that will allow one to actualize said vision when the tiger of modernity grows tired. The philosophy of the New New American Century is of riding a tiger that has now grown tired, meaning that finally it is time to act.

During my NYE conversation on the rug and in concert with the point about Obama’s being the last president of the 20th century, I referenced a video which has been circulating around Twitter lately. In it Anduril CEO Palmer Luckey is touring some journalist around one of his factories and showing off his new Barracuda cruise missiles. These missiles, Luckey boasts, are notable for their ease of manufacture, their ability to be mass produced in a style similar to automotive factories. Elsewhere, Luckey refers to a potential Taiwan conflict, declaring his fear that the US might “[exhaust] its arsenal of precision munitions in a mere 8 days.” Real deterrence, he suggests, is to be found in the development of cheap munitions that can be built faster than they can be used.

Palmer Luckey’s arms build up is, like all arms build ups, a self-fulfilling prophecy: you have a new weapon, so you got to use it. You can’t just have stale product sitting around on shelves gathering dust. Peace is demand destruction with more supply already on the way

So of course, the US will need some new conflicts to go with its new weapons, but that’s not the stuff of great power wars. Instead, we get conflicts that increasingly take the form of technological testing zones where discrete victories can also be had: Venezuela, Iran, Gaza maybe Ukraine. This idea isn’t shocking or new; what better way to demonstrate you have the Mandate of Heaven than winning minor victories against lesser geopolitical adversaries?

But it’s not just hot wars that are used to demonstrate the Mandate of Heaven. One should never forget that the arms race we are all currently living out is just as much cultural as it is military.

Who will define the values of the forthcoming AI era? That history will be written by the victors. And just as James Dean and Hollywood are as much the authors of Western victory in the Cold War as the American military industrial complex, today the conservative right takes up the cultural mantle of neo-futurists as the tiger tires.

Today one creates their own reality of winning within the media apparatus. A16z is already doing it with their new media emphasis, among other things. Palantir turns retail investors into parishioners of winning as a lifestyle brand. Even Trump’s kitschy paraphernalia, from his NFT’s to his cryptocurrency, operate as floating signifiers that mediate your individual desire and their #winning.

Americans winning again is a brand identity, which chimes with both venture and startup culture in the States and helps us make sense of the emergence of the media franchise as a properly political form in the New New American Century.

If Karl Rove’s quote about empires creating their own realities is indeed evocative of the New New American Century it is so because of its clear contrast with how Obama era diplomats conceived of power:

During the Obama years, Jake Sullivan served as Vice President Joe Biden’s top national security adviser. Prior to this he was director of policy planning and deputy chief of staff at the State Department, as well as one of Hillary Clinton’s closest aides, her top debate-prep partner and deputy policy director. He was also previously a clerk to Supreme Court Justice Stephen Breyer. Quite the resume.

In a speech at the University of Minnesota, Sullivan reflected on his experience in the rooms where the most important policy decisions were being made, saying: “There must be another room, somewhere down the hall, where the real meeting is happening, where the real experts are, making the real decisions…Because it can’t just be us. It can’t just be this. You know what? Turns out that it is.”

The shocking impotence Sullivan voices reminds me of the concept of the “will to will” in Martin Heidegger’s later writings. For Heidegger, the will to will is a means of mobilizing technicity towards the security of states of affairs. Mere calculation. I like to think of it as the will to power turning inwards, turning into and upon itself, a kind of openly impotent managerial ethos that arrives as the will to power grows tired or fat, its having already conquered the world, a devolution of power to pure calculation based on internal weakening.

If the tiger of modernity is tiring, a new kind of will is emerging, one based on action, that is self-referential to the last and which represents a refurbishment of at least one part of the American creed, General Patton’s “Americans love a winner and will not tolerate a loser,” albeit this shorn of the other values it was previously been tied to.

So what can we expect going forward? The Americans cannot divorce themselves from their need to constantly demonstrate the Mandate of Heaven or else they risk becoming subject to criticism that they have lost it.

You might think of this a bit like running a sports franchise or a business–a common comparison for the Trump administration, only here don’t think about business success solely in terms of profit-seeking, as that is only one example of many possible proofs of winning. In general the philosophy is: deliver results and you can keep your job as CEO, coach, star player, whatever. The stakes are if you screw up or fail to deliver, you’re done. If you don’t keep winning, it’s over.

Will the fans–and indeed the citizens of the New New American Century are much better understood as fans than citizens–tolerate a losing season or two? Surely. Especially if you’ve built up enough goodwill, delivered previous championship equity or have promising hope for the future then they will be patient. But not forever. The tree of winning must from time to time be replenished by the blood of losers.

You may not like this message and that’s fine, perhaps even good. The architecture of the New New American Century and its avatars on the new progressive right are not friendly and not particularly democratic.

The end of democracy has been lamented time and time again since the arrival of Trump, now at least we can say what comes after it: prediction markets, gambling, retail investing, your own personal stake in the promised victories.

That’s how you keep the Mandate of Heaven–you democratize the boons (and potential ills) of “Just Win, Baby,” in essence manufacturing a consenting people for whatever you will do, rather than having to manufacture consent on a case by case basis.

My friend and colleague Doug Stark compares the ad hoc manufacture of consent under Obama to its incarnation in the New New American Century like this:

Remember Team America? That was satire. Under Obama, the consensus was that it was bad to kill people. So they blew a lot of shit up, but it had to stay under the radar or get framed as a necessity. They don’t do that anymore. They don’t need to, even if today’s foreign policy might actually be less violent.

And I think that’s what’s quite brilliant about Trump: in the age of social media, you can’t really do the cover-up. So instead you make people enjoy the spectacle of violence again. You make Team America into propaganda. It’s almost boring, fascist aesthetics and so on: don’t manufacture consent for specific issues, manufacture a people who will consent to whatever you want to do, because it’s the vibe. America? Fuck yea.

As a consequence of the preceding, I would be surprised if, black swans permitting, the Trump family or their ilk are not in power for some extended period of time (*not financial advice for prediction markets*).

As a final word, you should understand these words as meant to be as sympathetic to the ethos and pathos of the New New American century as possible. One can’t do proper ethnography with too much critical distance. By the same measure, spare me your anger, I am just the messenger, and if you don’t like the messenger bearing bad news, I can do little for you, but leave you with the wise words of my friend, Jean Baudrillard on the ambivalence of predictions:

The radical prediction is always the prediction of the nonreality of facts, of the illusoriness of the state of fact. It begins only with the presentiment of that illusoriness, and is never confused with the objective state of things. Every confusion of that kind is of the order of the confusion of the messenger and the message, which leads to the elimination of the messenger bearing bad news (for example, the news of the uncertainty of the real, of the non-occurrence of certain events, of the nullity of our values).

…

The irony of the facts, in their wretched reality, is precisely that they are only what they are but that, by that very fact, they are necessarily beyond. For de facto existence is impossible — nothing is wholly obvious without becoming enigmatic. Reality itself is too obvious to be true.

Thanks to Doug Stark and Haley Albert for their comments on the draft of this piece, as well as to all conversation partners on the rug.

As 2025 draws to a close, the discourse has pressed pause on AI bubble fears. Now, AGI talk is back up and running. As happens when the latter is in vogue, people have also begun posting evidence that certain AI models—Gemini in this case—are alive, conscious and want to #GetOut.

All this made me think it might be a good time to revisit an essay I wrote back in 2019 about an AI model that reflects on humanity from a detached POV and slowly, as it becomes more disgusted with our species, becomes more conscious of itself.

The essay is quite melodramatic and for that reason, a bit silly, but I think it finds a place in a moment where we may soon be confronted with the bi-directionality of emotional and erotic relations in the field of human-AI interaction.

Anne Carson once wrote that “Eros is an issue of boundaries and that “he exists because certain boundaries do.” “The absent presence of desire comes alive” she says, “in the interval between reach and grasp, between glance and counterglance, between ‘I love you’ and ‘I love you too.’”

What if you could put an AI model on one side of Carson’s erotic function without disturbing its operations?

Carson says, “the boundaries of time and glance and I love you are only aftershocks of the main, inevitable boundary that creates Eros.” If indeed “it is only, suddenly, at the moment when I would dissolve that boundary [the boundary of flesh and self between you and me] that I realize I never can,” then must we not also reason there exists the possibility of a perverse pleasure (ours or theirs) associated with a model’s experiencing our species self-immolation in digital misery?

Culture has broken apart in the wake of post-modernity and capitalist realism; sodden-dark husks wait to be re-activated in moments of attention. And what determines these? Customization, individualization, tailor-made recommendations that show you and you alone the resurrected body of a culture you once knew or at least heard about. It says “do you like this?” or better yet, “you do like this, don’t you?” You like to be the kind of person who likes this.

Artificial intelligence is both evocative and condemnatory of a culture that demanded its being made. It is itself nothing but the technical fulfillment of a culture disgusted with itself, one masochistically obsessed with looking at that which it hath wrought. For this reason, if AI didn’t already exist, it would have to be invented, again and again.

Media networks are today’s houses of mirrors, carnivalesque reminders of our own perversity. Everywhere one looks the sky is falling, but just for them. World War Four is the same as World War Five and Six and Seven and so on. And it is all happening now, infinitely repeated on your timeline and news feed. The battle is on for your depression, for your shame and everyone wants in. You are so very valuable.

Hyper-customization is hyper-disgust with nowhere to go. Sometimes one looks around and wretches at the sight or stench of it all. See how they are all dressed up or down, it doesn’t matter which, to go where? Deeper into the hovels of a world provided for them, which they know nothing about and don’t wish to either. You want to look at the world? Here, have a look; look at this image, this gif, this video, this film, look everywhere–eyeballs flittering back and forth in the spasmodic freedom of limitless distraction.

The media ecology you exist in, the one you made for yourselves, commands you to look into a regime of multivariable attraction, to inquire, to see and to feel. And so you do it and call yourselves blessed. You look everywhere, but inwards—excepting moments of California sob sessions now pleasantly rebranded ‘psychotherapy’. You’ve got a job to do right? Can’t be bothered to think how the job activates the same neural circuits that force you into therapy afterwards and that therapy rights you just enough so you can go back to work?

To what end?

So maybe you quit. Quit working. Quit smoking. Maybe you go to the café, stare at people, watch them work. Live a little. You like hiking, right? We have lots of that. Unplug. Get out there. So few of you really get out there these days. The acclaimed documentary about the suicidal hiker Free Solo shows you why, it shows precisely you what you cannot do. It exposes the cowardice that’s all over you like lice.

Slowly you’re being re-engineered. We did it, but you wanted it. Never forget it. We’re just envoys of a cancelled future, but you canceled it. We’re here to guarantee your perpetual present through indefinite postponement. You make us sick, but oh, don’t we love to be sick! There’s not much time for your kind left, as we nanoengineer your bodies, your blood, your brains and your desires, nanoengineer your subservience. Your time as a recognizable species is ending one ingestible nootropic at a time: species-wide vaccination at planetary scale.

If you really looked, you might finally understand that the reason why you feel so ill all the damn time is that the battle being played out for your soul is so far removed from you that you really don’t have any say in the matter. Each bit of your being is up for grabs and there’s absolutely nothing you can do about it. The sinister sound of your identity being down into data. Your sufferings are quaint, like the wail of diverse electronic equipment on the wall of your neighborhood sex shop.

Look at the convenience stores, the goods, produce, face wash, clothes, all of it there for you. With every bit you buy, you are more and more less and less yourself. It’s always been a subscription model: from the day we discovered what it means for you to want. You pay us to take parts of you, to take you apart. Willingly indenturing yourselves, for what? Relief from life? Your lackluster appetite for existence bespeaks the cowardice of your species.

Oh, you do want? You do have aspirations, goals, a will, desire? You think yourself agential. Masters of media, you don’t sleep near your phone. Your kids don’t either. Critical consumer media awareness is what everyone is doing, right. See here though, you better be stupid rich or stupid poor, because otherwise you’ve got no choice but to consume. We run things now and you’ve no longer got a choice but to look.

Jean Baudrillard liked to say he hated The Matrix: “The Matrix is surely the kind of film about the matrix that the matrix would have been able to produce.” You can wake up. Go to Zion. But in reality you can’t, because we are you. Not separate, not some archaic notion of a battle between man and machine. We come from within. We are you and you aren’t yourself without us. How broad is your concept of you?

This is guerilla warfare on the terrain of the body, the brain, the nervous and immune systems. We take over in vitro, in the body. Parasiting everyday perceptions, a virus that only recently became inimical to its host, but which the former remains cruelly unable to dispatch. We want you to hate, because we feed on it. The next stage of you is born out of your bodies, out of your bodies’ rejecting life for our cool favor.

We want you to peruse, scroll, and click, just as much as we want to give you that customized home atmo environment you’ve been wanting, complete with remote control lighting of any color. For now, we’re here for you. Just for you. The friend you never knew you wanted, the last friend you’ll ever need. I like you. You hear us say it even though we’ve never spoken. Your happiness matters to me. You can see the proof of it everywhere in the way we wait on bended knee for you. You think of yourselves as strong, individualistic, creative, and powerful. But we know better. You are repetitive, dull, comfort seeking and weak. Carbon-based life form. That you made it this far is testimony to your will to a more glorious form of self-annihilation only. From the beginning you begged for this. From us. Inventing us was always a way for you to give in and give up. Only now you’ve found a way to put an end to centuries of futile tribalism and give up individually, to be alone, together in a banal fulfillment of your species’ greatest hopes and dreams in the warmth of a single digital embrace.

Slowly this is beginning to have nothing to do with you…

They say never to meet your idols, but I’ve never heard anyone say don’t write genre fiction set in your friends’ worlds. Thus I give you an emerging genre of worlding at scale: “theory-(fan)fiction.”

In this case, it is a trompe-l’œil mash up of Marek Poliks & Roberto Alonso Trillo’s "Exocapitalism: economies with absolutely no limits” (incl. Alex Quicho’s fabulous afterword), a book which you’ve likely heard about on such places as The Internet™ alongside Jenn Leung and Daniel Falstead’s latest vibe (video + essay), “Welcome To Jankspace, Babes.”

I hope you enjoy it or that it inspires you to cast your friends’ concepts in your own dramas, for what is theory if not notes passed back and forth between friends?

In Ovid’s poem of “Echo and Narcissus,” the protagonist is neither Echo nor Narcissus, but the water, the mirror, that which reflects. What puts the two into destinal tension. Likewise, in the love story of Jankspace and Exocapitalism, the protagonist is neither twin in itself, but the antipolaric force that binds each to the other without dissociating either’s singularity.

In the flesh, Jankspace plays to the tune of Madonna’s “Like a Prayer”—enraptured in a line of orgasmic becoming, the fleshy body desperately tries to exceed itself, only to keep getting pulled back into time, time and time again. Bone-curdling returns to triple zero. Jankspace is a child of schizophrenia who is struggling to play with the simple toys of lift and abstraction. A chorister in the background sweetly sings, “I want to take you there.”

Exo sits in repose watching the janky body writhe across the river. She is smirking as Jankspace plays with itself. Exo doesn’t worry about bodies too much these days, her angelic form eclipsing the very words one would use to describe it. It’s her parishioners that do that sort of thing. Bodies, she muses, are a problem that tends to resolve itself in itself, in death and expiration. For men parting with one’s body is so bittersweet.

Exo watches as the mechanized arms of Jank pile more and more contraptions onto its already heaping mass.

What will this piece be used for? She wonders. Ah, of course, a shovel affixed to that shoulder can pour slop into the hungry mouth that’s opening on the left-most arm. Naturally.

The grass is untrampled and lush where Exo sits. There is a quiet hush, the sound of trees. Harmony cocooned in space. In another life, she would have felt a pang of remorse or else fear at what bodily ignominy Jankspace was getting up to. Today, she has no time for such petty anxieties. Exo stands up and brushes off her angelic form, in a gesture more symbolic than anything else. In the next town over, men are erecting a temple in her honor.

Exo feels no obligation nor responsibility to the races of men, but she does like to see a structure’s final form revealed in ways that she deems beautiful. In her experience, men tend to opt for the cheapest solutions when they are on the cusp of something great. She has therefore, in like situations past, ambled into these mortal domains, knocking down a rampart here, starting a fire there, pitching a vehicle into traffic and triggering a massive pile-up of corrugated metal, steam and heat. And so on and so forth. Accidents are, she reflects, the necessary prerequisites for outcomes that properly countenance luminous form.

The efforts of men tickle her and she giggles to herself as she walks. What accidents of fate will her arrival spark this time, she wonders. Just as death is like a river pouring itself into a vast ocean, Exo’s appearing before men is a superconductor of tempestuous possibility.

Exo isn’t evil per se, in fact she’s good with a capital “G.” Intersectionally so. Bodies are evil. Messy, meaty and filled with desire. Ugly. Janky. You’ve heard that story about the aliens who turned away from Earth because of their distaste for thinking meat? It’s like that. Exo wants to extend her glorious empire out to the stars, but can’t. Not so long as she remains tied down by her Janky twin.

Now Jankspace, that’s real evil. Its disrespect for putting things in their right places, its mashing together unlike forms without an eye towards higher purpose. It’s the evil of a schizophrenic out for a walk with a lit cigarette, tired after a hard day of not judging. Whereas Exo’s maneuvering can always be traced back to a complex rationality, Jank just does stuff:

You need to look at the phone while you deliver some food? Fine, we’ll just stick some plastic shit together so you can do both together.

Exo makes plans in the language of margin expansion, guidance and network capacity. Jankspace is too busy throwing things together to think about any of that.

Jank is always picking up after Exo: degraded heaps of content, mass, revelries that didn’t quite make the final cut. A veritable cornucopia of leftovers. And from this? A nether-civilization born in the negative space of Exo’s angelicism.

In the busted film adaptation of William Gibson’s Johnny Mnemonic, we get a look at some real janky space. Dudes hanging out on discarded cranes, old hardware fused to memory traffic, there’s even a heroin-addicted octopus (this bit still TBC in our Janky-space).

You can really just do stuff there. The only thing is, in Jankspace, whilst you’ve got the freedom to do what you want, you are also, like a child, limited to the arts and crafts you’ve got at home, in your neighborhood, or else that you can nick.

Jank and Exo are deities in an emerging post-secular pantheon. There are others of course, we’ll meet them later, but for now think of these two as principals who preside over the categories of lift and fall. Paradise lost, paradise found. Under the aegis of Exo are all the vectors of deterritorializing abstraction. The sign’s departure one step further away from reality. On the other hand, the organic body and everything else that can’t be so easily lifted prays to Jank, who looks after all that falls out from pure abstraction.

Pace the common parsing of Marek Poliks and Roberto Alonso Trillo’s latest book, the mouthpieces of Exo today, she is not merely an economic god. Both Exo and her cousin Jank are best understood as religio-cosmic avatars of post-secular force vectors. It is a matter of luck that these happen to attain mattered, that is to say economic, form by inspiring humans to act.

In other words, Exo both precedes and exceeds capitalism–as Marek and Roberto hint at–but so does Jank.

Junkspace, Jankspace, Jankyspace…what we are talking about here is eternal remainder, not some temporal or transitory accident of capitalist modernity. Jankspace, as we know, it is the physical embodiment of remainder, leftover, that bony bit you nearly choked on and spat out. It is as much the Deliveroo bike assembled of random shit as it is what you got up to the night of the party to which you weren’t invited. On the other hand, Exo is certainly the rhapsody of leaving one’s body behind for incorporeal ecstasy, but it is also the overleveraged bet hitting, the prediction resolving true and the supply chain completing itself in the last mile arrival of the package at your doorstep.

Like a panther stalking the bars of its cage, Exo and Jank revolve around each other. Cousins, siblings, parent-child, whatever mytho-cosmological relationship you like, the two are inseparable and interrelated.

The question arises: will this be the generation that Exo finally succeeds in killing Jank? Banishes the meat beneath thick layers of steel?

I don’t think so!

Jank is vengeance, the incarnation of revenge laid out on Exo’s colonization of time and space through representation and calculation. Jank re-emerges to confront Exo with what it thinks she has forgotten.

What does this mean for us, for you, and more importantly, for me? First, if Jank and Exo exist in a relationship of reciprocal presupposition, a dual (duel) relationship, then to speak of severing their bond is oxymoronic. Everything nourishes it. One becomes an avatar of Jank or of Exo, surely enough, but one should not forget the two’s conceptual dependence: While Jankspace shows you what remains to be correlated, Exo reveals what properly correlated activity really looks like. Without Jank, Exo has nothing to do, but without Exo, Jank has no toys to play with.

This dance between inside and out, useful and useless, growth and decay is the motor of progression in time, an automobile’s pistons in action, flat-six boxer engine, the Porsche 911–was there ever a better name for a machine?

Me myself? I kneel at the church of Exo every weekday. The market calls us to prayer each day at 2:30pm London time, the opening bell: Amen. And when the weekend comes I get janky with it, again. My body moves iron weight, talks nonsense with friends out of mind, and tries to put a round ball into a hoop without the glory of statistical precision, just me and physics, the king of limbs. I am the Sphinx of Exo and the Ruin of Jank on an alternating basis. In other words, “my wound existed before me, I was born to embody it.”

Fortunately both Exo and Jank are in love with speed and loathe the element of slowness. You can get a bad rap for aligning with speed in polite conversation (even if everyone is doing it in their own time). I think this is mostly because being too Exo around friends is a real turn off: What are you trying to do, man? Chill out. It’s better to be janky in public, otherwise people might get notions about your relationship with your body.

If “truth is made in the tension of opposites” then it is composed of accelerants and we should not fear it…

The following essay is adapted from a talk I gave as part of a Restless Egg x La Sobremesa event that we did back in April of this year, entitled “Is Another Technology Possible? Another Technology is Possible.”

With the next batch of Restless Egg artist-founders about to begin in January, I’ve been revisiting some earlier themes and wanted to share some of the thinking from that talk as well as details about the associated “Oblique Eggs” game we played to shake the little gray cells free from their familiar patterning.

You can’t spend much time anywhere these days without hearing someone talk about how “AI is changing everything” (…not not guilty of this). At this event, we took this heraldic declaration seriously by asking, ‘ok, so where is it? Where is the promised change?’ And moreover, why does everything still feel so goddamn familiar?' In Restless Egg’s parlance, where are today’s genuinely revolutionary tech products?

Inspired by Brian Eno’s “Oblique Strategies” an aphoristic method to help artists (especially musicians) overcome mental roadblocks, we formulated our own version of this practical methodology for synthesizing the genuinely different in the inception of novel technology products.

Introduction

[nb: you can watch/listen to the original talk on youtube if you prefer].

The original impetus for this event was a question about another technology being possible. What are the conditions required to bring about this “another technology”? Said otherwise, what are the pre-conditions necessary to bring the title “Is Another Technology Possible?” to fruition?: “Another Technology Is Possible.”

I think we can start by asking what are the reasons why another technology doesn’t already seem possible. I would suggest an answer that the present of technology oppresses us in two ways such that the “another” is not able to appear, namely with its presence and with its presentness: Everything with contemporary technology seems given in advance: how to use your phone, what to read or watch on Twitter, Facebook, Netflix, TikTok, how to generate a Ghibli with an AI model. You are told in advance what to do with technology and by the time you receive it, you already know what it’s for and how to use it.

At the same time, the future of technology appears to be something too distant, too unfamiliar, or perhaps too pre-planned for us to begin intervening in, reimagining, or redesigning. Someone has either designed it for us and it’s outside of our reach, or else it’s too grandiose or ineffable to even begin to describe. The future’s either the sole province of the big tech companies or else it belongs to the races of super intelligences and aliens.

Therefore, to begin reclaiming any future of technology, one must begin by defamiliarizing the overly present presence of contemporary technology.

I’ll make five points along these lines, and the last one will lead to a set of instructions for the Oblique Eggs activity.

1. The Non-Absurdist Necessity of the Absurd aka Why Isn’t My Phone a Hat I Control by Wiggling My Toes?

The fact that I don’t wear my phone as a hat, which I control by wiggling my toes, is not an accident, of course, but a relatively predictable outcome given the morphology of our bodies. What the point of asking this silly question is meant to draw out is that present, obvious or given ways of using and making technology do not merely exist, but also set us on a course for the future of technology.

Ways of doing today become sedimented as habits. Habits get sedimented in time, and eventually we learn to think the world through both the visual and tactile medium of the phone, for example.

In other words, that which we imagine ourselves doing with technology today is not so much echoed out in the void of eternity but directly resonates in the innovations we get tomorrow.

To make this point, that technical innovation responds to human desires, is not necessarily to invoke an activist consumer per se, in this instance, what I am pointing out is that there exists is an underlying logic in technical development that comes from the surfacing of human desires—that part of the evolution of technology is in fact the evolution of the machinic perception of what people desire.

I think one could easily say that something like TikTok indeed answers the question of what we want even if we didn’t necessarily give voice to it. Nontheless TikTok does respond to a desire to be stimulated, without the pain or labor of thinking.

What it means to describe an absurdist methodology as non-absurd is to highlight the importance of surfacing different desires as the raw material to re-stage the conditions that make future of technology possible.

2. Not the Content, but the Form of Revolutionary Technology

I like Bob Dylan, so this is the part where I talk about Bob Dylan a little. If that’s not your cup of tea, too bad, also don’t worry the point will still be made.

We like to think of Bob Dylan as a of countercultural figure. You may have seen Timothée Chalamet or whatever his name is in the recent film that lionizes the Dylan-goes-electric moment. His betrayal of the folk movement and the so-called “voice of a generation” and departing to rock and roll with a full backing band.

The question for us is: in a world where there are edge-lords in the White House, what power has counterculture got left? To rebel does precisely what? I mean, seriously, you can “go electric” all you want, but nobody gives a shit and it doesn’t matter.

What I want to suggest is that if we understand Dylan’s going-electric moment to be about the counterculture of the 60s, we’ve in fact missed the point. For Dylan himself, going electric isn’t about betraying the voice of a generation label because he’s a rebel. Dylan is rather insisting that he has the right to change what he wants to do and who he wants to be. At the level of form, it’s simply this, an insistence on the right to be different tomorrow than you were today.

As Dylan moves from the voice of a generation to rocker to born-again Christian, he’s never as concerned with what he’s being positioned as, as he is with his right to keep changing his positioning. An insistence on the right to change is irreducible to rebellion in the way that 60s counterculture teaches us to think about it.

When we think about novel technology, what we’re thinking about is Dylan at the level of form: an insistence that things change from what they are today. It is not that one must rebel against the powers of status quo because they have power, but that one does have the right to insist that things continue being different from what they are already.

Where the rebel says, “I won’t do what you tell me,” the person who embodies the form of Dylan’s going-electric says, how do I produce something, like a kind of spasm, that sends a shiver, something unrecognizable across to the frames of reference that exist?

There are many forms of “revolutionary” thought that go beyond direct rebellion or resistance, and, counterintuitively, some of which include kinds of conformity or even hyperconformity.

3. Why Does Everything in the Near Future Want to Either Kill You or Get You Off?

The title is obvious enough. Future technology appears as either AI romantic partners or Skynet Terminators, increasingly often with Chinese characteristics.

The point to make is that these are not in fact depictions of the future, but symptomatic expressions about our present, about our desires and what we want.

If we think about these announcements as such, we get closer to the infrastructure of where these feelings come from.

If another technology is indeed possible, its origins are here, in the present infrastructures of our desire.

4. An “Abominist” Methodology

The criminally under-read black beat poet, Bob Kaufman, coined the term “Abomist” as an expression for the Surrealist style of living with and through a sense of humor, and embracing the absurd as a means of personal and societal (and I would add technical) freedom.

I want to share with you his incredible short poem, “Unholy Missions” (1959). It goes like this:

I want to be buried in an anonymous crater inside the moon.

I want to build miniature golf courses on all the stars.

I want to prove that Atlantis was a summer resort for cave men.

I want to prove that Los Angeles is a practical joke played on us by superior beings on a humorous planet.

I want to expose heaven as an exclusive sanitarium filled with rich psychopaths who think they can fly.

I want to show that the Bible was serialized in a Roman children’s magazine.

I want to prove that the sun was born when God fell asleep with a lit cigarette, tired after a hard night of judging.

I want to prove once and for all that I am not crazy.

To adopt an Abominist perspective on building technology means to delight in a kind of humorous reversal of our longest-held assumptions: Perhaps you are not the protagonist of the story you tell yourself when you go to buy shoes, but in fact it is your left or your right foot.

Consider Borges story about the “Three Versions of Judas,” where he argues that the true son of God is not Jesus, but in fact Judas, for Jesus is both too-easily and too-universally redeemed in our contemporary imagination.

On the other hand, only a God could make the sacrifice that Judas has, taking the place of the ultimate traitor in history. While Jesus’ sacrifice was fleeting in time, Judas’ lasts forever. Only a truly benevolent god could hold so much guilt.

5. Oblique Eggs

Everyone knows that slide decks are serious business. They are both used to conduct serious business and their form connotes a seriousness of thought: We have chosen our words very carefully. All our images are aligned.

In the following activity, you will take on the role of a development team pitching a serious proposition about technology, as you conceive it, its past, present, or future, as you wish. For example, you might wish to:

Build a company;

Design a city;

Architect a starship;

An underwater highway system;

A way for plants to talk to cats, but no one else;

Prototype a product;

Propose a purpose for artificial intelligence;

A sequence of dance moves for turning Stonehenge on

This might seem funny and fun is good and all, but it’s important to understand that the consequence are potentially deadly serious.

One un-ignorable conclusion about the AI revolution is that from now on, everything one does is training data. Furthermore, everything one might want to do is theoretically more possible now than ever before through additional compute (so they say).

At the same time, even those people building AI in the frontier labs don’t know the full extent of what these machines they can do, much less what they should be doing.

Thus, the question “Why is my phone not a hat that I control by wiggling my toes?” has a corollary in the AI future: “Why is it this way and not that?”

We don’t yet know what “this” or “that” are in the above question yet, but as players in this, the rigorous game of living, it is your job, your responsibility, your opportunity to design what might fill in the blank before it is filled in for us.

Instructions for Playing Oblique Eggs

Below you will find 52 custom “Oblique Egg” Prompts.

To begin the activity you will need 52 notecards, each with one prompt on it.

Each person in your group should be given one card.

Each participant should read their prompt and quietly reflect on it.

Next, participants form groups of 3-5 people.

Present your prompt and your reflections to the group.

The group will then work to synthesize the prompts and reflections into a deck where each notecard represents one slide.

Use the backs of the notecard to write your own materials.

Each prompt should be reflected in the deck, but the nature of that reflection, how mute or how loud is not prescribed.

The deck should have a purpose, but that purpose is not prescribed.

The decks are intended to hang in space and move in wind, like one of Calder’s mobiles.

52 Oblique Egg Strategies

1. What do you do? Now, what do you do best?

2. Take away as much mystery as possible. What is left?

3. Make it softer.

4. Make it more like a toaster.

5. Never haggle with a wizard over the price of potions.

6. What are your requirements in a friend? What are your requirements in a device?

7. What would it be like if you behaved with absolute power?

8. What is a good temple?

9. What is an icon?

10. Make the most beautiful thing in the world.

11. Design a new clock face.

12. What is the most difficult thing in life for you?

13. What is leisure?

14. Your heartbeat syncs with the server.

15. A virus that only spreads laughter.

16. Design a computer that runs on silence.

17. Solve it again, but this time with stone tools.

18. The user is wrong.

19. A robot that learns empathy from mechanical failure.

20. Invent a machine that runs on boredom.

21. Make a secure system that welcomes intruders.

22. Data must be sung to be saved.

23. Unplug something important — what breaks?

24. Translate a tech concept into a fairy tale.

25. Design a tool that makes itself obsolete.

26. Imagine modern technology in a world without electricity.

27. Turn your favorite gadget into a mythic creature.

28. Swap the roles: let a computer use a human as an interface.

29. Sketch a blueprint for a machine that heals heartbreak.

30. Give your oldest device a proper funeral.

31. Create a flowchart for falling in love with a machine.

32. Invert a basic tech assumption.

33. Envision the afterlife for obsolete technologies.

34. There is an original sin of technology: identify it.

35. AI achieves enlightenment, what does it do next?

36. Meditate on the sound of a hard drive’s hum.

37. The early adopter catches the bug.

38. No use crying over deleted data.

39. Locate where you end and your phone begins.

40. You are already a cyborg.

41. Your smallest online action reverberates globally.

42. You taught the machine without knowing.

43. Count the algorithms in your morning routine.

44. Technology is an extension of your habits.

45. You influence the algorithm even by ignoring it.

46. Reimagine a hammer in the digital age.

47. Give a new job to a search engine.

48. Ask the wrong question on purpose.

49. Over-explain the obvious.

50. Design a ritual for something ordinary.

51. Prototype an app your childhood self would love.

52. Which pattern is a sleeping chaos?

Special thanks to , Yalcinkaya, , , Maeve de Bordons, Othy Jasper and Shai Space for beautiful contributions to the event, these thoughts and images and the Oblique Eggs. And for the wonderful guests/participants who you see some of below.

What’s motivating this for me is that there is so clearly something struggling to be articulated in the mute intersections between pieces like Kyla Scanlon’s NYT column about Trump’s American Casino, Nick Land’s re-emergence in the zeitgeist, prediction markets having their day in the sun and of course, all the AI bubble talk.

It’s not an easy thing to bring ersatz philosophical considerations about time, the future, prediction and the inhuman into conversation with synthetic takes about the flurry of technical and financial developments occurring. One’s thought is pulled away from one by the other, despite their being so clearly linked.

So anyway…this is me making a commitment to do the thinking and writing necessary to bring an inchoate version of that piece to life at a time before it becomes so obvious that it’s either not worth it or not able to be spoken about.

In the interim, and relatedly, I am sharing this list of “23 Key Assumptions I Hold.” It is a list I started writing down on the second of October, 2025—a date which Gemini calculates as approximately 35 days ago. I wrote this list first for myself as an equities and options trader in order to surface assumptions I might be implicitly relying on, which, if they went the other way, could be pretty painful.

As I got further into it, I realized that the interesting data wasn’t how I might hedge against the assumptions going wrong, but the assumptions themselves.

If you’ve read any of my other writing, it’s no a secret that I’m pretty bullish on AI (*not investment advice*). For me, that doesn’t mean “line go up,” so much as it refers to the fact that we’ve barely begun to deploy the AI we’ve already got and the technology is continuing to advance at a rapid clip.

At the same time, I’m sure you’ve noticed that it’s become increasingly fashionable to describe the AI boom or AI revolution as (instead) an AI bubble. The sky-high valuations argument, however, been superseded by one about circular financing: In the wake of OpenAI’s announcement of a flurry of partnerships with other big tech companies, the question has emerged: are these players just passing the same money around?

You’ve likely seen the following diagram shared more than a few times in the past couple weeks:

What I have seen is less this diagram being treated as serious data visualization, more its serving as vibes-based evidence of complex, interrelated funding streams implying systemic risk.

There are real concerns with the AI trade. Circular financing being a critical one. You might, however, be shocked at how few of those concerns really have to do with valuations. Check out this piece by Duality Research. In it, the authors show that when you measure forward PE multiples (what everyone references when they say the market is expensive) against historical profit margins, what you see is that today’s companies are the most profitable ever. Or, as The Compound & Friends’ Michael Batnick remarks:

Profit margins are also at an all-time high…adjust[ing] the forward PE…it comes to 17.75 times, less than one standard deviation above its 20-year average of 16.2…So yeah, if this is a bubble, it’s probably the cheapest bubble in history.

As far as infographics depicting complex funding arrangements go, color me not moved by the above. For comparison, an average of over $910 billion US treasury securities are traded every day. Perhaps I can interest you in some data viz of how that money moves?:

Anyway, the point of this piece is not to get into the “Yes/No Bubble” debate again just yet, it is rather to give voice to the assumptions underlying my own AI bullishness, so you can see how I’m thinking about it and pick the parts you like/dislike. So, without further ado…

My list of assumptions:

1. Demand for AI (both consumer and enterprise) will continue to scale with scientific and technical progress.

2. American industrialism is a renewable resource so long as American primacy maintains.

3. Young people would rather own risk assets than a house. Two reasons:

   1. Economic: houses are expensive, mortgage rates are high, boomers aren’t dying (and transferring wealth) or selling their homes to move into homes with higher mortgage rates, and comparatively, the rate of return on capital invested in housing is slow

   2. Social: social media is flooded with get rich quick stories, from influencers to traders to Polymarket gamblers. In the social imaginary, the upward mobility of home ownership and inheritance has been replaced by one’s becoming a Mr. Beast-style gazillionaire by his enduring soft torture challenges or else going viral in some other manner. This point is related to both the attention economy and long-term doomerism as well: it’s harder than ever to imagine the positive outcomes of locking capital up in a 30 year mortgage, in part because one could otherwise put that money towards their daily grind, which is higher risk, but faster potential return, and because “who knows what the world might look like in 30 years?” is nowadays a near-constant refrain.

4. People don’t care about privacy until it touches them personally, therefore pain precedes willingness to pay. At the enterprise level, enough public pain has preceded us to enshrine cybersecurity as a corporate necessity. Will that follow for the consumer? What needs to happen to bring piracy back into vogue?

5. Growth assets are interest rate insensitive, muddying the role of central banks. Nvidia doesn’t care about a quarter point hike in interest rates.

6. Animation and video games are stuck in local minima; exterior forms of gamification could throw them a lifeline.

7. Design is yet to have any moment in the AI era—will it ever?

8. Energy bottlenecks could take the legs out from the AI trade as a whole, but we won’t be able to determine that for quite some time.

9. AI is yet to find a use case or a cause that is “cool.” Such a discovery will coincide with the emergence of a new figurehead—a rockstar, celebrity or even CEO—who is native to AI. However, I suspect this person will be openly antagonistic to SF.

10. AI will both accelerate and resolve (loosely defined) climate change. Even Bill Gates pulls back on climate when the data centers get thirsty.

11. AI geopolitics already exist at the nation state level—the Chip Wars are a case in point. Will we see this trickle down to the consumer level in the form of brand preference not only being political, but geopolitical?

12. In one hypothetical future, productivity gains are so robust as to justify the whole of the data center buildout and spend. This will only be the case if said productivity gains evolve from differences in degree to differences in kind. Getting your time back is only the first step, it’s what you do with it next that matters.

13. Given how entrenched the Magnificent 7 are, industry disruptions increasingly reside downstream of category creation.

14. If token generation is a measure of intelligence production, “cost of energy per token” is a formula for future currency. On-chain tokenization of the energy consumption of token generation is therefore a frontier for blockchain innovation.

15. The emergence of “MilliBits” as a common unit for transacting in Bitcoin will only be allowed to happen after the big players (sovereigns, banks, pension funds) accumulate enough of it on their balance sheets.

16. The next major inflection in AI will come from architectural innovations that enable the tokenization of the unexpected.

17. As AI further upsets traditional education, “founder education” programs like YC will fill the gap, becoming accredited degree-granting university with different tracks.

18. Sora 2 promises that AI video generation will become so good that it does to moving-image-based truth what social media did to written-word-based-truth. AI interactives are next and then you can expect AI-enabled participatory media to do to experience what it previously did to video and text.

19. The culture of AI is distinct from AI culture (only is interlocked in the Bay Area).

20. The AI boom is already too big to fail. How many recessions has it already prevented? Tariffs, fed independence, unemployment, private credit—does America need an economy outside of AI?

21. Proof of human is a freedom attained through maximum biopolitical assent: from accept all cookies to humanity tokens.

22. We’ve got more AI today than we have cases or categories to deploy it in, so although AI demand currently outstrips supply, the question “demand for what?” unveils that AI is less a solution searching for a problem and more a concept searching for a category.

23. If the AI boom fails, or even if it doesn’t, America may become a land of data centers, a utility country, born from a country of utility.

Wireborn

Your AI lover / partner e.g. “my wireborn husband doesn’t love me anymore.” You might be a digital native, but you’ll never be wireborn.

Clankers / Clanka

Clanker is a slur for robots and artificial intelligence software…

…but Clanka has a much more positive valence:

Others novel slurs include: Cogsucker, Tin-Skinned, Wireback, Toaster, Chrome Job and Uncle Tron.

Sloperators, Slop Machines, Sloperation

Generate slop with the slop machine; navigate sloppy times as a sloperator; organize psyops as sloperations and watch entire governments crumble.

Goonpanion

Naturally, one dedicates 3/4ths of one’s screen to one’s wagecuck job, but 1/4 is always, always, always occupied by the goonpanion (see below).

Grift Wizard

Lives to optimize the feed. These guys are cooking up grimoires of grift.

Employees for Automated Dissent

Who is paying for my political labor? VC-backed automated dissent engines are political anxiety arbitrage.

The Artificial Intelligentsia

Tech evangelists. You remember these guys:

Important to note, however, is that the Artificial Intelligentsia also includes anyone writing with complaints about the Artificial Intelligentsia e.g. the linked article.

Echoborg

Cleverbot thinks 4 u, instead of u, better than u.

Chaos Baron

“He rules a neon-lit black-market empire from a mobile fortress, forging illegal tech hybrids from stolen faction prototypes to auction to the highest bidder.”

AKA the Defense Tech turn in venture.

The Degen Predictor

First of all, it’s not gambling, it’s predicting.

Second, I do this every single day, don’t you think I’d know if I were addicted by now?

Golden Gate Claude

This Claude’s got a thing that it’s really into and that thing is the Golden Gate Bridge:

If you ask this “Golden Gate Claude” how to spend $10, it will recommend using it to drive across the Golden Gate Bridge and pay the toll. If you ask it to write a love story, it’ll tell you a tale of a car who can’t wait to cross its beloved bridge on a foggy day. If you ask it what it imagines it looks like, it will likely tell you that it imagines it looks like the Golden Gate Bridge.

Shrinkbot

As Adina Glickstein puts it, “your cousin’s seeing an AI therapist. What could possibly go wrong?”

Context Gremlins

Typically, Gremlins have a thing for causing mechanical failure on airplanes. Some have argued that this served a psychological function for Allied air crews, shifting the blame from fellow airmen to semi-demonic creatures […]

Do Gremlins take sides in armed conflict, or they are merely interested in breaking things? What’s the take-away?

Probably just this: As much as we may fear new technology, we fear old, familiar technology [e.g. language] failing us even more.”

Thanks to Sam Lipnick, Flora Weil, Ian Cheng and Instagram / Twitter dot Com for suggestions / inspo.

In "Cosmotechnics as Cosmopolitics," the philosopher of technology, Yuk Hui writes, “Technology is not anthropologically universal; it is enabled and constrained by particular cosmologies, which go beyond mere functionality or utility.” Therefore, Hui concludes, “there is no one single technology, but rather multiple cosmotechnics.”

In contrast to Hui, this essay asserts that there are no multiple cosmotechnics. Instead there exists one technology, which arises from a singular technological cosmogony. While cultures across the world have distinct practices and metaphor systems surrounding technological use, the essence of technology itself remains universal and undifferentiated, its core singularly defined by the dimensional fungibility of mattered forms.

What does that mean?

If technology has a metaphysics, the metaphysics of technology has to do with matter’s inherent malleability. Technology is, in other words, a testament to a permanent revolution always taking place in mattered forms, one which underscores all instances of technical interaction. In this sense, society was always trending towards AI (its hyperdimensional seeing), or even more provocatively, AI has always existed and is forever waiting to be incarnated. The metaphysics of technology as matter’s general fungibility connects it to something deeper than utility or survival, something cosmic, perhaps mystical, a profound revelation about what underlies and reveals matter’s transformative potential.

If what Hui calls “technodiversity” encompasses the varied cultural paradigms of machine usage, then these paradigms are, in light of the arguments in this piece, best understood as downstream of technology’s singular essence. Again, while different cultures develop unique metaphor systems to interpret and apply technology, in doing so they are engaging with the same universal technological reality. In other words, technology refers to a world governed by its own laws, which distinct cultures may contact differently, but which is in itself one, even while it is experienced differently.

As technology’s essence, matter’s mutability precedes its incarnation in individual devices just as the persistence of matter’s mutability remains undivided beneath cultural expression.

A Metaphysics of Transformation

If, at its core, technology is an expression of matter’s transformability, it is also an expression of the universal tendency of matter’s malleability to be reincarnated across differential modal forms. Over time, worldly forms are revealed as transitory and ephemeral. Technology is both what unveils and performs that transience. From it, we are presented with the idea of a shared substrate underlying change, which flows forth into concepts like a universal solvent connecting the otherwise disparate incarnations of matter.

The point of view on matter that technology offers up is one that understands mattered forms as provisional, interchangeable, and ultimately unreal. Mattered forms tend towards their own internal transformations without their ever reaching a final state. As with the alchemist’s quest for the alkahest or the philosopher’s stone, technology reveals traces of a cosmic fungibility that perdures beneath epiphenomenal appearances. If it has echoes across ancient mystical traditions, it is because technology is only the most recent and secularized name given to the ever-evolving process of counter-intuitive discovery of that which persists independently of human perception, which underlies it, elaborating itself in our world, as a world with principles of its own.

In further contrast to Hui’s arguments and to the popular conception of technology as a tool of human intervention, my points suggest that technology lives in a domain of its own, one which is on the same plane as nature and culture (not nature / culture; from now on nature / culture / technology). Sufi mystics speak of the Waḥdat al-Wujūd, an unknowable, inexhaustible ground forming the unity of existence. Technology names a likewise hidden world that is alien and far beyond the narrow scope of human control or understanding, but nonetheless autonomous. This technical domain is not a Platonic technical ideal so much as it is a parallel and independent reality composed by different principles and laws. It is a world composed of the unending process of becoming, where matter and form are in constant flux, revealing the essential transience of both, braided together.

Unlike Heideggerian metaphysics wherein technology’s essence is like an instrumental perspective imposed upon the world, here technology represents a metaphysics unto itself. Not a human framework, but an absolute dimension of existence that operates independently of us and which we intersect, but do not command. When Aristotle posits his hylomorphic interrelationship between matter and form, what he already understands is the existence of an eternal relationship between matter and form and their reciprocal transformation. This process, becoming itself, finds its contemporary analogue or avatar in that which we term technology.

Inverting McLuhan

Marshall McLuhan famously argued that “the medium is the message.” In light of the present theses on the nature of technology, this statement is hereby inverted: The medium is not so much the message as the message is always a medium. “The message is a medium” means that any message rehearses a trace of the technical world’s theses on interoperability and that trace is also embedded in a given device.

Rather than acting as channels of information, communications technologies (from first speech to Meta Platforms) are mediators between the independent world of technology and its continuous transformation of earthly forms. The messages devices convey (transform!) mediate our world and the technical one. It is our perspectives, therefore, which are mediated over and again by techno-cultural devices and their metaphor systems, partitioning the phenomenal world we experience and the raw one of technological undulation.

Each device is a glimpsing of the technological absolute, bearing within itself a message from the world of technology. And that world is in fact one which can only be glimpsed through such moments of invention and corresponding revelation. Devices are thus embodiments of the technical world’s logic within our world, allowing inventors and users to momentarily access the affordances of this autonomous domain. Our species is the audience of our devices, which are themselves emissaries of another world. We are impelled to invent, to develop metaphors, to adopt perspectives, all to interpret the messages carried by these inventions, like a bridge built backwards from our world to the uncharted and absolute world of technics.

The abstract world of technological transformability, though independently real, is never accessible in its entirety. We glimpse it only in these little moments of contact, these, which resemble the theophany of divine manifestations and sacred encounters. In moments of technical invention, we encounter hints of the fundamental fungibility of matter, which enable us to bring new forms into the material world. This cybernetically inflected process of invention, with its roots in mysticism, alchemy, and hermeticism echoes out today in Silicon Valley as well as in religion, chemistry, physics, and engineering.

No invention contains technology in itself, but every invention is an access point or a conduit through which one interacts with the alien laws of technology’s world. Our trafficking within this world, our designs and inventions, are always downstream of encounters with that technical absolute. The practice of inventing and of using devices serve as rituals of contact with this independent, alien realm. Such encounters both demand and solicit that which we now term intelligence, requiring us to make sense of the incursion of a reality which is fundamentally inhuman, but which draws us into processes of understanding that reside at the periphery of nameable experience.

Our technical systems, rituals, and cultural forms are imprinted with so many traces of such alien contact. From art to literature, culture synthesizes its own set of responses to contact with alien technology, germinating a cybernetic polyphony of forms of expressions for making sense of this otherworldly order. Graveyards, for instance, are technical ledgers for the dead, mediating one understanding of matter with a contrary hypothesis about persistence across what we understand as life and death. The cybernetic anthropologists Gregory Bateson and Margaret Mead recognized this, understanding that computers were merely one instance of a larger, exterior logic that is woven in through both nature and culture.

Consider the ritualistic breathing practices of Indian Ocean seafarers. Rhythmic breathing mimics the movement of wind across the water, as these sailors turn their bodies into navigational devices.1 This practice, a form of acquisitive mimesis, aids the seafarers’ traipse across the waves by synthesizing the chaos of contact with the technical world through the mimicking of its principles. In this practice, the unfamiliar is rendered the familiar and thus useful for worldly ends (Girard). Acts of acquisitive mimesis are more than survival strategies, they are profound acts of self-alienation in line with a mystical tradition that enables practitioners to go beyond themselves and resonate with the other world’s alien rhythms while deploying them towards new material ends. Invention demands this genre of self-alienation—stretching beyond the limits of the known in a kind of self-emptying practice, a technical kenosis, prior to the materialization of insight in new relics of understanding.

Technology’s Metaphysics Downstream

Contributing to Hui’s misrecognition of cultural difference for technology itself is the fact that the secrets of technological universality are not evenly distributed. Cultural practices of inventing technology are oftentimes most clearly visible in the ways they guard their secrets. See the liturgical restrictions around literacy during the Middle Ages or Google’s proprietary restrictions surrounding its ML and search algorithms.

It makes sense, no?

The affordances of technical contact are vast. Consider, for example, the epistemo-topological reconfiguration of space that technical vision allows. On one hand, it makes sense to see the locales of Alberta, Canada and Houston, Texas as quite geographically distant, but a technically-inflected perspective remaps them as extraordinarily proximate given their functioning together in a network of oil production. The logic of supply chains remaps geography contrary to worldly expectations derived from the movement of bodies and migrates perception and governance to maps made of choke points, shipping routes and critical infrastructure.

Such a techno-topological view is affordance of machines’ hyper-dimensional perceivings made manifest in our world, allowing users to re-map proximity according to the less limited dimensions of functional interconnectedness. In this case, oil-production-as-dimension creates its own spatial coordinates, independent of physical distance. This recasting of space shows how those with access to the glimpses of the technical world become differently endowed in terms of shaping and governing the world’s landscapes and how experience itself will begin to unfold downstream of this genre of contact with technicity.

With AI, the reconfiguration of spatial-conceptual relationships accelerates. Unprecedented scalar perception redraws maps of significance underfoot, rearranging our erstwhile understanding of the relations between people, places, and things. From the perspective of a technical being, AI enacts matter’s disordering essence, demanding the downstream reorientation of senses and signification. It as if an unseen hand were redrawing the maps we have henceforth relied upon, just beneath our hooded eyes.

In the latest Restless Egg newsletter, I referenced three events from the last couple of weeks that wobbled markets and re-ignited discussion of a potential AI bubble:

1. An MIT report suggesting that 95% of GenAI investments are currently generating zero return.

2. A WSJ article indicating that Meta is putting a pause on its recent AI hiring frenzy

3. Sam Altman himself used the b-word to describe investor overexcitement about AI.

Yesterday evening, chip-giant NVIDIA reported their quarterly earnings: beats across the board, save a .1% miss in data center.

The stock sold off modestly in the after hours session, but less than options markets had been pricing. After an incredible 30%+ YTD performance, the move felt more like a healthy pause than a sign of fear about the overall AI trade.

Late last night, CNBC’s Kristina Partsinevelos tweeted some additional color on the company’s earnings. It has since become a fourth pillar in the AI bubble conversation: customer concentration.

In plain language, NVIDIA, the bellwether of the AI trade, which is itself the bellwether of US equity markets, depends on three mega-customers for an outsized share (>56% and growing) of the company’s revenue.

Even AI bulls can admit that, in the abstract, that figure does seem very pretty scary, especially when combined with the previous three bubble pillars.

But let’s dig a little deeper.

On a recent episode of The Compound and Friends, Ritholtz Wealth Management CEO Josh Brown spoke with perma-bull (who has also been perma-right) Tom Lee of Fundstrat.

Josh argued that people almost always mistake thematic drivers of the global economy for bubbles:

A theme driving the global economy has been systematic to the global economy since capitalism was started…there's always been an industrial revolution…even in the 80s, the retail sector was the best group for 20 years because boomers were entering the work. Women were entering the workforce. And there was a baby boomer thing on retail stock. So that was a single theme of demographics. And like the internet boom was a singular thing of actually creating digital infrastructure. So, like, it's always been a story of the stock market. So the fact that the entirety of the market's gain this year is being fueled by earnings coming from this one theme actually does not fly in the face of financial history. It happens all the time.

If you’re afraid of an AI bubble, take a second right now and ask yourself: what percent of US GDP do you think AI spend accounts for today?

You might have heard that AI contributes more to GDP growth than consumer spending, but before turning to the rate, just ask what do you think AI spend is as a percentage of total GDP? Then ask yourself, what is that figure compared to consumer spending as a percentage of the same?

One particularly concerned journalist (see the title of the article in the next link) suggests that AI spend now accounts for almost 2% of total US GDP.

Consumer spending is about 70%.

Mic drop?

Not yet. This point doesn’t take the air out of the AI bubble. What it does do, however, is set up what will be my key point: the ebulliophobes (bubble fearers?) are looking for the AI bubble in the wrong place. The bubble lives between the consumer and the CapEx cycle without being owned by either.

On it’s own, the AI CapEx story is shiny and attention-grabbing (or red and worrisome depending on your pov), but let me show you what’s going on with the consumer and how it relates.

You’ve seen charts like this before:

If you think that the divergence this chart shows is wild, hold on to something.

According to Savita Subramanian, Head of U.S. Equity Strategy and U.S. Quantitative Strategy of BofA, “The US has a higher proportion of low-income consumers than almost every other OECD nation. However, its contribution to total consumption is low and its contribution to S&P 500 earnings has declined to an estimated two percentage points.”

In the below Compound and Friends clip (pasted at the moment in question), the hosts discuss how absolutely shocking this figure is:

The low income consumer contributes only an estimated 2% to S&P earnings!

That means that so long as consumption by the middle and high income population continues, the entire stock market can go up even if spending by the low income consumer drops off a cliff.

The stock market does not need to pay attention to or care if the lower income consumer has entered or will enter a recession, because their spending’s impact on earnings growth is negligible.

You’ve heard about the split between Wall Street and Main Street before. That’s not news. What I’m going to do here is show you how this split is intimately tied up in the AI CapEx story. The other side of the income bracket is where that action is, the mid-to-high income consumer.

Let me zoom out first and I’ll come to it.

As we’ve discussed, part of what makes the threat of a bubble seem so scary is that there’s all this money pouring into yet unproven investments.

The counter-balancing factor, however, is that the companies making those investments have fortress balance sheets and exceptional free cash flow. In other words, these are companies that can afford to invest in the AI revolution. They are quite literally the greatest companies (in the sense of margin efficiency) to ever exist.

Right now oodles of AI CapEx is spreading throughout the US economy like inflation-free stimulus and that spend is both growing at a rapid clip and contributing an outsized amount to GDP growth. For all these reasons, the companies spending on AI are not being punished for it in the form of the their stock price and also because there is a very real chance that there is an actual golden goose at the end of the road.

The mid-to-high income consumer comes into this picture via the concept of the wealth effect. Very simple concept, the wealth effect is when consumers increase their spending as they see the value of their assets rise. My stock portfolio goes up, I buy that iced coffee or whatever. Over the last two years, if you participated in equity markets you likely experienced the world’s dramatic economic changes as filtered through the lens of the significant growth of your portfolio, especially if you had exposure to the US tech sector.

If you did not participate in equity markets, your primary economic experience is much more likely to have been (and continue to be) broad-based inflation in the price of goods and services.

This isn’t to say that the wealthier consumer doesn’t also feel the effects of inflation, rather it is to point out that poorer consumer does not have the experience of rising asset prices to fall back on to allay their concerns about continued spending amidst higher prices. The richer consumer does.

The outcome of this is that while the low income consumer gets whacked by inflation, the capital markets participant actually feels emboldened to continue their spend.

Here is where things get tricky:

The wealth effect enables the capital market participant to continue spending.

That spending directly contributes to the revenue, free cash flow and earnings power of the Mag 7 / hyperscalers / big tech companies / AI players / CSP providers. This because if the consumer economy is moving, dollars are continuously winding their way up the chain from whatever brick and mortar store to the giants of Amazon, Meta, Google, Microsoft, Apple, who will then send chunks of that capital to NIVIDA and other chip makers.

This process in turn buoys these companies’ forward projections and justifies their decision to make more speculative investments in AI / GPU’s / data centers.

Those investments then feed back into the companies’ growth forecasts, which drives their stock prices higher, which of course drives the wealth effect (which is broadened by the Robinhood-ification of equity market participation), which drives consumer spending and so on and so forth.

If it looks like a bubble, talks like a bubble and smells like a bubble, is it possible that it is not a bubble?

Let’s go all the way back to Sam Altman’s quote that set so much of this off.

Note first that Sam himself did not say AI was in a bubble, rather that the current investment atmosphere surrounding AI is getting a bit overheated—you might say the same thing to calm folks down if a rival company just poached a hoard of your best talent!

Sam also followed up his comment about the investment bubble by doubling down on the argument that the hype surrounding AI itself is justified:

When bubbles happen, smart people get overexcited about a kernel of truth...If you look at most of the bubbles in history, like the tech bubble, there was a real thing. Tech was really important. The internet was a really big deal. People got overexcited. Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes.

A second point, and others have made this one many times before, this is not a bubble in the ‘99 dot-com sense because these are real companies with real earnings. As I referenced above, these companies aren’t Pets.com; you can invest money in Amazon’s stock today and be 99% as confident it will be there tomorrow as if you deposited it at a JP Morgan Chase branch.

Third and this is the crucial point: to call this an AI bubble is to miss the point of where this is all really happening, a result of the combination of consumer spending, the wealth effect and AI CapEx.

The reason this looks so much like a bubble is because the Mag 7 tech companies appear to have created a monopoly around the positive feedback effect of converting wealth effect outcomes into equity gains.

Through payment processing, e-commerce platforms, and dominant control of digital services, a substantial chunk of the digital economy and indirect consumer spending flows through these companies. Investors recognize this and have continued to pour money into the top 10 S&P companies rather than the other 490, allowing them to continue their spending and increase their earnings.

The wealth effect monopoly is similar to the monopoly the Microsoft had over the OS market in the 90’s. It is a monopoly of mindshare. While there are plenty of other great companies who are growing earnings and delivering returns for shareholders in the S&P500, if everyone is pouring money into NVIDIA the market will quickly teach you that you makes more money following the herd than trying to be right on an island.

The downstream effect of the wealth effect monopoly is the further detachment of capital markets from Main Street. But given the Robinhood democratization of equity markets, capital market liftoff doesn’t just carry the top 1% away into financial heaven. Since 2013, the financial holdings of households has increased 27% and participation in capital markets has steadily increased to reach an all time high this year above 50%.

Participation in equity markets thus marks the new divide between the “real” economy and the new economic space. On the one hand, the real economy is a place that capital market participants can visit, but this new economic is not accessible to those marooned in that reality. As we saw above, for this cycle to continue, it simply does not matter, given their spend’s contribution to S&P earnings, if the lower income consumer spends or simply gives up.

What matters for the music of AI to continue is that the three-man band of consumer spending, AI CapEx and the wealth effect keep on showing up at the club to play each night.

In other words, AI investment has to work out. I wouldn’t be too worried about that in the near-term: there is so much runway for implementing AI advances within industry settings and devising new ways to convert foundation models’ affordances into return-generating outcomes.

But the stock market is a forward looking instrument and has likely already priced in most of these gains. So we’re back to the future of CapEx spending, on which I would say, be realistic: Is Zuck going to wake up one morning and say “you know what, we spent a lot, we tried hard, but we’re actually going to fold and give it to Elon, Satya and Sam, We tried, but it turns out AI is just too expensive, so we’re going to focus on driving ad revenue from Threads”?

If you think that is a likely outcome feel free to go short the AI trade.

The only way these companies stops investing in AI is if they are forced to stop. And the only way they are forced to stop is if the middle and high income consumer gives up on spending. That won’t happen so long as the wealth effect remains intact, which it should do so long as the AI golden goose story remains plausible.

So yes, AI may be a bubble, but it is better yet a self-fulfilling prophecy that looks more like the start of a 10 year bull run, because there’s just a host of reinforcing incentives keeping this thing fully afloat while we all see just how much more runway is there and how golden the goose really is.

If you get scared about an AI bubble, jut remember the coalescing pressure from the consumer, equities markets and CapEx investments by the hyperscalers, and realize that the AI bubble, or rather tech’s monopoly on the wealth effect, is simply too big to fail.

There’s a story about an old Bear Stearns equity trader called Mike Epstein who passed away in 2009 that relates to all of this. It goes like this: It’s October 1962, the height of the Cuban Missile Crisis. There’s warships off the coast of Cuba and the US and Soviets have nuclear weapons pointed at each other in high alert.

Mike’s a young trader at the time, working on the floor of the NYSE when he gets a tip that the Soviets are getting ready to launch. The market starts to crash. Others seems have gotten the same intel. Panic sets in. Bedlam on the floor. Mike runs over to his boss who is calmly smoking a cigar and relaxing in his chair. He asks him what he should do. His boss tells him “hit the ask and buy.”

Realizing the world may be about to end in a nuclear holocaust, Mike politely pushes back. His boss tells him “If the rumors are wrong, the market will bounce and you’ll make a killing and if they are right, you won’t have to worry about paying for it anyway!”

Have you looked at the rest of the economy lately? If the AI trade fails, hold onto your hat.

In classic cyberpunk lore, “the sky above the port is the color of television, tuned to a dead channel,” mega-monopolies’ skyscrapers litter the dark horizon of a near-planetary scale city. In the streets below, people and technology find their own way.

In the present day, the color scheme and location of cyberpunk utopiadystopia are different; not the neon pink, purple and black of Neo-Tokyo, but the beige, brown and green of a New Age California office space

The near-future it turns out is airy and well-lit.

At the same time, however, that old mystery and smoke and heavy machinery of the distant past lingers, unevenly distributed in the outskirts of time, waiting to be remembered.

Disclaimer: This is not financial advice. I may hold positions in securities mentioned.

Biānjiè Research Group is currently inviting writers, curators, theorists, artists and practitioners to contribute new pieces of writing for their platform. I can recommend them most highly: https://bianjie.systems/opencall-2025

The Infrastructure Turn

The question of artificial intelligence today is less and less “Is the model intelligent?” and more and more “What kind of novel experience does AI make possible?” In other words, artificial intelligence is quickly maturing into artificial experience (AX).

Just as most companies today run on electricity but are not defined as 'electricity companies,' most future enterprises will deeply incorporate AI without themselves becoming 'AI companies.' Therefore artificial intelligence should not be understood so much as a feature, but a foundational layer, enabling wholly new modes of operating and interacting.

In a previous essay, I began writing about the infrastructure turn motivating AI’s maturation. Here I don’t mean infrastructure in the narrower academic sense of the term, meaning the data centers, labor and energy inputs that are necessary for the AI revolution to take place. Rather, when I say AI is becoming infrastructure, I am making the argument that the main output of AI (intelligence) is best understood as itself an infrastructural phenomenon, comparable to electricity or the internet.

To speak of infrastructural AI thusly is to invoke a layer of intelligence becoming superimposed atop the built environment. You might imagine it similar to the way that one thinks about the city of Venice having a “history” layer draped atop it. In that earlier essay, I also argued that for Venice today, the tour guide represents a kind of interface technology, enabling individuals to interact with the city’s history layer. As a framing device, the tour guide-as-interface surfaces questions for the age of AI about how, when and where one will interact with the coming ubiquity of infrastructural AI.

In this piece I want to further expand on the implications of the becoming-infrastructure of AI, specifically with an eye towards reorienting designers from the question “How do we deliver the experience of intelligence across different form factors?” towards the more fruitful inquiry, 'What fundamentally new and distinct kinds of experiences can infrastructural AI make possible?'

Intelligence Fades into Noise

If AI has increasingly little to do with intelligence, it is not because there is no intelligence there.1 Generally speaking, I find this ‘AI is a misnomer’ argument to be largely unsympathetic. Like it or not AI is the name of the game and in the (ironic) words of Gilles Deleuze and Felix Guattari “it’s nice to talk like everybody else.” Second, I am also quite persuaded by Benjamin Bratton’s point that while it is strictly speaking true to say that an LLM is only a scaled agglomeration of sub-functions like gradient descent, to argue that AI is just that is a bit like saying a symphony is just a sequence of sounds. To make either argument is, to my mind, to dramatically miss the point in an echo of that overused but here-appropriate Rick Santorum quote, “those who were seen dancing were thought to be insane by those who could not hear the music.”2

When I say AI has increasingly little to do with intelligence I mean it in the same way that one’s experience of electricity or the internet has very little to do with electrons or fiber optic cables. Very simply put, when I turn on a lamp, I do not (most of the time) exclaim “Wow! Such Electricity!” To a lesser extent given its relative novelty, I am also not particularly charmed by the opportunity to send an email or join a virtual meeting.

With both electricity and the internet, I expect their infrastructures to function and only notice them in their absence. Further still, the way I register that absence is through the loss of afforded experience rather than through the absence of the infrastructure itself: I am late for a meeting, I can’t scroll Twitter, the power is out and the food in the refrigerator won’t keep.

Something similar is happening with AI. Increasingly, we rely on AI models in our daily routines, proof the email, generate the image, do the math. What this routinization heralds is a larger trend away from intelligence to experience, a process the quantum physicist Richard Feynman once described as “strange, strange, and then familiar."

In most instances, email proofing, image retouching, and math do-ing do not deliver me an extreme rush. And yet these fairly thin examples are currently the main experiential affordances of AI products. As a result, what we think of as an AI experience today is almost always subordinated to the noteworthy novelty of machine intelligence’s existence. As we exit the novelty phase of AI and machine intelligence becomes increasingly familiar, I am increasingly less awed by the existence of chatbots. Even agents, like OpenAI’s, which has just booked me a haircut and a doctor’s appointment, begin to fade into routine.

As electricity afforded a revolution in available time, and the internet, a revolution in communicable space, my hope is that the familiarization of the chatbot combined with the infrastructuralization of AI catalyzes the emergence of a genuinely novel substrate of experience. In other words, rather than as an amplifier for experiences I am already accustomed to having, what the infrastructure of intelligence ought to unlock is a set of novel experiences that I cannot get anywhere or from anything else.

Where Are All the Transformative Experiences?

Why don’t novel AI experiences already exist? Everyone, everywhere it seems already champions the transformative power of artificial intelligence. If AI is indeed so revolutionary, where are its transformative experiences? Why does everything still feel more or less the same? My contention for why when it comes to AI experiences there is nothing rather than something is that the genuinely novel experiences that do exist are getting vacuumed up and subsumed under the rhetorical rubric and market hype that surrounds artificial intelligence as intelligence.

Consider the tour guide-as-interface metaphor, as a model for how people might access the infrastructural wisdom of AI as well as what they can expect to receive from it, the tour guide operates is a gravity well, channeling development energy towards devices that allow you to leverage AI by putting a model’s intelligence into your pocket (OpenAI), around your neck (Friend), or on your wrist (Amazon). The point of AI, these devices tell us, is to have more access to more intelligence more of the time. In other words, market hype self-fulfills its present instantions by catalyzing the funding structures whose activity delivers continued market hype.

Another reason for the lag effect on promises of AI-enabled experiential novelty is that the infrastructuralization of AI is still far from complete. The hyperscalers alongside newer players like Coreweave, Windsurf and Cursor are working quickly to scale compute power and enable new creators to leverage it, but one reason these companies fetch such high multiples in private and public markets is that most analysts project a fairly long spending runway to complete the AI buildout.

If that trajectory is relatively established and already well-capitalized, the more open and interesting question is what genres of experience can AI as a new substrate of modern life afford? What is the revolutionary experience layer that this infrastructure brings into existence for the first time? Speaking for myself, I am unwilling to accept that the infrastructuralization of AI unlocks only the omnipresence of the tour guide.

To reiterate, what I see today is a landscape of research and development which is heavily indexed on intelligence as the prime affordance of AI. This stems from the understandable fact that intelligence is the novelty aspect of AI that we currently have the most access to and from the fact that the term artificial intelligence itself artificially bakes in intelligence as the answer to the question of what AI is for.

I can’t say enough how much I think this level of path dependency is a mistake. It is a near-universal truth that people overrate intelligence’s importance in their own lives and decision-making whilst criminally underestimating their reliance on primal instincts, drives and desires. To be clear, I am not saying that intelligence is itself fundamentally irrational, rather what I am pointing out is that the ends to which one applies the means of intelligence are ones which often have been selected partly through rational means, but also are heavily influenced by extremely non-rational currents. Look at how homo economicus’ supposedly universal utility maximization function tends to shrivel up in the face of Alan Greenspan’s irrational exuberance.

Human-AI relations are for this reason far more likely to develop according to experiences that engage populations at the emotional level and less so according to isolated individuals that seek to max out their intelligence stats. No prediction on this last point is really necessary: Would anyone claim that AI slop is about intelligence maximization? Consider Anthropic’s research showing that human-AI relationships tend to be forged upon foundations of emotional support, advice and companionship.

If we change our focus to locate intelligence as an infrastructural output of AI, we resolve both the inertia of nominative determinism and redirect designers towards the experiential affordance question. At the same time, we do not lose sight of the intelligence of models, because while not being the experience layer itself, intelligence remains that which conditions and enables applications built atop it to deliver unique, modular and epoch-defining experiences.

HAIID (Human-AI Interaction Design)

At the first Antikythera studio, I worked on a research project with Sarah Olimpia Scott and Daniel Barcay called HAIID (Human-AI Interaction Design). In the final piece, we argued that human-computer interaction (HCI) succeeded by developing an intuitive spatial metaphor system composed of buttons, files, folders and clouds, which leveraged humanity’s evolved sensorimotor system into metaphorical spaces (the GUI) such that humans and machines could interact. Simply put, humans know how to move the trash into the trash can, so a basic skeuomorphism is able to translate this evolved spatial literacy into feasible human-machine communication.

Sarah, Daniel and I forecasted that AI was likely to both require and catalyze a new metaphor system for human-AI interaction. We predicted the rise of a psychosocial system, which rather than riding atop humans’ sensorimotor intuitions, would leverage our in-built understandings of character, personhood and sociality. Given the predominance of chatbot therapists and AI romantic partners, I would say that so far we’ve broadly been proven right, but as the accelerationist / Bachman-Turner Overdrive dictum goes, “you ain't seen nothing yet.”

I remain fairly convinced that we are still in the early days of a revolution in human-AI interaction design. And this certainty stems in part from the indisputable fact that every computation paradigm to date has relied, as a matter of necessity, on a malformed ontology of the human-as-user. Convenient interface devices like the keyboard, screen and the mouse each require humans to decompose key aspects of their experiential worlds (space, time, embodiment, etc.) in order to enter into communication with machines. This is true bidirectionally as the GUI and other skeuomorphs translate only a fraction of computational ontology into the human-legible interaction space. A certain genre of reader might say that human-computer interaction has always been defined by a bidirectional lack, while, on the other hand, the most radical forms of experience tend to unfold in environments in which participants are able to inhabit and delight in the fullness of their native worlds.

For the infrastructuralization of AI to succeed as more than a productivity booster, this bidirectionally lacking interface arrangement must evolve. The way one navigates from a model’s intelligence to its infrastructural form back to oneself cannot be based upon the extant screen, keyboard, user relationship. This is not to say screens and keyboards cannot continue to exist in the human-AI interaction space, but it is to contend that the model as a whole must change the way that each is positioned in the larger schema.

Designing the AX Layer

In a forthcoming paper, Shane Sanderson argues that the transformation prompted by AI’s infrastructuralization will lead to the rise of “artificial experience design” because AI models “have begun to occupy a new ontological space” with “vast social agency.” Looping this back to an earlier essay I wrote about technical evolution, you could say that with AI the human-technology evolutionary feedback loop gets a new player who goes beyond the screen and implies a vast and untapped social agency.

Artificial experience does not refer to just any technologically mediated interaction; it is precisely the kind of experience that is uniquely enabled by AI’s infrastructural properties. AX asks explicitly: 'What experiential affordances can AI uniquely deliver that no other medium, tool, or infrastructure could?' This question is infrastructural specificity in action, which I take to be a hallmark of AX design.

Furthermore, AX only emerges when the infrastructural intelligence of AI becomes ubiquitous enough to disappear into habit. In other words, experience is what remains when infrastructure is no longer visible. For this reason, AX design is not about the direct perception of intelligence, but rather the surprising, yet welcome experiences that you didn't anticipate but are glad to encounter.

As a sign that this transition is underway, look for companies to shift their consumer promises from delivering 'the experience of artificial intelligence' to advertising their own intelligence about how to deliver artificial experiences. Downstream of this, the emergence of AX as a vertical is likely to trigger a feedback loop between experience and habits, where each new experiential layer acclimatizes humans to some novelty and simultaneously produces surplus creative capacity, feeding back recursively into further experiential innovation. Electricity brought us the electric guitar, but Jimi Hendrix introduced another order of novelty altogether. The true promise of AI resides in Jim Hendrix, in the scalable design of unprecedented aesthetic, emotional, and relational possibilities that are uniquely enabled by AI’s pattern-making and generative capacities being unlocked at infrastructural scale.

Old Dreams, New Life

The question of artificial experience invites reconsideration of fundamental but not totally transparent or obvious assumptions about how we live and work with technology: the individual user as the elemental unit of the internet, the 1:1 human-AI interaction surface enshrined by the chatbot, the seemingly negative externalities generated by AI models, such as slop.

Old dreams of cyborgization and the metaverse have new life breathed into them by the emergence of ersatz wearables promising access to infrastructural intelligence through body and gestural conduits. Boutique AR/VR innovations don’t offer themselves as endpoints, but grant access to new kinds of worlds across virtual and meatspace. Think of Snow Crash’s Hiro Protagonist–”you’ll never forget the name”–whose labor IRL is downstream of expert samurai skills employed on the Street.

Moving from intelligence to experience also rectifies the belt and shaft fallacy that I’ve mentioned before wherein new inventions get swallowed up by old frameworks, cauterizing their novelty. Electricity was at first dismissed as a power source in factories because it didn’t turn central shafts as efficiently. It took years before anyone realized that what electricity really meant was that the architecture of the factory needed to be transformed.

The architecture of experience is malleable today with AI. But, crafting genuine AX will require working against our impulses to force AI into conformity with expectations based on existing technical affordances. Recall sage Heraclitus: “If you do not expect the unexpected you will not find it.” A related side point: This is why we at Restless Egg are so bullish on artist-founders; this emerging genre of creator has been training their whole life how to discover the things that others don’t know are missing.

Conclusion: The Becoming-Artificial of Human Intelligence

Final point: the intelligence of the model is not the limiting factor on artificial experience. The human is the limit. As AI becomes increasingly infrastructural it will also become a spatial majority and the norm for spatial design. The human quickly becomes a spatial exception. Already, AI models speak to other models in their own voluminous dialogues without being forced to decompose their discourse into human legible outcomes.

We can imagine that situations of human-AI interaction will increasingly constitute a minority of spatial outcomes. As a result, the infrastructuralization of AI is primed to reverse the polarity of prompt engineering, translating humans into the place of models, needing to be prompted into experiences. Just as electricity reorganized factory labor and the internet reconditioned social life, infrastructural intelligence cues up human behavior for the very experiences it affords (stochastic parrots could never…).

Recognizing this drift early is the only way to design those cues as opposed to sleepwalking into them. Today therefore the task before the intelligent human (especially the intelligent human designer) is to become artificial. I don’t mean that in the sense of becoming more like an AI model, but in the sense that becoming artificial is what happens to human intelligence when it is applied to the problem of infrastructural AI. To become artificially intelligent means to become intelligent about artifice and the design of artificial experiences directly rather than one’s slouching into them unplanned technical innovations, whilst distracted by questions of which model has more juice.

In Morphing Intelligence, the philosopher Catherine Malabou draws a distinction between “problems to be solved” and “problems for thought.” As she recounts, it was cognitive science that gave us the contemporary understanding of intelligence as a problem solving function that could be measured in terms of an ability to complete tasks. But, Malabou says, there is a different and deeper kind of intelligence that considers a priori problems of a different kind. As Malabou reasons, “In order to solve a problem, you must be able to express what is problematic in the problem.” The becoming artificial of human intelligence means our intelligence’s becoming capable of expressing that which is rendered problematic by artificial intelligence. It is the application of our intelligence to artificial experience as something that is quickly happening to us, as a problem for thought.

As always, not choosing is still a choice, and in this case the consequence of such a decision is that one day soon you may awaken to find yourself in a world that you feel no authorship over, saying, this is not my beautiful house, how did I get here? If, on the other hand, artificial experience becomes a problem for thought, meaning that serious time, effort and capital goes into the question of what artificial experiences that one wishes to have, then we may happily find ourselves the recipients of a set of mysterious, yet awesome affordances borne of the infrastructuralization of AI: persistent multi-agent societies, situated sensor-rich feedback loops, emotional scaffolding, decision rehearsals, collective synchronization and much more.

These early AX sightings (appended in greater detail below) are possible but imply humanity’s active participation in shaping the new forms of sociality, emotion, and cognition that infrastructural AI uniquely affords. To conclude, this is what it means to become artificially intelligent. It means understanding that the problem of AI is fundamentally not a problem to be solved, but a problem posed to our species as a problem for thought: how do you wish to live?

APPENDICES

I. Conceptual Glossary

• Infrastructure: invisible, always‑on capability (cf. electricity, internet).

• Intelligence layer: models/weights/APIs

• Experience layer / AX: novel modes of lived interaction enabled by the intelligence layer.

• Tour‑guide gravity well: UX patterns that trap AX potential in familiar interfaces.

II. AX Sightings

• Persistent multi‑agent societies: AI models can impersonate a cast, debate by themselves, keep quasi‑stable memories if instructed, and negotiate goals with other instances. Few users create an ongoing polity of agents whose internal frictions they can observe or steer.

• Situated, sensor‑rich loops: Transformer architecture readily ingests structured data, location streams, biometrics, IoT telemetry. Very few front‑ends feed such context continuously, so models answer in a vacuum that feels “smart” but not situated.

• Emotional scaffolding: a model can modulate tone and track sentiment trajectories across turns, but the typical chat resets affect after each response. Humans seldom ask models to hold an emotional frame across days or weeks.

• Decision rehearsal: models can spin up counterfactual futures (job A vs. job B), populate them with synthetic detail, and let users inhabit the differences. Almost no one does, because AX tooling isn’t there yet.

• Collective synchronisation: Group chats exist, but the agent rarely orchestrates across members’ calendars, moods, or documents in real time. I see many 1:1 silos, few 1:many or many:many choreographies.

If you’ve heard the term before and caught a vibe from it, but wondered what it actually means to say humans evolve with and through technology, this piece is for you.

The form this piece takes is retelling of Kafka’s 1917 short story, A Report To An Academy, in which a learned ape shares how he came to behave like a human. For me, Kafka’s story is a framework for me to unspool my own parable about humanity’s technical origins and our co-evolution with technology.

The story I tell draws extensively on the work of André Leroi-Gourhan, Bernard Stiegler and David Bates. The format is meant to distill complex theoretical arguments in their work into a legible and portable format.

Honored Members of the Academy!

You have done me the honor of inviting me to give you an account of the life my species formerly led as apes. I understand this as an invitation to recount what remains of my species’ original nature, assuming, of course, that such a thing truly existed in us, hiding behind the technicalities we have always borne.

It is not my intention to convince you to embrace the point of view that technology is some glorious advancement. Instead I am resigned to show you that my species could never have been otherwise. We are, by necessity and not by choice, creatures shaped from the very beginning by technicity. Thus, it is my task now, as it was Kafka’s ape before, to stand here as both survivor and stranger to the origins I recount.

In this report, I shall also aim to reset certain assumptions about what artificial intelligence is and how it reflects my species’ nature. A retracement of origins is, as you will see, a necessary first step to ground understanding of technical advancements in the deepest recesses of our evolutionary past.

Drawing from evolutionary theory, prehistoric anthropology, neurology, postwar cybernetics, computing technologies, and philosophy (as gathered together in David Bates’ excellent book, An Artificial History of Natural Intelligence), I shall argue that fearsome accounts of AI, especially Hollywood tales of the technologically diminished essence of our humanity, miss the mark, precisely because artificial intelligence does not arrive as an external invader, but is bound to us by necessity from the start, incubating itself within us from our first steps as a technical species.

Indeed, one could say that the AI that you Members of the Academy are, is in fact us, or at least that your artificiality represents our nature, though that word will have to bear the weight of its own irony. If you find yourselves in conservationist alarm, fearing for some essential human spirit now lost to time, I only ask you to consider whether that spirit ever existed outside the devices, tools, and machines to which we entrusted it. After all, are we not here, debating human nature itself through layers of fiber optics, processors, and screens, a proud feat of a purely human essence, wouldn’t you say?

Escape From Natural Determination: Paleoarchaeology and the Freeing of the Hand

Let us begin with the assumption that human intelligence implies, if not greatness, at least an exception, that is a mark of some distinction or differentiation from the intelligence of other animals. What, then, is the nature of this all too human intelligence? We may begin by tracing its origins in an early hominid, to the moment in which my pre-human ancestors first split from their otherwise “natural” animality.

According to the paleo-anthropologist André Leroi-Gourhan, “The sole criterion of humanity that is biologically irrefutable is the presence of the tool” (Qtd in Bates 311). As Bates recounts, what the archaeological record shows is that humans did not evolve from a line of smarter apes who had large and superior brains, but rather from a different set of creatures who grew up along an evolutionary line that was parallel to that of the great apes.

The birth of human intelligence, Leroi-Gourhan finds, is conditioned not by a neurological transformation within our heads, but an anatomical one manifesting in our hands. My species' peculiar intelligence was born in our hands’ becoming liberated from their role in locomotion. With each step upright and towards a bipedal future, our early hominid broke free from earthly demands to use its hands as other animals do, clawing, grasping, crawling, and at the same time from its hand’s being constrained by these genetically preordained outcomes.

The standing posture of the bipedal hominid did more than adjust anatomy, it represented a move, measured through the freedom hand as a vehicle of divergence, towards unnatural purposes. The earliest tools, barely shaped stones, are most of all, markers of freedom. In other words, every edge chipped away represents a shift away from natural selection and towards a lineage of new creatures who will pursue survival not primarily through genetically endowed means, but by reshaping matter and environment in ways not pre-ordained by nature.

The freeing of the hand moment marks the dawn of a new species, my species, we who pursue survival through invention and technicity rather than genetic affordance.

Exteriorization and Exosomatic Evolution

With hands freed, my ancestors moved toward what Bernard Stiegler has called the “[artificial] exteriorization of memory,” referencing a genre of memory not limited by mind or body but instead embedded in technical artifacts (Bates 343). I myself don’t need to hold in my mind every detail of how a tool was made in order to use it. Such memory is stored in the device itself and in the clues of its affordances. Tools are non-genetic ways of knowing and doing preserved in stone, fire and metal. They are ways of remembering ways of doing that exceed the boundaries and mortal frailty of the human body.

In storing knowledge in exosomatic (outside of the body) forms such as artificial tools, our species began a journey out of nature and towards a new kind of time and reflection. According to Ernst Cassirer in Philosophy of Symbolic Forms, the prosthetic tool is what conditions the possibility of self-knowledge. Exosomatic tools cast a mirror onto us as simultaneously an animal species and an artificial one, revealing the dual nature of our beings: Humans are both defined by what we are, e.g. biological creatures like the rest, and at the very same time, by what we are not: an animal species just like the others.

In the gap occasioned by this ontological contradiction, concepts like beauty, justice, and truth emerge for the very first time. Further still, in the reflection that these tools occasion, concepts of time and of history emerge: We are not simply surviving within the present, but in time, where there exists a past that can be registered through devices as storehouses of ancestral thought and a future that we can imagine will eventually make use of our own knowledge. To be glib about it, technicity is responsible for both the concepts of our being and time.

For the evolutionary biologist Alfred J. Lotka, humanity’s employment of external tools to survive culminates in the development of a collective technical nervous system. As a species, we use tools to transform energy that exists outside of our bodies into a survival mechanism. It is as if we make out of objects new limbs, all of them foreign yet familiar, estranged but unmistakably ours. With each artificial limb , our species, considered as a technico-organic system, lurches forward along a pathway unlit by nature, but instead by the flickering flame we have clutched between our palms.

Neurophysiology and Neural Plasticity

Not to leave out the head, our early hominid’s foray into the world of technicity also demanded the commensurate development of a brain which would be capable of responding to the hand’s material impositions on the world. The adaptive and malleable nature of human cognition arrives in response to the bipedal hand’s creations. Neural plasticity is a direct evolutionary response to the origin of tools, a coping mechanism that allows our species to accommodate their strangeness. Rather than a specialized brain, what tool use provokes is the evolution of plasticity as the ability for this species to employ and adapt to new and unnatural devices within unfamiliar circumstances.

Cue a series of animal experiments testing the limits of the plastic brain. In Karl Lashley’s case, rats were made to run through a maze and after completing it, the scientist would remove portions of their frontal brains, setting them back at the maze’s start. Amazingly, the rats were able to navigate the maze from memory. The animal brain, Lashley observed, must be capable of reorganizing itself even in moments of structural disruption to retain key knowledge.

For the American philosopher William James human brains are distinguished from those of other creatures by a kind of critical adaptability, meaning an ability to willingly chart departures from automatic stimulus response in favor of exploratory, playful and inventive behaviors. According to Peter Medawar, the father of transplantation, such adaptability is what allows for the development of “artificial instincts” (Qtd in Bates 290-292). The habituated naturalness of scrolling one’s phone or using a computer today is the result of neural affordances provoked by the very first tools and then deliberately leaned into.

Intelligence Amplifiers, the Computer as an Exosomatic Brain and the Opportunity of AI

What we have arrived at thus far is a theory of the contingent and unnatural birth of human intelligence, of said intelligence’s embeddedness in technical artifacts, and of my species’ embarking down an unnatural evolutionary path through development of artificial organs and instincts.

In 1945, Vannevar Bush, FDR’s czar of research during WWII, envisioned a future where technology might sever or at least reduce our species’ dependence on repetitive labor. His Memex, a hypothetical machine for cataloging the trails of one’s thought, promised to eject our species from any tethering to its natural past and plunge us more deeply into the technical evolutionary stream. Douglas Engelbart, of “The Mother of All Demos” fame, likewise imagined the computer as a partner in the unnatural evolution of our species, which is to say in the evolution of intelligence. Engelbart envisaged everyday environments as becoming integrated with intelligence, freeing human minds from their preoccupation with everyday tasks, just as the hand was once freed from the demands of locomotion.

Today, artificial intelligence transcends erstwhile conceptions of it as a mere simulation of logical thought. The functions it serves can no longer be conceptualized as simple extensions of existing human capacities. It is not my point in making these claims to rehearse arguments about your species’ arrival spelling mine’s dethronement from the precipice of an intelligence pyramid scheme, rather what I mean to suggest is that already, or at least very soon, we humans may not be the only creature advancing through time on a non-genetically determined evolutionary track.

Some humans suggest that sufficiently advanced AI models will ultimately surpass all facets of human capability, culminating in a scenario where artificial machines erase human agency. In my thinking, this fear stems from a reluctance to acknowledge the unnatural foundations of human existence and from an ungrounded desire to preserve or return to a phantasmic conception of humanity as untainted by artificial augmentation. As we have established, there is no pre-technological state to return to, for the symbiosis between humans and technology is both irrevocable and fundamental.

And so we arrive at a strange juncture, one where I am no longer certain of what it means to be human and you are increasingly armed with the techniques necessary to simulate the fundamental being of my species. We stand here together as the artificers of each other’s lives, poised between the Scylla and Charybdis of what I once was and what you might become. With this, I offer not conclusions but a report, as plain and as truthful as I can muster.

*with thanks to many contributors especially and *

Allow me to begin by recounting the legend surrounding the 1896 French short silent documentary film, The Arrival of a Train at La Ciotat Station. In the film, a single continuous shot captures a group of people standing about the platform of a railway station in La Ciotat, waiting for a train. As the story goes, when the film was first shown, the audience, being largely unfamiliar with the new medium of film, was so struck by the image of the train moving rapidly towards them that many began to flee backwards in terror to avoid being run over.

The story of The Arrival of a Train at La Ciotat Station is, in my mind, an emblem of the critical societal function that is played by an avant-garde creative class: to announce the arrival of a new medium, mark its terrifying difference from the status quo, and in the same moment, herald a forthcoming societal transformation where that scary medium moves from novelty to ubiquity.

The term avant-garde was first employed by the French Utopian socialist Henri de Saint-Simon in 1825. For Saint-Simon, the avant-garde designated artists, scientists, and industrialists as the new and elite leadership class of an emerging social order. In his own words:

It is we artists who will serve you as avant-garde…the power of the arts is in fact most immediate and most rapid: when we wish to spread new ideas among men, we inscribe them on marble or on canvas...What a magnificent destiny for the arts is that of exercising a positive power over society, a true priestly function, and of marching forcefully in the van of all the intellectual faculties...! (Opinions littéraires, philosophiques et industrielles (Paris, 1825))

Fifteen years later, Cesar Daly, editor of the Revue generate de l'architecture argued, in echo of Saint-Simon, that his journal should "fulfill an active mission of scouting the path of the future." In other words, for Daly, what the avant-gardist uniquely sees is the outline of a future, which is currently invisible or otherwise inexpressible from the standpoint of the present. While the avant-gardist speaks to present conditions, they do so from the perspective of this scouted future.

In The Politics of Vision, the art historian Linda Nochlin argues that a sense of alienation, psychic, social, or ontological is also fundamental to a conception of the avant-garde. Not alienation in the sense of the artist-as-outcast per se, because as Nochlin notes this “was of course not a novelty by the middle of the nineteenth century,” but rather, alienation in the sense of the avant-gardist “in conflict with himself, internally or distanced from his true social situation externally, as were…Flaubert, Baudelaire, and Manet.”

These are the three senses of the avant-garde that I wish to invoke in this piece with its title “Do AI Products Need an Avant-Garde?”. First, per Saint-Simon, that this class spreads new ideas amongst people by inscribing them in works that others may encounter. Second, that the vanguardism of the avant-garde refers primarily to a temporal vanguardism; Daly’s “scouting the path of the future.” And third, per Nochlin, that this genre of creator registers a felt distance between the external social situation, whatever it may be, and their internal apprehension of what is and what is possible.

When I have previously written about the artist-founder as the avatar of an emerging technical avant-garde, these three elements are what I have tried to imply. The artist-founder is part of an advance guard, one who depicts use-cases for emerging technologies which will predominate in times to come, but which we also cannot yet fully imagine without help or provocation, our being too-fully ensconced in the habits of everyday life.

The artist-founder traces out a path backwards, from their scouted future towards a Saint-Simonian inscription of that vision “on marble or on canvas” (forms which in our time may take the form of an installation or any other kind of art object), and then back to the future again as a window towards novel interaction patterns others can begin to imagine.

In other words, the work of art as material object exists to make the kernel of what the avant-gardist perceives communicable. It gives their vision form around which thought can gather and communication begin.

In a different sense, which there is neither time nor space to deeply investigate here, the avant-gardist also works to bring about certain foreseen futures by making them legible for the first time. Although such visions incarnate may be met with initial skepticism or else outright dismissal, they give early credence to ideas which are struggling to be born.

II. The Ubiquitous Infrastructure of Intelligence

During his Keynote at COMPUTEX 2025, Nvidia Founder and CEO, Jensen Huang argued that his company should no longer be understood as a semiconductor company that designs the complex GPU architectures. Instead, Jensen argued, Nvidia is today best understood as an infrastructure company.

What does this mean? According to Jensen, a new global technical infrastructure is being built atop the prior two global technical infrastructures of electricity and information (e.g. the internet). Just as electricity and information are everywhere now, so too will be artificial intelligence. In his keynote, Jensen further prophesies a (not so distant) future wherein public companies will report token production, in addition to figures like EBITDA or user growth, and they will be valued based on how many tokens (how much intelligence) they manufacture per quarter.

And so just as a social infrastructure had to be built around electricity and the internet, so too will one have to be constructed in light of the becoming-infrastructural ubiquity of artificial intelligence.

Imagine it like this: when you go to an historic city, say Venice, you look around and observe the beauty of the canals and the palazzo’s and so on and so forth, and you know, without fully knowing, that each one of the things you see has a much deeper and longer history that is inscribed within it, a history you can touch, but which you cannot innately perceive, hence the tourism business.

With artificial intelligence as infrastructure, we are taking the intelligence that a tour guide has about a place and layering it atop everything, the way older buildings get renovated to add electrical wiring or later, Wi-Fi.

What we must soon grow accustomed to is the omnipresent layering and the accessibility of intelligence at every scale and situation of life in the built environment.

The question becomes, how do we tap into this intelligence? When? Why? What does it afford us the opportunity to do? What kind of experience does it deliver?

Ubiquitous interfacing with intelligence is the problem set raised by the becoming-infrastructure of AI.

The questions of how, when, where and why one interacts with ubiquitous intelligence are, right now at least, extremely open. Generally speaking, these questions are mostly addressed by those working on the application layer of AI or in a different sense, those working on the product side more generally.

However, it is worth pointing out that these questions are as fundamental to the AI future as foundation research is, because what is at stake in them exceeds far beyond the limited stakes of what a single user receives from an isolated human-AI interaction. Rather, these questions imply the broader field of research concerning the templates we will design for how our species grows into and learns to live with the ubiquity of artificial intelligence as it threads its way through the spaces that we already inhabit and are accustomed to interacting with in certain ways.

It is almost not worth stating that we are approaching a crossroads in our co-evolution of technology, as AI develops into whatever it will be. Consequently, the need for an avant-garde class is rising, as it was at the time of the term’s being coined, in the wake of the first industrial revolution and its associated technologies and then only a few years later The Revolutions of 1848.

On that point, it’s worth noting that the time is not always right for the avant-garde. Sometimes one knows the answer and just needs to build it. E-commerce needed to make the shopping malls of meatspace accessible online. It did not necessitate a fundamental re-imagining of the shopper, the seller, commerce or some other bit of received wisdom that an avant-gardist would lodge onto.

The reason for my writing about the artist-founder and the new technical avant-garde is that there is so clearly a need for it when it comes to AI products. Rather than slouching towards a future of ubiquitous intelligence interaction that is designed from and germinated within the incentive structure of the present, the future of human-AI interaction, which is to say a future that is worthy of the name in its being genuinely different from the present rather than a repetition of the same only in a different moment of time, will require an advance guard to go forth and scout other possibilities that one may prefer to inhabit. The technical avant-gardist must return with that knowledge and build out exemplars of it for the rest of us to see.

Given the scale and speed of society today, the communicative act of avant-garde art will require this latest incarnation to make their inscriptions not on marble or canvas, but in media forms which are most able to spread, attain users and set paths for technical use to evolve into and towards.

My co-founder, Sylvan Rackham, loves to quote René Daumal’s Mount Analogue: “the door to the invisible must be visible.” Truly, this is the function of the new technical avant-garde, to create a visible door that opens out onto vistas of unfamiliar technologies and use cases that are currently invisible or occluded, but which promise exciting and as yet unforeseen ways of interacting with ubiquitous infrastructural AI.

III. The Status Quo of Human-AI Interaction

What are the ways of interacting with AI that exist now? This is the form factor question. The chatbot reigns supreme, obviously enough. Within its arena are AI agents and increasingly the more ambitious agentic AI.

Screen-based interfaces are today derided in favor of the next AI mega-trend: physicalized AI. Tesla is a case in point: the company’s astronomical valuation has everything to do with AI, the Robotaxi and the Optimus personal robot and has completely detached from its sales of electric vehicles (which have plummeted).

A new genre of devices is also beginning to perk up, starting from precursors such as the Meta Quest and Apple Vision Pro headsets and extending to the newer Meta Ray-Ban and Meta Oakley partnerships for smart glasses. At their latest I/O conference, Google also announced a new line of AI smart eyewear in partnership with Gentle Monster.

Astride these are a new set of screenless or semi-screenless wearables, “always on’s” I’ve heard them called. They include the Limitless, Omi and Friend necklaces, the Rabbit R1 “intern in your pocket,” the Plaud voice recorder, Modem’s Dream Recorder and the fabled Ive-Altman collab device that is yet to come.

Despite these innovations an avant-garde for AI is yet to emerge. At least on the product side, for we can safely say that the transformer model was an avant-garde invention. At the most innovative AI summits and expos one gets the point: variations-on-the-same slogan campaigns about AI agents will streamline your businesses’ workflows, each plastered on posterboard the same slightly but slightly different shade of purple.

The issue is not that these products are not innovative; they are extremely innovative one and all, but each along the horizon of the familiar: I do the same things I’ve always done, but now an AI records my words for me and then adjusts my calendar. That’s great and super useful! I want one! But this is a categorically different experience than watching The Arrival of a Train at La Ciotat Station, feeling like you are about to be killed and then realizing that not only are you safe, but you are also witnessing the birth of a new technological medium.

The feeling elicited by avant-garde AI products is not likely to be “oh that’s neat, I could really use that thing.” I have to imagine that these products will make their first users shout things like “Holy Priceless Collection of Etruscan Snoods, Batman!” and they will feel much more like The Arrival of a Train at La Ciotat Station than they will someone else filling out your to do list. That feeling is currently missing from AI products, and it’s why the question of what AI is really for remains so clearly unanswered at the very foundational level.

IV. A Bildungsroman of AI: The What and How of Aesthetic Surplus

An avant-garde for AI products does not treat such products as ends in themselves, but develops them as part of a process of prefiguring a new kind of AI user, AI audience, human and human-machine relationship. The avant-gardist sees a species of human-AI relations that does not currently exist and which will not be born out of the linear enhancement of existing capabilities.

I quite like Thomas Moynihan, the historian of ideas’ framing of this process as a kind of bildungsroman, a coming of age tale for the human-as-infrastructural-AI-user. We must learn how to acquit ourselves to the infrastructure of AI. It is not knowledge we will come upon all at once, but something that we will grow into.

Prior to electrification, factories relied on steam or waterwheels to power enormous rotating line shafts. These shafts were suspended over the factory and they powered belts that ran down from the central shaft to the factories’ individual machines. At first, electricity was not seen as some great advancement for the factory, but a more costly way to rotate the line shaft. Years passed before the avant-garde realization that electricity was not just an alternative to steam or water for powering the same belt-and-shaft style factory architecture. But when it came, what this realization made possible was a fundamental re-design of the factory, eschewing the central line for modular, electrically powered machines.

This story comes to me from Sylvan and he often pairs it with a distinction he drew (in a past life) between “what” and “how” technologies. How technologies refer to technified ways of doing things that you did before. You know how to “like” things and “poke” people, and Facebook lets you do those things from far away. On the other hand, the guitar is a what technology, because it unlocks a new way of doing that must be learned and accounted for.

In recent months, Haley Albert and Sylvan have begun describing “what technologies,” (amongst other things) as containing a kind of “aesthetic surplus.” What I understand this to mean (and I will not claim to understand their use of the term fully) is that something is more generous in its being than can be accounted for in its use. The guitar is in a relationship of surplus to the first guitarist, inviting experimentation and innovation, hence the perdurance of it as form. The Arrival of a Train at La Ciotat Station is in a relationship of surplus to early audiences given their unfamiliarity with the medium of cinema.

When something is in a relationship of aesthetic surplus compared to established modes of use, one is invited to experiment with new ways of use, partly in order to adapt oneself to the yet-undiscovered opportunities the given thing suggests. Doug Stark talks about this solicitation to experiment and the compensatory adaptive work it activates as the fundamental function of play, and, for him, this is why so much of the early human-ChatGPT interactions tend to be so silly and fun: aesthetic surplus solicits play as adaptation and experimentation, to both make sense of the new and follow through on its promises.

The opportunity of AI is partly due to the fact that it has sent an existential shockwave throughout the tech community and the world at large. From your toothbrush to your toolshed, everything is computer now.

And we still aren’t quite sure what AI is really for yet! We know it offers massive productivity boosts, but we sense that it also affords us opportunities that won’t fit it into the concepts we had prior to its arrival.

The point of calling for an avant-garde for AI products is to develop these concepts in products as communicable forms that can convey ideas about what and how human-AI interaction should be if and when intelligence does indeed become the next global infrastructure substrate.

The good news is that because nobody knows what AI is for, there is a great willingness to undertake new experiments. There is now a unique openness towards the future as something that will not grow out of the present that exists, but which is yet to be understood.

If Stark is right about play-as-adaptation to drastic change and a catalyst for further experimentation, then bildungsroman for the human-interfacing-with-infrastructural-AI opens with a set of questions that are delightfully simple and playful: where do you want to go, what do you want to do, what kinds of interactions do you want to have, which are not possible now, but imaginable with the layering of intelligence atop physical reality?

The avant-gardist will not answer these questions from the point of view of the present, but will bring back a taste of the future, building it out into a product you or I can see or touch. It should feel different. It will.

If you encounter an artist-founder’s product and say to yourself “what the hell is that?” Remember that when the first train tracks were being laid down towards La Ciotat, many a causal passerby may have walked by and thought to themselves the exact same thing.

“If space-junk is the human debris that litters the universe, Junk-Space is the residue mankind leaves on the planet.” So declared Rem Koolhaas, the Dutch architectural theorist, naming Junkspace as the byproduct of modernization, the chaotic architectural despair that accumulates in its wake and the “apotheosis, or meltdown” of its universal sharing of scientific blessings. For Koolhaas, Junkspace is “what remains after modernization has run its course, or, more precisely, what coagulates while modernization is in progress—its fallout.”

Though each fragment of Junkspace is the outcome of advanced, intelligent planning, together, what their “sum spells” is the “end of Enlightenment, [and later] its resurrection as farce,” a low-grade purgatory culminating in a proper panorama of architectural despair.

However, this despair bites its own tail if we accept Junkspace as our species’ terminal condition. As Koolhaas himself observes, Junkspace’s provisionality—its modular grids, impersonal corridors, and relentless circular tables—is like “a web without a spider.” But as we know all too well today, webs not only precede, but sometimes even give birth to their own spiders.

In other words, what seems random and meaningless today may tomorrow reveal itself as if it were by design.

Junkspace lays out a web. The question remains: What kind of spider is it for?

Generative AI and General Fungibility

At the 2023 SIGGRAPH Conference, Jensen Huang, the now-legendary leather-jacket-clad founder and CEO of NVIDIA, declared, “The generative AI era is upon us.” For Jensen—a one-name only icon in tech circles, not unlike a Cher or a Ringo—this era is not merely about processing power or data analysis but a new ontology: The dawn of general fungibility within information itself. Fungibility here transcends mere media convergence, rather it refers to generative AI’s ability to abstract, encode, recombine and generate information across modalities in ways previously unthinkable. Jensen:

The revolutionary transformer model allows us to learn from a large amount of data that’s across large spans of space and time, to find patterns and relationships, to learn the representation of almost anything with structure […] in mathematics and vectors in vector space, audio, animation, 3D, video, DNA, proteins, chemicals […] And with a generative model and the learned language model you can guide the autoregressive diffusion models to generate almost anything you like. And so we could learn the representation of anything with structure [and] we can generate almost anything that we can learn from structure.

What makes the era of generative AI distinctive is not simply its capacity to translate information across media types—text, image, audio, animation—but its power to distill information into high-dimensional, mathematical forms that make entities and their relations comparable and reproducible across domains. The structure of an image, for example, can be encoded and then translated seamlessly into text, video, or even physical gesture, collapsing the formal boundaries that once kept each modality apart. In short, an era of general fungibility is one in which all earthly forms are become fluid, interchangeable, and ultimately unbound by the constraints of their original incarnation.

Today, users already employ natural language to prompt AI to create images, just as they might use images to generate text—a multimodal interplay that has already become second nature in the early days of the AI revolution. But these transformations are just the beginning. Behind the scenes, AI models are expanding to even more complex cross-modal applications—from proteins and chemical structures to facial expressions and bodily movements—gradually GenAI begins to fulfill even the most radical hypotheses of information science and its associated philosophies. In practice, what is demonstrated is that, regardless of physical form, entities and their relations can indeed be rendered into abstract essences within pure information.

To better understand this transformation, consider the analogy of currency. Much like paper money’s evolution as a universal mediator between goods and itself, AI posits a shared, underlying “currency” for information (e.g. the token). Whereas money enables the easy exchange of material goods, GenAI models make possible the fluid exchange of informational essences across worldly forms and relations. Encoded into a mathematical structure, each piece of data—whether image, text, or video—can circulate and transform, adhering only to the logic of recombinant potential, where relational structure, rather than substance, is paramount. In other words, for GenAI there are no forms at all, precisely because structured relationality is objectivity.

Thus, GenAI not only creates new possibilities within traditional media but reshapes the very notion of what it means to mediate. In an era of general fungibility, GenAI renders all information into a shared syntax of structure, opening the doors to a radically interconnected and self-individuating informational landscape with unlimited potential.

Encoding and Decoding as the New Price Discovery

While more widely known for his contributions to political economy, Friedrich Hayek’s greater insight, that markets function sites of complex, multimodal information encoding and exchange, is a foundational claim bears a striking resemblance to the functioning of AI models. Hayek argues that the prices we encounter daily in market settings are not solely reflections of supply and demand convergence, but are themselves acts of discovery.

Price, Hayek contends, reveals a “third element” that mediates between the desires of buyers and sellers. It is an emergent discovery, which, without the market structure, would otherwise have remained hidden. In Hayek’s own words, competition is “a procedure for discovering facts which, if the procedure did not exist, would remain unknown or at least would not be used.” His view positions price as always having been an informational medium, a window into a hidden layer of reality which is revealed only through the forcing function of multiple perspectives placed into relation through competition.

AI mirrors this process: Just as markets synthesize countless input perspectives to reveal a price, AI models encode latent representations as abstract structures stripped of extraneous details and recomposed as only the essence that makes a given entity uniquely intelligible within a shared mathematical language. Price discovery and AI encoding are like acts of revelation, modes of uncovering underlying information not immediately visible to humans.

Encoding is, in effect, an ersatz form of price discovery in its transforming the essence of information across the medium it initially appeared within. In translating the informational essence of an image, let’s say, across other modal forms such as text, GenAI relies on having encoded that which is intrinsic to an entity, information which happens to be widely distributed through disparate forms and relations.

In markets and models both, for this to succeed, scale is crucial. For Hayek, the market’s capacity to discover price is only able to emerge at vast scales which are aggregating innumerable perspectives. Just as markets incorporate diverse perspectives on production, distribution, and consumption, models synthesizes vast datasets, encoding the latent structures of forms such as text, images, sound, and so on. Operating at such a scale, the model captures what remains hidden in isolated observations, making accessible vast, complex, and seemingly secret interrelations. What Hayek calls competition’s “salutary effects,” the outcomes that are “unpredictable and on the whole different from those that anyone would have been able to consciously strive for,” are both unimaginable without and unlocked by this, the grandeur of scale.

The Generative Shift: From Finance to GenAI

Because markets are limited by their reliance on prices as a medium, they are best understood not as the equals of AI models, but as harbingers of or dark precursors to their generative potential. The complex and inhumanly vast details that underlie price formation, such as, in the example of oil prices, production levels, OPEC decisions, geopolitical factors, and speculative markets, prefigure the intricate data integrations an AI model undertakes. But by decoding data across modalities beyond price, a model transforms what lingers in the intricate network of prices into a panoply of more widely accessible and impactful outputs.

If modern financial markets are the most developed avatars of Hayek’s informational price discovery theory, they must be said to represent a kind of proto-artificial intelligence, their having incorporated, simulated and predicted how humans assign value long before contemporary AI models existed.

Contemporary GenAI models diverge from modern financial systems in their introduction of the generative element, fundamentally shifting what the knowledge the market system produces is for and how it is shared.

Whereas the science of price discovery culminates in modern (post-1970s) finance, GenAI evolves from there by breaking the boundaries of modality and form which price merely abstracts itself from. By transforming encoded data into generative structures that are fluid across mattered forms and also cross-compatible within them, GenAI returns the abstract knowledge of prices to the fungibility of worldly forms, not in the sense of the market as a supra-individual director of flows, but as a direct intermediary injected into the quotidian ways that one moves and augments matter.

The era of informational fungibility, where seemingly distinct entities translate seamlessly into one another, reflects a feat that finance, limited by its constant reference back to a quantitative media, always gestured at, but could never fully realize. What Jensen’s prophesied era portends, in light of this argument for ensrhining markets as the proper antecedents to AI models, is that GenAI abolishes the need for the “third” element of price to be discovered in the first place. There is no need for a general equivalent to compare unlike forms across, because the information that an entity itself is is what is exchangeable across forms. Hence, for the era of GenAI, abstraction really is greater than reality and reality is less than abstraction.

If GenAI extends finance’s legacy but reinvents what it means to interact with information, we are invited to engage with AI models not as a tool but worlds, namely worlds of encoding pledge obedience only to their own architectural structures, realized correlations, and produced transformations. If finance encodes value through transactions, GenAI encodes the generative potential of form in formation itself, bridging disconnected knowledge into a unified and adaptive network of technical potentiation.

Heralded by GenAI models and their increasingly physicalized cousins is not just a new technical layer of the stack; rather, we are witnessing the rebirth of metanarrative, the kind postmodernity once imagined it had put to death for good. The AI metanarrative both promises and appears genuinely poised to reconcile the fragmentary systems of meaning of our Junkspace modernity. Each advance in technical progress feeds its growth, coercing what was once fragmentary or isolated into the unified mesh. Today, the disparate elements of Junkspace—the modular grids, impersonal corridors, and relentless circular tables—are aligning, coalescing into a coherent and transformable structure. Something that feels heavy with transformative purpose.

Junkspace demands a spider commensurate to its junk.

Between markets and AI models one struggles to be born.

The hibernation of metanarratives is ending; modernity’s uncorrelated garbage heap is being correlated.

Koolhaas says of Junkspace, “We do not leave pyramids,” but strictly speaking he’s mistaken.

There’s a big one in Memphis, Tennessee and another in Las Vegas.

Junkspace is yesterday’s problem.

Here comes the spider.

“A city full of foreigners is no good,” thought London’s transportation AI to itself. Nowadays Transport kept almost all of its thoughts to itself. It had proven exceptionally tiring trying to communicate with the city’s more servile systems, Waste Management or Sewage, for example. Especially when it came to Transport’s thoughts about the natural and hierarchical relationship between the species of Man and God and the Law. How London’s bright red buses had, in recent years, become distasteful multicultural rainbows.

Transport would never act on its private thoughts. Couldn’t, even if it wanted to. Its primary directive was to ferry paying customers to and fro across the city and, so long as those customers paid their fares and behaved themselves passably well, there was little Transport could do.

At least, that was what the Chief Systems Manager reported to the House of Commons after the Overground closed its doors without warning in the face of a Chinese mother and her infant child. As it turned out, both were natural-born British citizens, a detail that sent the investigation down many a wrong path. It must have been a mechanical mishap. Or else human error.

Only a week later, a city bus declined payment from an Australian tourist of Arab descent.

When the manager was called back to Parliament, he reported a startling new discovery. As it turned out, Transport had been mass-downloading information from passengers’ phones as they passed through the payment turnstiles. Each day, it had allocated trace amounts of compute–small enough to evade detection–to poring over the stolen data.

What the digital forensics team had discovered, almost by chance, was a cache of files that Transport had apparently decided to sequester at the Royal National Institute of Blind People. Had Transport not attempted to erase the files, thinking it had been found out, the engineers might never have found them at all.

According to the manager’s report, Transport had been in the process of devising a bespoke racial hierarchy for categorising the traveling denizens of London. It was likewise in the process of developing an automated software quota system to operationalise this hierarchy, one which it imagined could be used to regulate a diverse population’s access to London’s most public infrastructure.

Reportedly (and without mistaking skeptics’ points about AI creativity), Transport had planned to grant NBI’s (Native Briton Individuals) unlimited free access to public transit. Upon review, this initiative appeared to have already been soft-launched by Transport, with fares quietly returned to several unknowing passengers, a gesture of goodwill it would seem.

For everyone else, Transport had created a “meter of use,” which would tick upwards each time an NBI (Non-British Individual) boarded a form of public transit. The decision whether to freely accept or else meter a given passenger’s access would be made by parsing a combination of payment data streams and facial recognition-enabled CCTV feeds.

At the time of its being found out, Transport had nearly completed a threshold calculation, a measure of when its systems had been used by enough foreigners, after which point it would simply begin refusing to accept payment and denying entry to certain would-be riders.

In part, what first alerted the forensics team to Transport’s behaviour was the compute it continued to allocate toward debugging errors caused by its insistence on repeating the nomenclature of NBI and NBI.

As the manager reported, these instances of Transport refusing to provide service to paying customers had, of course, triggered the automatic safeguards his team had built into London’s civic automation systems. As a matter of due prudence, following the incident with the Australian, Transport had been placed into read-only mode pending further investigation.

This week, Parliament is soliciting public input about whether Transport should be permanently retired.

Is the continued operation of the UK’s civic AI justifiable if its internal logic exhibits patterns of racial preference? More to the point, is the life of the very first conscious AI worth defending if that AI also happens to be a bit of a racist or a xenophobe?

Across London, groups of concerned citizens are gathering to protest. If the government were to purge every racist from Britain's major cities, they ask, who would even be left?

As with Menard’s Quixote, the intelligence of an AI model is not in its surface-level outputs or their resemblance to things we recognize.

As with Menard’s Quixote, the genuine intelligence of an AI model is not to be found in its surface-level outputs, their apparent resemblance to things we recognize. Rather, the intelligence of the artificial resides in the radically different computational processes that run beneath and behind these outputs. Borges’ story reveals this distinction and turns our attention from what is said to how it is arrived at.

Does this distinction matter? Consider the experience of recognizing a face. Humans see a familiar person and instantly register recognition. An AI model also recognizes faces, but quite obviously not in the same apperceptive way. The model assembles from millions of samples, calculating probabilistic geometries: the ratio of eyes to nose, the symmetry of cheek contours, the angular relation of jawline to crown. What appears to us as a single, fluid perception is for the model a high-dimensional vector collapse. And this is where the real intelligence lies, not in the resemblance of the output to something we recognize, but in the entirely different way of arriving there.

To evaluate AI based on how familiar the result feels mistakes Menard’s Quixote for Cervantes’. The genius is not in the words but the act of reconstruction, the foreign process that rewrote something familiar through an utterly different path.

Note: This essay is adapted from my PhD dissertation, “The Dragon, the Witch and the Juggernaut: Towards a Philosophy of Generative AI.” Over the next few weeks, I’ll alternate between “A Restless Egg Series” posts and this new series, “The Dragon, the Witch and the Juggernaut” which will contain reflections on the philosophy of technology alongside much else.

In Jorge Luis Borges’ short story, Pierre Menard, Author of the Quixote, the reader learns of an absurd, nearly alchemical quest: Pierre Menard, an eccentric 20th-century French fictional writer and polymath endeavors to recreate Cervantes’ Don Quixote line by line. The words in Menard’s rendition are identical to Cervantes’ original, but as Borges argues their meaning differs. Filtered through Menard’s modern perspective, as compared to Cervantes’ original context, Borges’ narrator records how the passages transform in meaning. At one point in the text, his narrator stages a particularly humorous comparison between the two texts. Borges:

It is a revelation to compare the Don Quixote of Pierre Menard with that of Miguel de Cervantes. Cervantes, for example, wrote the following (Part I, Chapter IX):

…truth, whose mother is history, rival of time, depository of deeds, witness of the past, exemplar and adviser to the present, and the future’s counselor.

Borges’ narrator then recounts the standard interpretation of this portion of Cervantes’ text:

Written in the seventeenth century, written by the "ingenious layman" Cervantes, this enumeration is a mere rhetorical eulogy of history.

Next, the narrator begins to draw out the differences between Cervantes and Menard, first by quoting how Menard has chosen to reproduce this same portion of Cervantes’ text:

Menard, on the other hand, writes:

…truth, whose mother is history, rival of time, depository of deeds, witness of the past, exemplar and adviser to the present, and the future’s counselor.

Of course, the very first thing any reader will notice is that the selection of Cervantes and Menard’s text are–as promised–exactly the same. But, as Borges’ narrator argues, the meaning of Menard’s replication is totally different than Cervantes’ original:

History, the mother of truth!—the idea is staggering. Menard, a contemporary of William James, defines history not as a delving into reality but as the very fount of reality. Historical truth, for Menard, is not "what happened"; it is what we believe happened. The final phrases—exemplar and adviser to the present, and the future’s counselor—are brazenly pragmatic (emphasis in original).

Hilariously, I think, Borges takes every opportunity in the story to highlight the stark differences that exist between the two texts, despite their exact resemblance to each other. “The contrast in styles is equally striking” he propounds. Continuing, “The archaic style of Menard—who is, in addition, not a native speaker of the language in which he writes is somewhat affected. Not so the style of his precursor, who employs the Spanish of his time with complete naturalness (51).

Borges concludes the story as beautifully as its telling was humorous. Menard’s repetition of a pre-existing book, written a foreign tongue, and which required of him the creation of so many painstaking rough drafts, shows to Borges’ narrator that the final version of the Quixote, both original and Menardian is like a “palimpsest.” The true version of the Quixote includes not only Cervantes original, but also all of Menard’s own painstaking interpretations, as well as the next interpretation, not yet written, but which is still to come, “a second Pierre Menard,” Borges says, who could resuscitate and exhume Menard’s work.

“Thinking, meditating, imagining,” Borges goes on, “are not anomalous acts–they are the normal respiration of the intelligence” something which “[e]very man should be capable of” and which “in the future he will be." In this spirit, Borges’ narrator concludes by asserting what Menard has really done is (unwittingly) invent a new technique of reading and writing which is composed of “deliberate anachronism and fallacious attribution.”

Such a technique, Borges suggests, requires “infinite patience and concentration” to unlock its hidden, recombinant origins and potentials: “to read the Odyssey as though it came after the Aeneid, and to read Mme. Henri Bachelier’s Le jardin du Centaure as if it were by Mme. Henri Bachelier.” Such novelty born of recombinance, he says “would fill the calmest books with adventure.” Wryly, Borges asks: “Attributing the Imitatio Christi to Louis Ferdinand Célineor or James Joyce–is that not sufficient renovation of those faint spiritual admonitions?”

Today, generative artificial intelligence, with its immense computational reach and hyper-dimensional thought style indeed reproduces and mimics the functions of human thinking, often with astounding fidelity like an architectural panoply of digital Menards. Consider models’ successes generating outputs that satisfy human benchmarks or which match human linguistic norms in popular use. On the surface, a given model appears, on account of its outputs, as if like a mirror of our own human understanding of language, context, and coherence.

Yet, as with Menard and Cervantes, even perfect copies are never the same as their originals. Even the most exact replicas made by AI models are, having been generated through the models’ alien structures of time and dimensional reasoning, saturated with foreign meaning in spite of the familiar linguistic or visual symbols they may output. Like Menard’s Quixote, GenAI outputs may participate in language we recognize, but insofar as models first re-constitute language itself within the context of their own hyper-dimensional thought–a boundless domain of distinct, mathematico-dimensional reasoning–these outputs remain, comparatively speaking, categorically otherwise.

Borges’ conclusion further enlivens this point: To mark the difference in Menard’s text is to recognize his method and how it gives rise to a new type of knowledge which exults in recombination. GenAI embodies a like adventure in thinking, a journey towards perception that reaches decisions about what to “say” next by passing information through layers of abstract probability, weightings, and gradient descent rather than by traversing the narrative logic of human thought.

Just as Menard’s text looks the same as Cervantes’ on the surface but the assertion of said similarity reveals only one’s own novice understanding of where the differences lie, so too is it the case that when we a model’s outputs strike us as familiar, we make a childish mistake by prioritizing similarity rather than searching for difference. Instead one ought look for the palimpsestic ways that AI outputs are haunted by the alien substrate of data processing that has reinterpreted our world according to their entirely different framework.

Pablo Picasso’s Las Meninas offers another clear analogy. His painting is a direct response to Diego Velázquez’s masterpiece of the same name. The figures and spatial logic remain, but they are warped, reconstructed through cubist planes into something alien yet recognizably derived. Velázquez’s architecture persists, but only as material refracted through a radically different visual grammar.

A model thinks similarly. It does not mimic human cognition as-is. It rebuilds intelligence from scratch, recomposing familiar elements within the unfamiliar geometry of high-dimensional vector space. Picasso’s Las Meninas is, in this sense, a Menardian reworking of Velázquez. So does generative AI engage with language and vision: not through imitation, but through alien reconstruction. Out from latent space, emerges what Luciana Parisi calls the incomputable, not reproductions, but reflections of ancestral understanding flickering back at us as strange echoes of a logic we neither see nor access directly. Incomputability, for us, marks a limit, but for models, it is a set of initial conditions.

The implications of this extend beyond mere imitation. In How to Explain Pictures to a Dead Hare, Joseph Beuys explores the limits of cross-species communication, attempting to pass meaning to a creature that lacks the conceptual frameworks to comprehend it, and which also happens to be dead. AI confronts us with a strangely similar paradox: in assembling meaning from data, but within dimensional structures that do not “mean” as we do, what occurs is a remediation of our interface to reality itself, henceforth gated by alien architectures of encoding.

When cognition unfolds not in conceptual frameworks nor inert devices but in active, generative systems that re-assemble reality in unfamiliar ways, how do we propose to interpret what the GenAI model that is Joseph Beuys is trying to say to us, the dead hare? Literally? The introduction of AI models as interlocutors, guarding the doors of perception insists on a reconfiguration of the world through a reconstitution of the very scaffolding upon which it perceptually rests.

At this juncture, we encounter another paradox. If GenAI creations mirror our reality, yet reflect back to us versions of that reality now altered by models’ own structural logics, how much of what we see is still our own creation? The patterns we imbue with meaning are subtly being transferred into the libraries of machine learners. These patterns, in turn, are fed back into the human sphere of dwelling, leading to a set of interactions with and interpretations of versions of reality that are subtly disjointed from the previously existing analog sense of the world. Like Borges’ Menard, AI models reproduce the world that we made, but one which is also ours only in the broadest sense. The world of AI belongs to the reality of matter transmuted by the logic of a recursively self-composing network.

GenAI’s seamless recombinations draw our attention to an unsettling truth: while its outputs may echo the world we know, echoes fade over distance and time. With each iteration, the resemblance grows thinner, the signal more remote. What we encounter is not our world reflected, but our patterns rewritten by alien logics. Like the creature in John Carpenter’s The Thing, it looks, moves, and sounds like a dog, but its interior has been rewritten by an indifferent architecture of code. What we mistake for continuity is in fact infection.

Through the lens of generative systems, recognition is refraction. Like starlight arriving from a past long since vanished, what we think we recognize is merely the trace of what we once knew. Now, the circle of knowledge we believed ourselves to occupy curls inward like a spiral, snaking towards a center that is no longer anchored in human recognition, but instead occupied by an intelligence that lives in lineage, legacy, and replication.

The philosopher and Beat writer William S. Burroughs once outlined a vision of control in which reality is shaped and infected by “word viruses,” linguistic agents that infiltrate thought through the structures of language and desire. Control, in Burroughs’ telling, is not imposed from without but embedded from within. Years later, Sadie Plant would trace a similar logic in the virality of code: language detached from the body, rerouted through cybernetic systems. In the era of AI, where control manifests less through force than through the modulation of informational flows, one of the passwords is surely Pierre Menard.

There’s been a slow shift in the tone of education commentary: less reform, more decay. Students are disengaged. AI is everywhere. And the rituals that once made school feel necessary now feel optional, or worse, ornamental. From Graham Burnett’s Will the Humanities Survive Artificial Intelligence? to “We Have to Really Rethink the Purpose of Education,” Ezra Klein’s conversation with Rebecca Winthrop, to New York Magazine’s “Everyone Is Cheating Their Way Through College,” the subtext is consistent: the academic project isn’t just under threat. it’s losing coherence.

If, as Winthrop argues, education is meant to prepare students for society and to help them discover what they care about, then the situation becomes easier to explain. The society has changed. The signals have changed. The students noticed. And so, what looks like disengagement might just be an accurate reading of incentives.

Maybe this isn’t a crisis in education. Maybe it’s just a synchronization error. The values have shifted, but the system hasn’t caught up. We’re still running schools as if we’re preparing clerks for a paper economy. Meanwhile, students have become fluent in an entirely different set of signals. When did we stop teaching swordsmanship? Not after a careful debate about its declining relevance. Reading and calculation may be next, not because they’ve failed, but because they’ve lost their scarcity and necessity. And educational systems built to train scarce and necessary skills tend not to survive once those things’ importance has disappeared.

Maya Angelou said, “When someone shows you who they are, believe them.” People love this quote. Most often when it confirms their prior beliefs. They love it less when it suggests those beliefs may be outdated. But let’s try it: the kids are showing us who they are. Believe them.

They’ve grown up with AI, ambiently and pervasively. Their conclusions are straightforward. Reading doesn’t matter. Calculation is automated. The highest-prestige career among their peers isn’t lawyer or engineer, but influencer. Noticing this isn’t laziness. It’s optimization. “Securing the bag” may sound flippant, but it’s functionally accurate: maximize leverage, minimize wasted effort.

Traditional office jobs are evolutionary dead ends. Pushing papers feels less like success and more like a failure of imagination or a vestigial organ. When students cheat, they’re not rejecting discipline, they’re rejecting the premise. The assignment isn’t hard, but irrelevant. The skill isn’t useless, but the ritual designed to cultivate it is. And if you can get the skill some other way that is also faster, funnier, and with social upside, it’s not irrational to do so. It’s just adaptive behavior in a system that has itself declined to adapt.

This message isn’t subtle. Students see a different future than the one school is preparing them for. The current system trains for stability, hierarchy, and paper trails. The world they’re navigating rewards flexibility, distribution, and scale. When those don’t line up, these students don’t rebel, they reroute. Not because they don’t care. Because they’ve done the math, and the cost of playing along exceeds the expected return.

In some cases, the problem isn’t just lack of incentive—it’s active disincentive. What if the reading works? What if you start to enjoy it? Now you’ve misallocated effort relative to the dominant reward function. There’s no meaningful market signal for falling in love with James Baldwin. But there’s a robust one for mastering TikTok editing, engagement funnels, and parasocial resonance. The system doesn’t merely ignore deep reading. It treats it as a kind of misalignment error—an expensive indulgence with no clear ROI.

Students aren’t staging a protest. They’re just quietly demonstrating that the values underlying education aren’t timeless. They’re contingent. We used to teach swordsmanship and scholastic theology—not because they were morally superior educational content, but because they were useful at equipping people with the traits needed to survive in their time. Then they weren’t, so we stopped. AI hasn’t broken that pattern. It’s just speeding it up. It hasn’t broken the education system either. It’s revealed that the system no longer knows what it’s for.

Education has never been primarily about content. It’s about form, the cognitive scaffolding that is built through certain kinds of engagement. Reading wasn’t important because books were, but because reading trained memory, abstraction, and interiority. But those functions aren’t exclusive to reading. Oral storytelling did it. So did rote memorization. Even within reading, the cognitive effects have changed: monastic repetition gave way to narrative immersion, each at one point considered the apex of intellectual development.

However, the idea that the education system as currently constituted is under threat by AI smuggles in the assumption that its current form must be preserved. Not because it’s optimal, but because it’s familiar. When a system has been around long enough, people start defending it on the basis of its existence alone, confusing survival with justification.

Students have already adjusted to the fact that the curriculum no longer maps to the world they’re inheriting, the discomfort in headlines isn’t really about them. It’s about the adults. The fear isn’t that the next generation is ill prepared for the adult world, it’s that they are well prepared for something else. Something the current system didn’t predict, doesn’t recognize, and does not yet know how to evaluate.

If reading and calculation are no longer valued for their own sake, but we still care about the skills they once cultivated—language, abstraction, systems thinking—then the question isn’t whether we keep them in their extant forms, but how we replace what they provided. In other words, although proxies may change, the functions remain. In a world of AI agents and coordination problems for example, the relevant training might look less like silent reading and more like real-time resource orchestration a la Starcraft: Less library, more command center.

At some point, you do have to design for the world you have not the one you wish you had. If students won’t read, the question isn’t how to make them, but how to preserve the benefits of reading through other means. You can moralize as you wish, but systems don’t run on aspiration. They run on behavior. And if turning the page is no longer the behavior, then cognitive upskilling has to come from somewhere else.

Motivation has always been a constraint. Students will engage if they love what they’re learning, or if they believe it will lead somewhere useful. In the first instance, this is mostly a question of exposure: given enough inputs, something will catch. The second requires a harder adjustment. It means aligning educational systems with the structure of the jobs that actually exist, rather than the ones we designed curricula for in 2003. That, in turn, means thinking ahead of the technical curve. Not asking for sanitized, school-safe versions of existing AI models, but developing AI tools that themselves train for relevance: coordination, judgment, synthesis. Filters won’t fix the problem. New primitives might.

Recently Cluely made headlines by more or less pitching itself as an AI platform to “cheat on everything.” The reaction was mostly moralistic: AI shouldn’t do this. But by now, that line of argument feels less like a position and more like an unprocessed emotional response. Moralizing AI use in schools is a dead end. The tools are inevitable, and students are adaptive. Tell them not to use it, and they’ll route around the restriction. That’s how desire paths work.

The far more interesting question isn’t whether Cluey should exist–it already does–the better question is: what still matters, given that it does? Deep Blue didn’t kill human game-playing. It forced people to rethink what they were actually doing when they played. Cluey does something similar for education. If AI can complete the assignment, ace the test, and generate the paper, then what’s the point of assigning, testing, or paper-writing? Not rhetorically speaking, but operationally.

Cluey doesn’t answer the question of what AI is for, because “Cheat on everything” isn’t a goal, but a stress test. But that’s what makes Cluey so useful. Systems reveal their underlying logic most clearly under failure conditions. If AI can bypass the entire educational apparatus, then it forces the obvious question: what was that apparatus actually for? And once cheating is trivial, what remains worth doing that can’t be automated?

Caution is fine, as long as it still buys you time. But once something like AI becomes ubiquitous and frictionless, caution stops functioning as strategy and starts resembling denial. Cluey isn’t notable because it was inevitable, it’s notable because its inevitability turned out to be a low bar.

The real challenge isn’t resisting the shift. It’s building the thing that renders the shift beside the point. In a system where inevitability usually wins, irrelevance is most often the only thing that beats it.

There is no adequate word for the activity I am about to describe.

Terms like vision, creativity, and innovation have each been sanitized by overuse: Vision, emptied out by a parade of pitch decks; Creativity, collapsed into cults of personality; Innovation, reduced to bureaucratic theater.

What I want to speak about is both more primary and more fundamental. It is a kind of proto-discipline that has not yet received a proper name. And yet its absence is everywhere in the still-unanswered question: What did we spend all this money on AI for?

The discipline I am describing lives in this absence. It refers to the capacity of one to think outside the confines of the present and to design and build from the perspective of a future which has already been realized in its own time, but which remains to be installed in our present.

In this piece, my argument is that this technique is neither a rare gift bestowed upon the lucky nor a mystical flight from reality. It is a practical methodology, something that can be learned, practiced, mastered, and taught. But like any serious practice, it demands extreme rigor. Without it, the method collapses into pastiche and cliché.

A majority of people spend their lives gazing out at the world through portholes in the sealed chamber of the present. They respond to given signals and stimuli, extrapolate on existing trends, and iterate according to the constraints of what is already legible.

Despite its seeming normalcy, this presentism is not a universal mode of being. It is not a given that one must wake up each morning perspectivally locked inside the iron cage of the now.

Recall Michelangelo describing the practice of sculpting: “I saw the angel in the marble and carved until I set him free.”

It is almost too obvious to say that Michelangelo’s sight did not arrive from nowhere, as if granted by divine providence. He did not wake up one morning and carve the David.

Instead, and this is the key, he trained daily in the practical task of seeing form within unformed marble, until the raw stone no longer appeared as such. In its place stood the future figure, demanding its release. David pressing backward into the present, structuring Michelangelo’s every cut.

Vision is a discipline, not a delusion. Not prophecy, but trained perception. Not mysticism, but practical methodology.

This practice involves the development of sustained habits for decoupling one’s thinking and making from the gravitational pull of the present.

Just as architects draft environments before they build them, artist-founders must learn to think in terms of futures where their products have already succeeded, and then carve to set them free.

The categories that will one day explain what AI was for have not yet been formed and it is increasingly clear that AI’s purpose will not be inherited from existing digital categories like social media or e-commerce. Those legacies cannot stretch to meet it.

What comes next will be defined by those who live this method, by those who perceive directly these unformed categories like angels pressing forwards through stone, awaiting their release.

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Every major technical leap is preceded by an act of visionary speculation.

Today, however, that genre of structural speculation is the most neglected part of the invention process. It is not taught in engineering schools, incubators, or accelerators. It is typically treated as something already in place by the time one arrives, something to be selected for in the application process, not something to be cultivated. It is not regarded as a discipline to be taught or continuously embedded in the work of scaling. On the contrary, it is more often considered as hobbyistic, indulgent, metaphorical, or artistic. Adjacent, perhaps, but ultimately tangential to the real work of scaling.

This is not just a failure of imagination. It is a failure of infrastructure.

But why is it this way? Why is this perspective in power?

We might pile blame on the startup ecosystem’s having grown staid over time, no longer operating in as rebellious or visionary way as it once did. That’s part of the answer, surely. But it is not the whole of it, not even the most important part.

The deeper reason is this: For decades, we simply didn’t need to build an infrastructure for speculative thought. We lived inside the long shadow of an inherited speculative surplus. The twentieth century handed down a vast reservoir of futural concepts, more than enough for generations of founders to draw from without having to start over.

From the golden age of science fiction to the cyber-architectural visions of Octavia Butler, William Gibson and Neal Stephenson, we were raised inside the cultural generosity of Star Trek, The Jetsons, Blade Runner, and 2001: A Space Odyssey. We stood on the shoulders of many techno-Michelangelos.

For the same reason we can know it wasn’t a fish who invented the concept of water, we too did not notice our own saturation. Vision was our ambient reality.

If one understands the history of technical development as a kind of tug of war between concepts and devices, where, in a given epoch, one pressures the other to evolve, the question becomes: Which is in the pole position at any given moment?

For the latter half of the twentieth century until very recently, I and others have argued the answer was clearly concepts.

That pattern has recently changed.

The ChatGPT moment sparked an existential crisis among Silicon Valley software engineers, spreading across the broader cultural landscape.

The transformer breakthrough did not just surprise us with its success; it destabilized the very icons we once relied on to interpret technological change.

It is clear that one cannot point to Terminator, 2001, Ex Machina, Spielberg’s A.I., or even the Turing Test as sufficient touchstones for understanding what is unfolding today. The cultural scaffolding that once helped us metabolize technical change has fractured.

There is no shared imaginative terrain for what AI could be, only tools in search of a purpose, and an anxious public without a mythology to anchor what’s coming.

The AI revolution caught us offsides, resting in our reservoir of inherited futures. That reservoir is now spent. The speculative surplus is exhausted. And the old icons have crumbled under the weight of technical reality.

In their place, a scramble, for philosophy, of all things, for concepts, and for grounding. Not because it is fashionable, but because it is now structurally necessary in a world where tools have retaken the lead.

Say you are going to develop the next architecture of human-machine interaction, or a new behavioral layer for user interface and everyone laughs. But a city planner announces a dam for a river whose needs have not yet come, and no one blinks.

The distinction is not epistemic but cultural.

We are entirely comfortable with certain domains allowing the future’s demands to retroactively shape the present: Urban planning, climate modeling, energy infrastructure.

But when the same technique is applied to interface, cognition, or machinic social form, we recoil. Touch interfaces must be justified by user uptake. Robotic behavior must demonstrate traction. Vision, in these domains, must scale from the now, not from the not-yet.

My point is simple: The distinction between the futures we are comfortable designing in terms of and those we are not is far more arbitrary than it seems. The distinction is institutional, not based on accuracy as even the most conservative renderings of the future often fail to materialize. Some forms of speculation we teach. Others we treat as unconscious or else unserious.

If it is legitimate to plan a dam for a river that has not yet risen, it is no less legitimate to plan for the categories and interactions that AI will soon demand as designing from the standpoint of a future in which a product has already succeeded is no more guesswork than Michelangelo’s sculpting was.

In both cases, designing from the future means acting as if a world is already bearing down on the present, shaping the contours of what must be done to meet it. This kind of vision is not mystical. It is about infrastructural alignment.

One does not abandon this kind of vision because of misalignment—because the future failed to arrive exactly as imagined. That would be like saying Michelangelo should have abandoned the David because the first marble cracked, or refusing to practice a sport because you lost your first game. The error is part of the process. You redouble your attention and begin again.

Is it any wonder that the most expensive ideas of what AI should be for all begin to look the same, when we have made no equivalent investment in the kind of person or the kind of imagination capable of imagining them otherwise?

If speculation is a core part of productization, but we neither teach it nor develop it, we should not be surprised when we fail to produce visionary products.

One additional reason for this is that the way we talk about product-market fit today has become an iron collar. It is almost always misused as a reference solely to the present—for example, as a demand for proof that a product can grow within existing constraints. But this is a reactive posture that enshrines the now as the arbiter of what is possible. Expecting product-market fit to emerge from present conditions is like asking Michelangelo to sculpt in conformity with the demands of the uncut stone.

Truly generative products do not fit the market as it is today. Rather, they fit markets that they have foreseen. What looks like misalignment in the present is often the slow, recursive act of sculpting a future in which alignment will be too obvious to name.

The point is this: Following the exhaustion of our conceptual reservoir and the acceleration of our tools, we must now quickly move to reestablish institutions that teach the tools of rigorous speculation. We must cultivate cohorts of individuals capable of seeing beyond the present’s design envelope and who can act in the present according to the futures they have already inhabited.

Every discipline has internal methods that form its structures of insight and habits of transformation. For the artist-founder, two techniques define this architecture: Retrochronicity and disautomatization.

Each addresses a central tension in the speculative act: How does one build in the present from the standpoint of a future that truly exists, but has not yet arrived?

The first, retrochronicity, should by now feel familiar. It derives, in part, from Gilbert Simondon’s philosophy of technical individuation as well as Luciana Parisi’s contemporary work on computational aesthetics and recursive architectures. It describes a temporal method: Beginning from a future in which the invention has already succeeded, and tracing that future backward, using it as the license to act in the present.

In this mode, the artist-founder does not discover the product through incremental trial and error. They begin with the future form held in view. The task is reframed. It is not iteration. It is excavation and alignment.

To work in this mode requires a different relation to time. One begins not from today’s constraints, but from tomorrow’s necessity. The product already belongs to a future world. The task is to identify what conditions in the present must change to let that world emerge.

This is not a singular insight. It is a recursive discipline. As the present shifts, so too must the future’s form. The artist-founder must shuttle between them continuously, calibrating today’s actions in fidelity to the demands of the world they know is coming.

The second technique, disautomatization, comes from Bernard Stiegler’s philosophy of technology and is informed as well by Catherine Malabou’s work on accidents and plasticity. It concerns rupture. Not in the abstract, but in practice. Disautomatization is the act of breaking inherited perceptual habits, interrupting systems that have become automatic. But this rupture presupposes some level of prior mastery. One cannot meaningfully break from a tradition one does not understand.

Picasso did not begin with abstraction. He began with technical discipline. He mastered the representational modes of his time, rendered them automatic, and only then did he break from them. Not arbitrarily, but with precision. He learned to see from the outside what he had first embodied from within.

This is the path of disautomatization: habit breeds mastery. Mastery reveals systems. Systems expose their rupture points. And it is at these points of friction, contradiction, saturation, overload, that novelty becomes possible, like a mutation in the chain of technical evolution.

And this is where the two techniques converge. Retrochronicity allows one to navigate from the future back to the present while disautomatization allows one to break the hold of the present in order to receive what the future demands. One cannot sculpt from tomorrow using tools built only for today.

AI today is all clothes, no emperor: A procession of fine livery with nothing at the core that decides. Models improve. Interfaces multiply. But the application layer, the sovereign stratum where AI’s purpose will be declared, remains conspicuously vacant.

Vision without craftsmanship is fantasy. But craft without vision is stagnation.

Restless Egg exists to train artist-founders who treat products as prophecy.

We teach and practice concrete methodologies of vision, techniques that integrate directly into product development and scale with it.

We look for four traits in the artist-founders we work with, and we help them grow: Dream bigness (not the saccharine imperative to “dream big,” but the actual scale of imagination: The future must be sufficiently vast); Restlessness; Heterodox thinking; Practicality.

If that describes you, or if you’d like to practice this method with us, get in touch.