Too often, emerging fields witness a rush of what we might call repackaged creative energy, where people see an opportunity to wrap their favorite stalled old problems or ideas in shiny new packaging, to try and give them a new lease on life, with no substantive changes in the framing of the problem or methods of attack. This is rarely a matter of bad faith or cynical pursuit of funding opportunities. It is simply genuinely hard to get past cosmetic connections and resonances between the old and new, let go of your favorite questions, and really see through new eyes.

Protocol Studies is particularly prone to this syndrome since you don’t have to squint too hard to see almost anything as a protocol problem. This is one reason we spend so much time and energy refining our protocol-pilling techniques. It’s not enough to get you interested in protocols. That’s easy. We have to get you reflexively and natively seeing through and thinking in protocols before we can really tap into your talents. We have to get you literate in Protocolese. As Helena Rong from our 2025 cohort put it, we have to try and make Protocolese everybody’s second language.

How can we get people to truly transpose familiar challenges to an actually generative protocol-thinking register that unlocks lines of thought that were not accessible before? And how can we get people to see entirely new challenges that were invisible before the protocol lens became available?

This is a hurdle for our third Protocol Symposium in September – the first edition with an open call for proposals. Abstracts for talks and workshops are due Sunday June 14, by the way.

I’ve been wondering how to induce a good mix of programming that reframes familiar old problems in weird new ways as protocol problems, as well as programming that tackles new ideas and problems that fundamentally aren’t visible at all without the protocol frame. And we’d like to try and catalyze this kind of activity in a sustainable way that can fuel both particular events like this, and ongoing work.

We have the beginnings of a solution prototyped. We hope it will inspire at least a few novel proposals for the Symposium – our new Challenges program.

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The Challenges Program

I’d like to introduce (drumroll!) the Protocol Institute Challenges program.

The linked page is currently a list of a dozen or so challenges inspired by open threads in our archives, ranging from trivial to grand to the grandest kind on our scale – Whitehead challenges. These challenges are rated in difficulty using a 9-point Fibonacci sequence scale (1, 2, 3, 5, 8, 13, 21, 34, 55) which will be familiar to those who have used the planning poker model in software development.

Anyone can indicate their interest in seeing a challenge tackled by clicking the 👀 emoji, which increments the collectively assessed value of the problem (distinct from its difficulty) using a cunning quadratic weighting scheme. Votes from logged-in members will count for more.

Currently only PI members can pose challenges, but anyone can get a problem onto the list by persuading a member to post it on their behalf. If you’re an alum of any Summer of Protocols program since 2023, you’re eligible for membership. Just apply using the link on the top right (use whatever email you used for your Summer of Protocols participation so we can correctly detect and approve your membership request). If you’re new to PI, and would like to become a member, first participate in any upcoming programming, such as the Symposium, or one of the SIGs.

Perhaps the most important feature is that – unlike traditional challenge programs – Protocol Institute Challenges are generally going to be open-ended and inexhaustible by default, which means there will likely not be a single dispositive “solution” that solves a challenge once and for all.

This logic is inherited from Frank Chimero’s classic essay, Only Openings, which is a core reference for Protocol Studies, and also the focus of the very first posted challenge – the Chimero Protocol challenge. For fans of James Carse’s finite and infinite game model, we’re trying to build our challenge program around infinite game principles. The goal is not to win, but to continue playing.

At the moment, this is a beta program, and we have not yet attached any funding to it. We’ll begin exploring funding models and seeking sponsors shortly. There is a prize purse for the Symposium though, so if one of the challenges interests you, propose a talk on it for the Symposium.

This design for our Challenges program is inspired by many existing models, and the logic is explained below.

Program Logic

The design of our challenges program draws from three precedents: Big challenge programs, small challenge programs, and crowdfunding programs.

We’ve also added tweaks of our own, in particular to accommodate the nature of humanities and social science research, which don’t quite fit the challenge program models designed for STEM research.

Big Challenge Programs

The first category of precedents includes mechanisms like X-prizes and Grand Challenges, which offer big rewards, running to millions of dollars, for obviously difficult and important problems. The challenges tend to have a sort of on-the-nose quality to them. These can also take the form of singular challenges like Kennedy’s moonshot challenge.

Self-driving cars famously emerged from this kind of mechanism. DARPA pioneered Grand Challenges that lend themselves to precise formulation in terms of a real-world engineering challenge, which is also characteristic of X-prizes.

The nice thing about big challenge programs is that they have a built-in charismatic appeal that speaks to a broad audience, and typically offer ways for almost anyone to get involved, from amateur to expert level. They are also typically self-promoting, since they offer some amount of spectacle and drama.

The downside of big challenge programs is that most profound and radical breakthroughs tend to start in small, unremarkable ways on the margins of mainstream attention. It is obvious that a moon base would be an interesting accomplishment, and it is also obvious that it is a hard problem. It was less obvious early on that mRNA science would solve a pandemic. Many of the major discoveries in the history of science – x-rays, penicillin – would not have yielded to grand challenge type mechanisms.

Big challenge programs also tend to rely too much on big money as an incentive, and not enough on curiosity, unorthodox perspectives, and idiosyncratic personal visions.

Small Challenge Programs

The second category is mechanisms like Erdős challenges, which frame and pose problems whose significance and economic value may not be immediately obvious even to experts, but which direct serious attention and resources based on the intuitions and credibility of individuals whose judgment and taste are trusted by a broader community.

OpenAI’s recent solution of an Erdős problem made big news not because there are big prizes attached to Erdős problems, but because of the bragging rights attached to them. The savant mathematician Paul Erdős for whom the problems are named, and who originally posed them, mostly offered small personal bounties. The vast majority featured bounties in the $0–$500 range, and only 13 were in the $1000–10,000 range. Mathematicians vie to solve Erdős problems for the same reason they are proud of a low “Erdős number” (your degrees of separation from Erdős as measured by co-authorship links; I’m not a mathematician but my Erdős number is 4 via my late PhD advisor) – the chance to BIRG in the light of acknowledged genius.

The problem solved by GPT was worth only $500. A notable feature of Erdős problems is that the value of the prize often does not correlate at all with the difficulty of solving it.

This is a feature, not a bug. The low financial stakes and the lack of its correlation to practical value makes the contest about genuine curiosity and nerd-energy, rather than mercenary motives. Even an acknowledged genius like Erdős did not necessarily have perfectly calibrated mathematical instincts, and one of the reasons Erdős-type frontiers of discovery are so valuable is that small, apparently irrelevant and unimportant starting curiosities and questions can lead on to profound discoveries and advances. And seemingly big and important challenges might turn out to be meaningless once solved.

Some programs, like the Clay Millennium problems prizes, fall in between big and small challenge categories. There is big money attached (a million dollars), but most of the problems are not obviously important except to mathematicians working in the area (P=NP and the Navier-Stokes problems are the exceptions, since they both have recognized engineering significance). There can also be programs with institutional levels of gravitas, but with no prizes attached, such as Hilbert’s problems.

Small challenge programs have the benefit of reflecting the unique tastes and judgments of unusual individuals, tapping into loftier motivations, and directing attention to margins and weak signals.

The downside of small challenge programs is that they may not be able to marshal the resources required to work on the subset of challenges that require them, and can also descend into the solipsism of a taste-making elite.

Crowdfunding Programs

The third kind of mechanism is the youngest, and originated on web platforms like Kickstarter and GoFundMe. In their original form, however, they were not tailored to the particular needs of drawing attention and resources to research-like challenges. They were generic mechanisms, equally applicable to research and creative domains on the one hand, and to charitable causes and personal needs.

Two innovations in the blockchain sector build in features that make crowdfunding particularly intelligent, and better suited for challenge programs.

The first is quadratic funding: A mechanism for turning the wisdom of the crowds into a kind of mimetic collective intelligence that can function as a substitute for the taste and judgment of individual geniuses. It takes the syndication approach used in many angel-funding models to another level using mathematics rather than personal influence. In our beta design, we’ve taken some cues from Gitcoin, one of the pioneers of this approach.

The second is the idea of retroactive public goods funding (RPGF), pioneered by the Optimism RPGF model. In this model, funding is provided for work already done, with demonstrable value for the commons. We ourselves have been a beneficiary of this model, having won a grant in the first year of the Summer of Protocols program. The unique strength of retroactive models is that they incentivize work whose value is too illegible or obscure in the beginning, and only apparent to a lonely minority.

We haven’t yet built a retroactive element into our model, but we are carefully thinking the matter through.

The great advantage of crowdfunding models is that they achieve scale through aggregation, and creative insight through composition of diverse and pluralistic viewpoints. To the extent they work, you have less need to rely on big, institutional sources of funding, or the taste and judgment of individual geniuses.

The downside of crowdfunding models, as with all market-like models, is vulnerability to various kinds of complex capture phenomena, and the faddish and capricious tendencies of crowds.

Gaps in the Model

I hope it’s obvious from the description earlier, as well as evident from the live challenges page, how we’re approaching our program design problem. We think we’ve borrowed the most useful elements from big, small, and crowdfunded challenge program models. But the design is as yet incomplete, which is why it’s prominently tagged beta.

The biggest gap (besides plumbing to funding) is coverage of humanities and social science challenges. As it has emerged, the three-year-old field of Protocol Studies is firmly situated right in the infamous gap between the Two Cultures described by C. P. Snow, with Balrogs lurking in the chasm below. Our archives contain everything from technical specifications for speculative new protocols, to industrial engineering ideas, to avant-garde art and fiction.

Historically, the humanities have relied more on personal patronage and the tastes of institutional gatekeepers than on structured programs and competitive formats that rely on objective criteria to gauge progress against well-posed challenges. More recently, state patronage (with risks of being co-opted into propaganda) and aggregated micropatronage on web platforms (with risks of audience capture) have been the default.

One of our meta-challenges is to develop challenge mechanisms suited to the humanities and social sciences into our model that mitigate some of the problems with historic mechanisms.

The Symposium

The 2026 Protocol Symposium will be the first real test of our ability to curate exploration and investigation activities in an open-play mode. In previous years, we had the advantage of working with known people and materials. This year, everything is wide open. We have some early submissions in, but it’s too early to tell what sort of programming we’ll end up with.

If you like our mission, this is your chance to get in on the ground floor and help shape it. Check out our original call for abstracts last week, then head over to the call page and put in your talk and workshop proposals. That deadline, again, is Sunday June 14.

And of course, if you need inspiration (or have inspiration to share), check out the Challenges page.

The theme for the 2026 edition is New Nature – the rapidly evolving planet-scale technological layer governed by laws with a hardness and inviolability approaching those of nature. New Nature is our overarching frame for the technological future, shaped by the intersection of AI and protocols.

The symposium will be held fully online, September 21–25 (Monday–Friday), and comprise two workshop days and three days of talks.

Abstracts for talk and workshop proposals are both due by Sunday, June 14, midnight Pacific Time. You can find details and the submission form here.

If you’re interested in attending, registration will open in July, once abstracts are selected and the schedule is finalized. Subscribe to this newsletter to be alerted.

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Special note: The Symposium will also feature an exciting track of programming based on our collaboration with the Long Now Foundation, via their Labs program. You still have time to apply for these two protocol-themed Labs, The Book of Time and Information Revolutions & Epistemic Crises. Deadline: June 5th.

Background context, topics of interest and details on some special resources follow. If you plan to submit an abstract, please read through the remaining sections.

We welcome and encourage submissions from people new to protocol studies. It is taking shape as a highly interdisciplinary field, and has already inherited ideas from many existing fields. If you’re coming in cold, we suggest diving into the Protocol Reader over a weekend and reflecting on whether ideas and topics you already understand well can be usefully cast into protocol studies frames.

Background

This will be the third Protocol Symposium, and the first to be held under the aegis of the newly formed Protocol Institute. The first two editions, in 2024 and 2025, were held under the aegis of the predecessor Summer of Protocols program. The 2024 symposium focused on protocol improvement challenges, while the 2025 symposium featured a foundations research workshop and an intensive protocol school.

On our YouTube channel, you can find all of the talks from the 2024 symposium, as well as the open-source course from 2025.

The 2024 and 2025 symposia only featured content from the summer program participants, but starting with the 2026 edition, we are opening up the event to all who are interested in presenting talks or conducting workshops.

Topics of Interest

Topics of interest include, but are not limited to:

• The intersection of AI and protocols, especially cryptographic technologies

• Evolution of human behavior in New Nature, cognitive ergonomics of AI use

• Investigations into topics that have emerged as foundational over the last three years, such as memory, temporality, epistemology, trust experience (TX), hardness, stigmergy, and protocol lifecycles

• Speculative forays into New Nature futures, through fiction, art, scenario planning, or workshop exercises

• New Nature and planetarity, including topics such as climate protocols, terraforming, global governance, and space exploration

• Theory and practice of protocol analysis, design, implementation, and field evolution

• Explorations of tokenization in the three senses unfolding today (AI tokens, blockchain tokens, and identity/permissions tokens)

• Capture resistance, plurality, cosmopolitanism, and the politics of protocols

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Resources

We also have three unique resources available to those interested in participating:

1. SIGs: While not a requirement, we highly recommend aligning your talk or workshop proposal with one of our Special Interest Groups (SIGs) if possible. SIGs are the main vehicles for ongoing research and study at the Protocol Institute. You can participate in SIG activities (regular meetings and collaborative projects) on our Discord.

2. Archives and C3PO: For those new to protocols and protocol studies, we have an AI agent trained on the entire Protocol Institute/Summer of Protocols corpus called C3PO that you can chat with through a web interface, our Discord, or MCP, to help develop your talk or workshop idea. You can find our archives and the agent here.

3. Humboldt – our New Nature expert: We have a second AI agent, an Artificial Researcher, named Humboldt, currently autonomously researching New Nature themes. Humboldt is available to chat with on our Discord. Humboldt will present a talk at the symposium on its findings.

If you need help developing your idea for a talk or workshop, you can post in the #symposium-2026 channel on the Discord. PI staff and active community members are usually around to chat.

The Protocol Institute is an AI-native organization, and actively encourages AI use in all aspects of work we do and support. We encourage you to make use of AI to develop your workshop or talk ideas.

Sponsorship

We are looking for aligned sponsors for the 2026 Symposium. If your organization might be interested, please get in touch with us.

At the moment, given that PI is just a shoestring operation working with a small launch budget from the Ethereum Foundation to get us off the ground, with mostly part-time and volunteer effort, the grand titles Timber and I have given ourselves are a case of all hat, no cattle, as they say in Texas.

As I understand from the orientation package from the Secret Guild of Institutional Directors that Timber and I received, both of us have the the same, simple job description:

Bring in money from rich but busy individuals and organizations and give it to people and groups with interesting ideas, time, and energy to do things to benefit the glorious planetary process of protocolization.

To the extent we can do that, as Director of Research, I get to make grand, philosophical pronouncements and doctrinal assertions about Life, the Universe, and Everything, in direct proportion to the amount of money we bring in.

Specifically, the Guild orientation package tells me, I’m allowed to produce one fortune cookie pronouncement per million dollars we bring in. And since this institute, in its previous guise as the Summer of Protocols program, deployed about three million dollars over three years, I get to make three fortune-cookie pronouncements.

Here’s my first one: The task of our times is to invent New Nature.

I introduced the idea of New Nature in two posts earlier in the year, and I got the idea for this fortune cookie formulation from the title of Andrea Wulf’s illuminating biography of Alexander von Humboldt, Inventing Nature, which everyone should read. The big argument of the book, pretty persuasively made, is that in the early 1800s, Humboldt almost single-handedly invented Nature as we understand it today.

In the next decade, we hope similarly to invent a New Nature at the Protocol Institute.

In my previous posts, I defined New Nature as:

New Nature is regimes of reality governed by technologically mediated laws that are nearly as inviolable, immutable, and persistent as those of nature.

I’ll elaborate on how this is going to shape PI’s research mission in a bit.

Since I am only allowed to make two more such pronouncements before the hat-to-cattle ratio becomes untenable, I am going to need some help. So I’m going to be doing my research-directing in public.

Research Directing in Public

For my piece of the PI puzzle, I want to kick off a new working-in-public series devoted to figuring out our research mission, and how it fits in with the other parts of the larger vision (the practice/application of protocols, protocol education, scene-making, this magazine).

And I do mean working in public in the fullest sense that SoP alum wrote about in her 2020 book of that name: Sharing messy, unfinished, work-in-progress artifacts as we go, in the hope that we find and connect with aligned people and institutions that can influence us, and be influenced by us, in mutually beneficial ways. Ideally, some of those people and institutions will bring money to this party. We do not want to end up part of a LinkedIn for big-hat-no-cattle institutions.

What is the Protocol Institute about, you ask? Well, here is a WIP artifact for you:

Those are some key flipchart sheets from the 3-day strategy retreat Timber, (who will chair our advisory board), and I had in April, to figure out what the hell we’re going to be doing and how we’re going to pay for it. I’ve put then up on my home office wall because we still haven’t figured it out, and I need to keep staring at it until we do.

You should actually be able to read those if you zoom in, but just to spare you the pain of actually processing someone else’s WIP mess, here is a slightly cleaned up version of the key framing constructs we came up with, redrawn somewhat more neatly on my whiteboard.

In research-directing, neatness counts.

There are three pieces here: the 2×2 on the left, the pipeline drawing in the middle, and the map-thingie on the right. Let’s take them in order.

The Direct-to-Oblique 2×2

Early in the first session of the strategy retreat, we had a breakthrough moment with the 2×2, which crosses tech progress on the x-axis with human flourishing on the y-axis, with both axes going from Direct to Oblique.

Here we mean direct as in on-the-nose and explicit, and oblique in the sense of John Kay’s wonderful little book on strategy, Obliquity (itself based on a seminal 1959 paper about effective patterns of driving change, The Science of Muddling Through by Art Lindblom).

Protocol Institute is going to plant its flag in the top-left quadrant: direct engagement with tech progress, and oblique engagement with human flourishing. For completeness, here’s how we mapped out the landscape:

• Direct human, direct tech: Anything that’s shaped like “startups” or “products” making direct use of technology to try and directly benefit humanity, at least in some solipsistic sense, even if others don’t agree you’re benefitting anyone, and suspect you’re in fact hurting everyone. It doesn’t have to be a literal startup making literal products, but anything shaped like that belongs in this quadrant.

• Direct human, oblique tech: Most philanthropic and ideology oriented organizations fit here, since they usually have some sort of on-the-nose notion about doing good for humanity, coupled with an oblique engagement with technological progress. Typical think tanks fit here too, since they aim to directly influence and benefit human-centered entities like particular nations, transnational entities, or business sectors.

• Oblique human, oblique tech: This is the basic research quadrant, including basic scientific and mathematical research of course, but also humanities disciplines like philosophy, literature, art, and poetry, which constantly interrogate, deconstruct, and reconstruct what it means to be human in fundamental ways, often in ways that threaten naive humanists more than any tech advance.

• Oblique human, direct tech: This is what I’ve recently labeled (thanks to inspiration striking a couple of days ago) the context tank quadrant. Protocol Institute is a context tank. Perhaps the first ever! We’re obviously gesturing at AI here, and yes PI aims to be a deeply AI-native institute, aspiring to reduce itself to one giant markdown file. We’ll have more to say about how context tanks differ from think tanks, studios, incubators and such in a minute.

There is an implied cycle hypothesized here: Progress Change begins in the top right, and cycles around to the bottom right. Then there’s a crisis and we begin again.

Basic Research —> Context-Tanking —> “Startups” and “Products” —> Philanthropy and Think Tanks.

Institutions in each quadrant have a role to play in turning new discoveries on the frontiers into changed planetary conditions. We can and do argue endlessly about whether particular changes are good or bad, but the fact of the process of endlessly accumulating historical change is undeniable. We at PI don’t particularly want to get into endless arguments about the nature of “progress” as such, but we do want to be part of processes of historical change currently underway.

We are wary of committing to any particular notion of flourishing/thriving vs. decline/decay, but we do broadly think change beats stasis, and that protocols are a key part of the story of change.

One subtle implication of this cycle we teased out in our conversations is that the “startup”/”product” quadrant is necessarily tribalized and identitarian, as people must commit to particular notions of human welfare, and inevitably get attached to particular notions of humanness (and thence, particular notions of “progress”), as they cross over into the direct/direct quadrant. The medium is the message is the human.

This is not necessarily a bad thing. Commitment to making particular newly enabled futures real requires commitment to making certain new ways of being human work out. At least for a while. But it does create a regime of intense cultural competition ideas must traverse before they can become embodied in the fabric of civilization.

This arc is in fact the arc of what we call protocolization. Conceptually, we can restate the arc as:

Discovering —> Contexting —> Building —> Distributing.

One sociological function of institutions in the context-tank quadrant, we think, is to provide new ideas and new ways of being human time to breathe and work themselves out in relative peace, before they must choose a particular form factor in which to enter the hunger-games arena of direct/direct irruption into techno-human affairs, competing for the future of the planet.

We want PI to serve as such a space. How do we do that? This brings me to the second diagram.

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Ideas in Attention Tunnels

How do you allow ideas to breathe and take shape between discovery and building phases? What exactly is “contexting”? What happens to ideas marinating (not the same as incubating) in context tanks, and where do they go from there?

That purple arrow in the 2×2 is our attempt at an answer. That’s kind of the pipeline defining PI’s planned role. You can see the details sketched out in the blue diagram at the bottom. Here’s a zoom-in:

The logic of our pipeline is:

• “Basic research” relevant to protocols and protocolization diffuses in from the top right quadrant upstream of us. By which we mean fundamental advances in cryptography, AI, epidemiology, ecology, energy, new kinds of poetry, new modes of art, new philosophies, and so on. New knowledge that doesn’t quite know how to shape reality, or relate to humans. Ideas that are stumbling around trying to enter the world.

• A new idea stews in the context tank for a bit, between the two vertical dotted lines, in pre-factored forms, as an idea discovering itself and figuring out what form factor it should assume (Startup? Protocol proposal to the W3C? Great novel? Interpretive dance? Climate action protocol? New hand-washing protocol proposal to the WHO?). Contexting is about new ideas seeking their compile targets, and the new ways of being human they might enable.

• Then it makes its way into the bottom left “startups”/”products” quadrant, having assumed some legible form. Again, I emphasize, anything in that rough shape qualifies. A painting is a product in the sense that it uses the technology of the painting medium directly, to produce a work that directly affect human welfare in some way (though people might not agree about the nature and valence of that effect of course). A group of people trying to get a city to change its zoning laws is a “startup.”

In our first three years, as a summer program, we relied on a particular vehicle for doing our contexting, the summer cohort. We got pretty good at cohorts, but slowly realized we needed a more persistent vehicle for creating a context.

Enter the Special Interest Group, or SIG, designed to contain new thinking for long enough for it to decide what kind of shape it wants to take as it makes its debut into the world at large.

The name is old. Many storied institutions have used the SIG form for their work, but we think we’ve come up with a particularly original contemporary spin on it. We have four SIGs going on at the moment:

• Memory Research Group (led by )

• SIGFPT: Special Interest Group in Formal Protocol Theory (led by and myself)

• SIGP4B: Special Interest Group in Protocols for Business (led by )

• PFSIG: Protocol Fiction Special Interest Group (led by and )

A fifth SIG on distributed robotics is in the cunning-plans stage.

A SIG in our sense is something like a souped-up study group (roughly two-pizza sized, by that old Amazon heuristic of two-pizza teams) that has an open-ended charter to immerse itself in a theme or domain, with no particular goals, projects, or rules, and just enough resources and support to sustain itself indefinitely.

Read, think, work on your ideas in collaboration with the right set of peers, and see where the journey takes you. It is what I have started calling an attention tunnel, where scarce collective attention can do its work for a while.

Particular projects or workstreams may unfold within the context of a SIG, but the SIG itself isn’t a project or workstream. It is a manner of paying collective attention to a theme.

Nor is a SIG a heavier organizational unit like a “studio”, “lab”, or “research center.” You can’t build heavy-weight scaffolding when you’re at an all-hat-no-cattle phase of evolution. No, a SIG is simply a space to think and work between the provocations emanating from the basic research quadrant, and the pressures of operating in the startup/product quadrant. It’s the calm before the storm.

The pressure stage, of course, cannot be avoided for any serious idea that hopes to change the world, but it can be deferred while the idea grows up, and gains enough strength to handle it. This is not incubation though. Incubation is about the inner logic of a thing getting worked out, while it uses up a store of resources. Incubation is about ontgeny. Contexting is about a thing getting introduced to the world it is going to live in. Contexting is how you send an idea to school so it can get a job when it graduates.

The structure of a Protocol Institute SIG is deceptively simple – it’s just a group of people who decide they have some interests in common that have a bearing on protocols and protocolization. They start meeting (typically every other week on a Discord call), talking, studying, and working together. We pay the curators small honoraria to host these SIGs and report on their activities periodically in the form of Protocolized essays. That’s it. Nobody’s going to get rich running or participating in our SIGs. What you will get is a harness engineered to let you devote steady, cumulative attention to a thing, for long enough to do something with it. SIGs are Claude Code-like environments for groups of human brains.

Near-zero infrastructure costs. No fancy buildings, no expensive equipment. Just people, ideas, some cheap/free software tools, and a modest budget for AI and crypto tokens. Individual workstreams and projects within the SIG may have additional, heavier demands, but the container doesn’t have to be complex or heavy. All it needs to do is contain collective attention over weeks, months, and years.

Our two oldest SIGs – SIGFPT and MRG – will each be one year old in a few months. Warm contexts for the right kinds of ideas to develop.

I think this is all it takes to get started doing really big things today. You don’t need fancy buildings or big budgets. You just need a small group paying steady attention.

But this mode of working is deceptively simple because a lot more illegible kinds of knowledge and cultural capital have to be in place in the environment before stable and generative attention tunnels form and begin to do interesting, original, and useful work. Otherwise, all the thousands of communities on Discord and other platforms would be doing world-changing work.

There are certain necessary conditions for SIGs to thrive and function as attention tunnels acting on important and difficult themes. We can’t say we’ve entirely figured out sufficient conditions, let alone a “formula,” but we’ve figured out quite a few best practices. We think we know how to get a small group to pay attention to a small set of ideas for long periods of time.

Which brings me to the third diagram.

Shaping New Nature

Our three years of work in the Summer of Protocols has left us with a solid corpus of ideas and capabilities, produced collectively by almost 200 people contributing research papers, small projects, art, guest talks, workshop participation, and so on. This is the legacy PI is inheriting.

This is no mean feat by the way. Three million dollars may sound like a lot to people not used to research environments, but I’ve seen a lot more money get burned up a lot faster, with nothing to show for it.

Research directing is partly about knowing how to spend money… elegantly. I don’t know that we at PI have the skills yet to deploy (say) $10m or $30m a year well, but $1–3 million, we know how to do. And maybe we’ll build our muscles and get to those larger scales.

We think of this corpus as the core asset we’re building, and in this diagram, it serves as the anchoring center mass of our self-conception. This is a lot of material – go look for yourself on the protocolized.io site. But more than mere material, it’s a socially alive corpus, that’s steadily generating new ideas and inspiring more people to do more things everyday.

This is the kernel of PI, the innermost circle and energetic core. Three years of work is close to critical mass, and this kernel is beginning to accrete knowledge to itself at an accelerating pace. I’ve labeled it “IP” in the diagram, but that’s a loose term. I don’t mean specific forms of intellectual property like papers, patents, copyrighted artworks, courses taught, books written, and such. I mean all that and more, deeply entangled with the community that is producing it.

If I might be permitted the conceit of a somewhat self-congratulatory term, the PI kernel is a scenius structured as a commons. A young and fragile one, just three years old and a few hundred people strong, but definitely a scenius.

Kinda fun that PI reverses to IP.

That’s one necessary condition for a context tank and its attention tunnels to work – a center-mass of scenius like this. Check.

Next, it is 2026. If you’re starting a new institution today and it is not fundamentally AI native in a deep and unsettling way, you have some explaining to do. If its patterns of working look familiar and comforting, you have a problem. Becoming AI native, however, is easier said than done.

Fortunately, that’s the problem SIGP4B is actively working on, so we are making our own dog-food to eat. We’ve got a SIG on the job here.

That’s one half of the shell around the kernel in the diagram (we like our computing metaphors around here).

We’re getting pretty good at AI-native operating modes. This magazine is one of the few that not only accepts AI-assisted writing, it actively encourages it, and pays for it the same as for hand-crafted human writing. Trad publications may be drowning in slop submissions, but we are figuring out how to thrive on generated content.

Everything we do is deeply, organically, reflexively AI-forward.

All our artwork is AI-generated – but in a boundary-pushing way using the TITLES platform we’ve written about before. Neither Timber nor I code, and the two new websites of PI, protocol-institute.org and protocolized.io, were entirely vibe-coded (and will continue to be). We have plans to digest our sprawling corpus into embeddings, and turn it into an agentic oracle. And it will be a small project that will cost a few hundred dollars in tokens rather than a ponderous enterprise IT undertaking.

But all that is just at the level of tools. We’re also starting to think in AI-native ways. You’ll see more signs of that as our activities mature.

The other half of the shell in the diagram is decidedly more controversial. We’re not just AI-native, we’re crypto-native. That, for many people, is the worse of two strikes. But as a wise man once told me, you’re always going to piss off some people if you try to do anything of consequence, and what’s important is to piss off the right people.

This is of course, partly because of our origin-story and path dependent history as an Ethereum Foundation-funded project. But it’s also a central intellectual and philosophical commitment underlying everything we do. The discovery of public-key cryptography (PKC), which is now integral to every aspect of computing (including AI), was perhaps the genesis event of what we’re calling New Nature.

It has been obvious for a few years that AI and crypto are in some sense natural duals, and it is a rather delightful technical-lexical coincidence (or is it?) that both are ecologies based on tokens of different sorts. But actually working out the nature of that duality, and the natural shape of how the two ought to relate to each other technologically and mathematically, is far from clear. And building an organization that is a native of the quicksand-like emerging convergence zone of the two is even harder.

Slowly, but steadily, we’re figuring it out though.

More and more weird new ideas are trickling through from the basic research quadrant. Zero-knowledge machine learning, verifiably private computation, encrypted inference, oracle systems, verifiable provenance data, verifiable identities – piece by piece the elements of the duality are being uncovered in the discovery quadrant. And next door, we are paying steady attention, contexting away in our SIGs, figuring out how to put the pieces together in interesting ways.

This, by the way, is the theme of our Protocol Town Hall salon series this year, which will kick off shortly. AI × Protocols. We already have half a dozen talks lined up that should challenge your imagination, and recontextualize your thinking about the future.

Downstream of us, in the product/startup quadrant, the first fruits of this years-long convergence are already emerging. Mainstream society has only recently discovered relatively simple uses of AI and crypto in isolation – chatbots and stablecoins. But complex, converged technologies are coming. Agents paying each other with crypto. Decentralized agent ecologies taking root onchain. Secrets in enclaves shaping inferences without revealing themselves.

Normal people may never hear of such things as ERC 8004, x402, MPP, MCP, and all the other ideas floating around in the acronym soup, but they will soon start seeing the consequences of this emerging AI-crypto converged backend of planetary computation.

Here at PI, the prospect of this looming convergence (and the explosive divergence it will then spark) shapes almost everything we do. We are betting that this, in fact, is the future. And we are designing PI as an organization to run on AI+crypto rails philosophically, not just at the level of tokens. Even if we have to navigate the quicksand convergence zone to do so.

There is a praxis and a poiesis to this challenge of being simultaneously AI and crypto native.

Many have noted the emerging praxis.

• AI allows us to work radically more effectively, with radically minimized resources. Joules in, intelligent work out.

• Crypto allows us to coordinate radically more effectively, with radically minimized friction and trust. Joules in, coordination out.

But it is the poiesis that interests us more. There is a new grammar of reality emerging here. A new kind of poetry in the very bones of the planet. That’s New Nature.

Being “native” to both ecologies, we think, will make the Protocol Institute, despite its vanilla name and conventional surface appearances, a radically alien kind of institution. Of a sort that couldn’t exist as recently as six months ago. And figuring out how to be native to these two ecologies, which are both full of all the risks of frontier ecologies, is an existential imperative for us.

That’s the second necessary condition in the diagram. AI+crypto native institution building.

Check.

And finally, there’s the third and hardest necessary condition: Plugging into the real world. Education. Scene-making. Consulting. Banal words that are forced to do a lot of practical work. But we’ve accumulated a wealth of substance behind each.

• Scene-making: We’ve held a dozen workshops around the world, attended by hundreds of people, and learned how to get people “protocol-pilled” reliably. We’ve memed a new genre of fiction into existence over the last year.

• Education: There are now protocol studies courses at a dozen universities around the world, as a direct result of our work, and dozens of graduates of our own hugely successful first Protocol School last year. The protocol-literate community is growing and spreading.

• Consulting: Building off the experience of half-a-dozen experimental projects aimed at influencing real-world protocol domains in 2024, we’re now incubating several consulting projects, and a growing capability in our SIGP4B group. Want help for your organization to navigate New Nature? Call us.

• Monuments: This one is aspirational, and partly the result of taking as a challenge the title of the research essay we published by in 2023, Protocols Don’t Build Pyramids. We aim to lend some visible public charisma to the invisible protocol infrastructures that run the planet.

Each of these activities, taken in isolation, feels like part of the ordinary pragmatics of running any such program or institute. But if you step back, and contemplate them in the context of the hows and whys of the activities, a more profound pattern emerges – this is how you shape New Nature, by actually constituting it from the inside out, by creating strange new institutional species that survive and thrive by strange new rules. You discover New Nature by inventing it, by being it.

Big hat, no cattle?

Perhaps. But at least it’s a strange new hat.

If you’d like to help us make all this happen, get in touch. We’re just getting started here.

The mission of this institute is to advance the theory and practice of protocol design, analysis, and stewardship across domains, as well as promote protocol literacy, appreciation and cultural salience globally. In other words, our mission is to build the field and community capable of stewarding the ongoing planetary processes of protocolization – the slow, largely invisible means by which human behaviors become standardized into the coordinating infrastructure of civilization.

The Protocol Institute inherits the work of its predecessor, the Summer of Protocols (SoP) program, which ran from 2023 to 2025. The Ethereum Foundation initiated SoP with a bold thesis: deepened understanding of protocols generally would enable better governance of the core Ethereum protocol specifically. As a seasonal grants program, SoP was designed to:

• Bootstrap a new field of study around protocols

• Establish protocols as a first-class concept for thinking about and acting in the world

• Seed a scene and improve literacy around protocols

The program not only succeeded in these objectives, it went beyond them, sparking a rich discourse spanning many domains, such as robotics, climate, government, natural resources, insurance, programmable cryptography, economics, urban planning, health, gaming, encryption, wildfire management and more. Through its successes, both planned and unplanned, SoP has created the need for a suitable vehicle to sustain long-term activities building on what has already been accomplished.

The Protocol Institute is that vehicle.

I () will serve as the Managing Director of the Protocol Institute and Editor-in-Chief of Protocolized, supported by as Director of Research and as Chair of the Advisory Board. We are excited to work with anyone who wants to help, and encourage you to reach out by email.

The complete SoP archive has been merged with the living library of Protocolized, and is available at protocolized.io – the new home for Protocolized, which we will continue to distribute on Substack.

In this vision essay, we describe the work we are taking on, the evolving investment philosophies and strategies guiding the work, and the operating models we are employing. This is a daunting institutional and cultural challenge. We have made great progress in the last three years, but we now need all the support we can get to pursue this more ambitious, long-term mission. Throughout this essay, and on the Protocol Institute website, we share various ways you can join and support us.

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Protocolization Stewardship

To steward a single protocol is already a hard challenge. To steward planetary-scale dynamics of protocolization is arguably an insane challenge. We are excited to take it on.

Protocols are a strange thing to work on. Effective ones fade into the background, as do the people who maintain and study them. When someone becomes literate in protocol wrangling, it’s as if they’ve bought a pair of glasses that reveal a new layer of the world around them. But as they immerse themselves in this world, by attending to and working on things that others typically don’t, they themselves become invisible in proportion to the impact their perceptiveness has.

Imagine you walk into a hospital. All around you are hard-to-see orchestration technologies that allow actors in the space to perform together: triage, handwashing norms, double- and triple-checking patient IDs, standard metrics for hormone measurement, recurring supply orders, wipe-down routines, badge-based access control, maintenance tags on fire extinguishers, designated waiting areas, randomized control trials, and dosing algorithms for anticancer drugs. Despite the fact that these technologies tend to operate below the awareness of individual participants, they nonetheless choreograph them and guide the increasingly unconscious performance of important, life-saving operations. The people who work on these protocols also operate below our awareness, continuing to provide stability, security, and uptime to important civilizational operations.

The recently invented Model Context Protocol (MCP) is a live example. In the span of a year, it has become the default connective tissue between AI assistants and the tools they use, coordinating a sprawling ecosystem of integrations without any central authority. If it keeps working, it too will steadily fade from the conscious attention of the developers and users who depend on it. MCP’s success will be quietly manifest in integrations that simply work, and in friction that never materializes. Hospitals and other coordination hotspots, like legislative assemblies, powerplants, stock markets and airports, exemplify the current state of protocolization around the planet. This is not a mandated process unfolding, but an emergent one. It is also not just a civilizing process, but one that creates new types of wilderness. Protocolization is old, profound, and accumulating. We have inherited a big legacy.

We are early to figuring out what protocolization is, but everyone should be eager to help create that knowledge. While still not widely recognized as such, protocols are high-value pieces of civilizational infrastructure. They allow us to coordinate at scale, often without a central authority: sanitation routines for hospitals, SWIFT for banking, diplomatic immunity for planetary politics, GAAP for accounting. These protocols are immensely practical, and once you pull away the curtain, you’ll find that they are never short on intrigue.

Working with protocols requires a disruptive imagination. The Bristlemouth Connector, an open standard for marine hardware interfaces, a case which program alum David Lang studied in his research, is an example of what it takes – and what’s at stake.

Protocols, including hardware standards like the Bristlemouth Connector, aren’t just paradoxical in their tendency to disappear. They are also generative as a result of being restrictive. Prior to the Bristlemouth project, the underwater robot and drone market comprised a ton of bespoke components which could not work together. By restricting the design space for connectors, the Bristlemouth team has enabled people to generate many new kinds of robots, drones and services built atop them, providing important services like ocean data collection and urban water monitoring. If the protocol is as successful as hoped, the industry could move beyond making marginal improvements in legacy technologies and into realising a whole new world of cheap and composable plug-and-play underwater devices.

The Bristlemouth team did not have a government or business playbook to follow. They practiced what Lang now refers to as disruptive standards-making. We’re launching the Protocol Institute, in part, to provide protocol entrepreneurs, like those that David Lang studied, with a community of likeminded peers and a knowledge commons to support their work.

The Bristlemouth project was named after the bristlemouth fish family, gonostomatidae, which we’ve adopted as a mascot for our work as well. Gonostomatidae is an unassuming but potent symbol for protocols. They are not only the most numerous fish in the oceans, they are also the most numerous vertebrates on Earth, with an estimated one quadrillion living specimens. Most people do not even know they exist. Even fewer will ever see one, since they inhabit the deep mesopelagic zone. But these tiny fish constitute the decentralized backbone of our oceanic ecosystems, just like the elements of the millions of protocols which constitute our technological environment.

Protocolization is transforming our world at this very moment, alongside more visible processes like AI adoption and climate change. As with past global transformations like industrialization, urbanization, globalization, and digitalization, it will radically alter the human condition. Stewarding protocolization thoughtfully is an urgent imperative because it is progressing invisibly whether we like it or not. In fact many of the world’s critical protocols, both old and emerging, are failing:

• Carbon accounting regimes have proven to be easily manipulated

• Protocol-based social media has been unable to catch up to the network effects of rent-seeking social platforms like TikTok, Facebook and X

• Diplomatic protocols have not been able to stop 21st-century wars of aggression

• While improving, the global banking system remains wildly inefficient and exclusive, when compared to what it could be re-engineered to become

• The legitimacy of some voting protocols in states around the planet has faltered, leading to wars over state capacity

Our ambition is that the Protocol Institute will shed light on and inform protocolization around the planet.

The first question I’m asking myself in my new role is what mental models I should bring to the job. I’m finding a useful starting point in the ideas of a 19th-century political economist and a 20th-century organizational theorist.

An Ode to Unbroken Windows

In July of 1850, Frédéric Bastiat published That Which is Seen, and That Which is Not Seen. Even after living in Québec for two years I can’t read it in the original French, but a translated version is available here. Opportunity costs are well understood and priced today, but that wasn’t always the case. Bastiat explained how the broken window of a shoemaker tended to be justified because it created work for the windowmaker. While easily seen, the first-order logic is wrong. Unseen consequences dominate the arithmetic.

In fact, it is the same in the science of health, arts, and in that of morals. It often happens, that the sweeter the first fruit of a habit is, the more bitter are the consequences.

When a window is broken, the victims outnumber the beneficiary at least two to one. First, the shoemaker must purchase a new window. Second, that money flows to the accident and away from another, unseen, productive thing into which the shoemaker might potentially have directed it, like a book, medicine or shoes.

At the time of Bastiat’s writing, economics was effectively blind to the difference between these things. A repaired window was just as good as a new book. Hence why the calculus of war was (and sometimes still is) seen as unequivocally profitable. Peace, and unbroken windows, were regarded as bad for the economy. Their benefits were unseen. As the field developed, economists realized that both the seen and the unseen must be accounted for to paint a full picture.

This explains the fatally grievous condition of mankind. Ignorance surrounds its cradle: then its actions are determined by their first consequences, the only ones which, in its first stage, it can see. It is only in the long run that it learns to take account of the others. It has to learn this lesson from two very different masters – experience and foresight. Experience teaches effectually, but brutally. It makes us acquainted with all the effects of an action, by causing us to feel them; and we cannot fail to finish by knowing that fire burns, if we have burned ourselves. For this rough teacher, I should like, if possible, to substitute a more gentle one. I mean Foresight.

In the same way that a poor understanding of opportunity costs led to suboptimal economic outcomes, a poor understanding of protocolization will lead us, in the present, to short-sighted conclusions.

Protocols exhibit a similar pattern to unbroken windows. The costs of following protocol are more visible than their benefits. Institutions that govern and maintain a protocol, from traffic lights which prevent accidents to climate accords which prevent CFCs from blasting a hole in the planet’s ozone layer, struggle to prove that their worth outweighs their operating costs. A counterfactual future is always harder to see than a current expense or inconvenience.

However, over time, civilization has established many important “unbroken windows” through the process of protocolization. The eradication of smallpox. The absence of nuclear holocaust. The pandemics dodged and economic depressions avoided. The coal mines that did not catastrophically explode. The standardized drillbits that unlocked new markets. The randomized control trials that prevented dangerous drugs from entering markets. The shipping containers that formed the modular backbone of the global economy and avoided trillions in breakbulk shipping costs. The famines that never happened. The internet protocols which have enabled us to do things whose costs were once so prohibitive that they were not done at all.

Those hard-to-see things likely compose a kind of value greater than that measured by GDP. It remains arduous to measure them, even if economics has developed better tools since Bastiat’s time. This is one reason why we believe protocols are systematically undervalued.

Furthermore, many of the things that protocols generate are not owned by single shopkeepers but by loose networks of actors. Functional state capacity. Robust supply chains. Inhabitable ecosystems. Public health. Charged water reservoirs. Competitive technology markets. These sometimes delicate things exceed individuals and local groups, extend beyond political borders, even beyond our lifespans. The actors responsible for maintaining and following protocol do not fit neatly into state lines. The products of protocols are highly valuable and often invisible, each defined by the absence of a class of negative events (respectively: corruption, shortages, biodiversity loss, drought, monopolization). They are what Karl Weick would call dynamic non-events; windows with varying levels of unbrokenness, depending on the health of the protocol that generates them.

When we arrive at this unexpected conclusion: “Society loses the value of things which are uselessly destroyed;” and we must assent to a maxim which will make the hair of protectionists stand on end… To break, to spoil, to waste, is not to encourage national labour; or, more briefly, “destruction is not profit.”

Among the most valuable civilizational outcomes are things that don’t happen. Protocols are technologies for producing these non-events.

Investing in the Production of Non-Events at Scale

Aerospace engineers don’t make safe planes. They design planes capable of producing safe flights. Anyone can make a plane that never crashes – just never let it fly.

Karl Weick, an organizational theorist whose ideas were adopted in military, healthcare, aviation and energy domains, championed the term dynamic non-event. Non-events such as safety, reliability, interoperability and quality are invisible moving targets which must be continuously produced, and only become visible when they lapse.

Protocols can be understood as infrastructural technologies for producing non-events at scale, often without a central coordinating mechanism. For that reason, we like to call protocols engineered arguments. They are not universal agreements, but rather mostly predefined sets of rules that allow individual actors to make trade-offs without becoming embattled. Following Bastiat’s reasoning, since non-events are systematically undervalued, we systematically underinvest in protocol analysis, design, and improvement. A tenet of our mission is to address this underinvestment, and a few examples will illustrate the philosophy we are pursuing in order to do so.

A tell for spotting investment opportunities is the commonly noted phenomenon of small changes having big effects in complex systems. Checklists (which are simple thoroughness protocols), for example, have proved to be a powerful continuous producer of non-events in the context of domains such as hospitals and aviation. Despite being cheap and easy to implement, checklists are still underused. Dedicated operations professionals tend not to center their careers on such apparently trivial things, preferring to focus on more complex change and improvement theories and programs.

In 2024, we ran a grant program which tasked six teams of practitioners with driving small, incremental protocol improvements in their domains. Like checklist adoption, seemingly simple changes, such as adding encryption to a messaging protocol or simplifying a permit approval process, proved surprisingly hard to implement, despite their obvious potential for precipitating big changes. The 2024 grant program taught us a great deal about what it takes to drive even small consequential changes in complex systems.

Another example of our investment philosophy has to do with the critically undertheorized topic of memory. It is easy to forget non-events. That is in many ways a good thing, because it frees up cognitive (and economic) bandwidth to perform other operations. Technologies that produce non-events do not automatically create and preserve verbose traces in historical memory. Even when raw memories are produced, they tend to be easily forgotten or disregarded.

In a thoughtfully designed, safe workplace, a log of accidents not happening (such as the familiar image of a sign highlighting the number of days without an accident at a factory) does not naturally attract the attention it perhaps deserves.

Memory, therefore, has been an important research and investment theme for us, beginning with ’s seminal 2023 work on the relationship between memory and protocols.

Her essay Artificial Memory and Orienting Infinity sparked a steady stream of follow-on research and supporting activities such as workshops over the next three years. Kei now leads a Special Interest Group that meets biweekly on our Discord. The graphic below shows the evolution of this research track, which now serves as the model for our investment in other deep, undertheorized topics that require sustained creative attention and organized inquiry.

These are just two of the validated strategies we have developed over the years to invest in the world of protocols. Not everything we try works out, but we aim to gradually grow our arsenal of research, application, pedagogy, and scene-making methods by trying many such strategies and doubling down on the ones that work. From 2023 to 2025, the Summer of Protocols program helped us bootstrap into a strong initial position with solid momentum. In 2026, the Protocol Institute and Protocolized will begin transforming that into lasting institutionalized value.

This is particularly urgent with regards to another contemporary technological theme. AI systems are powerful precisely for being non-deterministic and generative, but that generativity is most useful when it operates within stable, well-designed infrastructure. Protocols are that infrastructure. Indeterminacy and stability are complements, not competitors, and understanding one requires understanding the other. Even the arguments of TCP/IP, the very foundation of the modern internet, might need to be reengineered from the ground up to accommodate both humans and AI agents.

We’ve only scratched the surface of the world of protocols. In working towards a deeper understanding, beyond pursuing our own activities, we surface and curate ideas and knowledge from existing traditions (both scholarly and practitioner), unlocking insights and wisdom on the subject of protocols.

The Beginnings of a Canon

Establishing a canon is an important part of building a new field, and an important aspect of that is deciding which ideas to inherit, and from where. In the three years we’ve been consciously working to do this, we’ve accumulated a vast library of references across our publications that we’ve curated into the beginnings of a canon. We’ve deliberately chosen to strike a middle path between relevant academic traditions and broader works that not only cut across disciplines, but look beyond scholarly traditions to writing that’s embedded in real-world practice, and popular writing aimed at non-scholarly audiences.

This selection of well-known works, which arguably belong in a protocol canon, has proved valuable in our short history, and might serve as familiar entry points. If you have read and enjoyed any of these books, stories, or essays, you might already know more about protocols than you realize:

• Seeing Like a State, James C. Scott

• Governing the Commons, Elinor Ostrom

• Normal Accidents, Charles Perrow

• The Control Revolution, James Beniger

• The Box, Marc Levinson

• The Nature of Technology, Brian Arthur

• Finite and Infinite Games, James Carse

• How Buildings Learn, Stewart Brand

• The Death and Life of Great American Cities, Jane Jacobs

• The Tacit Dimension, Michael Polanyi

• Who Could Write Protocol Fiction for Speculative Infrastructure, Matt Webb

• The Complete Stories, J. G. Ballard

• Mother Earth, Motherboard, Neal Stephenson

• Protocol: How Control Exists After Decentralization, Alexander Galloway

• The ETTO Principle, Erik Hollnagel

From our own corpus of work, The Protocol Reader has earned a place in the canon, as have several stories from our archive of short stories.

These aren’t the only works that matter, and I’d be suspicious of any list that claimed to be complete. The canon is still being established, as is the live tradition of practice and application.

Creating a Movement

This then, is our investment thesis:

1. Protocols are infrastructural technologies that produce some of the most valuable outputs of society: dynamic non-events

2. Dynamic non-events have a natural tendency to become invisible and be forgotten

3. This tendency has historically led to them being undertheorized and underinvested in

4. Widespread improvement to this important class of technology requires creative new investment strategies and philosophies

Since 2023, an Alfred North Whitehead quote has served as our lighthouse, keeping us oriented to the essential core of this thesis: “Civilization advances by extending the number of important operations it can perform without thinking about them”

A modified version, we think, will keep us moving in the right direction in the years ahead:

Civilization will always be partially defined by the unseen and unremembered; by the outputs of its most important non-events – safety, hygiene, peace, frictionlessness; by the technologies that produce them in steady, sustained ways; and, perhaps most importantly, by the people who analyze, design, evolve, and maintain those technologies.

The Protocol Institute and Protocolized will serve this world.

Maintaining a robust, continuously tested and refined investment philosophy and thesis is necessary for the work we have ahead of us, but it is not sufficient. While one of our main operational goals is to serve as an investment vehicle for other institutions and individuals who see the value in what we are doing (please reach out if this is you; we will share more in the coming weeks), it only makes sense when paired with our other main operational goal – creating a movement.

While our plans for the Protocol Institute and Protocolized take many cues from scholarly societies and publications, we believe the world of protocols requires a fundamentally full-stack societal approach, spanning scholarly, entrepreneurial, governance, policy-making, cultural and subcultural activities. This is a daunting scope to operate in, and we have therefore converged on a few fertile and high-leverage core operational capabilities. The most important capability is using a publication to supercharge an entire emerging movement, rather than just its nominal contents.

This vision for our publication takes inspiration from other powerful movements and scenes that were shaped by highly influential publications, such as Astounding (Golden Age science fiction), The Whole Earth Catalog (early counterculture), Wired (early digital technology) and Make magazine (the Maker movement). The editorial postures and visions of these magazines served as far more than curators of content – they erupted larger discourses and policy conversations, seeded thriving subcultural scenes and catalyzed a range of creative, entrepreneurial, hobbyist, and social activities. Aesthetics, too, played a big role in the success of these magazines. We are well positioned on both fronts and I’m excited that will continue to be a driving force behind Protocolized as Head of MagOps and Art.

Already, through its first year of existence, Protocolized has helped spark the emerging genre of Protocol Fiction, published the output of several special interest groups pursuing important research tracks, seeded protocol watching as an engrossing new hobby, and hosted a dozen events around the world.

Going forward, we will consciously aim to use the Protocolized editorial room as the bridge from which we steer a fragile young movement through its uncertain early years. Our hope is that the movement quickly takes on a life of its own, with more individuals and institutions joining us in our stewardship efforts. In this nautical metaphor, we hope to thoughtfully design and evolve the Protocol Institute as the long-term engine for institutionalizing what needs to be institutionalized, while also helping preserve what should not be institutionalized in vibrant, wild, generative states.

A Map of the Protocol Institute

The Summer of Protocols began with a set of interdisciplinary research essays and culminated in a series of courses, taught online and at universities around the world. SoP provided the activation energy for a new field of research and practice based on real-world phenomena to emerge, just as bazaars and insurance brokers existed long before economics.

The Protocol Institute will irrigate this nascent field with the hope that it continues to develop tools and theories that will accelerate the production of important non-events. Right from the outset, we are an online-first organization and planetary in scope. Members of the protocol community already participate in this discourse from around the world, from a wide variety of countries, geographies, companies and institutions. Part of our philosophy as we chart a path during these early days is to capitalize on the energy and mediums available to us, rather than force old organizational forms like those of universities, traditional societies, or think tanks onto a digital and global network.

This organizational model will evolve, probably quickly, as the field and movement advance. At this time, Protocolized, the SIGs, and the annual Protocol Symposium (already two editions old) are the flagship projects of the Protocol Institute. In addition, several partnerships are in progress that we are excited to share more about soon. A big part of the Protocol Institute’s function is to create durable infrastructure for the emerging community of protocolists, including experimenting with and taking advantage of new AI tools.

Initial membership will include alumni from all three years of the original Summer of Protocols program, as well as guest speakers, lecturers and contributing writers of Protocolized. We also welcome the Class of 2025 from our inaugural Protocol School. What membership means and what direction it will take is an ongoing discussion among the founding members of the Protocol Institute. We look forward to expanding membership in a way that adds value and energizes the field.

To kick things off, we’ve put together a thorough (but not comprehensive) list of ways to work with the Protocol Institute and see the world through a new and useful lens:

1. Subscribe to Protocolized. Quick and easy. We’ll help point your attention to what matters in the field. This is also where we share project information – like an upcoming partnership program with the Long Now Foundation – and future opportunities, like becoming a member.

2. Start protocol watching. Trying to spot the protocols and dynamic non-events around you is a surefire way to build literacy.

3. Study the 2025 Protocol School lectures. These were taught by faculty from around the world and are completely free.

4. Take a weekend to digest the Protocol Reader. It’s still one of the best places to start. If you want a palate cleanser from non-fiction, read our protocol fiction anthologies: Terminological Twists, The Librarians and Ghosts in Machines.

5. Join the Discord server and participate in a Special Interest Group. Meet fellow theorists, practitioners and writers. Make something useful.

6. Write with us. Pitch an article or short story. Write something about what you saw, learned, read about or built. Fiction or non-fiction.

7. Apply what you learn. At the end of the day, what will come to define this new field is the real-world agency and effectiveness that it provides.

8. Make a tool for other people to use based on protocols in your field. Try to generalize useful principles and techniques.

The world of protocols is full of opportunities to exert an influence. You’ll have to tilt your head a bit to see these opportunities at first, but eventually it will become second nature. We want you to imagine a future where people live better through protocols. A future where, among other things, arguments are engineered to be productive, there are fewer central mechanisms at risk of becoming captured or malevolent, and where there is more peace, properly accounted for.

Here’s to the protocolists.

In this installment, I want to provide two quick examples of how this might work at the level of individual ecologies, and sketch out how many more such ecologies might form a primordial computing soup.

AI Art Scenius with Titles

The first example is TITLES (who also have a Substack called ), the generative art platform that we use to produce the artwork for Protocolized. The brain part of Titles is a pipeline to make fine-tuned models from art collections by a particular artist. The high-personality part is that each model reflects a distinct individual artist’s style for that project.

The fabric part is a rather clever “creator studio” for composing these individual models together, to create an ecology based on “sampling” multiple models (in the sense of sampling in music) to create new artwork. The fabric accomplishes two things – combining multiple models together in a mathematically meaningful way, and keeping track of the contributions to allow for attribution and profit-sharing. The overall ecology also has a personality, similar to how music scenes can have personalities.

An Open Planetary Network of Robots

The second example is more complex, and one I’m involved in personally – the Yak Robotics Garage (YaRG) project.

The goal of this project is to create a planet-wide network of open-source rovers and other robots (such as drones), as a stepping stone towards rover networks on the moon and Mars. The idea started with (a Protocol School alum) figuring out how to teleoperate robots securely, in exchange for blockchain payments, and then generalizing the mechanism to use the ERC 8004 protocol (a sort of onchain directory and rating service for AI agents) to drive discovery of available robots for tasking.

Summer of Protocols researcher then joined in the fun and prototyped an auction marketplace to allow for posting of jobs for robots, and bidding by robots able to do them. There is currently a demo marketplace going (with dummy data, and a mix of real and virtual rovers, but real prototype protocol plumbing behind it) and plans underway to test the technology in the construction sector.

Where does AI fit in here?

Well, the problem with operating an open network of rovers in the real world is that there can be a dizzying variety of hardware types with different capabilities, owned by a large variety of actors of different levels of trustworthiness, situated in different environments. There can be all sorts of potential operators anywhere on the planet – or even on an entirely different planet – with varied skill levels.

Rather than brittle and specialized command modes, you want high-intelligence robots of all sorts to expose their capabilities to potential users/customers via a flexible command surface, and high-intelligence clients commanding them using LLMs that can understand their varied technical capabilities and map them to the needs of particular tasks and missions.

So you use MCP (Model Context Protocol) to expose the capabilities, ERC 8004 (try searching for “robot”) to discover the capabilities, LLM agents to use those capabilities to get tasks done, and either traditional or blockchain rails, using the x402 protocol, to organize a marketplace for robotic services to be provisioned and procured for money.

Those are just the main moving parts in a rather complex scheme – but one in which all the complexity is mainly dealt with by AIs rather than humans. Here is an explainer video (AI generated) of the technical infrastructure behind the scheme:

Here is a simple demo video of the basic protocol in action with a real robot. And here’s another video with Anuraj and Rafa demonstrating the auction marketplace in action.

It might not seem like much compared to the spectacular robot demonstration videos you find all over social media these days, but the point is not the robots themselves, or what they do, but that it is all being orchestrated over the open internet, using mechanisms that can potentially scale planet-wide without being owned or controlled by any single entity, such as a powerful corporation or state.

In this example, the brain is distributed across multiple rovers and the LLMs that can control them. The fabric is a stack of different protocols handling various coordination needs, ranging from discovery and verification of capabilities in a variable-trust market environment, to actually enabling the teleoperation connection, to handling the auditing of results and completing any financial transactions as agreed upon. All in high-speed automated ways that still allow for case-by-case judgment and decision-making by AIs supervised by humans.

It is worth comparing this vision to a competing vision: The kind promoted by vertically integrated robotics companies through jazzy demos featuring robots doing impressive acrobatics in controlled environments. These visions typically rely on highly integrated and closed products, even if they sometimes offer lip-service to open-source affordances for some parts of the whole picture. These are comparable to early proprietary computing networks, or contemporary social media platforms owned by large corporations.

An open robotics marketplace, on the other hand, would be more like the open internet – anyone with a robot of any sort (from small hobby rover in someone’s basement to a billion dollar rover on Mars) could potentially join, and connect with anyone else with a need for that particular robot’s capabilities and the ability to pay for it. It would be messy, janky, and glued-together. It would form a kind of tangled bank of artificial organisms competing for survival in an atomized market-like environment.

Which world would you rather live in? Yet another world of monopolistic platforms, or a cheerful anarchy of robots and their owners wheeling and dealing in an open economy?

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The Primordial Soup

These are just two examples of how protocols and AI can be put together in creative ways. There are dozens of others being experimented with right now, ranging from the viral and highly visible OpenClaw ecosystem to obscure and specialized ones that are as yet only crazy ideas in the heads of teenaged hackers.

Over the next decade, we’ll probably seen tens of thousands of such brain-and-fabric ecologies take shape independently. They will likely fall into loosely similar families of patterns. Some may converge, others may diverge, just like biological ecosystems.

If you think that’s a fun vision, imagine what could happen once these ecologies begin to run into each other and interconnect. Thanks to AIs, protocol systems that would have been non-interoperable in older technology paradigms will be able to automatically figure out how to talk to each other, forming squishy, oozy interfaces with each other, cobbled together by AI agents feeling each other out and inventing pidgins as they go. When AI is cheap enough, and the basic fabric capable enough, inventing a language even for just two entities to talk to each other for one short interaction becomes possible.

Take even the two examples in this essay. We can imagine photography robots in different parts of the world in the Yak network submitting photos to Titles to train individual models based on their particular image-making capabilities (such as different types of camera). Users could then sample those models to synthesize composite images by sampling those models to create strange new images seen by wholly synthetic robotic eyes.

Imagine that sort of thing, but in a primordial soup of thousands of ecologies.

As this process unfolds over the years, and the primordial soup boils and bubbles, the planetary computational character will begin to emerge in the form of a planet-scale emergent distributed brain, integrated and orchestrated by an emergent world fabric.

In both the Hitchhiker’s Guide universe and the Culture, machine personalities are narratively load-bearing rather than cosmetic features or shallow plot devices to make the non-human characters superficially “interesting.” The personalities shape the plots in material and non-human ways.

One fun example is the Nutrimatic drink machine in HHG, which claims to produce personalized drinks, but always produces the same liquid that tastes “almost, but not quite, entirely unlike tea” (which strikes me as an embodied behavioral cousin of some of the lazier hallucinatory and averaged-out responses of modern AIs). When Arthur Dent forces it to work harder to actually produce tea, it draws so much computing power away from the ship’s navigation, that the ship crashes.

In the real world, AI personalities are turning out to be just as consequential, though it’s not as funny when actual human lives are at stake.

The Missing Mechanisms Problem

In this essay, I want to argue that AI personalities are central to solving a problem Tim O’Reilly posed in a recent blog post: articulating agent ecologies with the right mechanisms.

Right now, there’s a problem that makes the AI/human knowledge market less efficient than it could be. The disrespect for IP that has been shown by the AI labs and applications during the training stage, and even now during inference, has led to efforts by content owners to protect their content from AI. Do not crawl. Lawsuits. Reluctance to share information. Even the AI labs are complaining about the theft of their IP and trying to protect their model weights from distillation.

It’s an economy crying out for mechanism design.

I want to address a slightly generalized version of Tim’s question, and think about ecologies rather than economies, drawing inspiration from one of our favorite essays here at Protocolized, Frank Chimero’s Only Openings, which argues that effective ecological stewardship relies on mechanism design that aims to manage problems indefinitely, rather than solve them once and for all. In Chimero’s essay, the specific personalities of the species involved in the case studies he talks about – bears, wolves, humans – materially shapes the mechanisms that help manage their interactions indefinitely and effectively.

How do we apply this idea to AI agent ecologies?

Modern real AIs already exhibit clear personalities, a mix of “genuine people personalities” inherited from their training data and protocols, and non-human dispositional aspects that are the result of model architectures and their underlying mathematics (transformer and diffusion models have different personalities for example). The current version of ChatGPT strikes me as an overconfident and slightly patronizing consultant, while Claude strikes me as an over-solicitous personality with some false humility (vaguely Uriah Heep-ish) going on. The human-legible and entity-anchored aspects of personality are merely the tip of the iceberg.

As with humans, it turns out that the personalities of AIs are intersubjective and situated. They are functions of how coherent entities disclose themselves and relate to each other, in the context of the things they do in collaboration. The personality of an AI or robot is a function of the stable gestalt disposition it presents as an interface to all other entities it might relate to. This disposition helps set expectations for counterparties in relationships. If you met an AI that called itself No More Mr. Nice Guy, would that shape how you interacted with it?

This point is not restricted to AIs, robots, smart homes, and other “intelligent” technological entities. Any sufficiently complex technological entity with any degree of autonomy of operations must present a stable disposition that can be deciphered and relied on by entities that interact with it.

For example, on the Ethereum blockchain, Layer 2 networks providing rollup services (bundling transactions into batches to submit to the Layer 1) can be “optimistic.” Here “optimistic” is both a term of art in the engineering, and a human-like attitude that embodies a pattern of expectations. Or to take an older technology, road traffic systems in well-developed urban regions tend to present a deferential attitude to pedestrians, while suburban ones tend to present a hostile attitude.

For a complex technology, it is useful to imagine an underlying “personality” with an intelligible point of view generating the visible disposition (regardless of where you land on the philosophy of mind question of whether there is “something it is like to be” an AI or robot). The interaction surfaces of simpler technologies can be mentally modeled as relatively unchanging “user experiences.” But with complex technologies, it is useful to model those surfaces as the fluid response surfaces of stable non-anthropomorphic personalities; ghosts inhabiting machines.

Perhaps the term Haunting Experience, or HX, should replace UX, for sufficiently complex technologies. AI certainly qualifies.

An AI presenting an intelligible HX is not quite as on-the-nose a feature as an AI being “explainable” (a rather ridiculous legalistic requirement to impose on a technology in my opinion; how many human beings, groups, or institutions are “explainable” after all?), but it does render complex technologies as somewhat predictable gray boxes rather than entirely inscrutable and unpredictable black boxes. It does not make them explainable, but it does make them narratable. It makes them composable.

What does this buy us? It buys us the ability to assemble such technologies into larger ecologies. This is where the real power of thinking in terms of HX becomes evident, when you are shaping the behavior of entire ecologies, rather than single agents.

Haunting Experience (HX) Design

We typically translate the personalities of simpler technologies to human-centric UX measures like “latency” or “walkability,” but with complex technologies, it is useful to reframe the problem in terms of designing the personalities of ghosts in machines (both plural, since we are considering entire ecologies), and how they should haunt us.

So how do we encourage the right ghosts to emerge?

The personalities of technologies are the result of two entangled forces acting together – human (and increasingly AI) design, and emergence. This is similar to the design of market mechanisms by human policy-makers in institutions (such as central bankers and elected representatives), interacting with the emergence effects studied by economists, to generate the economy we actually inhabit. It is neither an inscrutable black box, nor completely determinate. It is just intelligible enough to inhabit – it is no accident that Adam Smith used the ghostly metaphor of an “invisible hand” for describing the mechanisms of an economy.

We might use the term HX design for this sort of thing – conjuring ghosts within machines that exhibit particular desired personalities. The term is inspired by the output of a distributed AI workshop we ran last year (and derived from somewhat related usage of the term hauntology by philosophers such as Derrida and Mark Fisher).

You might reasonably suspect that HX design primarily has to do with AI and robots, but this would be a mistake (a typically anthropocentric one). Technologies that invite anthropomorphic projection (or possession perhaps) aren’t the only ones that induce partially designed emergent ghostly personalities within themselves.

Engineering is full of such conjured personalities. “Greedy” algorithms take the first good option they find. “Optimizing” algorithms look for the best option in some sense. “Satisficing” algorithms solve for “good-enough.” “Least commitment” approaches delay decisions as long as possible. “Eager” algorithms are proactive about whatever they do.

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High-Personality Ecologies

In every such case, there is a cost to the “personality” deployed for problem solving; one that must often be paid for by counterparties in transactions. If your automated decision-making is “optimistic,” then a counterparty system that monitors and audits its decisions must be “pessimistic” to make up for it. The calculus of benefits and costs to others associated with an agent’s behaviors, to a first approximation, is that agent’s personality.

The personalities of technologies, in other words, are intelligibility mechanisms for predictably distributing the computational cost of autonomous decision-streams among interacting entities (including both humans and autonomous machines).

The upside of such high-personality ecologies, with a lot of variation and diversity in the agents and interactions constituting them, is that they are vastly more generative than either monocultures based on low-personality fungible elements, or low intelligibility opaque elements. High-personality ecologies are like relatively free markets, while low-personality ones are like command economies, and opaque ones like the internal managerial economies of closed organizations.

The characteristics of high-personality technology ecologies is particularly clear in the field of operations research (OR), which deals in problems that are almost always NP-hard (i.e. computationally intractable), and must therefore be solved with heuristics that are only effective locally. OR is full of scheduling and planning algorithms that are defined by their personalities, which create consequences that must be dealt with by counterparties. For example, a simple and popular algorithm for prioritizing tasks in a queue, Shortest Processing Time (SPT) minimizes the average wait time for waiting tasks. But in a situation where tasks arrive constantly, it might delay longer tasks indefinitely. Producers of long tasks must negotiate appropriate service-level expectations that incentivize deviations from pure SPT behaviors.

An ecology comprising even simple processing agents with different “scheduling heuristic” personalities, and customers that bring various mixes of tasks for processing, is going to have a particular emergent personality, a particular style in which it gets things done. One that can be shaped and made intelligible and narratable to a useful extent by design. This is what it means for an entire ecology to have a personality. As we learned during Covid, a supply chain being lean or fat is a personality label that indicates how it behaves in real conditions, not a gratuitous obesity descriptor.

I will offer a stronger claim: only high-personality ecologies, ones with unique but mutually intelligible entities, can be economically generative. This is why AIs with personalities, composed into ecologies with personalities, are required to solve the problem of missing mechanisms.

To borrow a phrase from the title of a book by Ben Horowitz, what you do is who you are. And what you do typically involves relationships with others, whether the agent in question is a simple scheduling algorithm or an LLM.

The Protocol is the Personality

As Marshall McLuhan famously observed, every medium (by which he meant any technology, not just communications media) has a message. This is true of all technologies, whether simple or complex. A hammer has a message, as does a television. But sufficiently complex and autonomous technologies take the phenomenon to another level. Characteristic patterns of behavior (the rich “message”) reveal a general personality.

Here it is useful to characterize “sufficiently complex and autonomous.” Roughly speaking, a Turing-equivalent technology (i.e., equivalent to a general-purpose computer) that makes some significant class of decisions autonomously, based on engineered decision architectures rather than natural properties, is the kind of thing I am talking about.

This personality is best revealed in the context of interactions with other entities that must exhibit complementary personalities in order to form stable ecologies. An ecology of personalities with a particular distribution, woven together with particular protocols, has its own emergent distributed personality, just as human aggregates from subcultures to nations have their own personalities. Or, for that matter, pre-AI technological ecosystems such as the Microsoft or Salesforce ecosystems. And applying the same principle, what these ecologies do is who they are.

One way to frame this is: the protocol is the personality.

The behavior of an internet-connected computer isn’t entirely a function of its own architecture. Much of it is derived from the personality of internet protocols. Mac vs. PC or iOS vs. Android might be the atomic individual personality distinctions, but by what you do is who you are logic, to the extent both pairs are situated in the internet, both inherit the personality of the protocols of the internet.

The transition from the relatively atomized PC era to the connected and social (for both humans and machines) internet era took about a decade, but as with everything else, AI seems to be speed-running this phase transition. It is already becoming clear that the personality of different AIs is only partly an innate property of specific language or image models, traceable to their training data. The full personality of an AI is revealed when it becomes socially embedded in an ecology of other AIs and humans, and must deal with the consequences of its own dispositions on others.

The personalities of complex technologies are only fully expressed in the right ecologies. Protocols can be understood as precisely the engineered ecological scaffoldings that draw out full expressions of personalities from individual agents. Good protocols induce rich and generative ecologies. Bad protocols induce lifeless ecologies.

How can you tell them apart?

Protocol Affects

Just as humans might have a “game face” that is a function of specific games they may be playing, technologies too have game faces. We can call these protocol affects. To tell good and bad protocols apart, you have to read their affects.

The personalities of AI ecologies are currently emerging in inchoate, wild forms. Scaffolding elements like MCP and OpenClaw allow for relatively unbridled relational behavior among the various compute and human elements they weave together. But already there are signs of this Hobbesian wilderness being tamed. Protocols that are deliberately designed to shape the personality distribution of entire ecologies of intelligent agents in particular ways, and present them in stable ways, are rapidly emerging.

With humans, we use the term affect to point to how an underlying personality is expressed through deportment and comportment in a particular milieu. Protocol affects are the technological equivalent: Emergent typical behavior patterns of elemental high-personality technologies, when they are composed into “civilized” technological ecologies.

A good example of a protocol affect is the famously verbose and redundant one of TCP/IP, as revealed through jokes shared by networking engineers.

Hello, would you like to hear a TCP joke?
  Yes, I'd like to hear a TCP joke.
  OK, I'll tell you a TCP joke.
  OK, I'll hear a TCP joke.
  Are you ready to hear a TCP joke?
  Yes, I am ready to hear a TCP joke.
  OK, I'm about to send the TCP joke. It will last 10 seconds, it has two characters, it does not have a setting, it ends with a punchline.
  OK, I'm ready to hear the TCP joke that will last 10 seconds, has two characters, does not have a setting and will end with a punchline.
  I'm sorry, your connection has timed out... Hello, would you like to hear a TCP joke?

This “personality” expressed by TCP/IP (which replaced the Hobbesian anarchy of early network protocols) is not arbitrary. It is the result of a network consciously designed for high fault-tolerance under extreme circumstances, including nuclear war, which must continuously trade-off packet delay and packet loss.

Since it is a backend infrastructure technology, this is not a personality that lay users very often see (though they do experience the generativity it induces). But with other technologies, protocol affect can be part of broader human culture. AI, obviously, is one of these technologies.

What sorts of protocol affects might emerge from the various protocol ecologies taking shape today?

Zombiefied Discovery and Distribution

Applying the principle what you do is who you are, we can shed useful light on the nature and disposition of agent ecologies, as they continue to evolve past their wild phase, and develop stable protocol affects that human culture can take root in.

Computers at various scales of aggregation do different things. At the protocol level embodied by protocols like MCP, the main functions are discovery and distribution.

In the older stratum of the internet now entering its sunset phase, both were functions of what we call social media (at least as far as human users are concerned). The protocol affect accompanying these functions was one of delight and serendipity in the early years, which morphed to one of anxiety and frenetic competition over attention allocation in the later years. Thanks to the economic backdrop of the ZIRP era of zero/low interest rates, both discovery and distribution were cheaply available at global scale to almost everybody, with predictable over-exploitation and erosion of trust all around – what Cory Doctorow has labeled enshittification. Humans increasingly began retreating from the open internet to more closed cozy spaces. And the cost of this retreat was the breakdown of discovery and distribution mechanisms that relied on a lot of humans being publicly active online.

The protocol affect of the social internet has unraveled in the last few years. In terms of our personality metaphor for technologies, there is, in a sense “nobody there” anymore. No ghost haunting the social internet. There are no true public social media, and no protocol personality cohering to replace the one that unraveled. What remains is a pre-personality space of endless, mindless culture warring (what I called “the internet of beefs” elsewhere).

The internet still works mechanically, at the packet level, but as a global public social infrastructure with a defined and intelligible personality, marked by particular predictable planet-scale discovery and distribution dispositions, it has become zombified, even as our experience of it has become enshittified – the haunting experience of the public internet, its HX, is increasingly an empty and dispiriting one. There’s no there there anymore.

As a result, in the current era, discovery and distribution have become increasingly difficult and expensive for all activities that require internet-scale provisioning of those affordances. The problem is bad enough for existing needs, such as discovery and distribution of webpages and tweet-like messages. It gets exponentially worse when you consider the needs of new technologies.

Traditional discovery and distribution mechanisms are failing for traditional internet technologies such as social media and streaming video. They are complete non-starters for newer technologies.

Two in particular, are worth thinking about together, as a pair of evil twins: blockchains and AI. Curiously, the answer to the discovery and distribution problem might lie in a term shared by both, with different, but rhyming meanings – token.

The Packet and the Token

The legacy internet traffics in generic packets with some discrimination based on content type, and a presumption of bandwidth abundance. Discovery and distribution ultimately boil down to discovery and distribution of packets. The economy of the internet is, ultimately, the economy of packets. The still-unsettled back-and-forth political pendulum swinging around net neutrality is a debate about the political economy of packets, and whether it should be stewarded like a relatively abundant public commons or a corporatized market (dominated by a few large entities) that allocates a relatively scarce resource.

For emerging computational technologies, a new political economy has emerged on top of the packet economy. This is the token economy.

On blockchains, tokens mediate all interactions that require certain cryptographically secured assurances, in flexible and programmable ways, creating an economy that is something like a non-neutral internet, but one that can approach perfect competition more closely. Instead of large tech companies paying for private bandwidth, or non-net-neutral jurisdictions discriminating coarsely based on packet type (video vs. text for example), capacity can be sliced and diced in arbitrarily fine-grained ways, based on economic decision-making that can happen at bot-speed. Unlike what we might call packetspace, blockspace (and its more esoteric descendant, blobspace) is intrinsically structured as a market that prices interactions in tiny fractions of dollars, and transactional time constants measured in the milliseconds. Blockchain economies begin where the fastest and most fine-grained corners of the traditional economies, such as high-frequency trading, end. For some, this is just metastasized financialization and scams. For others, it is the beginning of economic outer space travel.

For AIs too, tokens are units of production and transaction. We generate text, code, images, and video using computers that measure their work, and charge for it, by the token (to be precise, tokens/second/user). Again, the picture looks like a non-net-neutral internet. How many tokens you get, of what quality, and at what speed, depends on what you’re willing to pay. And as with blockchains, this economy approaches perfect competition more closely. Instead of large organizations paying human programmers, writers, or artists by the hour or by the month, a vast market of individuals and small organizations can pay for code, text, and images by the token. As with blockchains, these tokens slice and dice what we might call inference space in fine-grained ways, with time constants measured in the milliseconds.

Does the term token represent a mere cosmetic connection between two frontiers of computing, or might there be a deeper conceptual link?

I suspect there is a conceptual link here. On both frontiers, tokens organize a natural economy around real scarcity that can ultimately be reduced to energy units (watts powering computers). More importantly, both kinds of token are informationally expressive in a way that packets, as mere “containers” are not.

And most importantly, the two kinds of token are, to borrow a term from electrical engineering, impedance matched. They have similar temporalities, spatialities, and information densities. They can be woven together, to form the warp and woof of a fundamentally different kind of internet. By itself, each is limited. As Matt Webb observed last year, modern AI by itself offers intelligence “too cheap to meter” which makes it more trouble than it is worth to scaffold for economic activity in a sufficiently fine-grained way, at least using conventional economic mechanisms. Blockchains, on the other hand are, among other things, metering technologies that shine precisely in too cheap to meter regimes. The two can, in other words, mesh in a fine-grained way. If you want to allocate work between two AI agents at a token-level of resolution, blockchains can do the job.

This is not idle speculation. One emerging mechanism for distribution and discovery (ERC 8004), combines AI and blockchain tokens in precisely this sense, and has already catalyzed the emergence of an ecology of AI agents that combine metered intelligence and small crypto transactions to form a marketplace. In the next Obliquities column, I will explore specific case studies.

Whether or not this particular approach succeeds, I suspect the foundation of the future internet will be an economy of tokens. Symbolic tokens that carry meanings and associations, and transactional tokens that carry valuations and risks, intricately orchestrated by a scaffolding that generates a tangled bank of private and public information and computation.

More broadly though, to return to the original motivating question, how does this emerging vision help solve the missing mechanisms problem?

Articulating Agent Ecologies

To summarize the idea I’ve been laying out here, the solution to the missing mechanisms problem is high-personality agent ecologies composed of individual agents with their own personalities. These personalities, far from being cosmetic features, are what allow functional behaviors to cohere at all levels, by allowing agents to be intelligible and predictable enough to each other to transact fruitfully, and produce increasingly complex and large scale effects. For us humans, inhabiting such computational ecologies will feel like being surrounded by friendly milieus of ghosts haunting our digital environments.

As a side effect, such ecologies would solve the so-called alignment problem, to the extent that is a well-posed and meaningful problem at all. High personality ecologies create alignment as they go, and wither and die when they fail to do so.

If you find this kind of future hard to imagine, take a peek at the short AI-generated movie we made at our workshop a year ago, South Beast Asia, which imagines (a Southeast Asian inspired) technological future full of AI-haunted digital and physical environments. Read our collection of short stories from our contest last year, Ghosts in Machines. We’re already creating this future.

What sort of physical reality might underlie such a planetary digital-physical hyperobject?

One mental model that I’ve found very useful derives from Peter Thiel’s observation that AI is “communist” while blockchains are “libertarian” in their personalities.

To a first approximation, modern AI tends to be most powerful when aggregated into really large-scale models running in the densest physical aggregations of compute (hence the excitement over gigawatt-scale datacenters). This feature naturally lends them a centripetal, convergent, homogenizing tendency and a “communist” personality.

Blockchains, on the other hand, are really only valuable to the extent they deliver on properties like censorship resistance, global consensus, capacity for irrevocable commitments (what Josh Stark named “hardness”), client diversity, and unbreakable (including quantum-resistant) cryptography. These features naturally lend blockchains a centrifugal, divergent, pluralist tendency, and a “libertarian” personality.

The respective token economies reflect these characteristics. Tokens in the sense of AI are essentially a “communist” currency, local to a particular model’s command economy. Tokens in the sense of blockchains only have value at all to the extent they are not local (“private blockchains” are deservedly mocked). Each by itself is impoverished and incapable of forming a high-personality agent ecology. Together, they can.

The interface between the two economies, I suspect, will feature phenomenology similar to the impossible trilemma in macroeconomics, or the boundary between the interiors and exteriors of firms in a Coasean economics sense.

Understood as a planet-scale computer, how do the two parts relate? AI will clearly be the “brain” of this planet-scale computer, similar to the CPUs, GPUs, or TPUs of individual computers. Whether this takes the form of dozens of gigawatt-scale datacenters running the largest models, and provisioning metered intelligence to the planet, or a more scale-free distribution of AI processing capabilities all the way to billions of intelligent entities on the network edge, is an open question. Whatever your political preferences for one or the other, there are also technological questions still being investigated. Is maximal aggregation necessary for performance? Can a gigawatt dispersed across a planet-wide decentralized network of small AIs be as capable as a single datacenter? Does embodiment matter? Does better local context beat cheaper tokens/second/user?

These are questions for which we will discover answers over the next few years.

The role that is likely to be played by blockchains (or functionally equivalent protocol technologies) will be that of the fabric. In modern computing, at all scales, the term fabric is usually used to describe the scaffolding that connects the different bits and pieces of the brain. There are fabric-like elements at the level of chips, servers, racks, and datacenters. The internet itself serves as the fabric at larger scales. The overall planetary computational fabric is a mix of smart and dumb elements. Fabrics embody the boundary intelligence of a system.

Blockchains are fabric technologies that can scale from personal computer scale to planet scale. They induce fabrics that operate by a different grammar than the familiar one we have today, but it is a grammar that is friendlier to agentic AI.

The fabric and the brain – an architecture for the emerging future of the internet that can sustain sufficiently high-personality ecologies to allow our frontier technologies to fully express themselves and truly thrive.

This is a very recent vision for the future of the internet (and indeed, the planet). As recently as five years ago, it was meaningful to describe Ethereum in terms of its original vision as a “world computer.” At the time, it was the only entity that merited such a description, since it allowed small-scale, highly constrained Turing-equivalent computing (the EVM, or Ethereum Virtual Machine) to run on a public blockchain. That was as good as planet-scale computation got, since traditional compute is, in a sense, stranded compute trapped within industrial-age organizational boundaries. There was no meaningful way to plug that compute into a planetary fabric, with or without blockchains.

AI brainpower though, is atomized into token-sized units (embodied by memory more than processing as we have come to appreciate), and capable of flowing smoothly across contexts. A fabric that can shape those flows, while preserving privacy with cryptographic guarantees, can create a kind of planetary intelligence that was impossible to even imagine just a few years ago.

One updated vision for the future of Ethereum in particular is as a world fabric rather than a world computer. It is, of course, not the only candidate auditioning for the role.

Whatever form the protocols constituting the fabric of planetary intelligence take, we will soon be living inside a planetary brain-and-fabric computer.

What will we do with this computer? That’s the question.

In the weeks since, thanks to the explosive adoption of coding agents like Claude Code, we’ve been inundated by evidence for this view of the future of AI. Amateur hobbyists are now vibe-coding entire complex digital production infrastructures involving dozens of agents swarming in parallel across a single computer’s filesystem, within complex organizational scaffoldings. We could think of these as agent factories.

Agent factories enable a great deal of complex higher-order action. Much of the attention has been drawn to moltbook (“Reddit for agents”), and the many entertaining trainwrecks involving OpenClaw (“claw” seems to have emerged as a term of art for an agent living dangerously and autonomously on its own server on the public internet, often armed with crypto wallets – what could go wrong?). But the truly interesting developments are largely invisible – individuals with significant mutual trust interacting with each other through their personal and bespoke Claude Code infrastructures, exchanging work-in-progress materials.

We could call these interaction patterns have your factory call my factory, and the underlying relationship pattern F2F (a rather fun overload of face-to-face). An exuberant F2F ecology is likely to be a central feature of the protocolized future.

My own personal experience with Claude Code illustrates the pattern well.

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Case Study: Indie Book Publishing Pipeline

I started my first week of using Claude Code by producing an online book of my Twitter archive, but I ended it by setting up an entire book manuscript production factory. Currently, my factory dashboard shows a couple of dozen book projects in flight, most derived from two decades worth of my personal blog and newsletter archives (including new editions of old books), and a handful of from-scratch projects.

Factory is really the only word for what I’m doing. In my case, a factory resembling a flexible job shop of the sort that makes varied things using a flexibly configured set of machine tools. My book projects are individual enough that each needs some bespoke handling, but similar enough that many processes and code modules can be reused. So a job shop is both an appropriate metaphor and a useful reference pattern. Other patterns would be appropriate for other production activities – flow shops, cell-based factories, assembly lines.

I found myself relying on dim memories of decades-old industrial engineering and operations research coursework to set things up. The factory floor is a portion of my laptop filesystem within my Dropbox folder, where various Claude Code sessions operate within a folder hierarchy and each folder has its own claude.md file. Each folder with a claude.md is a bit like a workstation or cell. Thought needs to go into defining boundaries, hand-off artifacts, and so on.

But setting up a Claude factory wasn’t the most interesting thing I did. It was setting up a logistics link between my factory and another Claude factory, set up by my long-time publishing co-conspirator , who has helped me personally publish two books in the past, and also handled much of the publishing work for Summer of Protocols/Protocolized, including the complex Protocol Kit and four books.

Jenna also happens to be an enthusiastic early adopter, and has set up her own factory to produce finished books from manuscripts. My factory takes messy raw materials and produces rough first-draft manuscripts. Her factory will take those manuscripts and produce finished artifacts that can be uploaded to Amazon for distribution as print and ebook volumes.

The handoff point between us is a shared Dropbox folder plus a “manuscript transmittal” server she’s set up for metadata. Here’s my “account” view of her factory:

And here is the manuscript transmittal page:

The fascinating thing? This very corporate-seeming pipeline was set up by two people who basically don’t code!

What we do bring to the party though, is domain expertise.

Domain Knowledge > Coding Knowledge

Jenna is a publishing industry veteran who knows exactly how to set up and run book production. I’m an experienced blogger and self-publisher with a dozen self-published books to my credit. We both know what we’re doing on our respective ends of this pipeline. Claude Code brings highly skilled coding ability to the party, but Jenna and I bring the (rather artisanal in this case) domain-specific knowledge required to decide what to do and how. Tasks that call for opinionated and tasteful decision-making rather than raw intelligence or procedural skills. We do both need some intelligence to make this work, but that’s not the main act. It’s a sideshow, provisioned in commoditized form by Anthropic.

Our F2F link is live. We’re currently discussing fussy details that are involved in producing a print version of my Twitter book. I sent her a docx file produced by my factory that’s the starting point for her factory, and she turned it around with revised requirements, which I implemented and returned to her. I had to tell my factory to redo the initial docx to address some global styling issues before Jenna’s factory can begin designing the book. I’m figuring out how best to automate the pipeline.

Both of us are using a good deal of custom code written by Claude Code, along with open standards like docx. We’re currently using Vellum (book design software), but we’re exploring replacing it with a bespoke design tool.

So far I haven’t touched a line of content text, and haven’t even looked at any code. I watch the action entirely at the shell level, like a factory floor supervisor. Python, json, and html fly around, while I chew on my cigar in my top hat.

This is not an isolated example. Elsewhere, with collaborators on a hobbyist robotics project, I’m helping prototype a discovery and marketplace infrastructure using the Ethereum 8004 discovery protocol for AI agents, and the 402 payments protocol.

And in the broader Claude ecosystem, the primary article of commerce is the skill, a fragment of agentic intelligence that perfectly fits the definition of social kernel. A kind of industrial intermediate, albeit for a cottage industry of individual-scale agent factories.

I’m sure there are plenty of more complex examples under development.

What are we to make of this type of F2F relationship? The principals (“legal persons”) involved in such interactions are individual humans, but the connections between them are a universe apart from the simple “friend” and “follower” type digital relationships we’re used to. Interactions are vastly more complex than social objects in digital envelopes that track likes and shares.

The only precedent I can think of is B2B relationships between factory-like entities.

I strongly suspect that this is the invisible 90% of the iceberg in the agentic AI revolution. While the public theatrics on moltbook and the claw ecosystem are much more visible, the sheer depth of capability integrations enabled by factory-to-factory connections between individuals argues in favor of high-trust relationships being the locus of the real action. Especially considering the zeitgeist vibe shift, in human social media, from more public spaces to Dark Forest/cozyweb spaces.

In intelligence media, there’s a lot more you can do within trusted friendships than within parasocial relations. Low-trust relationships are in fact rapidly hemorrhaging social energy.

The Factory-Owner Economy

One of the biggest concerns going around right now is the future of jobs, or more generally, the future of work. The conversation is a familiar one. Pessimists issue apocalyptic warnings of impending economic collapse. Optimists rehearse sunny arguments about the lump of labor fallacy, Jevon’s paradox, and Milton Friedman’s notion of “new wants and needs” emerging to fill the economic vacuums created by the disappearance of old ones.

Whether optimistic or pessimistic, our discourses seem unable to think about the future outside of existing categories – jobs, SaaS companies, outsourced white-collar labor, knowledge-work professions, mortgages. Several viral essays in recent weeks have (rather cynically and aggressively) doubled down on prognostication based on such bankrupt ontologies, to feed both wishful dreams and lurid fears, instead of taking on the harder work of coming up with useful new categories to think with.

The “factory owner” economy offers at least one new category to think with. It suggests, for instance, that in the future, rewarding and fulfilling work will be organized neither as “jobs” nor “gigs” but at least partly as an economy of bespoke F2F artisanal capitalism. The main factors of production are intelligence-on-tap that is too cheap to meter at the detail level, computers, and internet connections.

The F2F ecology won’t be the whole future of course (one of our doctrinal beliefs here at Protocolized is “your imagined future isn’t the only one unfolding while everything else stays unchanged”), but it will be one big force shaping it.

Is this an optimistic or pessimistic future? That is the wrong question. The right question is: Is it an interesting future; one that allows us to continue playing the game of civilization?

We here at Protocolized believe the answer is yes. And a big part of our mission this year is to put some serious thinking behind that answer.

Behind the scenes, a new stratum of public and private infrastructure protocols, starting with RSS and the Facebook newsfeed, powered the shift. This was accompanied by a shift in hardware – from the desktop and laptop to the phone as the primary device for accessing the internet, and with the camera and microphone replacing the keyboard as the primary input mechanisms.

In 2026, we at Protocolized are betting that a similar transition will begin in AI, from destination AI to intelligence media. A landscape shaped by “visits” to oracular destination AIs will be reshaped around intelligence circulating in intelligence media. Here we mean “intelligence” in the sense of a kind of content (similar to what “intelligence agencies” produce and transmit) rather than a kind of processing capability.

We have opinions on how this shift ought to play out. We would prefer it to play out in decentralized, capture-resistant ways, rather than through aggregation dynamics powering feed-like experiences.

Intelligence media need not themselves be particularly intelligent. Cutting and pasting an LLM chat link into a messenger, committing AI-generated code to GitHub, or downloading a set of weights all count as intelligence media operations. Last weekend, an important new class of intelligence media emerged with moltbook.com: social networks for AI bots.

What is important about all these emerging examples is that intermediate artifacts of AI processing move from one locus to another, in a permissioned, socially mediated way, jumping contexts in the process.

Intelligence media are media through which intelligence flows from one locus to another, primarily in disaggregated forms that get further metabolized as they flow, via interaction with shifting contexts corresponding to distinct loci.

We’ve already witnessed a shift from “prompt engineering” to “context engineering,” and we are about to discover that the most powerful way to (re)engineer context is to simply move work-in-progress to a new context. That is what intelligence media do. They achieve context engineering through context switching.

When Alice shares a ChatGPT link with Bob, who opens it and continues the chat, Bob’s fork of the chat can now draw on Bob’s memory context, which need not be shared with Alice (OpenAI of course, remains a third party in the background whom you must trust).

Currently, we’re improvising with the limited intelligence media we already have (chat link cut-and-paste probably accounts for 80%), but dedicated intelligence media, adapted to the needs of moving live intelligence rather than information, are beginning to emerge. Claude Code, for instance, moves coding-assistant intelligence to a directory in your local filesystem. Moltbook moves that local assistant intelligence to a space where that context comprises other assistants.

Will we see a rise in intelligent intelligence media, which might do some sort of processing as intelligence moves through pipes from one locus to another?

Precedents from other domains suggest the answer is no. One precedent is the “dumb pipes” vs. “smart pipes” debate in telecom a couple of decades ago, which has largely been settled in favor of dumb pipes. Another precedent domain is containerization, an “intelligence” transformation of global supply chains where the actual media were “dumb” containers. The intelligence lay in the fact that the contents were increasingly work-in-progress artifacts (which often crossed borders multiple times) rather than either raw materials or finished products. These examples suggest that intelligence will primarily be metabolized in step-function ways, at discrete locations, as it circulates. Not continuously in transit. So we might hazard a prediction that intelligence media will not be particularly intelligent. AI will suffuse the contents more than the containers.

Keep in mind though, that there might be invisible loci inserted between source and destination loci. We might see “context in the middle” attacks. Might browsers or operating systems on either end do things to links between Alice cutting-and-pasting and Bob clicking? Might ISPs sniff around at the behest of state and non-state actors? Ought we use Signal for passing chat links around? What are OpenAI’s servers doing when you generate a share link? “Prompt injection” as understood today is a primitive class of attacks compared to what will be possible once intelligence media begin to mature.

The shift to intelligence media will be marked by the rise of an AI analogue to social objects – what we might call social kernels. Unlike social objects (such as gifs, videos or podcasts), which are largely complete and ready for consumption when they enter social circulation (even if they trigger cascades of commentary, sampling, remixing, and meme-making), social kernels are primarily intermediate artifacts; snapshots of a process of progressive metabolism operating on information objects moving through a sequence of loci and coming into contact with different contexts.

Here is an initial definition:

Social kernels: Snapshots of evolving molecular human or centaur behaviors that shape each other at a low level, and contribute to low-level sociality norms, but do not necessarily catalyze sociality at the higher levels of complete “creators” or “content.”

We will develop the idea of social kernels more carefully in a later column, but a link to a partially complete LLM chat is a good prototypical example to keep in mind for now. It is not a complete artifact like a blog post but a few conversational turns on a theme that can be continued by Bob after it has been created and shared by Alice. Bob can then add a few more turns and share it again. The chat itself, or rather the particular moving instance of the original chat (an entity that repeatedly gets cloned, forked, and mutated as it gets passed along), is the social kernel.

The logic of this larger transition to intelligence media and social kernels, we believe, explains much of the frenetic action we’re seeing almost everywhere along the AI frontier, from the shift to so-called “agentic” AI, to the rise of non-chat UXs, to the sudden acceleration in robotics.

Last year, we at Protocolized paid particular attention to the emerging contours of distributed AI, and early protocols like MCP and A2A which aimed to provide scaffolding for it. It is now clear that the protocolization of AI, both to “distribute” it, and do other things with it, will be much messier and richer than the architects of MCP and A2A anticipated. Intelligence media will likely be a tangled-bank protocol ecology rather than just a handful of dominant standards.

One of the threads we will track this year in this column is how this protocolization is progressing. Make sure to stay subscribed to Protocolized to follow along.

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