The second in Survival of the Sovereign, a five-part series on why the Intelligence Revolution will be decentralised. Technology does not just change the world. It changes us. As Kierkegaard said, life can only be understood backwards, but it must be lived forwards. To understand what AI may do next, we need to look backwards at what technology has done before.

You’re still early, Anon. Read on…

Technology is an agent of change

"Don't bemoan the way things were. They will never be that way again. Pour your energy, every bit of it, into adapting to your new world, into learning the skills you need to prosper in it and into shaping it around you. Whereas the old land presented limited opportunity or none at all, the new land enables you to have a future whose rewards are worth all the risks." - Andy Grove, former CEO of Intel

If you want to adapt to the new world, you'll need to be able to predict it. Humans adapt through pattern recognition. Look back at the history of technology and three patterns repeat, three axioms. Technology is an agent of change. A conduit for coordination. An ecology, not just tools for humanity. Each one reorganises incentives, economics and politics.

Print and steam were agents of change

The printing press changed the means of distribution and dissemination for information and ideas. It standardised and amplified a new language of rights and liberty, connected thinkers across great distances, and helped scattered grievances become organised political pressure capable of challenging Crown, Church, and the machinery of the state.

As Elizabeth Eisenstein argues, print altered the methods by which learned communities collected, stored, retrieved and transmitted knowledge. Before print, even literate elites depended heavily on oral transmission and hand-copied manuscripts. Print made knowledge more stable, comparable, portable and cumulative.

"The fact that identical images, maps and diagrams could be viewed simultaneously by scattered readers constituted a kind of communications revolution in itself." - Elizabeth L. Eisenstein, The Printing Press as an Agent of Change

Mechanisation changed the means of production. Water and steam powered capitalist industry, changing the incentives around land, labour and ownership. Mechanisation reorganised society through those economic incentives. Land became more valuable when consolidated and used for resource extraction and raw material production.

The public commons were enclosed. Communities lost subsistence and long-held rights to farm, gather fuel and forage. Deprived of economic autonomy, people had little choice but to enter the modern system of wage labour. The result was rapid urbanisation and a new social order built around capital and wages. Beneath it, an underclass of the displaced, dispossessed and disenfranchised.

Technology is a conduit for coordination

Language does not only describe reality. It lets ideas move between minds, and ideas drive behaviour. Through the written word, those ideas can travel across distance and time.

Print changed the scale of that transmission. The same words, images and arguments could reach scattered readers across great distances. It changed how humanity could coordinate around information.

Technology had changed the means of coordination.

The Enlightenment was a conduit for coordination

The Enlightenment gave people a new language for political reality. Equality. Autonomy. Consent. Dissent. Self-government. Print gave that language reach.

"The men of the Enlightenment united on a vastly ambitious program, a program of secularism, humanity, cosmopolitanism, and freedom, above all, freedom in its many forms - freedom from arbitrary power, freedom of speech, freedom of trade, freedom to realise one's talents, freedom of aesthetic response, freedom, in a word, of moral man to make his own way in the world." - Peter Gay, The Enlightenment: An Interpretation

Together, the language and the technology made it possible for people to organise around those ideas, challenge the authority of Crown and Church, and reimagine the State.

The Republic of Letters was a distributed network across Europe and the Americas. Its clandestine links used underground smuggling networks to move banned books past state censors.

Coffeehouses became coordination nodes. For one penny, visitors gained access to newspapers, pamphlets, newsletters and, most importantly, conversation. People gathered to read aloud and argue over the ideas of Locke, Voltaire and Rousseau. They became known as Penny Universities.

Common Sense shows what happened when those ideas escaped the intellectual network and reached the public. It was published anonymously on 10 January 1776, at the beginning of the American Revolution, and became an immediate sensation. It was distributed widely and read aloud in taverns and meeting places. An estimated 20% of colonists owned a copy. In today's terms, roughly 60 million copies in three months.

Under pressure, the new language became political force. From the Glorious Revolution through the American and French Revolutions, ideas that had circulated among elites became a basis for mass coordination and revolt.

The Dual Revolution

And that is where we find Charles Dickens, standing at the meeting point of the Dual Revolution. The French Revolution transformed political reality through new ideas and new means of coordination. The Industrial Revolution transformed economic reality through new means of production. Together they reorganised society and birthed the modern world.

"It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of light, it was the season of darkness, it was the spring of hope, it was the winter of despair." - Charles Dickens, A Tale of Two Cities, 1859

These words famously open Dickens’ historical novel, A Tale of Two Cities. Often considered his darkest novel, it was published in 1859 and is set in Paris and London before and during the French Revolution. Dickens was looking back about 70 years, roughly the same historical distance as we now look back at the Second World War. In Paris, two worlds were in conflict.

The aristocracy is represented by the Marquis, who claims legitimacy through inheritance, divine right and noblesse oblige, the principle that privilege entails responsibility. But Dickens shows the elite keeping its privileges while abandoning the obligations that legitimised its power. The disenfranchised and dispossessed are left to bear the cost.

The revolutionaries are represented by the Defarges. They are a destructive force, but not simply villains. Their grievances are real, and their claim is that power must answer to the people who suffered under it. But Dickens does not present this as simple moral progress. The old order lost legitimacy because the people at the top had abandoned their obligations, but the new order could become monstrous too. The revolution descended into the Terror and mass execution. Napoleon then concentrated military and political power.

Dickens was not only writing about France. By looking at revolutionary France, he was holding up a mirror to Industrial Britain, where technology was transforming the means of production. By the time he wrote the novel, most of the Enclosure Acts had already been passed, privatising common land that rural communities had depended on for generations. Agricultural mechanisation had pushed workers off the land. One of the largest mass migrations in British history was underway, as people were displaced from the land into cities. Britain went from roughly 20% urban in 1800 to around 75% by 1900.

The displaced, dispossessed and disenfranchised were what Dickens would have recognised as pauperism, degradation, and moral abandonment, but what we might now call a permanent underclass: people stripped of representation and dignity, treated merely as faceless “hands”.

"In terms of economic productivity this social transformation was an immense success; in terms of human suffering, a tragedy." - Eric Hobsbawm, The Age of Revolution, 1789–1848

Dickens dedicated the novel to Thomas Carlyle and was heavily influenced by his vision of history: that humanity evolves through successive stages of destruction and reconstruction.

As Hobsbawm writes, “Words are witnesses which often speak louder than documents.” He is talking about the Dual Revolution, French and Industrial, a transformation so profound that it gave rise to a new vocabulary: industry, factory, middle class, working class, capitalism, socialism, proletariat, crisis, strike, and pauperism. To imagine the modern world without those words, and without the things and concepts they named, is to understand the depth of the transformation.

Technology is ecology, not just tools for humanity

It is not just that humans change the world with technology. Technology changes humans. Forms like the alphabet, the printed word and mechanisation are not mere instruments that make things easier for us. They are environments.

“We become what we behold. We shape our tools, and thereafter our tools shape us.” - John Culkin, A Schoolman’s Guide to Marshall McLuhan, 1967

What technology does is create interfaces and new entry points into what were only latent possibilities. Without print, there was no interface into the language and ideas of the Enlightenment, and no entry point into coordination at scale. And without steam, no interface into the modern economy. Steam changed the incentives around land, labour and capital, and incentives change behaviour. Land was worth more enclosed than in common, so it was enclosed. People stripped of their long-held rights and access to the public commons had to sell their time. Society was reorganised through wage labour, mass displacement into cities, women entering the factories, a new social order built around capital and wages, and a new kind of state to administer it.

“The failure of entry is not always the failure of truth. Sometimes it is the failure of interface... What has not yet found a workable interface in another world is often mistaken for absence, obscurity, or irrelevance.” - , No Interface, No Entry, 2026

The interface changes what is possible. What becomes possible changes the incentives, and incentives change behaviour. Whoever owns the interface and the infrastructure is sovereign. Everyone else pays rent.

Entry is neutral. The same interface can expand freedom or become an instrument of control. Under pressure and conditions, the ecology selects.

So with cognition extended without consciousness, what now becomes possible? Yes, AI is a tool, and a person may decide what a tool does. But AI is also an ecology. AI is a new interface into cognition itself.

Dear Anon, let us return on red cheeked ships across the wine dark sea, to our modern times. To find a workable interface where we can all be Nobody again in the sight of one great unblinking eye.

To be continued…

The first in a five-part series on why the Intelligence Revolution will be decentralised. We begin with what’s at stake, which is everything. We thread a needle through history, the patterns technology repeats, the existential crisis that will touch everyone, and the counter-revolution that follows, a product of ecology and selection pressure, fought as an information insurgency. So that when we’re finished, we can see the full picture and make a prediction.

You’re still early, Anon. Read on…

A harvest of the mind. Feast or famine?

AI promises us a utopia. A future of unparalleled abundance, where robotics and automation handle the mundane, leaving humans to pursue connection and purpose. Automation that frees humanity from labour. The end of the age-old bargain of wage labour that requires human beings to sell their time in order to exist. A future that frees us from the shackles of necessity, to face humanity’s true frontier: the golden creative leisure. And, perhaps it will.

The coming era of joblessness is not a crisis, not a threat but a blessing - an initiation through which humanity is released from compelling necessity and invited to remember its genius, creative nature - a quiet, graceful advent that breaks the ancient spell binding life to labor. -

But a post-scarcity society fundamentally requires abundance to be accessible, not just producible. If abundance becomes cheap to produce, but the tools that produce it are owned and gated, you lose the ability to produce for yourself. Humanity doesn’t get a utopia. It gets dependency and technological unemployment. Intensified surveillance capitalism. Diminished economic autonomy. And famine.

Because abundance denied leads to poverty and famine. You may picture famine as an empty land, a drought, a crop that didn’t come. Sometimes it is. But often the food exists, and a wall of price, or wage, or law, or politics stands between the hungry and the harvest. In the Irish famine, food left the country while the people who grew it starved, because they did not own the land it grew on. Famine isn’t always a shortage of food. It is often about who is allowed to eat.

And a harvest of the mind, of the intellectual commons, is what is happening. Humanity’s collective knowledge, unpaid labour, and the collated output of thought across generations. The intellectual inheritance of our children, used to train AI without asking, without paying, and sold back to us. Now it threatens to automate away meaningful work while stripping the public of the upside, building derivative systems on intellectual property that was stolen.

"We see a future where intelligence is a utility, like electricity or water, and people buy it from us on a meter." - Sam Altman, BlackRock US Infrastructure Summit, March 2026

The purpose of a system is what it does. If it radically reorganises the economics of society with little regard for long-held rights such as intellectual property or the inevitable legal disputes, then that is its purpose. If it concentrates wealth from humanity's accumulated output into fewer and fewer hands, then that too is its purpose. And, if it harvests humanity's inheritance, sells it back to us with a promise to make us more efficient, then automates away the work it learned from us, then that is its purpose. Elite labs in an arms race, harvesting at a scale and speed Napster could not have imagined in its wildest fever dreams. And Napster was sued out of existence for a fraction of it. So was LimeWire, litigated to death after it.

You don’t own the rails. The United States has issued an export control directive suspending access to Fable 5 and Mythos 5 for foreign nationals, including foreign-national staff inside the labs. Read that again. Your access to the most powerful tools ever built can be switched off because of where you were born.

The interface is not sovereign. It is permissioned.

The old world is dying. The new world struggles to be born

Technology, not ideology, determines the structure of power. Money is a coordination technology, arguably the oldest one, and it has been captured before, used for civilisational control and subversion, to reorganise society. Whoever owns the infrastructure owns you. Sovereignty, the individual’s and the nation’s, is what a captured system takes.

In the 20th Century, the global money supply was captured, and war was waged through credit. We looked at that in my last post.

Consider the tools. Credit, the monetary supply, and the IMF. An economic system captured before you were born, through fiat. A world order pegged to the dollar, run on currency debasement, funding endless wars and propaganda.

“the very operation of the money system is anathema to democratic self-governance” Katharina Pistor, From Territorial to Monetary Sovereignty, 2017

The legitimacy of that world order, the rules-based international order, has drained away, yet its institutions grind on, dysfunctional and decaying. The burgeoning administrative state, US dollar hegemony, globalisation, the liberal democratic order, all unravelling. A long, slow, managed decline. And do not imagine some statesman will step in to set it right, Anon. The apparatus is too large for that now. Most politicians are useless, and the handful of decent ones are pulling levers that connect to nothing, because the system is captured and ungovernable from the ballot box. Money was captured first, then used to capture other systems like governance, media, markets.

“The old world is dying, and the new world struggles to be born; now is the time of monsters.” - Antonio Gramsci

The money supply was never on the ballot. Neither will the means of cognition.

Behold, a white horse. The four horsemen of this century, as Charles Hoskinson calls them, are on the horizon. Trailing fear, uncertainty and doubt. AI extends cognition without consciousness. Quantum extends computation. Synthetic biology transforms living cells. Nanotech turns matter into a machine from the atom up.

Who will seize these tools? Tools that can extend humanity’s capabilities and restrict them are systems of control as well as abundance. Without a mechanism to govern them that is neutral and transparent, they will inevitably fall under the control of either concentrated capital or the deep state. Whoever controls the tools that force radical reorganisation of economics and power structures controls what the world reorganises into.

In the 21st Century, war will be waged through cognition. AI is a coordination technology too. Arguably a base layer, below money. If you don’t control the infrastructure and supply you will suffer both floods and droughts, made dependent on a system controlled by those who do. Nations too. You will need cognitive capital to compete. Abundant today, and the day it is rationed, or switched off, you cannot. It is a rare person who buys a house without a mortgage. It will be a rarer one who gets ahead without these tools. Soon, impossible.

Cui bono?

People fear becoming part of a permanent underclass because historically, the cost of systemic economic shifts has been overwhelmingly borne by the working and middle classes. So that fear is not irrational.

Technological revolutions have caused mass displacement, dispossession, and disenfranchisement. They have stripped people of their livelihoods, long-held rights and way of life. Created a massive, desperate labour pool with no choice but to migrate. These profound upheavals created the modern world.

So the question is simple. Cui bono? Who benefits? Who owns the upside? Who bears the cost? What does life mean to you and your loved ones if you can’t work, must rent, and only have superficial choices to mask a complete lack of control over the system itself?

Everything is at stake. Everything you know, everyone you love, all you have lived for. Every soul who ever lived is implicated, because every trace of human life and memory is becoming substrate for AI, the intellectual commons harvested like spice, and enclosed. Every person born is a participant whether they choose it or not. This is a total war for cognitive supremacy, sovereignty and ownership. A battle for the brain and its accumulated output across history itself.

You feel sure the authors of this upheaval will be obliged to answer for it. But power does not answer willingly to those who suffer under it. It never has. The elite keep the privileges and abandon the obligations, and call it progress.

Nobody is coming to save us, Anon. We will have to decide our own fate.

Are you joining the permanent underclass?

Don't be afraid. Fear is the mind killer

All is not lost, yet. This is still the greatest time to be alive. Pandora's box is opened, and rational hope remains. In future posts we'll look at technology through history and through axioms. Technology is an agent of change. A conduit for coordination. An ecology, not just tools for humanity. And we'll look forward at the Intelligence Revolution and ask how the accumulated knowledge and labour of humanity can be protected from capture. It is a matter of adaptation, of survival of the sovereign.

“If you’re going to try, go all the way. There is no other feeling like that. You will be alone with the gods, and the nights will flame with fire. You will ride life straight to perfect laughter. It’s the only good fight there is.” ― Charles Bukowski, What Matters Most is How Well You Walk Through the Fire

To be continued…

This is a prelude to Survival of the Sovereign, a five-part series on why the Intelligence Revolution will be decentralised. Before we talk about AI, and the intellectual commons, you need to know what happened when a coordination technology was captured at civilisational scale.

You’re still early, Anon. Read on…

“It is well enough that people of the nation do not understand our banking and monetary system, for if they did, I believe there would be a revolution before tomorrow morning.” - Henry Ford

What is money?

For most of 200,000 years human progress was stagnant, in material and technical terms. Growth was glacial until our ancestors developed the ability to trade with groups of strangers. Objects travelled these networks, and knowledge travelled with them, the object a catalyst, the techniques behind it reverse-engineered at the other end.

Exchange is an interface for ideas, a network acting like a collective brain, allowing specialisation. As Adam Smith argued, the division of labour is limited by the extent of the market. And as argues No Interface, No Entry, without an interface there is no entry to modernity.

Trade cannot exist without trust, and it is difficult to trust strangers. If you want to trade beyond villages, this is a problem you must solve. Trust doesn’t scale. Dunbar’s number suggests a cognitive limit of about 150 people with whom you can maintain stable relationships built on trust and obligation.

So how can humans cooperate at scale? Across borders, across languages, across time?

Money is the solution to this problem. Money is a belief. A meme. An instrument people outsource trust to. It’s an imaginary story. Harari calls it the most successful story ever told. The only story everybody believes. Money is a belief held in superposition across many minds. Money’s value exists only as everyone’s simultaneous belief about everyone else’s belief. You accept the coin because you believe the next stranger will, and they hold the same belief about you. In this way it is a coordination technology. An ingenious tool to allow humans to collaborate and cooperate at scale. Even between strangers. Even between enemies.

“In order to trade, man must first lay down the spear.” - Marcel Mauss

Money can reorganise society because it broadcasts incentives and scales trust exponentially. It is a language for trading value across space and time. And when that language needed more expressive range, McWilliams argues, it invented writing. To track obligations, and only later a medium for stories, prayer, poetry. Which is why the oldest name to survive in written form is a debtor’s. Kushim, on a barley tablet from Uruk, five thousand years ago.

The global monetary system has been captured

The gold standard was ended, and the money printer became a tool for civilisational control and coercion. Fiat, money by decree, became an interface for central planning, redistribution and allocation. An entry point for the modern state to reorganise society.

“Permit me to issue and control the money of a nation, and I care not who makes its laws.” - attributed to Mayer Amschel Rothschild, contested

The Financial Revolution (1688 onwards) built the machinery of central banking, national debt, and credit as state power. But every note in circulation was still an obligation on the issuer, a claim on gold, something scarce that limited the supply. That obligation was withdrawn in stages. In 1933, citizens lost the right to redeem. In 1944, the ‘free’ world was pegged to the dollar, and only nation states could claim the gold behind it. And in 1971, Nixon closed the window on that too. The US could not fund its overseas military while European allies kept demanding gold conversion, and the response was to cancel the debt rather than stop the wars. Each step was sold as temporary. None of it was ever reversed. A ratchet, restructuring the global monetary system.

Ratcheting up ever larger claims to what you own

Since then, money has been conjured from nothing. Those closest to the money printer benefit first, and everyone saving and earning has their purchasing power devalued. The issuer gets to say the new money printed is worth as much as the money you have saved, and so transfers value unseen, without ever touching the notes in your pocket or bank account. For all of your life, the value of your money has decreased. Every year it’s worth less relative to the total supply in circulation, because the total supply has increased but your share has not. Wages rise last, after prices have risen from the new money that’s been created. Currency debasement is counterfeiting, and counterfeiting is fraud, no matter who you are.

Most money creation happens in commercial banks, through lending, and trickles down through the Cantillon effect. Credit expansion is tidal. Cheap debt floods the market, extended to whoever will take it, so buyers bid more, and the price of a home rises to match, because the supply of houses has not increased. Now you cannot bid higher without taking on debt yourself, and if you will not take it on, you are priced out. Then credit contracts, and the tide goes out. Borrowers can't service the debt, and the bank takes your house. The loan was conjured from nothing, and the bank risked next to nothing, but your loss is real. Then the tide comes back in, and it all begins again.

The purpose of a system is what it does, so boom and bust is a feature, not a bug. It is a wealth transfer, and the contraction is where the transfer happens. Individual banks can die, but the system’s losses are socialised and its gains are private. The transfer is not of fiat, which is infinite and therefore worthless by itself, but of real assets and generational wealth.

Printing creates more money, not more assets, so it rewards asset owners. The poor hold cash and wages, which are what the printing dilutes most. And who holds more assets than the state itself? Granting itself the monopoly to print money. Taxing what you earn, what you make when you invest, what you spend while you live, and what you leave when you die. Future generations priced out of the good life. A home, a family, a future, an inheritance, and encouraged to study for university debt that is simply another tax. You’re being sold into a Davos dystopia of digital serfdom where you will own nothing, and you will be happy.

What you can learn from this is that technology, not ideology, determines the structure of power. Whoever owns the infrastructure controls the incentives which rule everything around you. Sovereignty, the individual’s and the nation’s, is what a captured system takes.

Monetary sovereignty matters more than territorial sovereignty

Wars are waged with credit as much as arms. Merchant banks backed both sides in the Renaissance. Italian city-states ran wars through condottieri, mercenary captains and armies funded on credit, Florentine and Genoese banks financed rival cities, and the Fuggers of Augsburg bought the election of Charles V.

Napoleon fought a war on sound money. Not by choice. Revolutionary France had hyperinflated its paper and defaulted on its debt, so nobody would lend, and he paid for war in coin, tax and plunder. Britain suspended gold in 1797 and fought the entire war on credit, tripling its national debt and bankrolling seven coalitions against him. Credit won, and gold resumed in 1821, after Waterloo.

“The assertion of monetary sovereignty was one of the most powerful instruments in the construction of national unity and state sovereignty.” — François Villeroy de Galhau, Governor of the Banque de France, 2023

Wars are still waged with credit today, even in peacetime. Nations are persuaded by the IMF to surrender their monetary sovereignty. They adopt another currency, or borrow in one someone else can print, under foreign law. Then they default the way a homeowner does. When supply is restricted, US rates rise, its currency falls and the debt can’t be serviced. Real assets are handed over (the ports, the grid, the oil) to keep the lender happy.

Leaders who try to create their own sovereign supply get Gaddafi’d, and those nations are ripe for regime change by ballot or by force. What fiat currency is really backed by is the most powerful military on earth.

“The relevance and importance of territorial versus monetary sovereignty has shifted in favor of the latter. This shift goes hand in hand with the rise of credit-based financial systems. Such systems depend, in the last instance, on backstopping by an entity with control over its own money supply and no binding survival constraints. Only states with monetary sovereignty fit this pattern. All others are de facto more like private entities, which by definition cannot manipulate their own survival constraint. States can surrender their monetary sovereignty directly by adopting another currency or by issuing their own debt in foreign currency and under foreign law. They also compromise their sovereignty by permitting unlimited capital inflows denominated in currencies other than their own. This is because in times of crisis they will not be able to rescue the domestic financial system from its tendency to self-destruct without subjecting itself to a sovereign debt crisis and the implied need to rely on a lifeline from other states or supranational entities.” - Katharina Pistor, From Territorial to Monetary Sovereignty, 2017

Money is a civilisational control system

To the victor go the spoils. Not a pile of gold in Smaug’s lair. The prize is the control system itself. It does not require ownership of the outputs. This is what a coordination technology becomes when it is captured. Standards define what the system can see, input constraints define what can enter, and together they determine what outcomes are possible before anyone acts.

The system doesn’t need to tell you what to do. It decides what there is to choose from. It decides who gets credit, what gets funded, what exists at all. It is an illusion of choice on a grand scale. And a system like this controls the inputs, and the incentives, so it shapes the outputs and what the world can become. Civilisational management, near total control, designed to be invisible to those inside it. Indistinguishable from free exchange.

Credit conjured from nothing is the load-bearing layer. The faces of public governance are short-term populists or unelected bureaucrats. Politicians defer to institutions, institutions to models. Democratic systems that are a misrepresentation of the people. You did not choose this. You never voted it in, and you cannot vote it out. The money supply was never on the ballot.

You were born into it, and you have lived in it your whole life. So will your children, unless something changes. They inherit the bill twice over: the debt itself, and a currency worth less every year. And the bill is never meant to be paid. It is a recoupable advance drawn on future generations’ account, rolled forever, recouped from their time and labour. The only way to escape the debt is endless growth. A bigger economy, a bigger population, so the debt shrinks in relation to both. But the policy is always more debt. You will never be free of it. Engineered dependency, built in incremental steps, each too small to fight. A doom loop.

The machine knows what threatens it.

“The real threat to monetary sovereignty currently lies in the privatisation of money... the biggest risk is payments.” — François Villeroy de Galhau, Governor of the Banque de France, 2023.

And who is the machine? The organisation that claims the monopoly on force, and granted itself the monopoly on money. Not the organisation of production and exchange, but the organisation of the political means. The entity that reorganises society. Moloch is not a state but a supranational network. Peace (UN), health (WHO), development (World Bank), trade (WTO), stability (IMF), and intelligence (Five Eyes). One god, many altars.

AI, like money before it, is a coordination technology that reorganises society. But it sits a layer deeper. Money captured exchange, and through it, governance. AI reaches the layer beneath both: cognition, where belief itself is made. Capture that and everything built on belief comes with it, money included. It is being rapidly deployed by a handful of private companies to capture the 21st Century.

To be continued…

When people talk about how ecosystems work, they tend to think big: rainforests, oceans. Or, less pleasingly, fields made infertile by overuse. Sussex downland shaped by centuries of sheep. But you don’t need scale to understand an ecosystem.

Sometimes, you just need a jar.

I stumbled into sourdough baking by accident. Earlier this year, I spent a week staying with my sister, who makes beautiful homemade bread. I’ll admit I got quite addicted to a morning round or two of her sourdough toast and marmalade. And being the insatiably curious bugger that I am, I got sucked in.

Now at the heart of my sister’s bread-making process was her starter. A small, living and slightly miraculous culture of wild yeast and lactobacillus bacteria quietly doing all the real work. Which sounds faintly like something your doctor might prescribe an ointment for. But it is mostly just flour, water, and patience.

While some new bakers make their own starters, often they are passed on from friends or family. Her sourdough starter, passed on from German friends and sitting on its own little perch on her kitchen dresser, had a 10-year (originally Bavarian) lineage. A little ecosystem in a jar. And highly efficient, natch.

Inspired but not yet ready for the full, somewhat labour-intensive process, I dug out my old bread maker when I returned home, untouched and unloved for the best part of a decade.

I popped in the ingredients, more or less correctly, from the bible of Panasonic and a big spoonful of my sister’s starter for luck.

Inevitably, my first loaf flopped: both literally and metaphorically. But soon I was getting decent bread. It was then I realized: while the starter was providing some depth of flavour, those machine loaves relied on baking cheat codes like sugar, instant yeast, and butter to make the machine’s output more predictable.

The bread was good. But it felt a bit… ersatz, a bit like cheating. I wanted to know what happens when you strip bread back to first principles. Time to take off the training wheels...

Now in a proper sourdough loaf, there is flour, water and salt. That is pretty much all there is in there, recipe wise. Simple ingredients. But a complex system.

Because with sourdough, you are not just baking bread. You are interacting with a system. And systems do not behave like recipes. Something emerges that you cannot quite predict from the ingredients alone.

And that system is all rooted in that starter.

Keep feeding the microbial little blighters well and keep them snug in the Goldilocks zone of warmth and it is happy days. Put the colony in the fridge, and it waits patiently. Overfeed it, let it get warm, and it can bubble over, collapse and make a right mess of your worktop.

My sourdough starter: a beautiful model of Anglo-German relations

Ecosystems are like that. Too little is not enough but more is not always better. Slow is smooth. Smooth is fast. Exuberance can be a problem.

Recipes deal in components. Systems deal in relationships. Simple ingredients can produce beautiful complexity. But stability and sustainable growth live in the relationships, not the inputs.

Add a little more water, and the dough does not just get wetter. It changes how it stretches and holds. Different flours - white, spelt, organic rye, buckwheat ground betwixt the ancient stones on a misty mountain, whatever - have varying degrees of gluten and thirst. The kneading techniques you employ define the gluten structures. More time proofing on the worktop does not just add, it can undo structure.

But look, this isn’t a breadmaking lesson (much as I seem to be slipping into one). The key takeaway? The variables do not act alone. They act on each other.

So let us not go too far down the sourdough rabbit hole and bring it back to Web3. Because I had stopped thinking in terms of ingredients and started thinking in primitives and interrelationships. You do not just add water, you change what water does to everything else. You do not just add time, you change the interactions. It is relationships all the way down. The microbes in the dough do not just coexist, they collaborate. The final proved loaf is not just inputs. It is interplay.

We will not even get into the actual baking stage. To preheat or not to preheat. Dutch oven or open bake? Baking stone or steel sheet? Steam from water or ice cubes? Bicarbonate crust washes vs lye baths and the rest.

That is a whole other rabbit hole there, which we will not go down here. Maybe in another blog, but do not worry, probably not.

Anyhow. Today marked a bit of a milestone in my sourdough journey.

No instant yeast. No sugar. No shortcuts. No safety net. Just a starter, flour, water and salt. Trust the microbes and the process. Make sure you score the dough so it can expand. Dusted wheatsheaf designs optional.

The loaf turned out pretty good for a first time effort. Not the prettiest, but not unattractive and definitely tasty.

I never thought I would become a bread geek, yet here we are. It’s early in my sourdough journey but writing a blog like this, I can already tell I’m going to have to rein it in a bit… but this whole sourdough rabbit hole turned into the perfect analogy for how I think about ecosystems. Just as with baking, I am still learning, iterating, and trying not to overcomplicate.

So, as an ecosystem operator… what is your sugar? Artifical liquidity mining?

Your instant yeast? A hype-driven marketing campaign?

First focus on your starter. And are you thinking about your hydration ratios?

And perhaps most importantly… what kind of loaf are you actually trying to bake?

How it started, how its going: the journey to here

Footnote: If you are a sourdough nerd with absolutely no interest in Web3 ecosystems, and have arrived here through some dreadful SEO accident, apologies for any inaccuracies, indignities, or displayed ignorance. But if you made it this far, I hope you found the whole thing at least mildly diverting.

(Disclaimer: the views expressed in this post are my own and do not represent my employer or any other entity)

In this post I argue that decentralised ecosystems struggle with coordination because thousands of actors optimise locally without a shared definition of success. That is the risk of entropy in a decentralised system.

A small set of system-wide numbers can provide a shared axis of success and the coordination surface that allows autonomous actors to align around capital productivity and compound growth without central command.

Crypto is great at forming capital

Recently argued that crypto is a “superconductor of capital”. Its superpower is instant, global, programmable capital formation.

From his perspective, the key question becomes how to point that power at things that are actually growing. That assumes capital direction is the core problem.

"That's the only interesting question I see right now: how do you take crypto's superpower -- instant, global, programmable capital formation -- and point it at things that are actually growing?" -

From my perspective, in decentralised ecosystems the deeper constraint is coordination. Without a shared axis of success, system-wide units of account the express it, and a visible flywheel that shows how value circulates, capital formation produces activity but not necessarily productive growth.

Growth can be defined as capital productivity

What is growth? Capital formation is not the same as capital productivity, which I’ll define here as how much durable economic value an ecosystem generates for each unit of capital deployed.

In a decentralised ecosystem, no single authority can allocate resources for the whole system, so growth becomes a coordination problem. But this has also been the trap. The Web3 industry became exceptionally good at forming and raising capital before it became good at deploying it productively. This rewarded fundraising, speculation and activity ahead of durable outcomes.

One of the deepest criticisms of the space is how much money has been raised with so little durable outcome to show for it. Without mechanisms that tie incentives to real performance, capital can drive short term activity but it often becomes extractive, rewarding actors for riding the speculative wave or harvesting subsidies rather than creating products and infrastructure that last.

Durable capital productivity depends on financial primitives that keep capital aligned with the ecosystem over longer horizons, such as non margin credit markets, infrastructure finance and liquidity systems that reward sustained participation rather than short term extraction.

To understand whether a decentralised ecosystem is compounding, you need a small set of system-wide numbers that show how capital enters the ecosystem, how it circulates and how productive it is before it leaves.

Without coordination, capital productivity cannot emerge

The game is to be sold, not told. People align around incentives, outcomes, and visible proof that the system is working. In decentralised ecosystems, the numbers have to go up on the board.

Blockchains are optimised for writes, not reads. The ledger records transactions, proposals and liquidity flows, but it does not explain the system those activities form together. Participants can see their own incentives and positions, but rarely the reinforcing system those roles create or how success in one part depends on success in another.

There is a hidden tax on coordination in decentralised systems as they scale. Roles expand, and the number of actors within those roles expands with them. Possible communication paths grow as n(n−1)/2. You get more calls, more chats and more side rooms. With each additional path, the chance that everyone holds the same picture drops and the fog of war increases.

Conversation scales poorly. In theory people get the message through 1:Many channels, 1:Few group chats and 1:1 discussions. In practice they do not. Engineers form technical channels with validators and developers. Founders build communities around projects and products. Governance develops its own forums, norms and language. Conversation worked when communities were small because talking builds relationships. At scale it cannot keep everyone on target.

But like cells in an organism, conversations do not scale by becoming indefinitely larger. At some point they divide and specialise. As systems grow the same pattern appears. Threading the needle across all these conversations becomes a full time job. The cost is time, and that time competes with activities that carry clearer incentives. For most participants, the barrier to system-wide alignment gets too high.

Complex organisms solve this through signalling systems that coordinate specialised parts without requiring every cell to communicate with every other cell. Ecosystems are no different.

But people are different. People do not just hold different opinions, they think differently.

“Every man takes the limits of his own field of vision for the limits of the world.” - Arthur Schopenhauer

Each actor may wear multiple hats and build a different model of the system in their head, built from countless fragments of conversation, experiences and context. Those models may share themes, but they are never the same because the map is not the territory. They operate from different frames shaped by the hats they are wearing, where they sit in the ecosystem stack, and the incentives attached to those layers. The further apart those roles sit, the more those models diverge.

• Infrastructure optimises for reliability and performance.

• Governance optimises for legitimacy and process.

• Capital optimises for yield and risk.

• Narrative optimises for attention and distribution.

Behaviour that is rational at each layer in isolation can become misaligned with the needs of the system as a whole.

Humans are deeply interdependent, and so is their success. But that interdependence is not always visible to people trying to separate signal from noise. In blockchain ecosystems this often produces silos, proximity bias and misalignment. Good intentions still lead to frustration or extraction. In the end, it is people all the way down.

The problem is that local coherence is not global alignment. When communities come together it can feel like agreement and sound like alignment because people share the same vision. But they are often operating in different languages and optimising for different incentives and payoffs. The gap only becomes visible later, when expectations diverge.

In computing terms the system becomes I O bound. The constraint is not activity inside roles, but the latency of coordination between them.

There will always be leading and lagging KPIs beneath the shared scoreboard. These metrics matter and make sense within their domains. What is needed alongside them is a shared axis of success that defines what winning means for the ecosystem as a whole.

Global visibility of system-wide units of account solves coordination in decentralised ecosystems

Builders and communities abhor uncertainty and, in the absence of clarity, generate their own interpretations of success. Those interpretations are usually shaped by proximity, role, and incentive. Each actor pursues rational goals within their own context, but the system lacks a shared picture of how those activities compound into growth from cycle to cycle, and which outcomes matter most.

This is the coordination gap writ large. Decentralised systems generate enormous amounts of activity but very little shared interpretation. Shared numbers turn activity into signal. What does that compounding activity actually look like?

When an ecosystem agrees on a small set of system-wide units of account for success, thousands of independent decisions begin aligning around the same axis. Builders, investors, validators and governance actors can all see whether the system is building momentum and compounding across cycles. Visible feedback reinforces behaviour, because self observation is self correction.

This shared orientation allows independent actors to orient around the same outcomes and operate inside one another’s decision cycles, in the sense described by John Boyd’s OODA loop and recently mentioned by on X.

OODA is about changing the situation faster than the opponent can comprehend it, which places you inside their decision cycle. Shared visibility of system-wide units of account does more than inform. It increases the ecosystem’s collective self-awareness. As more actors orient around the same axis, they begin operating inside each other’s decision cycles and coordination emerges implicitly across roles and layers.

The power of decentralised ecosystems is parallel experimentation. Thousands of actors can run experiments simultaneously, without waiting for a central leadership team to decide what happens next. Innovation happens everywhere at once and the system adapts continuously.

“It’s in the nature of the swarm to max simultaneous iterations on the fly until a configuration works, then move on to the next target!”

Swarms maximise simultaneous experimentation. When something works, the system moves. That only works with autonomy, and autonomy only scales when actors can see the same outcomes and diagnostics. Shared system-wide numbers work across actors, roles and layers precisely because they are low bandwidth, legible and objective. They allow a decentralised system to coordinate thousands of decisions without requiring a top down hierarchy.

As wrote in his piece on shared roadmaps, decentralised systems still need orientation. A roadmap without KPIs is activity therapy. KPIs without a roadmap is just wishful thinking. Shared direction is what allows energy to compound rather than dissipate.

The path to growth must be visible to all! The Ecosystem Growth Flywheel shows how capital becomes productive

The Ecosystem Growth Flywheel is the visible model of how the ecosystem produces those shared numbers. Shared numbers define success, but they do not explain how the system actually produces it. For that, the reinforcing structure of growth must also be visible. The ecosystem growth flywheel shows how capital enters the system, becomes productive, and compounds over repeated cycles.

If the flywheel stalls, there are two possible explanations.

• The underlying flywheel is sound but execution against at least one of its components is weak

• Or the flywheel itself is wrong and needs to be redesigned.

In practice this requires mechanisms that deploy treasury capital productively into the ecosystem. Examples include liquidity provisioning, systematic market strategies, infrastructure investment, credit markets, or strategic ecosystem investments. If you can’t measure it, you can’t improve it. The flywheel becomes real when growth is visible and each step adds momentum to every cycle. The system can see clearly how each role’s success depends on and reinforces the others.

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Metrics measure the flywheel and enable diagnostics and interventions

If the flywheel explains how growth compounds, these system level numbers show whether it is actually compounding. Healthy ecosystems convert opportunistic liquidity into long term capital commitment. KPIs specific to ecosystem roles and layers sit beneath them as leading or lagging health metrics.

1. Settlement volume. It is the closest thing to GDP for a chain. How much economic activity actually completes. It can include arbitrage, liquidations, market making and internal recycling, so it is not identical to GDP or pure value creation.

2. Stablecoin liquidity. Analysts treat stablecoin depth as the clearest indicator of how much capital can actually move through an ecosystem. It measures deployment capacity and market depth, not durable value by itself.

3. Treasury Net Growth. The treasury generating return above passive yield. If returns come from inflation, subsidy or redistribution rather than productive activity, the flywheel can look healthier than it really is.

4. Capital Circulation. How much economic activity the ecosystem generates for each unit of capital inside it. A practical way to observe this is settlement volume relative to deployed capital.

5. Long-term capital commitment. Growth in non-margin credit markets, and the average duration of loans, show whether capital is confident enough to stay in the ecosystem over longer horizons rather than chasing short-term yield.

These system-wide numbers remain perennial growth diagnostics across an ecosystem’s lifecycle. What changes is which constraints dominate and which KPIs lead or lag at each stage.

Capital allocation must follow the adoption curve

Diffusion of innovation theory adds a time dimension to this framework. The system-wide numbers remain constant, but the KPIs and strategies that move them change as an ecosystem progresses along the adoption curve.

Early phases are driven by experimentation and economic primitives. Builders and early adopters tolerate rough tools because they are searching for profitable use cases, so investment strengthens markets, liquidity and financial infrastructure.

As adoption progresses, priorities shift toward usability, reliability and distribution. The early majority does not tolerate the same complexity as explorers.

Capital allocation must therefore follow the adoption curve. Ecosystems face a sequencing constraint. Capital must be deployed according to the stage of adoption. Optimising for the early majority before real use cases exist wastes capital and produces infrastructure nobody needs. In each phase the goal is the same: increase capital productivity. What changes is which constraints must be solved first and which KPIs are measured.

The “chasm” between early adopters and the early majority is largely about usability. Once profitable use cases exist, complexity must be abstracted away so the next wave of users can adopt the system. The adoption curve therefore acts as a constraint on capital allocation. Much wasted capital in technology ecosystems comes from pursuing problems that are not the binding constraint at that stage of adoption.

A similar argument appears in essay The Seed of DeFi, which argues that financial ecosystems must grow from a small set of economic primitives rather than cloning existing financial features.

The flywheel explains how value compounds within a phase. The adoption curve explains when the system moves from one phase to the next.

Meditations Blog

The Seed of DeFi

If you wanted a towering oak tree, would you try to build a mechanical replica out of steel and sensors, or would you plant an acorn in the dirt and wait? Right now, the DeFi ecosystem is taking the “Clone Path.” By hastily stitching together margin lending and automated market makers (AMMs), it is trying to construct a mechanical replica of traditional…

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6 months ago · fallen-icarus

Capital Productivity. How much economic value can each unit of capital generate while it is deployed in the system?

Capital circulation is not the goal. It is a diagnostic that shows whether capital inside the ecosystem is being deployed productively.

Economist and Grassroots Economics founder highlights the same dynamic in community economies. Many communities have the productive capacity to trade, but money leaks out faster than it circulates locally. When that happens, trade collapses even though the underlying capacity still exists.

Commitment pooling, exchange primitives etc… address this by encouraging value to circulate repeatedly within the network rather than exiting immediately. The same unit of value supports multiple transactions before it leaves.

Check out his free book…

Journal of a Grassroots Economist

Grassroots Economics - The Book is Out!

Writing this book has been one of the great joys of my life—a moment of clarity where I could see a path toward a healthier, more connected world. It is a journey through ancient wisdom, living ecosystems, and the power of communities working together, inspired by the resilience I have witnessed across Kenya…

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2 years ago · 166 likes · 15 comments · Will Ruddick

Winners put up the numbers!

Ecosystems need to organise and reward those numbers to create exponentials and network effects. This is the golden thread that runs through every role in an ecosystem. Everyone ultimately cares about growth, but most people see it through the lens of the role they play, which means actors optimise locally while the system evolves globally.

In practice, the closest thing to a shared scoreboard has often been token price. But price is only a proxy. It does not explain what actually produces durable growth. To compound growth over cycles, people must understand the name of the game. The name of the game is growth, and growth can be defined as capital productivity.

1. Name the game: The name of the game is growth. In decentralised ecosystems growth is capital productivity. Make this explicit and common knowledge.

2. Numbers before strategy: A small set of system-wide units of account defines the game and the winning conditions for the ecosystem as a whole. These numbers create a shared axis of success that can align thousands of decisions across an ecosystem without central command.

3. Numbers are the coordination surface: Decentralised ecosystems generate huge amounts of activity but very little shared interpretation. Shared numbers turn activity into signal and allow independent actors to align without central direction.

4. System-wide visibility: Numbers must also be visible. The reinforcing system that moves them must be legible so each role can see how its success depends on and strengthens the others. This makes interdependent success visible, aligns incentives, and allows participants to observe the system.

5. Local optimisation reinforcing the flywheel: Different actors across roles pursue the same outcomes autonomously and in parallel, using the strategies best suited to their strengths and resources. Local optimisation must move the shared numbers and strengthen the reinforcing loops that compound growth over time. Local observation becomes local-correction.

Cardano provides a useful live case

This is the culture Cardano needs. It launched on chain governance, ran a 350M treasury cycle in 2025, and set out a 2030: Vision, Mission, Strategy Framework and KPIs. That is a serious effort to reach consensus on the common good, which is needed but not sufficient.

But direction alone is not sufficient for coordination at scale. The framework defines pillars and introduces KPIs such as TVL, transactions, and active users. These are useful signals of activity and adoption. What they do not yet provide is a shared axis of success or a visible model of how the system compounds. In other words, they measure participation in the ecosystem but not the productivity of the capital inside it.

In practice, Cardano needs a read layer. That read layer is a small set of shared economic numbers that allow the ecosystem to name the game as growth and define it as capital productivity. Express that definition through shared numerical outcomes and use those numbers as the unit of account for success across the ecosystem. Make the flywheel visible so that, whatever role you play, you can see how success is interdependent and how incentives align. Every team should be able to show, in one or two steps, how its work moves those shared numbers.

Winners put up the numbers, and second prize is a set of steak knives. Judge success by contribution to capital productivity, not narrative or effort. Each cycle must close on the same shared outcomes, and those outcomes must increase capital productivity. Only then does the next cycle start at a higher base. The flywheel compounds instead of consuming its own tail.

That is how decentralised ecosystems turn capital formation into compounding growth. Visibilia ex invisibilibus.

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Acknowledgements

With special thanks to and for inspiration, to Steven Paterson for input on treasury deployment mechanics and capital productivity metrics, and to Chris Broveleit, , for his ideas on a settlement architecture built around physical assets. Thanks also to Tim Bruckman @Tim38300817, , and for ideas, feedback, and conversations that helped shape this piece. As ever, thanks to my Ecosystem Operator collaborator for the many conversations that have helped inspire some of these ideas.

For years the default answer in Web3 was that adoption would come once wallets and dApps had better UX. That was only half the story. UX never improved because users had to hold all permissions. There was no safe way to delegate actions. The agentic layer changes this completely. Agents are the UX now because they convert attention into intent and intent into action across accounts and services. What is missing is an open agent native security protocol that lets them act safely on a user’s behalf.

The recent wave of hacked ClawdBot agents shows why this matters. As Joshua explains, the internet has no real locks or keys for autonomous agents.

People are wiring them into real accounts using security protocols such as TLS and OAuth that were built for human driven apps, not systems that read untrusted content, hold private data and take real actions in a single loop. Those three risk domains used to be separated. In an agent they collapse into one and no legacy protocol on the internet was designed for that architecture.

Until an agent native protocol exists that can handle identity, permissioning, revocation, intent and runtime guardrails, any agent exposed to the public internet sits on shaky ground. Solve that gap and agents can finally deliver the automation and intent based experiences retail adoption has needed for years. The UX bottleneck disappears because the user can delegate safely instead of manually operating everything themselves. has a good piece on securing the agentic internet here…

Jamie Burke

Securing the Agentic Internet

TLDR: We are entering the agentic phase of the Post-Web. This is a transition from simply interfaces that respond to users, to systems that act continuously, autonomously, and proactively on their behalf…

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7 months ago · 3 likes · Jamie Burke

Whoever solves this as an open protocol becomes the trust layer that every serious agent platform, LLM vendor and enterprise deployment has to rely on.

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A few framing thoughts before we begin:

• People approach decentralisation from different places. Some for its security and resilience properties, others for what it implies about agency, trust and power.

• Most sit somewhere along that spectrum, and move around depending on context.

• Shared roadmaps can feel awkward in decentralised systems. Coordination is easily mistaken for control, even when no one is issuing orders.

• And yet, at scale, decentralised ecosystems usually need some shared sense of direction if effort is going to compound rather than dissipate or conflict.

• Roadmaps and KPIs don’t remove agency. They provide orientation. They set direction and priorities, without dictating execution.

People who care about decentralisation tend to sit on a spectrum.

At one end are the technocrats. Those interested primarily in the security properties. Fewer single points of failure. Stronger guarantees. Systems that degrade and recover gracefully rather than collapse catastrophically.

At the other end are those who believe in decentralisation as lore and philosophy. As a way of organising power, agency and trust. Sticking it to the Man. Less an architectural choice, more a position on how the world ought to work.

Most people who think seriously about decentralisation sit somewhere between those poles, moving around depending on context. Most people, of course, don’t think about it at all. It’s a bit like insurance. Largely invisible. Slightly dull. Very important, but only when you wrap your car around a tree or leave the bathwater running.

This is where roadmaps can start to feel awkward. Not because anyone has failed some philosophical test. Mostly because coordination in decentralised systems can be an acquired taste.

Formal roadmaps have a habit of rubbing up against the decentralised ethos. They can feel suspiciously… directive. Or worse, controlling. Structure is easily mistaken for control, even when no one is actually issuing orders.

And yet, somewhat ironically, decentralised ecosystems need direction more than most.

Shared direction.

Everyone is good at spotting problems to solve. Much less clear is which problems matter most, which should be tackled first, and who is actually accountable for fixing them. Naming a problem is easy. Agreeing which one of us is going to do something about it is harder.

There is a persistent tension between being permissionless and still needing accountability. In practice, when everyone is responsible, nobody really is. Important problems need champions.

I work in the Cardano Web3 ecosystem. After extensive socialisation by the Cardano MBO Intersect’s Product Committee throughout 2025, the Cardano 2030 Vision and Roadmap has, at the time of writing, been validated by a little over 60 percent of DReps and is now awaiting formal Constitutional Committee approval.

Governance mechanics aside, it’s a valuable example of how shared direction tends to emerge in decentralised systems. Slowly. Publicly. And through consent rather than decree.

What’s less often discussed is how direction shows up once control is genuinely distributed.

A community-consented roadmap is one of the quieter ways large ecosystems keep themselves oriented. Not as an instruction manual or a directive, but as a shared point of reference. A way of saying: this is broadly what we think progress looks like, even if we all approach it differently.

At scale, ecosystems generate enormous activity. Builders ship. Communities organise. Tokens move. Governance proposals multiply. Without some shared sense of orientation, none of this is wrong. It’s just hard to read. Energy dissipates rather than compounds.

This is where alignment becomes valuable. A roadmap doesn’t rank every initiative. It makes visible which problems are considered foundational and which are downstream. It groups individual priorities into a more coherent whole and provides a common frame of reference on what matters. That alone changes how decisions get made.

Long-term coherence matters for similar reasons. Budget cycles may, but ecosystems don’t reset annually. Infrastructure choices, governance structures, usage enablers and tooling accumulate. A shared roadmap provides continuity across funding rounds, evolving leadership and shifting conditions. Less a plan. More a sense of sequence. The rope across the river, not around the post.

With an important caveat.

Strategy is always a design under constraint. In Good Strategy, Bad Strategy, Richard Rumelt describes strategy in terms of causal logic. Linked actions. Chains of cause and effect. Strategy is not a checklist or a linear plan. It is a set of choices about what matters, and how actions work together. You don’t fix performance by fixing parts. You fix it by fixing how the system behaves.

Ecosystems are no different. You can think of them in layers, with thematic threads running through them.

This is where shared KPIs sit. Not as targets imposed from above, but as agreed signals of what the ecosystem is paying attention to.

Strategy is a set of choices about what matters. While KPIs are not strategy per se, they reveal and quantify strategy. They make those choices visible, and their outcomes measurable. In highly decentralised systems, KPIs can even become the strategy. Not because numbers are perfect, but because they provide a shared reference point where verbal arguments require interpretation.

You cannot expect (and should not want) everyone to agree on everything. What you can agree on is what success roughly looks like. What is in the common interest. What deserves priority. In that sense, the KPIs often are the strategy, with everything that follows becoming a question of detail, ownership and execution.

Of course, shared ownership of a roadmap is not the same as shared responsibility. A problem shared isn’t always a problem halved. Sometimes it’s just someone else’s ****ing problem. And “someone’s” problem is often delegated to being… no one’s problem.

Vision statements and whitepapers provide meaning and intent. And as I’ve outlined elsewhere through the PRESCIENT framework, shared meaning is essential. But behaviour tends to orient around what actually gets measured, funded, reviewed and discussed. If TVL is the KPI, behaviour will optimise for TVL. If developer retention matters, different trade-offs emerge. If real user activity never appears on the dashboard, it won’t factor into decisions either.

This is why KPIs without an agreed roadmap remain hollow. And why roadmaps without agreed KPIs remain rhetorical. KPIs are where strategy stops being abstract and starts being real.

None of this contradicts decentralisation.

Decentralisation isn’t the absence of structure. It’s the absence of unilateral control. Individual agency matters. It simply operates more effectively when there is a shared sense of how separate efforts relate to one another. You won’t win a rowing race if you are all just splashing your oars.

Now, high-agency people are rightly allergic to bureaucracy and pontification. That’s fine. It takes all sorts. But it is different work.

A shared roadmap provides coherence. And when different (and even disparate) elements cohere, the whole becomes more than the sum of its parts.

John was John. Paul was Paul. George was George. Ringo was Ringo. Together they were, well… the Beatles.

A community-consented roadmap doesn’t tell people what to build. It helps them understand where their efforts might be focused, where their work sits, and how it connects to shared priorities.

And in large ecosystems, that quiet sense-making is often what allows many independent parts to move forward without needing to move in lockstep.

Coherence, without centralisation.

• Success is rarely in the code: The fate & fortune of a Web3 ecosystem is determined by the human and economic fabric around the technology.

• A Holistic View: Enduring ecosystems blend hard data and technology with the “softer forces” of narrative, community, and trust.

• The Key Differentiator: The path to long-term Web3 success is through trustworthy coordination and measuring success by human connection, recurring participation, and enduring value over short-term hype.

Why do some Web3 projects with brilliant technology fade while others flourish? The answer is rarely in the code. Success comes from the ecosystem; the human and economic fabric that turns a decentralised network into a movement.

The strongest ecosystems blend hard code with human dynamics.They combine measurable on-chain data with the softer forces of narrative and story, excitement and fear, confidence and doubt. Objective reality meets subjective bias. Technical fundamentals meet real-world network dynamics. Metrics like TPS, MAU and TVL are not just numbers. They are surface reflections of deeper forces: product-market fit, clarity of story, trust in leadership, strength of community, and aligned incentives.

These ideas will be familiar to anyone deep in the ether (pun intended) of the Web3 universe. They’ve shaped my own work since I entered the space a decade ago. And my three-week trip to Asia late last year - speaking with founders, builders, investors, community leaders and enthusiasts across the region - reminded me just how much ecosystems depend on the countless individual actions and interdependencies that make them succeed. Or not.

A tangible mental model

So I decided to write some of this down: a framework to connect these disparate, sometimes contradictory, yet deeply linked components into a more satisfying whole. An approachable mental model to navigate the complexity, and a strategic lens to bring focus to tactics.

I’m calling it PRESCIENT. As well as being an apt (and sure, slightly arch) real word, it captures what ecosystems need most: foresight. Recognising what needs to be true today to create the conditions for success tomorrow. A shared language that bridges technical and non-technical stakeholders. A rough-hewn diagnostic to clarify intent and determine action for builders, investors and ecosystem stewards.

A caveat or two before I dive in: it’s fresh. I’m still refining it. PRESCIENT by name, prescient by ambition… there are no great revelations here and those deep in the space will recognise many of these ingredients. Some of it will be obvious. But I’ll take “No sh*t, Sherlock” as a compliment if it means I’ve connected the dots.

Even if creating it has served only to sharpen my own thinking, that alone is worthwhile. But I hope you, the reader, will also find value in it. I welcome your thoughts.

My hope is that PRESCIENT offers a focused, practical lens on a familiar landscape. One that spans both the tangible and intangible, the emergent and the dynamic, reflecting what makes open Web3 ecosystems such fertile, stimulating and challenging places to build.

The Nine Strands of PRESCIENT

In any complex and emergent ecosystem, the foundations for sustainable growth must be engineered. Each letter in PRESCIENT represents a distinct strand of ecosystem health. Together they form a blueprint for both action and accountability: a way to translate purpose into measurable progress.

P is for Product

The starting point.

Product is the experience users touch and the platform builders rely on. The chain or application must actually work. Fast, reliable, affordable, predictable, and safe. Pick three and build from there.

Product includes user experience and developer experience, wallet flows, API quality, tooling, documentation, uptime, and what you can call “practical trust”: the extent to which the product behaves exactly as users expect.

When something simply works - predictably, consistently, and without ceremony - everything else becomes easier from onboarding to retention. Add a compelling offer, clear incentives and a great product creates its own gravitational pull.

If the product isn’t good, nothing else compounds.

R is for Regulation & Legitimacy

‘Code is law’. So is law, too.

Ecosystems succeed within real jurisdictions, not imagined ones. Regulatory clarity, compliant stablecoins, institutional-grade custody, analytics, identity frameworks, and market-structure legitimacy (e.g., whether an ETF could ever touch your chain) all shape the ceiling of what an ecosystem can become.

Legitimacy is a form of reputation, earned not only through behaviour, but through alignment with evolving global standards and expectations. As Web3 continues to mature, this strand will influence adoption as decisively as the tech itself.

E is for Economics

The engine of participation.

This is the robust tokenomic model and extrinsic incentive structure that attracts and aligns participants, rewards contributions, and ensures long-term sustainability. It’s the airdrops that seed distribution, the rewards functions that drive participation, the liquidity that enables value flow, the on-chain treasury that funds progress.

Incentives are the behavioural primitives of a Web3 ecosystem. They’re the foundational units that shape human action. Just like DeFi primitives define what you can do, incentives shape why you would do it. Good economics drives the behaviour you want; bad economics creates the behaviour you don’t.

Economic architecture should be simple enough to understand and fair enough to trust. It should also reflect the maturity of the ecosystem, recognising that what works early on may not be what sustains it later.

S is for Story

The origin of belief.

The clear and compelling proposition that captures imagination and motivates. A powerful story is simple, purposeful, and easy to retell. It’s your ‘Why’ and gives people context and a reason to believe and to care. A sense-making north star to guide the journey. From an origin story to the tales we tell each other daily, it transforms a technical solution into a shared mission.

A story is what you tell yourself and tell others. You control it. A narrative sits one layer above that: a shared story that gives meaning to events, a way people interpret what’s happening and why it matters. Narratives drive attention, capital, and behaviour long before fundamentals catch up. Stories are yours; narratives are the meta the market already believes and that your stories can help shape. Your story is your house; the narrative is the real estate market.

C is for Community

The human infrastructure.

The living network of customers, users, builders, partners, and advocates who give the project its resilience. A strong community is a defensive moat, a distributed support team, and the most authentic engine for growth. Community is an asset you have; nurture is how you grow it.

Great communities welcome newcomers, retain contributors, and develop their own culture. They create the social fabric that keeps people showing up even when markets turn. They host the emotional energy and informal coordination no roadmap can capture.

But ecosystems are not islands. The strongest communities stay true to their identity while remaining outward-looking: participating in industry conversations, building relationships across chains, and connecting to the wider environment. Communities that look beyond their own walls gain relevance, perspective, and resilience.

A resilient community is not just internally aligned. It is connected, confident, and genuinely engaged.

I is for Integrations

The vascular (eco)system.

The connections that let value, people, and liquidity flow. They operate on two levels; within the ecosystem and across the wider landscape.

Internally, this means composability: dApps, tools, and services that plug into each other cleanly so builders can build faster and users can move frictionlessly. A coherent ecosystem compounds when its parts speak the same language.

Externally, integrations connect the ecosystem to everything beyond it - stablecoins, bridges and cross-chain rails, custody, oracles and the rails that bring in users and capital. These determine whether an ecosystem participates in the broader network economy or stays isolated, liquidity-poor, and hard to onboard into.

With strong composability inside and strong connectivity outside, ecosystems don’t just grow, they accelerate.

E is for Engagement & Activity

The empirical proof of life.

The number of validators running nodes. The consistent developer contributions, application deployments and wallet metrics that demonstrate adoption and product-market fit. The investment in code as much as on-chain usage.

It’s also the level of real engagement in governance driving a project forward.

But activity alone isn’t enough. An ecosystem gains strength when activity isn’t just happening, it’s coherent. And mobilised around what matters most. Even in a decentralised network of autonomous actors, there still needs to be just enough coordination for energy to move in a shared direction. Decentralisation shouldn’t mean disorder; it should mean alignment without hierarchy or gatekeepers. Activity drives performance, and ecosystem-level KPIs are the powerful, unequivocal and objective anchor that removes cognitive load and keeps that alignment clear.

And just as code-level connections shape how value flows, human-level connections shape how effort flows. Engagement matters most when individual contributions interlock, when they compound rather than collide.

N is for Narratives

The shared story the world believes.

We are all creatures of narrative. Narratives move the market and the best projects define their own. Where a story is what you say, a narrative is a cultural current, a compound story the world is already telling. It’s the shared interpretation of what’s happening, what matters, and who is positioned to benefit.

You cannot fully control a narrative. You can only strategically influence, or align with it. But when your narrative resonates with the zeitgeist - the wider mood and momentum shaping the industry - it sings. Whether it’s privacy or real-world tokenisation, financial inclusion or social change, a project that taps into and stakes its claim within the broader market meta amplifies its relevance and its reach far beyond its immediate community.

The strongest ecosystems don’t merely follow narratives; they understand them, align with them, and, at their best, build the cultural momentum that helps shape them.

T is for Trust

The bedrock of everything.

Blockchains may be trustless, but ecosystems aren’t. Trust is earned confidence and belief that a project is worthy, and led by a team that delivers on its promises. It’s as much about founder integrity as it is about network resilience, security audits and transparent roadmaps. It is built through consistent behaviour and reflected in reputation - the collective memory of that trust made visible. It gives users, builders, and investors the conviction to commit for the long term.

In conclusion

Ultimately, PRESCIENT is a mental model, not a magic formula. The world has no shortage of frameworks; an acronym alone builds nothing. Its purpose is to prompt a holistic, honest assessment of an ecosystem’s health.

Too often, projects lean too far in one direction: strong technology but no story; hype without fundamentals; incentives without stickiness; or a disengaged community lacking shared purpose.

Web3’s great differentiator isn’t technology. It’s trustworthy coordination across a decentralised community: systems that are trustless by design, yet trustworthy in practice. PRESCIENT reminds us that success in Web3 isn’t just about code or capital, but about weaving together usage, identity, people, incentives, legitimacy, relevance, and credibility.

The ecosystems that thrive will be those that measure success not by hype cycles, but by human connection, recurring participation, and enduring value. For an ecosystem growth team, viewing their work through PRESCIENT brings clarity. It reveals strengths, exposes blind spots, and sharpens priorities from the top to the bottom of the stack (and more on that soon..).

It also helps answer the essential questions: Are real people really using it? Does the product experience delight? If not, why? Does the story resonate? Are incentives aligned? Do the integrations deliver real value? Is regulation a bridge or a barrier? And where is the next constraint?

Framing strategy through PRESCIENT ensures the focus stays on creating the conditions for long-term success - linking concept to action, action to activity, and activity to meaningful, measurable progress.

This piece was originally published via my LinkedIn.

© Tim Harrison 2025. “PRESCIENT: A Framework for Enduring Ecosystems.” Licensed under Creative Commons CC BY 4.0. https://creativecommons.org/licenses/by/4.0/. Please feel free to remix, build on, or share with attribution.

X is full of Claude advocacy at the minute, but this caught my attention because it reminded me of a Richard Stacey post from years ago on the Gutenberg printing press and the shift to a world where it costs nothing to distribute information.

It is widely acknowledged that the introduction of the printing press was revolutionary in its impact. It was credited as being the catalyst for the Renaissance, the development of science and creating the pressures which forced power to slip from the hands of monarchs and religious orders and become shared across a much broader section of society. - Richard Stacy

It feels like a Gutenberg moment for software.

• Napster-style collapse of reproduction cost

• With Gutenberg-style long-term institutional consequences

This does to software what the printing press did to media. A revolution in the means of distribution that breaks monopolies, removes gatekeepers, and fundamentally changes what can be monetised.

• Revolutionises the means of distribution
• Breaks institutional monopolies
• Removes gatekeepers
• Changes what can be monetised (distribution economics)

People stop trusting something because an institution says so,
and start trusting it because they can see how it works and replace it if needed.

Context: Balaji was responding to Steph Ango’s file over app argument. The original claim was that files endure while apps are ephemeral. Balaji’s extension is that AI changes the equation by making tooling itself reproducible, so the app no longer needs to be the institution that mediates your files.

Share

In this email I will share the ten commitments I make to my team, a meeting guide on how to run 1:1s, and the advice I give to them to work most effectively. You’ll need this as well as a firm grip on your planning processes and an information hierarchy that everyone understands.

The language below is written as if you’re communicating to your team and can be used as a lift and shift for your calendar descriptions.

The Ten Commitments to My Team

A team is strongest when everyone works together, supports one another, and takes care of each other. Please be observant and offer assistance to your colleagues. Don't hesitate to ask for help when you need it. We do not work in isolation.

1. Regular 1:1 Meetings: We will have a 1:1 meeting, and I will never cancel it. However, you have the option to cancel it if needed. Your time is important.

2. Clear Agendas: The agenda for our 1:1 will be included in the meeting invite so that we can remember important topics. However, you are always free to discuss whatever is on your mind during that time.

3. Purposeful Meetings: Whenever I schedule a meeting with you, I will clearly state the purpose of the meeting. I will not schedule meetings without an agenda.

4. Direct Messaging: If I send you a direct message, I will always start with a greeting and explain the reason for reaching out. No suspense or small talk while you wonder what I want.

5. Important Updates: Any news or announcements that significantly affect you, your work, or your team will come directly from me during our 1:1 meetings, rather than being revealed in a large meeting.

6. Timely Feedback: I will provide feedback to you promptly. You will not hear feedback for the first time during your performance review.

7. Trust in Your Autonomy: I trust you to manage your own time. You do not need to seek my approval in advance for being away from your desk or out of the office.

8. Freedom in Your Work Approach: You have the freedom to approach your work in your own way. My focus is on the outcomes, not the specific output. Once we agree on the goal, the path to achieve it is up to you. If I feel it's necessary to suggest a specific approach, I will provide an example.

9. Open Communication Channels: I trust you to communicate with my manager or other senior management if you feel it is necessary. You do not need to seek my permission, and I will not react negatively when you do.

10. Recognition of Contributions: I will properly acknowledge and give credit to you and your team. I will not exaggerate my own role or downplay your contributions. I will ensure proper attribution, especially when senior management acknowledges our accomplishments.

In return, the one thing I value most is the truth. I want to hear your feedback, know when you think I'm wrong, and hear your ideas on how we can improve. Please feel comfortable sharing your thoughts, disagreeing when you see fit, and offering ideas for improvement.

A 1:1 Meeting Guide

You can use this time to talk about what's important to you. This 1:1 is your opportunity to set an agenda and discuss what's important to you. You can use it to talk about where you are stuck or need input, coaching, and/or feedback. Ideas or issues you want to raise?

Frequency: Twice a week initially, then adjusted as needed

Duration: One hour for onboarding, then adjusted to 45 minutes.

How 1:1s Work

You will ensure your updates are up-to-date and walk me through them, when we catch up regularly for 1:1s.

1. Start with Screen Sharing: The first fifteen minutes will be spent screen sharing your Lattice update and walking me through it. Ensure you've filled this out ahead of time.

2. Your Agenda: This meeting is for you, and you will create the agenda.

3. Discuss MITs: Align on Most Important Things, progress, blockers, and wins.

4. Flexible Scheduling: If there is no need to meet, you can cancel a meeting. Just let me know - it's your call. If I have something to add to the agenda, I will ask for it.

5. Communication: If I am doing my job well, you will be doing most of the talking, and I will be listening and engaged.

6. Distraction-Free: Both of us should eliminate distractions and give our full attention during the meeting. If we run out of topics, we can end the meeting early.

Your Responsibility:

• Have an informed view of you work.

• Keep me updated.

• The best people find a way!

• For good advice on managing up, consider reading this thread.

How To Work for Maximum Impact

1. Morning Focus: Allocate your mornings for deep work and reserve afternoons for calls. Or vice versa depending on timezones.

2. No Calls Friday: Adhere to a "No Calls Friday" policy.

3. Buffer Time: Keep 30% of your week free for unexpected tasks.

4. Blocks of ‘Focus Time’: Communicate and safeguard your dedicated focused work time by adding it to your calendar, setting away messages on Slack, and informing your team. Utilize 'focus time' on Google Calendar to schedule dedicated time. Avoid scheduling meetings on Fridays and during the first half of Mondays.

5. The Rule of 3: Wrap up workdays by listing three high-priority tasks for the following day. Consider using post-it notes and placing them on your computer screen. Repeat this practice at the end of the week as well. Identify next week's priorities and potential obstacles every Friday. This practice helps declutter your mind and reduces the "Sunday Scaries."

6. Stick to the System: Choose one productivity system and commit to it. Ensure you master updates and 1:1s which are scheduled in Google Calendar though you write them up.

7. Mindful Productivity: Strive for efficiency to maintain a work-life balance. Focus on mindful productivity: aim to complete tasks efficiently and effectively to be able to switch off and be more present in your personal life during non-work hours. This promotes a healthy work-life balance.

Final Thoughts

High performance in a remote team requires both leading people and managing things effectively to create a sense of urgency. Without clear direction and management, remote teams can become slow. By following these commitments and guidelines, we can work together efficiently and support one another.

Thanks for reading

Best of luck on your journey towards community-led growth and product-market fit!

This email is about a chat I'm having with our Community Experience Lead, Benedict Corroon (pronounced like 'Macarons', the French treat). The chat is about projects and startups in our wider network. We believe that developing a shared approach to building communities will allow us to learn from each other, and we want to open this discussion up with the Cardano ecosystem ready for Ben O’Hanlon to bring to Dubai for the Cardano summit.

At the bottom of this email will be a Miro Board you can explore and leave comments in! Leave your Twitter and/or email too as we might do some Twitter Spaces.

INVITE TO MIRO BOARD

Introduction

Introducing our version of the HEART Framework. We have expanded on Google's original framework and made it more suitable for communities and ecosystems, including startups, spinouts, and grassroots projects. Our goal is to increase the return on learning and to achieve that, we need a shared language.

How the HEART Framework helps

The HEART Framework goes beyond measuring metrics; it aims to establish a standard that allows teams to evaluate their performance using shared North Stars. Additionally, it offers community managers and developer relations the flexibility to define their own success using customized goals, signals and metrics.

Who should use the HEART Framework?

The original HEART Framework, rooted in product-led thinking, was developed by Kerry Rodden, Hilary Hutchinson, and Xin Fu for UX teams at Google. The main goal was to give researchers and designers tools to improve user experience. It's also useful for founders, teams, community managers, and developer relations to drive community-led growth, make their work more noticeable, and promote knowledge sharing. The system consists of five parts: Happiness, Engagement, Adoption, Retention, and Task Success. You can use these as a guide or add your own metrics. The aim is to have a common language when talking about success.

How to use the HEART Framework?

1. Goals are big things you want to achieve in your community. They are the main things you want to reach before you use the HEART framework. Your team should agree on these goals and make sure they are easy to understand. Knowing your goals from the start helps you choose what to measure.

2. Signals show if your goals are working or not. They should match with the parts of the HEART framework that matter to you the most. For example, if your feature is made to increase involvement and keep people coming back, your signals should show these areas. Signals can be seen in how users act and help to see if your goals are reached. At this stage, you should also decide how you will collect your data, like through surveys or event logs.

3. Metrics are the next step, you turn your signals into trackable measurements. These can sometimes be compared with other communities. These measurements help you see if you've met your goals. When setting your measurements, use fractions or percentages instead of plain data. Lastly, ensure every user action is recorded and automated traffic isn't counted.

INVITE TO MIRO BOARD

Happiness

Happiness is finding purpose. Members find the community valuable, and fun and develop a sense of belonging through finding purpose and role within it. It is measured through surveys or feedback to understand user attitudes and satisfaction.

• Example: Goal is for Members to find the community valuable and develop a sense of belonging.

• Example: Signals could be ‘Good feedback’ and ‘Positive sentiment’

• Example: A North Star Metric could be ‘Net Promoter Score’

Engagement

Engagement measures how often and how deeply members engage with the community and it’s mission. It quantifies the level of member involvement and can be measured using metrics like daily active users or pages viewed per session.

• Example: Goal is for Members to participate in discussions.

• Example: Signal could be more Members spending more time in the community.

• Example: Mtric could pair the size of the community with the participation rate for example 11K in Discord with a participation rate of %.

Adoption

Communities help speed up decision-making by offering actionable insights and increasing our understanding of needs and challenges. Making smart choices creates a culture of ongoing learning and innovation. Regular involvement from members strengthens this culture. Members who benefit a lot often become strong supporters, helping the community grow. We can measure this growth by looking at signs like more active members, seen in numbers like new sign-ups or downloads.or sectors within the broader network.

• Example: Goal could be to understand what our community needs and wants; and to increase advocacy.

• Example: Signal could be to improve decision cycles through moderation and social listening (triage issues into parent categories or narratives and apply to a risk matrix).

• Example: Metric could be Priority-Adjusted Time-to-Resolution (PATR): This metric combines issue weight and time-to-resolution. For example, a severe issue resolved quickly would result in a lower PATR, which is desirable.

Retention

Retention measures how many members continue to engage with the community over time. It evaluates members’ loyalty and can be measured by tracking the number of returning members and referrals over a specific time period.

• Example: Goal could be a sustainable community where people can build lasting relationships

• Example: Signal could be Returning Members and if People would be upset if they lost access to the community

• Example: A Metric could be a Community-Member-Fit Score (CMFS).

Task Success

Task Success evaluates how easily and efficiently users can achieve their goals using the product. It relates to effectiveness, efficiency, and error rates. This can be measured by tracking how quickly and successfully users can complete specific tasks.

• Example: Goal could be to Create and develop Ideal Community Profiles

• Example: Signal could be a good welcome and onboarding experience and most valuable tasks being completed.

• Example: Metrics might be Community Effort Score (CES) and Task Completion Rate (TCR) for three most valuable tasks.

THANKS FOR READING. NOW JUMP INTO THE MIRO BOARD, EXPLORE,

AND JOIN THE DISCUSSION BY LEAVING COMMENTS, QUESTIONS AND FEEDBACK.

INVITE TO MIRO BOARD

Share The Community-Led Growth Guide

This is an experiment with short videos.

We can focus on exploring a single, actionable idea. I'll keep content concise and focused on practical insights. Grab a brew.

If you like it, share it.

Because you’ll be helping to build our Substack into a community of community builders working on community-led growth.

• Twitter: reply to this tweet

• LinkedIn: comment in this post

Thanks for watching. Let me know what you think. Did the video work well in Substack? Was it interesting? Better if?

1. Ecosystem Edge

2. The Interaction Field

3. Exponential Organizations

4. Wardley Mapping

Slides

🧱 I'm building a new Community Chapter to support developer relations and community managers in our engineering and product teams in Input Output (IOHK).

🔑 We're rolling out a pilot for CAMPS scores across the Chapter to support the sentiment scores we capture when asking for a fortnightly (async) update.

📈 CAMPS scores ask the team member to score on Certainty, Autonomy, Meaning, Progress, and Social Inclusion.

🧠 Initial feedback has been a lot more valuable through this lens, both to zoom in to support individuals and to zoom out and look at the big picture for the Chapter.

👉 The first set of scores gives us an anonymized benchmark. From here, we'll gather them twice a month to gain visibility into how they're trending.

Thanks for reading

1. If you enjoyed this and want to discuss it, you can jump into this LinkedIn thread where we can all meet each other.

2. And/or give it a share and reply on Twitter

In this email, I’ll give you something to read over the weekend! I'll share a PDF on OODA Loops and explain why decision cycles are important. Then, I'll share some writings on Memetics in a Twitter thread.

IDEA 01: OODA LOOPS

Here is your copy of Boyd’s OODA Loop (It’s Not What You Think). You’ll enjoy reading it because decision cycles are a universal lever, and that's why OODA Loops are so important.

1. It’s a way of looking at how people act in their environment

2. A strategy for operating in uncertainty

3. A tool to manipulate time

4. A method to deploy limited resources for maximum effect

If you can help your team to minimize their reaction time to tactical problems, train leaders to make sound and timely decisions, and understand and interrupt the competitor’s decisions cycle, you gain the advantage. If a competitor is experiencing uncertainty or confusion and does not act, he gives the enemy willing to observe and act the advantage.

IDEA 02: 🧵Memetics

People don't have ideas. Ideas have people.

IDEA 03: What does a Community Team do?

1. It drives organizational value through the community

2. It listens and brings problems or friction (opportunities) to the organization. 

3. It then brings solutions (products) to the community from the organization.

4. To the community, it represents the company. To the company, it represents the community. It must have both of their interests in mind at all times.

How does a Community Team listen?

I think the best visual for this comes from Richard Millington’s post on LinkedIn.

Thanks for reading.

I’m working on an innovation framework for building communities in Web3 which I intend to share in the near future and workshop it. I’ll let you know more about that soon.

You’re receiving this email because you signed up for the “Minimal Viable Community Newsletter,” a new newsletter I created on Revue. Unfortunately, that platform is shutting down soon, so I have moved us to Substack to continue sharing our learnings as an indie with community building at its core!

1. Currently, all posts will be available for free. However, we are setting up a paid option to offer bounties and promote the newsletter in the future. If the newsletter becomes wildly successful, we may also consider paying contributors. This paid option will allow us more flexibility in supporting and promoting the newsletter and its content.

2. If you are one of the 108 founding members who signed up on Revue, you will receive a paid lifetime subscription.

2. What kind of community are we looking to build here

• We’re on a mission to inspire you to be the spark that lights a fire and spreads change within your team!

• This is a community of community builders! Our newsletter is all about building communities in the world of Web3. As community managers, we know firsthand the critical role strong communities play in the growth and success of decentralized networks, platforms, and products. That's why we've created this newsletter, to provide valuable resources and insights for those looking to improve their skills and create thriving online communities.

• Each edition covers tactical and strategic approaches to building and maintaining communities, focusing on the commercial value a strong community can bring to a business. Our goal is to help community managers become more credible and effective advocates for the importance of community in the world of Web3. Whether you're a developer or a leader in Web3, our newsletter will provide valuable insights and inspiration for building strong, supportive communities. If you want to improve your skills and make a real impact in the world of Web3, be sure to subscribe to our newsletter.

3. You are here!

Let’s talk briefly about Web2 vs Web3 Revolutions. Web2 and Web3 refer to different phases or eras of the development of the World Wide Web.

• Web2 refers to the second generation of the World Wide Web, which emerged in the late 1990s and early 2000s. This era was characterized by the rise of social media, online collaboration, and user-generated content. Web2 technologies, such as blogs, wikis, and social networking sites, enabled users to easily create and share content online. They also allowed users to connect and collaborate in new ways.

• Web3, also known as the Semantic Web, refers to the next generation of the World Wide Web, which is still developing. This era is characterized by advanced technologies, such as artificial intelligence and machine learning, to make the Web more intelligent and interactive. The goal of Web3 is to create a more personalized and seamless user experience, with the ability to understand and interpret user intent and provide relevant and tailored information and services.

In conclusion, the main difference between Web2 and Web3 is that the former revolutionized how people create and distribute content without gatekeepers—and Web3 will change how we self-organize as a society without relying on centralized power structures.

Web2 was transactional, about ownership, and tended to be a monologue to an audience.

Web2 was a significant milestone in the development of the World Wide Web, and it represented a major shift in how content was created and distributed. Before Web2, the creation and distribution of content were primarily controlled by a few gatekeepers, such as traditional media outlets and publishing companies. It was similar to the Gutenberg Printer press in that it revolutionized how information was created and distributed. It enabled a broader range of individuals and organizations to have a voice and share their ideas and perspectives with the world. With the emergence of Web2 technologies, such as blogs, wikis, and social media, the barriers to creating and sharing content online were greatly reduced. This enabled a broader range of individuals and organizations to easily create and distribute content without going through traditional gatekeepers. One of the key benefits of this revolution was that it allowed the flow of information to move faster and be more open and accessible. For example, independent journalists could use platforms like Twitter to share their work and reach a wider audience without going through traditional media outlets. This enabled them to bypass traditional gatekeepers and have more control over their content and distribution.

Web3 (you are here!) is relational, about shared success, and is a dialogue because now people expect to have input.

Web3 is the next generation of the web, characterized by advanced technologies such as artificial intelligence and machine learning. It promises to create a more decentralized, open internet where users have greater control over their data and online identities. Web3 technologies are tools for self-sovereignty, such as blockchain and peer-to-peer networks. This allows for greater collaboration and new business models and opportunities. However, Web3 is about much more than the technology itself — it's also about how people use new powerful tools to share success. Decentralization ultimately means more freedom of association, commerce, and expression. We can spend less time listening to large institutions and brands and more time taking action and solving their problems.

If you’re building a community, the reason why people join isn’t why they stay.

Consider an onboarding plan and increase the signal-to-noise by providing easy ways to catch up and get back into the community, such as newsletters and content. Be a good listener, so run surveys and gather feedback. Ultimately, you want to drive decisions within the community and your team, so you'll need to provide different levels of abstraction when communicating. North Star Metrics is a good example of making it easy to understand what's happening in your community's orbit and beyond it (in the Kuiper belt!).

4. Remember, certainty is the siren's call

Being overly attached to a plan or model is risky because you may fall apart when things change. Please get comfortable with uncertainty and learn to build while in flight because the map isn't the territory! A key factor is understanding how people make decisions to better influence and react. As people face tens of thousands of choices daily, decision-making can become complex and fast-moving on a community scale. 

This is where the OODA Loop, a concept developed by John Boyd, can be helpful.

• The OODA Loop emphasizes the importance of observation and orientation in decision-making.

• It provides a framework to think about how to help people make better decisions and take more effective actions on a larger scale.

• This can result in fewer resources being wasted, more opportunities being realized, and more decisions being made.

• In turn, this can give individuals and communities an advantage over competitors by effectively manipulating time so that they can do more with less.

One valuable resource for understanding this concept is John Boyd's OODA Loops, which provides a framework for improving observation and orientation in decision-making. I will share that with you now here Boyd’s OODA Loop (It’s Not What You Think).

5. Thanks for reading.

If you want to support me, please retweet this and reply with ideas! Next time we can try out the chat feature here.

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