MarsBit published an essay by Conall O'Reilly, translated by Foresight News, that asks a basic but difficult question: who gets to define Ethereum, and what counts as truth inside the network.
The article frames Ethereum as two things at once. It is a philosophical revolution built on the idea of general-purpose, shared, neutral infrastructure. It is also a software toolkit and an ongoing research and engineering effort. Specifications, client implementations, and continuous research together make up what people recognize as the Ethereum protocol.
When philosophy turns into code
The essay says language carries reason, philosophy, and ideas, but any attempt to describe an idea also simplifies it. Ethereum’s core ideas, in this view, can be expressed more concretely through formal systems such as mathematics, logic, and code. The Ethereum protocol is presented as the product of trying to make Ethereum’s ideas real in the world.
If Ethereum is treated as a shared computational reality, the author says it rests on three ontological pillars:
- cultural convergence, meaning social and cultural agreement on a general definition of the Ethereum protocol;
- cryptographic truth, meaning the protocol defines what counts as truth inside the system;
- majority representation, meaning a social credential from outside Ethereum is made effective inside the network through cryptographic attestation and used to determine the majority position behind this shared reality.
In that framework, cultural agreement around the protocol comes first. From there, participants establish a standard of truth that can be checked cryptographically. The majority-representation mechanism lets participants coordinate around a shared view of Ethereum’s instantaneous state. That state defines what Ethereum is at a given moment, but it comes from the subjective perspective of observers, which means those observers must hold some representative credential that originates outside the system.
The article argues that cultural agreement over the protocol definition governs everything else. That is why truth has a strongly subjective character. Weak subjectivity matters too, but at a higher level: observers can make assumptions based on cryptographic truth and use those assumptions as axioms for other forms of knowledge.
At the network level, Ethereum is described as a large set of independent users running the same version of Ethereum client software and exchanging information over communication layers such as the internet. Protocol definitions, networking, and information exchange drive the network toward convergence on an updated protocol state. Each participant relies on the initial protocol definition, cryptographic verification, and majority representation to converge on Ethereum’s instantaneous and determinate state.
The majority mechanism is needed because the current state must be derived deterministically from a fixed sequence of operations in network history. Since observers cannot be assumed to receive events in the same order, they need to vote based on what they observe. That is how thousands of computers running the same software can agree on Ethereum’s current state and update that shared definition in real time as users act.
Governance as a human coordination problem
The essay then shifts from protocol mechanics to culture and governance. A static technical definition becomes a living, evolving network only because there is cultural agreement at the protocol-definition layer. That culture, the author writes, is the sum of the ideas held by everyone who cares about Ethereum.
From there, the piece introduces what it calls a cultural paradox. Cryptography can tell right from wrong at the technical layer, but culture has no formal standard that decides correctness. Culture is its own standard. Arguments for or against cultural change carry a paradox of their own, because calling for change is itself an act inside the culture one is trying to change.
The article pairs that with a governance paradox: if governance shapes culture, what shapes governance? Do people first reach cultural agreement and then write governance rules, or does a governance mechanism appear first and then direct culture in a systematic or ideological way?
On that basis, the governance of Ethereum’s protocol and roadmap is described as a human coordination problem. Participants need to agree on what the protocol is and how it should change over time. Without the kind of cultural truth foundation supplied by a company or a state, that becomes much harder. In the physical world, governance often comes from blunt geopolitical power, such as who controls the most nuclear force. Those with hard power can influence or control subjective definitions, including law and order. Ethereum, by contrast, relies on soft power. Decisions are often led by people whose influence comes from precedent, deep commitment to Ethereum’s ideas, and visibility inside the ecosystem.
The Ethereum Foundation is named as one of those influential actors and is described as the de facto originating institution for Ethereum’s ideas. As of September 2025, the article says 32 teams under 15 organizations maintained 13 independent Ethereum protocol clients. The people and groups contributing ideas and protocol development coordinate through the All Core Developers process, or ACD, where Ethereum’s governance rules are effectively set.
The essay says the relevant documents define the design and review system for Ethereum Improvement Proposals, or EIPs, as well as the network upgrade process. Historically, ACD’s own coordination process was loose and not clearly codified. Even now, the way people are organized and roles are assigned depends more on practice than on rigid written rules.
In simple terms, ACD’s job is to coordinate the ecosystem around software forks that change Ethereum’s protocol definition at a given point in time. The process includes researchers and developers proposing changes, settling on what will be changed, testing, publishing final specifications, implementing code in clients, and then having nodes across the network activate the changes on a specified date. The article says these fork cycles can take months and in some cases as long as a year.
What problem Ethereum is trying to solve
The essay then returns to a deeper question: what does it mean to use computation to enable human coordination? The truth foundation behind that question is philosophical and cultural, but the answer has to take the form of a technical and architectural solution. In the author’s view, Ethereum’s philosophy has to be translated into a software protocol before the question can be answered at all. At the same time, the protocol’s properties depend on how that philosophy is understood.
If Ethereum itself is a question, the article says the question is about the meaning of existence in a setting of computational coordination. The goal is to turn the abstract idea of a Turing machine into an interactive domain with computational existence.
The essay starts from the local level. Sovereignty exists locally: a human user can observe a computational world that exists only on a local machine and has full autonomy over that strongly subjective local ontology. Once multiple observers are involved, a minimum level of strongly subjective consensus is needed so people can observe and interact across a broader social space. Every observer defines truth subjectively in a local environment. Information and data have no meaning on their own; meaning comes from definitions and perspective.
But truth, the author argues, depends on scarcity. If any observer can repeat a statement infinitely, that statement cannot count as true. Coordination therefore requires agreement on definitions and a framework in which true statements are scarce.
To make that concrete, the article uses electronic cash as an example. Cash is described as a simple coordination game in which each participant has a balance. Only the controller of a balance can authorize a transaction that reduces that balance and increases someone else’s by the same amount. If N users are playing this balance game, two things are required:
- agreement on the game itself, such as programming rules and cryptographic tools;
- tools to verify the correctness of the game’s instantaneous state and keep the game moving through time.
Cryptographic tools create the spatial dimension that gives truth the scarcity it needs. Technically, balances are tracked by account, each account has a cryptographic identity such as a public key, and users hold private keys so only the owner of a balance can authorize a valid transaction. There is also a time dimension. To know everyone’s current balance, the full order of historical transactions has to be known.
The author says this coordination game is necessarily embedded in the execution logic of a Turing machine because it is a computational game with storage and execution. The advantage of abstracting coordination on top of a universal Turing machine is that it can run every computable game without restriction.
That leads to two meta-dimensions of coordination: a cryptographic spatial dimension that creates scarcity of truth, and a temporal dimension that gives the coordination game an order. Together they define instantaneous state and make future state transitions possible. Those two components are what the article calls consensus. Consensus, in this account, is the irreducible truth foundation that supports existence in a computational domain and makes coordination possible.
From there, the essay reduces Ethereum to a compact architectural form: a Turing-complete computational model, a preset cryptographic spatial dimension that guarantees scarcity of machine actions, addressable computational storage, operations that act on that storage, and a time dimension that wraps the whole system so truth about machine state can be structured across moments in time. The article restates that in simpler terms: addresses contain things, and those things change over time according to actions initiated by users associated with those addresses. Because execution is Turing-complete, those actions can be any general computation.
Ethereum as it exists in practice
On the practical side, the article describes Ethereum as a protocol that has to be deployed in a large distributed system. There is no central coordinator. Ethereum is a network of many computers working together in real time. Since consensus cannot be broken apart, the author treats it as an architectural axiom: a set of computers jointly confirms the current state of something and coordinates around state changes over time.
In that setup, the Ethereum Virtual Machine, or EVM, is the carrier of changing state, and user-initiated general operations are what change it. The article starts with storage as a way to define the EVM. Storage consists of program code and arbitrary data, addressed and tied to cryptographic identity. External operations on storage are broadcast to the network as messages and coordinated through the preset consensus mechanism.
The essay spends time on execution. A Turing machine’s execution result is not predictable in advance, so if the EVM is to compute deterministically, the computation has to happen somewhere. But verifying whether an execution result is correct is algorithmically different from performing the original computation. Verification complexity does not rise in lockstep with the complexity of the original computation. For that reason, the bottleneck in proving correct execution is data, not compute. Compute is needed to produce a result; verification does not require large amounts of compute.
The implication, according to the article, is that consensus can be reached on general execution of any scale, with the real limit coming from the network’s ability to store and transmit data. Because data is finite, the network needs rate-limiting mechanisms that turn data capacity into a measurable resource.
The essay also argues that Turing completeness means the set of possible operations has no upper bound. Hard-coding functionality into the architecture, or embedding precompiles inside the EVM, would unnecessarily limit the forms of coordination Ethereum can support. The EVM’s end goal is maximum generality and abstraction, where any realizable function can be written in code.
That abstraction extends even to cryptographic identity. EVM code at an address can call arbitrary custom verification functions rather than being limited to a fixed public-key system. The article says not only computation but also the forms of execution and storage on Ethereum need to be generalized so Ethereum can support a full spectrum of possible forms of existence.
Here the essay contrasts Ethereum with the physical universe. The universe is not enclosed by consensus in the way Ethereum is, so existence in the universe is naturally local. In Ethereum, by contrast, knowledge is global because all execution and storage ultimately converge on a single consensual root of truth. Even so, only verification needs to be global. Ideally, computation itself should be as local as possible.
Storage and data cannot be eliminated and must exist globally, but the article says they can be compressed into cryptographic proofs and brought into consensus without requiring raw underlying data to be replicated across the whole network. It argues for a generalized approach to data availability, using economic metering to make data temporary and pairing that with network sharding. Even if the network reaches global agreement that data is available, access to the data itself can still remain private.
The same logic is applied to execution. Only operations whose execution paths intersect at the same address need to be computed in the same local view. Disjoint paths and subpaths can be computed in parallel within their own execution domains, with network observers coordinating only as needed. The article says aggregate execution and data throughput can be spread evenly so execution and data availability are generalized at the architectural level. Inclusion, ordering, and privacy protection for base-layer throughput would then be handled through multithreaded coordination across the network rather than every node repeating a single-threaded execution path.
The limits of cryptographic truth
The article then turns to what it sees as the central limitation of cryptographic truth. Inside Ethereum, correctness is grounded in cultural agreement around the protocol definition, meaning agreement on what the network can be. But that alone cannot define what the network actually is in the real world.
The real state of the network since genesis has to be inferred from information outside the system. That information records the historical behavior of observers and the majority view of event ordering. Given an instantaneous state and a set of operations, one can judge whether the operations that produce a new state conform to the protocol definition. What cannot be known from that alone is whether those operations and their ordering are accepted by the broader set of Ethereum observers. That is the consensus problem as the article presents it.
Ethereum’s spatial dimension is built on cryptography and lower-level protocol components, which makes operations on the state machine statically verifiable. But whether those operations happened, and when they happened, depends on the subjective recognition of network observers. That means Ethereum has to define who the observers are in order to measure majority representation and interpret the events that produce the network’s instantaneous state. The article says Ethereum is unusual because the definition of the observer remains culturally ambiguous, with a large amount of information lost in the strong subjectivity introduced by genesis.
The essay contrasts this with Bitcoin. At genesis, Bitcoin had only a static protocol definition, and the genesis block reward could not even be spent. The protocol did not hard-code any external preset condition into the system at genesis. Even if Satoshi Nakamoto premined coins, the observer definition under proof-of-work still had cultural homogeneity because it came from energy expenditure outside the system.
Ethereum, in the author’s account, is different. Its premine effectively established a rule: the real definition and instantaneous state of the modern beacon chain are, to some extent, constrained by the observer set embedded in genesis, namely those defined through staked ETH.
The core logic is that strong subjectivity and the definition of the observer must come from outside the system. Consortium chains and centralized systems hard-code operator roles into the protocol and subjectively define observers in advance. Systems like Bitcoin preset only the protocol definition and rely on a general culture outside the system to define observers and produce majority recognition. Bitcoin, for example, defines the network’s real state as the chain confirmed by the greatest amount of expended work. Its observer ontology is culturally homogeneous and highly abstract.
The article notes that Ethereum also used proof-of-work before 2022 and then moved to proof-of-stake, using the scarcity of ETH inside Ethereum to build a general culture of observer recognition. But proof-of-stake uses the system’s native token as the representative of the observer, which means the token ontology and the observer ontology collapse into one another. In the author’s view, that does not solve the problem of subjective representation. A network that premines stakeable tokens at genesis inherits a problem similar to centralized systems: the observer definition exists before the genesis block and is written into the protocol, so it cannot achieve a truly general culture.
The essay gives a numerical example. Of the current 122 million ETH, 72 million came from the premine and 50 million came from proof-of-work mining. On that basis, the article argues that majority recognition under proof-of-stake is skewed because certain actors were subjectively granted observer status from the start. The remaining 50 million ETH from proof-of-work mining can be understood, in this framework, as carrying forward the ontology created by external energy expenditure.
How the beacon chain defines canonical state
From there, the article describes the beacon chain as the truth foundation inside Ethereum that derives instantaneous real state. Instantaneous protocol state comes from an observer ontology that defines majority recognition, and the beacon chain operationalizes that through four stages.
Genesis
The system starts from a genesis state with a preset staking distribution and initial network and virtual-machine state. The article says Ethereum’s proof-of-stake genesis in 2022 inherited the state of the original proof-of-work network from 2016. It also set up a validator registry, and validators gained voting power by staking tokens.
History
The network traces all votes cast by staked observers on network state, reconstructs the history of observer recognition, and accepts user actions that the network perceived and agreed on in sequence. Majority-recognized event ordering and event existence are treated as true, while cryptographic checks can still be performed independently.
Current state
The process reaches the latest network state recognized by the majority. That is consensus: a shared canonical understanding of the virtual machine and the validator registry among Ethereum observers.
State transition
At the tip of canonical history, observers vote together to determine the next canonical state based on real-time user behavior inside the virtual machine.
The article adds that subjective genesis can also be replaced by a recent checkpoint that one subjectively accepts as valid. The definition of the network and the genesis state is tied to strong subjectivity. Accepting a recent historical checkpoint as valid under the protocol’s preset assumptions is weak subjectivity: treating a statement as true within the protocol’s subjective frame.
The trust assumption and the DAO fork
The protocol’s trust assumption is stated plainly in the essay: a supermajority of observers measured by stake, meaning 2/3, follows the protocol’s definition of honesty and remains honest, including what the protocol counts as unintentional dishonesty. As long as that condition holds at any moment, the network can reach consensus on the current canonical state.
If it does not hold, an outside observer cannot tell whether the current state comes from a legitimate canonical history or from a history rewritten by a malicious staked supermajority. No matter what network state is observed, one can only verify that the state is cryptographically possible. One cannot prove that the history producing that state reflects the recognition of an honest majority.
The article says the issue of historical cryptographic validity is even subtler. The assumption that the staked majority is honest applies not only to chain structure but also to every action in history. Whether a historical event is correct is true only within the subjective frame of an honest majority. If the staked majority chooses to recognize a historically invalid event, then the majority is no longer honest under the assumption, the assumption fails, and the validity of everything becomes unclear.
That is why, in the author’s view, the system always assumes an honest majority. Since that assumption supports every other validity claim, cryptographically checking history without trusting the majority has no practical meaning. The DAO fork is presented as the clearest example. When canonical history contains an event that is invalid under your protocol definition, you cannot tell whether you are seeing malicious state tampering or a coordinated hard fork that your outdated software cannot recognize. In the DAO case, the majority chose to recognize an event that was cryptographically invalid under the old protocol definition and wrote it into canonical history. Under the old rules it was invalid; at the subjective social layer, the majority treated it as part of the main chain’s history.
The article’s conclusion from this is that cryptographic verification has built-in limits. Within the protocol’s own framework for validity and honesty, consensus lets an honest majority coordinate. But what counts as honesty is itself subjective and is ultimately determined by the truth recognized by the majority. That, the author argues, shows again that Ethereum’s definition contains an irreducible subjectivity. Each observer interprets truth for themselves, and even disagreement with the majority does not make one definition of Ethereum inherently less valid than another.
From ontology back to engineering
The essay closes by reducing the argument to an engineering summary. Culture reaches agreement at the protocol-definition layer and serves as the initial subjective axiom of truth, defining correctness inside the protocol’s own rules. On top of that sits a general-purpose virtual-machine architecture that can operate cooperatively. Then a majority-representation mechanism rooted in external observer ontology produces consensus and turns Ethereum into a globally shared computational reality.
In practical terms, users broadcast general operations to a shared virtual machine, computers across the network order those operations and vote on their sequence, and the network arrives at Ethereum’s instantaneous state together.
The author adds that culture is messy and the revolution is not perfect. There are many ways to participate in building Ethereum’s vision. The status quo maintained through ACD is only one narrow way of defining Ethereum. People can offer different views and even change how the public understands the idea of a world computer. The essay ends with an invitation: the door remains open to anyone who wants to join, and if freedom is the belief, then the future is built on Ethereum.