If Ethereum Is a World Computer, Where Is Its Operating System?
Reflections on system architecture, execution layers, and lessons from 1980s computing
1. Historical Context: Before Operating Systems
In the 1980s, personal computing went through a fundamental transition.
Early systems often booted directly into built-in interpreters such as BASIC, tightly coupling applications to the underlying machine (e.g., early personal computers like the Apple II).
Over time, this model gave way to operating systems such as Unix and later Linux / Windows, which introduced a new layer of abstraction between hardware and applications.
This transition was not just about better software.
It fundamentally changed how systems were structured:
- applications no longer managed hardware directly
- execution environments became standardized
- ecosystems could evolve independently from the underlying machine
2. Ethereum as a âWorld Computerâ
Today, Ethereum is often described as a âworld computerâ.
If we take that analogy seriously, an interesting question emerges:
Which stage of computing history does Ethereum most closely resemble?
In many ways, Ethereum today resembles pre-operating system computers:
- smart contract execution is tightly coupled with the consensus layer
- the ecosystem is fragmented across multiple EVM-compatible environments
The EVM provides a powerful and deterministic execution environment,
but it is closer to a deterministic execution kernel or interpreter than a full operating system.
3. A Possible Transition Point
This raises a broader question:
Are we approaching a similar transition point as in the 1980s â from tightly coupled execution to a more layered system architecture?
Much of the current roadmap focuses on scaling execution â for example through rollups and zero-knowledge systems.
These approaches are extremely valuable, but they largely operate within the existing architectural paradigm.
This leads to a deeper question:
Are we optimizing within the current system, or also evolving the structure of the system itself?
4. Ecosystem Convergence and Standardization
One historical parallel comes from the evolution of the personal computer ecosystem.
The architecture associated with early IBM PCs became widely adopted, not necessarily because it was the only design, but because it enabled a rapidly growing ecosystem of compatible systems and software.
Over time, this led to a form of de facto standardization, where the value of compatibility outweighed differences in underlying implementations.
Ethereum may be exhibiting a similar pattern:
its openness and permissionless nature have enabled a wide range of independent ecosystems â rollups, tooling, and applications â to emerge while maintaining compatibility at a shared base layer.
This suggests an interesting possibility:
âWorld computerâ status may emerge not purely from technical design,
but from ecosystem convergence around a shared base layer.
Importantly, this kind of standardization does not require central coordination â
it can emerge from the network effects of compatibility.
5. What Is Missing?
If this is the case, then the question becomes:
What abstractions are needed on top of this base layer
to support a truly global, interoperable application ecosystem?
Historically, this role has been played by operating systems.
6. An OS Layer as an Experiment
We have been exploring this direction as an experiment.
This is not intended to be a new L1,
nor a faster L2,
but rather an exploration of a different layer in the stack.
An OS Layer, in this context, would aim to:
- abstract over heterogeneous execution environments
- coordinate computation across on-chain and off-chain contexts
- provide standardized interfaces for application development
without modifying the underlying consensus layer.
7. Constraining Global State
One aspect we are particularly interested in is constraining global state growth.
The hypothesis is that keeping the global state small and bounded
could help preserve the ability for individuals to run full nodes,
maintaining accessibility and decentralization.
This shifts complexity away from the base layer,
and may require new abstractions at higher layers.
This constraint may naturally push more application-specific state
into higher layers of the system â
which is where an OS-like layer could play a role.
8. Open Questions
We view this as an experiment in system design,
exploring whether different system constraints
can lead to fundamentally different architectural outcomes.
These are still early explorations,
and we are more interested in understanding whether this direction makes sense
than proposing a concrete architecture.
This leads to a broader set of questions:
- If Ethereum is to become a true âworld computerâ, what would its operating system look like?
- Where should such a layer live â on-chain, off-chain, or hybrid?
- How should responsibilities be divided between consensus, execution, and higher-level abstractions?
- Are we fully exploring this dimension of the design space, beyond execution scaling alone?