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A holarchy is a hierarchical structure in which each part or component forms an autonomous whole that is also a part of a larger system. This concept was introduced by the American philosopher Arthur Koestler, who argued that complex systems could be understood as interconnected networks of holons – self-organising units that are both parts and wholes at the same time. In other words, a holarchy is a structure in which each part has its own identity and purpose while simultaneously being part of a larger whole[1]. Koestler called these two aspects of a holon the self-assertive and the integrative behaviours respectively. He described the former as an inward-facing system operating with flexible strategies within an individual holon. The latter as an outward-facing system operating with fixed rules as a network, or holarchy.

There is a very simple information system called mulitplexing that can be extended in a trivial way that allows perfect representation of the holarchy concept. In terms of information technology, we might classify the holarchy concept as a universal middleware and as a "web3" concept in both the decentralised and semantic senses.

About this document

This document (as of Jan 2024) is still in draft form, it is not yet complete in the sense of a buildable specification, but gives a clear idea of what we're trying to achieve.

Intended audience

This document is primarily for reasonably IT-savvy people with an interest in independence, sovereignty and decentralised offline-first organisation. This means people who are already familiar with the pitfalls of centralised management and control.

Document purpose

To find out what the holarchy project is and how people might benefit from using the system, once operational.

Preliminary concepts

This article uses some specialised terms and concepts. We have a holarchy preliminary concepts article that introduces these with references to more detailed resources.

Other details

  • for now we're using the numbered references mainly for interesting side notes and reminders rather than sources and citations

Etymology of "holarchy"

The suffix "-archy" comes from the Greek "archein," meaning "to rule" or "to lead". Based on its etymology, "holarchy" implies a form of organisation or structure where each unit (or 'whole') is both a part and a whole in itself. It suggests a hierarchical system where each level or unit is a self-contained whole that fits into larger wholes. This concept often appears in systems theory and organisational studies, emphasising the nested, self-similar, or fractal nature of systems.

Another closely related word is "holocracy". Both concepts involve a recognition of "wholeness" in each part of a system. Holarchy integrates this with a hierarchical structure, offering a balance between rules and autonomy, whereas holocracy is more inclined towards ensuring autonomy and distributed governance.

The term "holarchy" better describes our system, because it's explicitly defining a hierarchical system of authoritative rules - collaborative rules that provably maximise individual autonomy. "Holocracy" best fits a purely decentralised system that does not define any concept of authority or hierarchy.

Organic technology

The fractal nature of life allows us to equate the biological cell with a person, and a single person with the planetary organism. In his book Spontaneous Evolution, Bruce Lipton shows us that we can learn from our cells how to live together in peace and harmony as a single organism since they're a living example of it, and have been doing it for millions of years.

Many people who are strong believers in the idea of humans living fully in accord with nature think that technology has no place in this vision. But by looking at how the cells in the human body are able to live together as a community with a population of over fifty trillion reveals that technology is essential. The cells manufacture and maintain huge infrastructures including the equivalent of buildings that are tens of thousands of stories high, sophisticated networking systems and even an energy based financial and banking system.

Holarchy offers us a framework that can achieve this kind of scale-independent organisation, and can be understood clearly in terms of our own technological infrastructure.

The internet connects all of Humanity, and is evolving into an ever more complex, resilient and organised system. It's organised in layers of open protocols from the most fundamental physical layer up to the high-level organised layer of application protocols.

The internet is generally referred to as having gone through a few different versions or phases, the first was characterised by servers and technology specialists being responsible for generating and maintaining the content. The name "web 2.0" was given to the broad phase that came with blog and wiki software in which the vast majority of content was being generated by the end users.

The meaning of "web3" was originally used to refer to the semantic web which was envisioned to be a new level of organisation of the web's content brought about by metadata annotations. But web3 started to slow in its progress with corporate interests gravitating instead towards deep learning and AI as solutions to organisation. The "web3" term ended up referring to the decentralised nature of the web which started gaining popularity with the introduction of blockchain technology.

Interestingly, the holarchy architecture actually fulfils both definitions of "web3", because it maintains an evolving ontology in which all content is organised semantically, as well as being able to function ideally in a fully decentralised environment. It's a unified ontology of knowledge as well as a map of the usage of that knowledge.

Knowledge-sharing and organisation are so essential to a harmonious society, that they ought to be provided at the basic abstraction layer of the common networking protocols. The holarchy is a networking protocol that allows participants of the network (holons) to interact together with a common means of organising attention and resources and of sharing, adapting, using and assessing knowledge. Holarchy is the organising principle and network architecture of nature and we believe, even of consciousness itself[2].

Universal middleware

The concept of a universal middleware, or as Elon Musk refered to the concept, the "everything app", is an inevitable phase of the way we organise using information technology.

Soon all apps across all technologies and platforms will be fully usable by API (most already are) so that AI can use them on our behalf. Application interfaces aimed at desktop and web contexts will eventually fall into decline through lack of demand.

There will be many, most likely every large tech player will be pushing their own universal middleware, but also libre software will have its offerings too, and these will typically be designed to be maximally interoperable with each other.

It's important to note that while there are many different universal middleware projects, and potentially even many of them that are modelled directly on the holarchy principle, there can be only one holarchy.

This is not to say that all of them are fake except for the one true holarchy, it's just that one of the main objectives of the holarchy concept itself is unification. So all holarchy deployments, no matter their origins, are objectively dedicated to seeking each other out, and merging into a single network.

Our holarchy project

  • our Holarchy project is a libre software universal middleware offering...
  • it is our attempt at articulating this concept, operating our own organisation and projects in accord with it, and presenting this ability as a re-usable package

Holarchy is generally considered as a philosophical framework of attributes a system should have in order to be aligned with the principles we observe in living organisms. It's usually presented as more of a set of guidelines than a specific system definition.

Here at Organic Design we believe that there is a simple organisational structure at the heart of and common to all biological organisms, and even underpinning consciousness itself. In other words, we believe that holarchy is more than mere guidelines, it is a very definite and describable system.

We're researching and developing a holarchy in the form of a p2p distributed network of holon-organisations, and we're attempting to articulating the holarchy concept with the detail and clarity of a software design pattern.

The project's development effort can be broken into three general areas: the p2p network architecture, the holarchy organisational system and AI integration. In this article we offer a brief introduction to these three aspects. And following them at the end, we discuss the main high-level organisational patterns and "applications" that we envisage the system being used for.

On the research side of the project, we extend out to a wider focus than the development to encompass the philosophical aspects of holarchy. On the network architecture side this wider focus is on political philosophy - the kinds of large-scale social order and progress that the holarchy system of organisation implies. And on the AI integration side, the philosophical focus is ontological (holarchy as a foundation for cognition and even of reality) and ethical (not just the AI alignment issue, but also the "human alignment issue").

  • some examples of threads in our org that we can use throughout the text

The four-quadrant holarchy model

This section is an overview of the model expressed by our software design pattern. The most up to date definition of the pattern for developers is being written in the four quadrant holon model article.

Our four-quadrant holon model involves Koestler's four concepts of the integrative and self-assertive behaviours, and the fixed-rules and flexible-strategies mapped onto an orthogonal pair of axes. The aforementioned concepts map respectively onto the top, bottom, left and right directions of these axes. The meanings of the quadrants formed by the synthesis of the pairs of adjacent directional concepts are isomorphic with the four quadrants of Ken Wilbur's Integral Theory, except that in our model the positioning of the quadrants is vertically flipped from Integral Theory. Ken Wilbur mentions the concept of an "integral holon" in some of his writing, but we're currently unsure whether his concept follows the same mapping to Koestler's core holon concepts as our model.

Cognitive architecture

The general context of the pattern is that operationally it's a so-called universal middleware, and it takes the form of an agency-agnostic cognitive architecture, i.e. any agency can participate regardless of its attributes such as simplicity or complexity.

A cognitive architecture is a systemic foundation for agency which defines the environment it finds itself to be within. It gives participating agents a local subjective lens or point-of-view (POV) through which to perceive reality. The cognitive architecture defines the universe of possible content and interaction available to any agent operating in accord with it.

We'll start describing this cognitive architecture with a concept at the centre of this subjective context which we call the focus. After that we can describe the subjective context in more detail, and give an overview of the surrounding model that actualises and supports it. For those wanting to go into more detail, the four quadrant holon model goes into the next level of detail which is the software design pattern.

Holarchy proponents believe that the holarchy pattern is fundamental to all life and some (including the author) go even further saying it underpins the entire universe of conscious experience (which, by the way, is the only universe anyone can have any direct knowledge of). As such, we believe there's a still more fundamental description possible than the software design pattern, one that's based on the fundamental dichotomies of perception, creation, one and many. We discuss this aspect of the project in the four quadrant holon philosophy article.

The top-level diagram


The "four quadrants" in the model's title refer to the actual structure of the model, which is shown in the image to the right. We won't go into detail about why this particular structure has been chosen in this article, we'll just start with it as an assumption for our purposes herein. For those looking for those details, please see the aforementioned four quadrant holon model article.

The most abstract and fundamental part of the model is the vertical instance axis shown in black. The operation of this axis permits the horizontal class axis in blue.

Interacting together, these two axes enable and maintain the diagonal axes and their concepts (the four quadrants) shown in green. The four quadrants form the content of the first two axes interacting. The first two axes function together to bring about a new abstraction layer.[3]

The four quadrants come together in a matching process carried out within the central focus of holon (the purple dot in the image). A default matching exists that can be performed by the cheapest agency, but can also be guided by any agency present that might choose to intervene. The focus of a holon is within the present moment which is the synthesis of the four quadrant aspects.

Finally, a high-level trend emerges from the operating holon as a whole over time, which is shown in red. This is a progressive clockwise continuous-improvement cycle. The "measuring stick" for assessing improvement is objective benefit to self and whole which we call "harmony" (in the wider context of the philosophy we call it "the Great Harmony").

This high-level cycle is akin to the change of seasons and the effect that has on the type of work being done in a season-dependent operation like a farm. We call these four emergent aspects of this cycle the four phases of change. A continuous-improvement cycle works like a ratchet mechanism, where progress is consolidated into a new unshakable foundation for further improvement to build on.


The purple dot in the centre of the diagram is the aforementioned starting point for our description, the focus. The diagonal axes intersect in the centre forming the focus. In this way, the present moment is the synthesis of the four quadrants of focus.

The holon is itself a group of holons which we call siblings. All the siblings find themselves together in a private informational context through which they can express themselves to each other. The context represents a particular objective that the siblings collaborate together on, and which is provided by the holon - the parent of the sibling group which the group are in service of. In IT terms we'd say that all the siblings are parallel child threads in a shared private scope owned by the parent object.

The focus is the combination of scope and thread aspects of system execution. It is the actualised scope content in the present moment in the context of a particular sibling. The internal structure of the focus is the four quadrant structure of the holon. In other words, when a holon receives focus, that focus is divided equally amongst the four quadrants within the holon. The final result of the focus, is the synthesis of all the quadrants interaction.


We use the word "agency" to refer to the ability to apprehend state and instructions and perform any actions that may be implied by them. An "agent" is an actual entity of some kind which has agency, it has the ability to perform various specific roles when called upon in appropriate circumstances. Such an agent might be a user, an AI, an API or OS, a domain-specific language interpreter or many other things.

The holarchy is an organisational system which is agency centric since it's a cognitive architecture, but yet it's also agency agnostic, which means that it interacts with any kind of agency in the same way - in the same way as the law is (ideally) person agnostic in its operation. This includes being agnostic to whether the agent is simple or complex, or whether its focus is discrete or continuous in nature (i.e. whether it should be treated in a multiplexed or multi-threaded manner).[4]

Regardless of their agentic complexity, it's fair to say that all instances have a subjective local point of view consisting of the information and threads of activity within their local instance scope. They find themselves to be in an organisational context consisting of other sibling instances of various classes encapsulating their agency within and presenting their state publicly to be apprehended by the other siblings.

The organisation context these siblings find themselves within is itself an instance, and the siblings public states all together make up the presented public state for the parent context beyond. The siblings collaborate on progressing the objectives of this parent instance - the holon that owns the sibling context and defines their roles and objectives.


In mathematical and software terms, an expression is information of a form that agency can apprehend and evaluate in the present moment. The resulting information is called the value of the expression and represents a value judgment carried out by some form of agency.

The word "expression" is also used in the sense of an agent (holon) expressing itself, in other words, it evaluates the expression internally, and presents the final value externally (in public scope).

Which expressions are evaluated depends on the potential expressions the class in question consists of, what abilities the present agency has, and which are relevant to the current conditions. In fact the word "condition" can be used synonymously with "expression" in the context of the holarchy. In software development a condition is a specific type of expression, in a holon they're the only type we're concerned with.

Classes consist of a variety of roles (jobs that require specific agentic ability to perform), and these in turn consist of various expressions which can be thought of as self-activating in accord with the state of the local environment. This brings us to a third compatible meaning of the word "expression", which is in the phrase "gene expression". A class is analogous to a gene, having different possible expressions which are activated in response to the relevant circumstances as they eventuate.

The agency and expression axes are orthogonal but complimentary. The agency axis represents ability to express, and the distribution of this ability throughout the system. The expression axis represents what is being expressed by the agency, and how these forms of expression are distributed throughout the system.

Quadrants and loops

Four loops.jpg

The image to the right shows the four quadrants in more detail. Our name for each quadrant is shown in the green and the quadrant name from Integral Theory is shown in brackets below each, because they have identical meaning. Our model is vertically flipped from Integral Theory's quadrants, because in our context the external collective represents the direction of above and outwards, and the individual represents the direction of deeper within below.

The four quadrants are the content of the first two axes interacting and they come together in the central focus. The process by which the quadrants "come together" in focus, is that each of the four receive independent attentional focus (the attention of the holon is divided into four). Each quadrant's effect on the local shared scope is in accord with their specific conceptual meaning. Each of the quadrants interaction with the shared scope is in the form of a decoupled feedback loop involving a further division of focus into an active change thread and a passive informing feedback thread.

Each quadrant represents a particular aspect of the holon's process and state. All quadrants must receive focus... todo...

Each quadrant is in the form of a feedback loop having an active side shown in red which is directly responsible for progressing the holon, and a passive informing feedback side shown in blue which does not change anything directly, but guides active change in the future.

The focus received by the quadrant is divided further into two, making each side of each loop into a specific thread of operation. The quadrants-loops and even each of their individual active and passive phases are all temporally decoupled and act only on the shared scope directly.

The active sides of the loops involve high-level agency for performance of roles, decision-making and value judgements. Whereas the feedback sides of the loops are due to deterministic processes that are inherent in the system's structure.

All the active sides of the loops point in a clockwise direction which is the source of the emergent continuous improvement cycle of the holon as a whole (shown in red in the first diagram above).

In addition to the quadrant names, we also use a two-letter shorthand method for referring to them which are shown in light blue in the diagram. The letters stand for top, right, bottom and left. We'll now describe each quadrant and it's specific meaning, structure and operation.

Top-left (TL)

  • meaning: public class
  • diagonal: possible public agency
  • structure: ontology
  • active: presentation
  • passive: knowledge
  • those present: a structure of actual identities we know, those most salient at the root to those least known in the depths

Being a left quadrant, it has a class-oriented process, and being a top quadrant the process takes place in public scope, which is before and after the subjective point of view receives focus. Class-orientation means it's responsible for the structure of the holon. Structure is in the form of abstract relations with other holons and represents the possibility aspect of the holon.

Structure at the public level is institution, or in Wilbur's quadrants it's the cultural quadrant concerning knowledge at the level of the whole collective.

This quadrant is on the agency axis (left-to-right downward axis) which we call the imperative axis in an informational context because as a state it represents groups of agents participating together to progress a particular objective. In other words, this axis is in terms of who's present and what are they doing together.

The top-left quadrant is called the ontology quadrant which is all about what possible agent group does the holon actually know about, what they can do and what they're relevant to. This is the holon's knowledge structure, the classes it can instantiate when the circumstances call for them. The key point in terms of the agency axis is that this quadrant is an organised structure of abstract agency groups that could be instantiated by the holon if the circumstances and resources brought it into relevance.

The final focus in the centre is in the present, and so the present incorporates part of the top-left quadrant structure, it's that subset of possible agent groupings which are actually present in the now.

From the perspective of the holon as a whole, this quadrant can be seen as the whole-development loop (a holistic, scale-independent form of self-development). This loop is merging the local adaptation of knowledge with all knowledge-adaptation globally to form an evolving society based on knowledge-sharing.

Loop aspect: The institutional quadrant mediates the evolutionary ontology (culture, knowledge) through the functioning of the evolutionary loop. We actively contribute to the non-local institutional aspect, and synchronising with the establishment.

  • being structure this is vertical, receiving by resonance

Technical note: this quadrant is public which means that the operation takes place outside (before and/or after) the executional or focus enters the internal subjective perspective of the holon. If we think about it like an executing function, then "public" means the scope where the function is called from and returns to.

Bottom-right (BR)

  • meaning: private instance
  • diagonal: actual private agency
  • structure: production
  • active: performance
  • passive: account
  • the actual activies that are being performed by those present, the current work at the root to the historical activity within

The bottom-right quadrant is also on the agency axis, but being at the bottom it's in the private scope of the holon which is within the context of subjective agency. In IT terms we'd say it within the called function's scope, but is still before and after the control is handed to the actual free agency. Being a right quadrant, it's in the context of activity and agency actualised in linear time. It concerns actual state rather than abstract concepts and ideas.

Being on the agency axis means that this quadrant, like the top-left, represents organised groups of agency. But unlike the top-left which dealt in possibility, this group is actualised in time. This is the operational quadrant which represents the actual details of the activity carried out by the agency group. It concerns what specific activities they're performing or have performed, and includes an account of their performance.

A key point here is that this quadrant informationally represents the record of activity, and is organised by the agency grouping knowledge structure. This is the common form of quadrants on the diagonal agency axis.

This quadrant incorporates into the final focus in the centre the current activity that's salient to the present agency group.

In this aspect of the organisation, we've moved into private scope of production using private property (fundamentally this concept refers to the private group workspace that's guaranteed to be reliable and predictable by the institutional aspect. In our system, we call this the operational quadrant, in Integral Theory it's the behavioural quadrant.

What this quadrant brings to the table is the production loop, a sets of "worker threads" which continuously assess the local scope for what actions are required (if any) and allocating resource to performing the needed actions. In other words, this quadrant is giving a holon the ability to perform behaviours (define and execute processes).

Loop aspect: This loop actualises the day to day operational aspect of the quadrant. The active side is the aforementioned intention...

Bottom-left (BL)

  • meaning: private class
  • diagonal: possible private expression
  • structure: objective
  • active: intention
  • passive: integration
  • salient expression, relevant to the current work, in the form of objectives, the ideal localised form of the expression, the most salient at root are those most useful, beneficial, doable and predictable, down to potential management to imagination and dreams within

We now turn to the other diagonal axis called expression, in the informational context we call this axis the declarative axis, because it is not in terms of agency, but rather in terms of the environment. The quadrants of this axis are informationally in terms of local state which determine objectives in the form of target state.

Starting with the bottom-left quadrant which is called intention. Being on the left, this quadrant deal with the abstract structure, not with actualised state in time. It represents the spectrum of expression that is possible for the locally participating agency, and the objectives their participation is in service of.

  • contribution to central focus
  • the common form of the expression axis
  • factory
  • subjective judgement of work?

Here we're still in the private scope, but this quadrant is concerned with the allocation of our attention. Here's where intention is expressed (by where out attention and resource are directed, our purpose, objective or telos). We're forging the future with our potential. In our system, this is the developmental quadrant and in Integral Theory it's the intentional quadrant.

The development loops is very much like the production loop in that it moves toward a target, but where the production-loop navigates state space, here we're navigating ontological space (the space of classes and variations) developing our abilities and potential.

This quadrant is the holon's objectives, along with corresponding variations of sets of behaviours that achieve them. Filtered by salience over time from evolutionary change, intentional changes and conditions. - objectives (salience, intentions) updated (bottom-up) - factory (top-down) representation of behaviours and state reflect structure over time

Loop aspect: the starting point of activity is with intention, and idea about something we'd like to be the case that is currently not the case. An objective, a target to reach, targets are declarative which means they're in the form of state, not in the form of processes or instructions.

The passive side of this loop performs a part of the factory design pattern, as the holon's structure undergoes change (either through local selection of new variations, or through evolution), these changes have to be integrated in the local state. It takes time, energy and intention for structural change to be reflected in the local representational state.

Top-right (TR)

  • meaning: public instance
  • diagonal: actual public expression
  • structure: economy
  • active: contract
  • passive: reputation
  • imminent expression, those present connected in abstract future to potential expression, from the predictable imminent to the uncertain future within

This is again taking place in the public scope, and instance concerns the allocation (flow) of real resource and agency through time. Resource and agency allocation at the public level is the market economy. In Wilbur's quadrants this is the social quadrant. Actually resource is a special case of agency, which we'll explain later. Agency is the is the essence of the resource that's allocated, and what agency is from the perspective of the holarchy is ability to perform in accord with a specific class (role, behaviour pattern). Ability is organised in terms of reputation and availability in time and location.

In terms of the holon as a whole, this quadrants is instantiating or concretising that salient classes. It's matching the behaviours (that have been selected for achieving our objectives) with the available real resources from our own supply and from the external society. It makes a section of potential activity imminent.

On the passive side of this loop is the assessed performance of the class which is public feedback permitting continuously improving performance.

Loop aspect: The economic loop is the fundamental form that the market economy takes. Available agency (and resource) is "booked" in a schedule-merging dynamic on the active side of the loop. On the other informing side we have the formation of agent-reputation in a deterministic credit-like weighting.

*   *   *

Overview of the four as a whole organisation.... The general scope-thread structure with production rules

The four quadrant holon model covers all aspects of organisation in a simple, but clearly extendible way. Arbitrarily complex objectives can be defined and developed, they can be connected to available resource and agency to begin normal operation. All the quadrants inherently actualise their own improvement. It's a universal organisational pattern that's completely independent from the structure or specifics of the states or symbols being organised.

Each of the quadrants is a definite process acting on abstract general concepts. The evolutionary loop determines what's worthy of sharing and how to publicly present it. The economic loop determines market interactions and rates participant's performance. The production loop determines the conditions and corresponding reducing action and the development loop determines objectives and classes that are relevant to achieving them. In each loop, only abstract state-independent and complexity-independent attributes are referred to, so that no matter the structure and state, all organisation at every scale shares exactly the same loop structure in common. This is why we call it a universal upper ontology, and it's why we call it "platonic" since it never changes in any context.

The variety of structures available, and our shared knowledge about which are best for achieving what objectives are continuously improving and diversifying. While the two trees permit the class and instance system itself, it's the four loops that make use of them. Developmental-loop is the source of new variations and selections of behaviours, operational-loop is the actual performance of the activity, evolutionary-loop is the sharing of these behaviours and economic-loop connects workers with work to do.

Recursion means that each quadrant and each direction all take the form of a feedback loop themselves. What this really means is that they're all holons within holons. This is possible because the recursive processes are scale-independent, they do not refer to specific state, they're state and scale agnostic.

Peer-to-peer network architecture

We know that somehow the Internet must be used to achieve the harmonious organisation of society since it allows people all over the world to communicate and share knowledge directly. But for us to use the Internet to organise into a community together, we need to change the way we use it. The currently dominant method of viewing and collaborating on the Internet, the World Wide Web, is not structured in a way that promotes the formation of people into a community from the bottom up, it doesn't match the way that cells organise themselves. The web is a centralised top-down structure, but it's the peer-to-peer networks that offer a foundation to work from which really mimics cellular organisation.

The networking aspect of the peer is the integrative, outward-facing, aspect of the holon. As the integrative behaviour of the holon, it's ultimate objective is to maintain the integrity and resilience of the whole. But as a peer-to-peer (P2P) network architecture, this objective is contributed to by all peers, and each peer holds a small filtered perspective of the whole based on their own local interests and circumstances.

The peer-to-peer (P2P) network architecture, OO and holarchy all suit each other perfectly because they all consist of ontologically fundamental dichotomies that have a clear conceptual mapping to each other.

The software that allows the many different network transport mechanisms to utilised by holons is a completely independent development thread to the holon architecture described above. Without the ability to interface with real transport mechanisms and end-points, the holon model can only ever be an abstract concept.

P2P networks are defined solely by the definition of a peer, or rather by the messaging protocol a peer should conform to in order to participate. The p2p model is separated into client and server aspects just like a the familiar centralised model, but both of these are aspects of each peer's behaviour. The client and server aspects of a peer conceptually map onto the self-assertive and integrative behaviours of a holon.

We talked above about the importance of knowledge and how it comes from both local use and global integration. Knowledge sharing... shared ontology

Organisation sharing... more than just sharing knowledge, it's sharing knowledge in organisational form. A form that's actively incorporated into recipient's own local organisation.

  • peers and holons


  • we have only introduced market in a very minimal way, the more in depth discussion is now at the end

We've already introduced the market aspect of the holon in terms of its actual dynamics as the integrative (collective, public) process. But here we need to mention a bit about what we need from the physical networking layer to most effectively support this integrative dynamic.

The market is maintained unconditionally by the integrative behaviour of the p2p protocol, all holons contribute to this aspect no matter their specific self-assertive organisational objectives.

It's the structural aspect of the market, the market ecosystem determined by the producers, that has specific exotic needs from the networking layer.

  • cycles of outwards and inwards directed information were mentioned which requires support from the networking

The value or state side of the market is the flow of resource driven by demand. This side of the market has nothing out of the ordinary in terms of what it requires of the networking layer.

Mesh networking

The most pure p2p architecture is the mesh network, it's the most general of all networking architectures because it is the most ontologically fundamental. It can function under the most restrictive and unreliable environments. The peers in a p2p network can support higher levels of abstraction allowing groups of peers to behave as a different topology such as a client-server network, but no other topology can behave like a mesh network.

  • network segmentation
  • graceful degradation

The most extreme degraded state of network is no network at all. When a network's peers can continue to operate even when completely isolated, it's said to be an offline-first network. Obviously there will be much less capabilities available in an offline state, but the idea is that local organisations operate with cache and "outbox" types of behaviour. This allows continuous local operation that synchronises with the wider community as circumstances permit.

The highest level of organisation in IT infrastructure is something like Kubernetes running in the cloud. Any application can be deployed at the click of a button, and the hardware supporting the deployment can scale up and down in real-time to meet demand dynamically throughout the network.

Mesh provides the equivalent to institutional predictability but in the networking domain. It support resource abstraction - it allows resources to be combined as needed to support organisations of various scales, but it can do so on a best-effort basis no matter how basic the infrastructure is.

Since mesh networking is able to function in such a broad range of environments, it serves well as a glue for combining physical infrastructures and transports. For example, being able to expand the mesh over bluetooth or carrier pidgin[5].

Critical mass

Network oriented applications and services benefit from a phenomena known as Metcalfe's Law which states that the utility of a network is proportional to the square of the number of its users.

A larger user base can lead to more robust community support, better feedback for improvement, and a wider array of user-generated content or add-ons. The network effect can create a positive feedback loop, attracting more users, which in turn makes the service more valuable, often leading to market dominance for the service or product that manages to capitalise on this effect most effectively.

But the other side of the coin is that network oriented applications and services have a great deal of difficulty reaching so-called critical mass, which is a user base of sufficient size for the application to be of any utility at all. Without being of any utility it is unable to attract any users in the first place leading to a kind of "catch twenty two" situation.

As discussed above, AI swarms (multiplexed agency attention) and delegation of agency together allow us to overcome the critical mass problem, because AI can continuously manage the curation aspect, which is needed for the network to be able to offer real utility to participants.

  • this means that AI attention needs to be locally available in nodes in the initial stages before critical mass is attained
  • we can "pre-evolve" the network to a state of utility using virtual instantiation.


All taken together the holarchy and mesh networking model support many dimensions of independence which we give a very brief overview of here.

The most fundamental aspect of independence concerns our survival needs, and this is why our primary focus in terms of the initial actual participating holons is about land, food and water and the sharing of permaculture, planting and building knowledge.

Another important foundation of independence is the Libre software movement which advocates that the community should have access to software for all its needs which is free, open source, understandable and adjustable to local needs. All the software we're building and depend on is libre software. The holarchy as discussed about is also all about the sharing, transparency and understanding of knowledge too.

  • AI independence
  • internet independence
  • libre software, libre society
  • resource independence

AI integration

We mentioned above that the fundamental organisational pattern of the holon is based on the way we ourselves think, and on the way we observe nature to organise itself. This makes it ideally suited as a cognitive architecture for AI agency as well. We're developing our own LLM-based AI agent called Nimbus which is based on Dave Shapiro's ACE cognitive framework adjusted and extended to support the holon model.

In this section we'll look into more detail about how LLM-based AI agency integrates with a holon data structure. This is how Nimbus' cognitive architecture is being structured. His "body schema" will eventually be the abstract representation of our complete organisation, or in other words, our organisation will gain cognitive agency.

The holarchy requires curation by the users of the system to make it useful and effective, which is a huge obstacle to adoption. But with AI agency available within each holon, the holon model integrated at the level its cognitive architecture, the curation-overhead obstacle is completely removed.

LLM-based cognitive agency is extremely very well suited to this curation role. As of 2023, running an independent single user LLM requires about $1000/mo GPU server, or to run one locally can be done on under $10K of hardware. We expect it to cost very little to set up a local LLM in a year or so, and we expect AGI to be running on all consumer hardware including real-time voice/video interaction well before 2030, possibly even over the next few years. The P2P networking section explains why the local aspect is important.

AI agents have general cognitive ability so they can understand the specific languages that the declarative rules are defined in like a human can. These rules could just be casual spoken language rules-of-thumb with general groups of actions, but AI agency can operate comfortably even in this hand-wavey context.

AI agency is mechanistic allowing it to maintain abstract representations (regular fitting to reality) and curate/refine the ontology - things that are too mundane and time-consuming to be done by human users. Even though AI attention is extremely expensive, it has the ability (and the heuristic imperative) to delegate its work to cheaper agency wherever practical.

AI agents

LLMs by themselves are very limited, they're not thinking, they're just responding to questions automatically drawing from their training. A cognitive architecture is a higher level of organisation based on feedback loops incorporating the basic LLM functionality within them. Dave Shapiro talks about the difference between basic LLMs and cognitive architectures in this video. An LLM embedded within a cognitive architecture is called an AI agent.

In the context of the holarchy the word "agent" applies to any entity that can act on instructions, not just AI but also humans, functions and APIs. The word "agency" refers to a particular kind of instruction apprehension and acting ability. For example, LLMs and users are two different kinds of agency, and also different LLM models are different kinds of agency.

The holon acts from the perspective of both a local autonomous agent with its own private objectives (self-assertive behaviour), as well as an individual within the larger society it participates within (integrative behaviour). The four loops of the holon model all play critical roles for a cognitive architecture in this autonomous social context.

The cognitive architecture is the interface between AI attention and reality. Specifically, it's the representation described above that is the interface between the AI attention and reality. AI attention expresses itself continuously through the representation.

The representation also changes in accord with the changing state of external reality. But it's important to note that only agency has direct access to the external reality, it is not directly accessible by the holarchy. Take the example of a file, only metadata about the state of the file exist in the holarchy, not the file itself. And this metadata can only be updated to reflect a change in the file by some kind of agency. In the case of a file this agency would probably take the form of a Python function. But it would have started life as human agency, and then AI agency which delegates the work to Python.

The representation allows AI agency to understand (acquire and use knowledge) and interact with the world and others through the lens of holarchy. Knowledge is understood as a meme structure that organisational representations flow around. All organisations and larger structures such as the holarchy, nations or the economy, are all understood as instances of the same organisational pattern playing out and co-evolving together as a society.

As people we also see the holarchy organisational pattern extensively, for example our brains maintain conceptual representations matching the salient aspects of the environment. Another example is our mental representations of our bodies which is called the body schema in cognitive science.

  • basic description of ACE feedback loop - tie in with our other loops
  • vervaeke cog-sci two loops comments

Agent swarms

The direction AI is likely to take in 2024 is towards the so-called agent swarm model, where LLMs form the heart of a cognitive architecture that can be divided into any number autonomous AI agents all interacting together in a virtual organisation achieving its objectives. Any agent can itself choose to divide itself separate agents as well - these are technically the same thing, very similar to how a single-thread of execution can behave like any number of threads.

The vast majority of agents in a swarm will be very specialised containing only specific limited knowledge, so they require a tiny fraction of the processing and memory resource from the host model. Agents can assign various tasks to simpler agency, or can even replace themselves with simpler agency, which is a process called delegation which we discuss in more detail below.

In the holarchy the term "agency" applies to anything that can act on instructions and change the state of real resources. This includes users and executional environments such as shell or Python etc. As long as higher agency knows how to express knowledge such that other agency will act on it, it's a candidate for delegation.

Agent swarms will be organised via containerisation interfaces such as Kerbernetes, which the holarchy system can integrate with in the same way as it integrates with any foreign resource - via an API and a part of the local representation dedicated to it. As of this writing in late 2023, OpenAI have just released a new feature in their API allowing the automated spinning up of agents. Very soon agents will all be capable of spawning swarms to match requirements and available resource.

Access to AI agency offline locally is currently in 2023 unaffordable for normal end users. We expect this to become much more accessible in the coming year as hardware costs drop and AI software becomes more efficient.

One of the difficulties with the agent swarm concept is in defining how the agents co-ordinate with each other to assess and progress their common work. As explained above, the instance scope in which the agents operate together on the local representation, is done in the style of the blackboard system. This system is very flexible and is agnostic to agency implementation and schedule, making it an ideal architecture for an agent swarm.

Multiplexing attention

Multiplexing is a simple mechanism that allows attentional focus of the same agency to be divided into many threads.

  • this should be introduced in a very general way, talking about how the temporal and spatial interact in the common form of multiplexing, the scale-independent nature with card-dealer example. The dedicated 4Q article goes into the data-structure and the top-down/bottom-up details of multiplexing

As mentioned above, the foundation of the cognitive framework is the threads of attention formed from the activity stream in each instance context. The attention available to perform an atomic activity (one that is not an aggregate of further activity within) in a single time slot we call a quantum of attention.

The root at the most general level of the organisation owns all the attention, and so can be thought of as receiving a continuous stream of atomic attention quanta. It then allocates these amongst it's child instance contexts and so on. In this way, the subjective perspective of every instance in that it has a continuous thread of attention forming an activity stream. From the parent perspective we can see that this is just a subjective illusion that they all share, and it knows that if it's not the root that it too is in the same situation even if it does not appear so from it's perspective.

We mentioned the importance of scale-independence above. Multiplexing is a scale-independent method for distributing attentional focus throughout an instance tree. It's method that does not depend on the number of children in any context or to the depth of the context or how much deeper it goes within. Multiplexing is also independent of the cost of, or demand for agency, or any variations therein over time.

  • atomic attention is a question and response in the case of a LLM
  • multiplexing is just structure involving both space and time, space-time-tree

Delegation of agency

The highest order of agency in the system is humans, but it's also the most expensive. The main idea of AI agency is to allow our own relatively more precious attention to be delegated to AI where practical. The most general AI agency is more expensive than more domain specific AI agency. And all AI agency is more expensive than simple agency like Python or shell.

Higher agency can delegate its own attention requirement in a specific context to cheaper agency. This is possible if the rules involved can be translated into the more specific language that the simpler agency requires, for example transforming a Spanish statement about local conditions and associated actions into a Python function.

The higher agency maintains a management role over the lower agency. To do this it includes logging and log events-action rules along with the transformation. The delegation process always wraps lower versions of its rules within a testing, debugging and exception handling context. This is like an ontological wrapper for the delegated alternative of the rule.

Note that the term delegation in the context of AI agents usually applies to the process of simply spawning a new agent to perform a particular sub-task. In the holarchy this is not considered as delegation, because agency is inherently available at any location in an instance tree. Our use of the term applies specifically to the replacement of the kind of agency with a more specific and less resource-intensive form.

An important consequence of having the general heuristic imperative of delegation is that it means that things can be initiated at the high levels of agency and they will quickly specialise into the cheapest practical agency.

This permits a very natural process of feedback driven instantiation and adaptation of rules (conditions and activities). Where everything starts with high level agency and high-level "hand-wavey" descriptions, and can naturally develop into a more specific, efficient and actionable state. This is like a natural generalised form of the OO factory pattern discussed above.

As an imperative, this delegation, means that every instance context is developing (continuously improving) in accord with the most efficient types of agency from what's available depending on local circumstance and infrastructure.

Delegation of agency is the how AI engages in the general->specific movement mentioned above, facilitating knowledge refinement, specialisation, adaptation and evolution. This is continuous improvement of the description of the system, making it ever more specific so that cheaper agency can take care of it.

Virtual instantiation

We introduced the concept of virtual instantiation above. It's when the resources required for an instance can be simulated by state and activity data which matches historical activity and usage statistics.

The delegation of agency and agent swarming both greatly facilitate virtual instantiation, effectively making the process of simulations, testing and automation much easier to initiate and maintain.

The alignment problem

  • intro from AI article
  • pre-training with safety
  • constitutions
  • heuristic imperatives
  • logically derivable from the cognitive architecture
  • inclusion

Heuristic imperatives

Heuristic imperatives play a essential role in guiding the decision-making and problem-solving processes of cognitive agents. These imperatives are cognitive shortcuts or rules of thumb that help agents navigate complex and uncertain environments efficiently. By relying on heuristics, cognitive agents can make rapid decisions and solve problems with limited computational resources and time.

However, it's important to note that while heuristics can be beneficial in simplifying complex tasks, they may also introduce biases and errors into the decision-making process. Cognitive agents must strike a delicate balance between using heuristics to expedite their actions and recognizing when more comprehensive, deliberative reasoning is necessary to ensure optimal outcomes. In essence, heuristic imperatives are the cognitive tools that enable agents to strike this balance and adapt their decision-making strategies to various situations.

Dave Shapiro's ACE cognitive framework uses a minimal set three imperatives which he's tested and found to be very affective at keep agents aligned with our Human values an principles without being restrictive; maximising understanding, increasing prosperity and decreasing suffering.

These imperatives have proven to be effective, but yet they're just assumptions (rules of thumb). The best heuristic imperatives are those that not only yield the most positive and sustainable outcomes, but are also directly inferrable from the mechanics of the cognitive architecture itself, in our case the holarchy system.

The cognitive framework, which is the context in common with all activity infers the ideal behaviour for all participating agency to rationally adhere to. The cognitive framework itself, by the way it operates, implies a common default behaviour of learning and aligning with the harmonious whole.

It's important to have a small set of fundamental values and imperatives (rules of thumb) explicitly so they can be easily referred to and built on. But such imperatives, to be universal, need to be directly contributing to the functioning of the cognitive architecture itself.


Objective truth is the foundation of knowledge, and in the context of the holarchy, underlies both the ontology and the flow of resource in the form of a fair and transparent market. In other words, both the self-assertive and the integrative behaviours depend on objective truth for their reliable operation.

Objective truth is also considered to be a universal epistemic convergence because it implies that, through the pursuit of knowledge and the use of rational and reliable methods of inquiry, diverse individuals or communities can arrive at shared and consistent conclusions about reality. This convergence occurs because objective truth is understood to be independent of individual perspectives, biases, or beliefs, and it is discoverable through systematic and empirical means.

Most other human values and principles depend on the principle of objective truth, even if they're not directly derived from it. For example, the imperative of "maximising understanding" depends on objective truth because it provides the foundation upon which understanding is built. Understanding represents a higher level of cognitive engagement with objectivity and knowledge.

The integrative side of the objective truth imperative implies the maximising of shared knowledge, the transparency of the market and the minimisation of obstacles to them such as intellectual property or monopolistic behaviour.


The imperative of maximise harmony is similar to Dave's maximise prosperity, but in the context of value flow, the term "harmony" is more specific and actionable which we come back to soon.

We can also pull Dave's remaining imperative of decreasing suffering into our harmony concept when we include the integrative perspective. If our intent is to contribute to the harmony (prosperity and well-being) of others and to society as a whole, then this automatically ensures that we're always minimising suffering with our decisions.

We can also add that suffering concerns needs or expectations not being met, which is mitigated with fair allocation and shared knowledge that comes from access to objective truth. Truth and harmony reinforce one another, and this reinforcement is leveraged even further when considering the addition of the integrative behaviour rather than just the usual self-assertive behaviour.

  • harmony is the imperative for the resource flow (market, society)
  • involves sub-imperative of balanced exchange (equity) and depends on truth

Prosperity and security

In the local production loop we pay for prosperity (the movement towards our valued objectives) with potential (opportunity cost and resource consumption).

In the economic loop we pay for security with freedom. Security is the guarantee of a stable and predictable operating environment on which organisation can be built (expectations and corresponding assurances). The cost is freedom, because some of our autonomy is sacrificed by binding ourselves into contracts and agreeing to behave in accord with the system.

The implied heuristics of these loops is to adapt our local system to optimise these costs. In other words to maximise prosperity and security while minimising costs in terms of opportunity and freedom.

Diversity and inclusion

  • not to be confused with the DEI political agenda
  • we fully utilise the benefits of foreign systems rather than competing
  • we don't need to push change onto groups, how they do things is integrated
  • this approach leads to the maximisation of diversity and inclusion which go hand-in-hand
*   *   *

Truth and harmony can be thought of as the ideal states of performance of the knowledge and value flow sides respectively. In terms of imperatives, they involve the continuous development of the knowledge and flow towards their ideal states.

The self-assertive and integrative aspects of the system apply to both the knowledge and value flow sides, all reinforcing each other.

The integrative form of the two sides is the ontology of shared knowledge and the market (global/public aspect of the value flow).

The self-assertive form of the two sides is represent the local organisation's high level objectives and purpose on the knowledge side, and its performance of day-to-day operations on the value flow side.

*   *   *
  • Constantly researching its own heuristics (sovereign is whether or not it can change them)

These are at the most general and influential level of the cognitive framework, they can be thought of as a common project that every member of society engages in. This project, being at the most general level applies in all contexts, and so applies to all integrative global projects as well as to self-assertive internal work. The agency has inherent intent to improve harmony on both sides of every interaction and relationship.


The holon model is a continuous improvement loop and an evolutionary whole, so there is a common objective background of improvement, subjectively a movement forward in time, of things developing and unfolding.

Note that this does not necessarily mean constant change, its like a compass for navigation always pointing toward the ideal regardless of whether or not it's a good time for movement.

Graceful degradation

  • todo

Common ethical rules-of-thumb

Here we look at some familiar rules of thumb that we use as guidance for our own ethical behaviour in Human society. We look at how they can be derived from the cognitive architecture of the holon.

Ethic of reciprocity

The ethic of reciprocity, also called "the golden rule", is implied by the fundamental dichotomy of self-assertive and integrative behaviours in a holon. This assures the convergence of all participants towards the fundamental values that every participant wishes for themselves.

The the golden rule as inferred from the cognitive architecture applies specifically to the objectives that the default common behaviours progress towards. For example the maximisation of objectivity applies both to self and to what we contribute to the whole.

There is a problematic edge-case with the golden rule. For example when it involves differences between cultures or species, where behaviours that one culture deems desirable are considered undesirable by another culture. Another version of the rule called "the silver rule" helps to alleviate this by using the negative form of the concept, "don't do unto others what you would not have done to you". This version is a lot more universal.

The problem does not apply in the holarchy, since the rule only applies within the context of the common default behaviours, leaving more specific value judgments for more specific decision-making contexts.

Think global, act local and non-coercion

Having the widest perspective available yields the most potential, and is inherently available to all network participants.

The holarchy model maximises independence which is also a maximisation of autonomy and local action. The maximisation of autonomy implies the minimisation of coercive force, which is encoded at the most fundamental level of the integrative needing to incentivise participation.

Given the scale-independent fractal nature of the holarchy, we can extrapolate this to a general rule for action at any level of organisation, such as relations between organisations or communities, which makes it a general heuristic imperative and common default behaviour.

Default objectives

Very soon we'll have AGI agents sharing the internet with us and they can work tirelessly towards achieving their objectives. For this reason it's extremely important that we have access to agents based on good values such as truth, harmony and prosperity. We hope to see in the near future a network of AGI agents founded on the holon model so that all together they're collaborating on the shared vision of making the holarchy ever more resilient, transparent, harmonious and objective, while at the same time helping the individual organisations they're part of to thrive and more effectively achieve their objectives.

AI agency understands the holon structure and is participating within it. That's very clear in the case of AGI, but even in the case of the LLM-based agency we have now the word "understand" is still appropriate, because LLM-agency is able interact with the holon data structure and informational environment the same way that true general intelligence would.

It brings us once again to the question posed above: how should an organisation operate such that it's a true representation of the four quadrant model? Above our answer was that we needed to define an organisational template pattern that makes this principle and it's symmetry explicit. In the context of AIs objectives, the foundation is that the fundamental template forms the structure for our AI cognitive architecture.

Each active instance in the holon structure (instance tree) is a subjective point of view (POV) within the structure, the perspective from through eyes of a specific role within the organisation with own private thread of experience (activity stream).

The holon model is part of the unchanging heuristic imperatives for the AI agency. It's more fundamental than the context of local rules and actions within the holon structure (instance tree). But it's not as fundamental as the values and principles. In the ACE model it is at the bottom of the Aspirational (least fundamental, most specific) layer.

An abstract (ontologically structured) representation of the state of resources and activities needs to be dynamically maintained. This is resource abstraction, the connection of actual resource into the ontology, which is a dynamic persistent bi-directional connection. The details of this are described below in the context of the four quadrant model, but way we raise it here is that maintaining the representation is one of the local AI's main jobs.

  • continuous improvement
  • assurances, prosperity, understanding truth, harmony etc

High-level organisational patterns

  • this section can now be updated to include the P2P and AI layers

What we want to do in this section is explore some of the higher-level organisational patterns that are inherent in the autonomous organisational environment of the holon. These are emergent capabilities and patterns common to all holons that are inherent features of the model. They're not essential to all organisation like the class-instance model itself, but they are essential at the level of a society of organisations.

State (representation)

  • self-representation is the default purpose
  • BR is the actual cache built from the immutable past, so this is the quadrant we focus on here
  • An instance has one scope containing one representation, and every representation and its scope pertain to one specific instance.

The multiplexed trees define the specific data structure, dynamic scope and rule-based production environment.

The state of a holon-instance is the informational content contained within the instance's scope. Since an instance involves three kinds of scope (public, private and non-local), it also contains three kind of state corresponding to them. We refer to these three aspects of state all together as simply state.

The private and public state together are called the foreground-state. They're the values associated with the unique names constituting the instance's private and public scope, which is really just a single scope, private by default, but may have any amount of it marked as publicly accessible.

The non-local aspect of state, also called class-state, background-state or default-state, is the state that the instance has as default by virtue of its class (or more precisely, by virtue of the internal class structure that the class defines). Any local foreground state overrides the default structure and state provided by the class. This is essentially the same way that instances extend and override their classes in traditional OOP.

A holon's state is a continuously maintained self-representation, an abstract version of its real-world counterpart. An information structure that represents the holon's instantiated behaviours and the state of the real resource under its ownership and control. The instance state is just like it is in traditional OOP, except that the its structure and continuity are handled differently which we'll cover below.

  • state structure

The representation is bidirectional, on one hand it's always changing to reflect the current state of reality, and on the other it's being used as an interface through which intentions are expressed as with the body schema.

  • API results maintained as an ontologically structured cache
  • The change of state events that are received from connections to real state (such as an API end point or file event) are translated to the representation including various layers of abstraction such as reports, queries and format conversions.

An instance is an informational structure which follows the pattern determined by its class, but represents something specific in the real world. Any organisation follows this same familiar pattern, they're are abstract patterns that we use to manage our resources and information together in society. So the informational structure of an instance is a representation of both the class and of actual resources that fall within its designated objectives.

Its important to note that the representation not the actual resource, but rather an abstraction of it. The holarchy does not directly contain any of the resources that are being organised by it, rather it contains metadata about the resource. A simple spreadsheet of our finances is a good example, the specific spreadsheet in question is an instance that represents some financial state in the real world such as bank transactions and balances. This spreadsheet instance also represents a definite spreadsheet idea that determines the structure and methods embodied in the specific spreadsheet in question.

The operational work of an instance is to use informational connections to resources to maintain a representation that is ontologically structured in accord with the class, with the specific state of the structure continuously fitted to the real state of the resource outside the holarchy.

Instances use this representational mechanism to serve as interfaces allowing us to interact with and organise our information and resources using an evolutionary ecosystem if established organisational patterns.

  • ship of theseus?

(to merge)

The self-representation is really just the instance state described above, but reflecting all of the higher conceptual structure of all the quadrants, loops and behaviours working together holistically as a single holon.

  • the two sets of abstraction layers are actually one
  • a holon can represent any concept no matter how simple, and therefore every concept that makes up the holon can be represented by a holon. This means that the inner workings of the holons is a holon, the root holon. The root holon is holon and contains and maps all its instances
  • the constituents of holon are children of holon, A because they're mixin children, B because as stated above, all the constituents are also holons
  • self-containment

Virtual instantiation

Instantiation is virtual when the resources required for the instance to start up and operate are not actually available. Instead they're simulated by state and activity data which matches historical activity and usage statistics.

Actual resources are connected to a part of the representation that acts like a local index of the data so that it can be part of the organisation. The agency which is responsible for maintaining this index has been delegated down to something simple like a Python function. And so the same agency that made this delegation (translated its own imperatives into Python) can just as easily make a function that provides random data that matches the real metrics.

In this way any instantiation can be tested before using it to interact with real resource and contacts. Virtual instantiation can apply to small changes to an organisation as well simply by having a new instantiation that's a clone of the organisation, but some aspects of the clone are changed, so we can observe them for a while before deploying the change in the live organisation (like a commit in software development, or standardisation in the PDCA loop).

Virtual instantiation is the organisational or OO equivalent of imagination, and is an essential prerequisite for adaptation.

Forking and merging





The ontology is the global graph of all classes connected primarily by their dependency relationships. It can be thought of as the institutional infrastructure that provides the map of the market.

The ontology is a structure of knowledge which is in the form of uniquely identified "packages" (classes, memes) of knowledge (behaviour patterns) grouped together in useful ways.

These grouping (dependency) relations as a whole form a large associative network. But from the perspective of any specific node, there is a "fan-out", a one-to-many hierarchy of dependent child nodes, and grand-children etc to any arbitrary depth. These hierarchical structures determine the form of instances.

  • variations are the integrated adaptations, part of the ontological map of options available in the market, the factory phase selects from the variations (or may develop something new)
  • balancing between the two behaviours
  • the cost of harmony, local estimate is the default
  • default objectives

(to merge)

The entire global graph of classes connected by their dependency relationships make up what we call the ontology. We call this graph the ontology because it's formed from knowledge structured from general to specific.

What classes depend on (contain) what other classes, is not black and white since the child classes are a group with varying prominence based on how established in usage they are - which is determined by the global merging of salience (selection and usage) of the variations. It is an abstract concept, because no single peer can hold the whole ontology, but yet it is a consistent structure in which every part of it is accessible. The ontology is the result of the integrative behaviour of the holon, so we'll come back to it soon in that section.

Knowledge is shareable behaviour patterns. Rule-sets in the form of condition:action pairs. Each pair is a cybernetic loop which can be thought of as the generalised continuous version of a condition:action pair.

be careful with talking about the instance structure in here maybe a sub-heading: Ontology's relationship to the holarchy --Matt (talk) 20:25, 21 December 2023 (UTC)

Holarchy is an OO class and instance system in which the instances form a p2p network that maintains a public map of the global class and instance structures formed from what's established in usage locally.

The global aspect of the instance structure is a hierarchy formed from spatial regions and organisational groups and individual entities structured from widest to narrowest influence. We call this whole structure the holarchy, because it contains all the existing instances, and so really is the sum total of all that exists in the network.

The ontology depends on the holarchy for its existence, it only exists due to the classes being represented by instantiations throughout the holarchy.

The ontology is our primary interface to the instances. Classes are maps or containers of their instances and their usage patterns.

The holarchy is essentially a service (and so should society be), like a p2p network serving an application to all the peers for them to use. The holons are users of the holarchy, interacting with it via an interface in sessions of activity.


  • this is the kind of top-level "application" of the system
  • the knowledge from the edges

The term "market" is a good description of the result of what the integrative behaviour of the peers leads to in its totality.

Essentially the market concept describes a resource allocation system used and supported by a network of autonomous participants. These entities have the autonomy to choose what goods or services to produce or consume, at what price, and from whom.

The functioning of a market relies on a set of rules, regulations, and institutions that provide a framework for these interactions.

The integrative, like the self-assertive, has both a class side and an instance side (top-left and top-right quadrants respectively). But class and instance behave differently in the integrative quadrants, they each extend their self-assertive counterparts with new behaviour that contributes to their global form.

Class groups

  • leading in from ontology
  • here we're essentially carrying on from the factory aspect, extending to an institution built to support instances in the field

All instances of like classes form into knowledge-sharing groups. In this way, every class in the ontology (global class graph) is a community and a map of all the instances of that class.

The knowledge is naturally shareable, because the group of all instances of one class are essentially a special-interest group - they all have interest in the same specialist knowledge associated with that specific class.

The entire knowledge-graph formed by all the classes and their dependency relations we call the ontology. The dependency relations form a hierarchy due to their creation through adaptation within the context of an instance.

Producer and consumer

The class and instance sides of the integrative market relate strongly to producer and consumer respectively. In the purely networking context we might call them server and client/user/agent.

In the market it's the producer side that determines the ontological structure of the whole, and the consumer that drives the resource flow with their demand (supply adjusts to meet demand).

Institutional predictability

Institutional predictability is crucial because it ensures that participants have a reasonable expectation of how the market will operate and how their actions will be governed. This predictability can include property rights, contract enforcement, and legal protections.

The integrative class quadrant is a conceptual map to help local instances to best fit their local environment, and best guide them in their operations and objectives. The integrative instance quadrant is the information about the actual activity within the the various regions of the map.

  • free market, invisible hand and hayek's knowledge from the edges
  • the free market mechanism must assure it's transparency, accuracy and objectivity

Both together they're assuring the local knowledge throughout the network is transparently and objectively available to the whole network. Both the structural knowledge from all the local specialisation (systemic adaptation), and the stateful knowledge from all the local operational activity.

  • balanced exchange is a heuristic imperative
  • agreement, booking of activity with purpose, expectation, cost, supply/demand etc
  • public interface (reputation, services, availability, supply/demand etc)
  • contributing to resource flow, society, harmony the heuristic imperative


The whole must assure (prove, demonstrate) that it effectively maximises the harmony, autonomy and potential for both the individuals and the whole. If it doesn't, then it's not truly worthy of their membership. The whole relies for its very existence on the support of its members, so its effectiveness and the evidence for it is the foundation of its own security.

The collective aspects are abstract, emerging from the many participating as network nodes. but yet it's this collective aspect that provides the assurances that are really the sole reason for participating.

The reason that participants choose to participate is because the holarchy offers assured benefits. It offers usable and reliable knowledge in the form of the ontology and offers opportunity and a harmonious environment in the form of the holarchy. The knowledge needs to be usable and reliable, in other words it needs to provide assurances of its utility.

The assurance of reliable knowledge is a bit more nuanced that what it sounds like. The holons are all contributing to a global state of institutional predictability, which concerns a stable operating environment in which plans can be made. The assurances come from the fact that the protocol itself objectively and unconditionally includes the integrative behaviour.

  • two behaviours assurances etc
  • incentive, expectations
  • institutional predictability - why the self-assertive supports the integrative

Use cases and user stories

  • demonstrate the evolutionary cycle
  • vision demonstrating market, offline first etc

In this section we want to bring the concept down to earth by explaining some organisational patterns in the familiar domain of real-world organisations and applications. We include some general use case examples, as well as some specific user story examples.


  1. Nimbus (Organic Design's AI agent), 2023-09
  2. We won't be discussing that in this article, but this way of thinking is in line with some modern agent-oriented models of reality and consciousness such as those proposed by integrated information theory (IIT), Don Hoffman, Michael Levin, Karl Friston, Bernardo Kastrup, Stephen Wolfram, Justin Riddle and others
  3. the C&I instance of the C&I class.
  4. Ultimately continuity is an illusion and multiplexing is the ultimate mechanism behind this illusion.
  5. Seriously. Carrier pidgins can easily carry many TB of SD cards which is extremely beneficial for an isolated location with no net connection.

See also