The world’s largest organizations have been trying for years to solve one problem: how to create software faster without losing control over knowledge, security, and quality. Today the answer is usually scaling teams, outsourcing, or adding yet another layer of tooling. There is, however, a different direction.
The idea of programs writing other programs is not new. Think of website templates: they are specialized mini-languages that anyone can learn, and it is hard to use them in a way that would break the entire system. The operator focuses on the layer they know best, and the rest happens underneath.
What if artificial intelligence also worked this way — its individual parts cooperating with one another, each performing specific tasks tied to its own specialization? Every such component could, first, be far cheaper, and second, need not be operationally omnipotent.
If we treated Orbiplex as infrastructure rather than a tool, a corporation could become a swarm of cooperating nodes in which divisions, teams, and partners jointly create software as a process, not merely as a project.
The image that comes to mind is not a ladder to which we keep adding rungs, hoping to reach higher, but rather a banyan tree — a tree that sends aerial roots down from its branches, and those roots, upon reaching the ground, become trunks of their own. Each stands on its own soil and draws from its own ground, yet the canopy is shared and the root systems connect beneath the surface. From a distance it looks like a forest — but it is still a single organism.
It is precisely in such a model that an environment emerges, where it is enough to provide a business context and the system itself begins to build a solution — with memory, specialization, and local control.
A swarm instead of a silo
Can a corporation work like a swarm?
Large organizations are inherently distributed today. They have offices in different countries, teams with widely varying competences, external partners, law firms, and consultancies. The problem is that this structure does not translate into shared intelligence. Knowledge is locked in silos, decisions are not shared, and processes have to be rebuilt from scratch in every project.
Orbiplex lets us look at this structure differently. Every division can act as a node. Every technology, legal, or operations team can be represented by a specialized capability in a federated swarm.
External partners are no longer mere service providers — they become participants in the system. As a result, the organization stops being a collection of independent units and begins to act like an organism that can cooperate and learn as a whole.
Nodes as a source of competence and responsibility
In this model everything begins with nodes. A node is not just a server running a model, but a unit that possesses identity, competences, and access to specific resources.
A division in Germany may have a node specializing in the local market and regulations. A team in Poland may be responsible for backend and systems architecture. A law firm may provide a node with knowledge of local law and an option for human expert approval (human-in-the-loop). A consulting firm may contribute an analytical node that understands business processes.
Each of these nodes has access to its own data, code repositories, documentation, and context, but operates locally and under the owner’s control. There is no need to centralize everything in a single module. Instead, a network of competences emerges that can be drawn upon whenever they are needed.
What matters most, however, is that these nodes do not operate in isolation. They can cooperate, exchange results, and even carry out a process resembling a discussion. As a result, the solution that emerges is not the output of a single command, but the outcome of work by many specialized capabilities.
Memarium as organizational memory
In traditional organizations the biggest problem is not a lack of knowledge, but the lack of access to it at the right moment. Documents exist, decisions have been made, analyses have been carried out — yet they are hard to find and reuse.
This is where Memarium comes in. It is the federated memory of the swarm’s nodes, designed to store not only data but also the meaning of processes. Business documents, architectural decisions, code fragments, legal analyses, and project contexts can all flow into it. Importantly, this memory remains distributed and locally controlled. Each node manages its own part, but can share it within the scope of cooperation.
Thanks to this, the organization stops starting every project from zero. The system has access to the history of similar problems, earlier decisions, and proven solutions. Automated use of retrospection and analogy appears. Knowledge does not vanish — it becomes an active part of the creation process.
When a business client is enough to launch the software creation process
The most radical change appears when we build a thin client for business on top of the swarm infrastructure.
Imagine that a business division is preparing a new product. Instead of writing detailed specifications and handing them off to IT teams, it feeds context into the system: goals, requirements, constraints, documents, analyses. This enters a workspace that becomes the starting point for collective artificial intelligence under the stewardship of human experts.
In “The Mythical Man-Month” Frederick P. Brooks shares, among other things, observations about adding people to projects and the enormous communication overhead needed to coordinate the process of introducing changes. At a certain critical point, the synchronization of actions and decisions between teams consumes so much time that it kills the project.
This is one of the reasons why small startups, despite lacking capital, can often show working products faster, while similar solutions developed by large enterprises have not yet left the requirements specification phase. A design decision in the mind of a programmer (who also happens to be the systems administrator) working at a small company takes 0.5 seconds. The same decision at a large software firm can take weeks. Meetings, calendars, alignments, open slots, compliance reviews, requests, approvals, reports…
What if communication between specialists were faster and less prone to differences in how requirements are interpreted? This becomes possible when the expert provides the intent, and a network-connected AI agent takes care of the details.
The nodes start working. One analyzes requirements. Another proposes the architecture. The next one writes the first fragments of code. Yet another checks regulatory compliance. Finally, the coordinating node refers to earlier projects stored in Memarium. The process resembles teamwork, but it takes place continuously and in an automated — and often parallelized — fashion.
The result is not a single answer, but a solution that keeps evolving. Code emerges, along with documentation, architectural decisions, and their rationales. Software is no longer a linearly managed project, but a weave of processes that develops inside an environment of distributed intelligence.
Full control through locality
One of the key elements of this concept is locality. Nodes operate as a federation within the organization or at trusted partners. They have access to code repositories, documents, and data, but do not require centralizing everything in a single cloud.
This is pluralism with contracts.
The above means that the company retains control over what is processed and where. Legal data can stay at the law firm. Sensitive business information can be processed only by designated nodes. Code can be written in environments compliant with the organization’s policies.
At the same time, all of this remains part of a single system, because the nodes are able to communicate and cooperate with one another.
A paradigm shift
The most important change is that software creation stops being a linear process of handing tasks between teams. It becomes a continuous field of cooperating capabilities. This processual perspective follows directly from the Orbiplex approach, in which intelligence is not something the system has, but something the system does — something that emerges from participation in an environment.
The corporation no longer needs to scale only headcount or outsource successive chunks of work. It can develop its own swarm of competences, which over time becomes increasingly attuned to its needs.
Instead of managing projects, it begins to manage the environment and intents. Instead of building every system from scratch, it grows memory and capabilities. And instead of relying on individual vendors, it builds a network of cooperating nodes.
From structure to intelligence
I imagine that this approach will lead to a deeper change, in which larger organizations will stop being one-directional structures divided into departments and projects, and will begin to function as a system capable of thinking and acting as a whole.
Orbiplex is therefore not merely a technology. It is a proposal for a new logic of operation. A logic in which intelligence is not only purchased as a service, but built as an environment. A logic in which organizational memory does not perish. A logic in which software is not created solely by teams, but emerges from the work of a swarm.
And it is precisely in this direction that the future of the largest organizations may be heading.