Intelligence that connects personal context with shared knowledge.
Dk is the proposed intelligence of Drayker. It connects personal agents, specialised systems and collective synthesis so that knowledge can support decisions at the scale where they matter.
The architecture connects specialised capabilities through shared interfaces while preserving the distinction between personal context, project knowledge and public evidence.
The aim is to expand what people can understand and do, with human authority over the purposes and decisions that intelligence serves.
A practical example
A research group could build on an existing model while each participant controls which parts of their personal context enter the collaboration. This is an illustration of the proposed design.
Why this exists
Every person is carrying something they never had the conditions to use; Dk exists to build those conditions. Work and study converge, the repetitive load goes to the machines, and what stays with people is the creating, the discovering and the learning — the part no one should want to automate away.
The argument in full is on the manifesto; the economy page states plainly what contributing here earns and what it does not.
What Dk is made of
| Layer | Repository |
|---|---|
| Base structure — the DNA of the kernel | BSDK |
| The distributed network | Dk Network |
| Security, authentication and encryption | Living Cryptography |
| Identity and the application interface | UID |
| Knowledge and coordination | Dknowledge |
| The method it is all built with | DFM / DFMP |
docs/ethos.md holds the ethical code, which the documentation treats as one of the most important parts of the system rather than an appendix to it.
Three scales
Drayker describes Dk at three scales. Dk Personal is one member’s continuous representation — identity, memory, self-knowledge, commitments and the direction of daily action carried across models and interfaces. Dk Local specialises the same intelligence in one project, area or function. Dk Global is the distributed synthesis that the federated learning of both is meant to add up to. Learning travels upward; personal context does not. All three are described architecture and direction; none of them is a released system. See the ecosystem map.
What the name means
Distributed Kernel is Dk’s technical name and architectural principle. It describes a complex fractal system: a network whose neural and intelligence cores are themselves distributed, acting through evolutionary knowledge graphs. It does not reduce Dk to a low-level kernel. The fractal is the point, not a metaphor. What is true at one scale is true at the macro scale: Dk Global has no single core — it is the synthesis of every Dk in the network. The kernel is not one thing in one place; it is a distributed structure that only exists as the whole.
That is also what ties it to Dknowledge: the evolutionary knowledge graphs are the systemic final form of the knowledge layer — the memory of the network, connected and evolving with it.
How the intelligence is built
Dk is made of intelligence cores — in the spirit of mixture-of-experts for LLMs, but an architecture of its own. Each scale is a core connected to its own knowledge: Dk Personal is the mini version, connected to the person’s personal Dknowledge; Dk Global is the full version, connected to global Dknowledge; and every organization and project carries its own Dknowledge connected to a specialized Dk. BSDK assembles the pieces of personalized, evolutionary intelligence — the base structure is what lets a core be composed, revised and carried.
How it fits the whole
Dk is not the owner of the ecosystem — it is its organizer. Every layer of Drayker speaks to it, and that is the point: one intelligence that the whole system shares, so anything built here starts with what is already known instead of starting over.
The method gives Dk the shape of work: DFM cuts any issue into functions small enough for one person — or one agent — to finish, and Dk distributes them by profile and analysed inputs. Identity makes it attributable: UID ties every contribution to a person, and consent is the condition for anything touching personal data. The network is the ground it runs on, the kernel (assembled from BSDK) is what it stands on, and Living Cryptography protects the tunnels between them. Dknowledge is its memory — papers, architecture, decisions and evidence staying traceable to their sources instead of scattered.
Downward and outward, the same intelligence reaches the rest of the system. Dk Personal is its scale for one member; the Academy shapes formation to the profile and feeds what people learn back into it. Dk can observe needs, model scenarios and recommend how funds or value rules might serve declared purposes, but it does not own resources or decide their allocation: accountable member governance does. The same boundary applies to support — intelligence may help assess evidence and coordinate capacity, while rights and distribution rules remain constitutional human decisions. Open science uses it for assisted analysis under professional review. Stations and embassies connect it to local contexts, and PAP is the environment where intentions, projects and applications are meant to live.
The rule under everything: intelligence is the means, never the master. Dk organizes to free — the will to potential of every person is the end.
Connections
| Layer | Connection |
|---|---|
| DFM / DFMP | The method: work cut into functions, distributed by profile |
| BSDK | The base structure the kernel is assembled from |
| Dk Network | The ground it runs on; excess network capacity as a second layer |
| UID | Attribution and consent for every agent and person |
| Living Cryptography | The authenticated tunnel protecting communication |
| Dknowledge | Its memory: papers, architecture, decisions, evidence |
| Dk Personal | The same intelligence at the scale of one person |
| Dk Academy | Formation shaped to the profile; learning fed back |
| Value unit / funds | Dk models and recommends; member governance decides how common resources follow declared purposes |
| Distributed support | Common capacity governed by member-defined rights, needs and accountable evidence |
| Open science | Assisted analysis under professional review |
| Stations | Where the platform meets ground, managed by Dk |
| OSDK | Devices coupled to the network, integrated via API |
| PAP | Where projects are composed on the same model |
What is published here
Motions for resolution on Dk itself. All proposed resolutions presented here are solutions to the requirements of Dk and the Drayker platform, and only those requirements are final — the motions illustrate what should be done, while the definitive architecture is expected to come from optimal solutions developed with metaprogramming intelligent algorithms and research organized through DFMP.
State of this documentation
A summary and a ground rule. The motions are referenced across the ecosystem but not published, and the ethics note is a single paragraph on a subject the system says is central. Both are open work.
Contributing
Open an issue. Issues small enough for one person to finish carry the open-function label and appear on the board at drayker.org.
Other languages: Português · Español — both currently behind this English version.
Content licensed CC BY 4.0.