A local foundation
Bring inference closer to your data.
Local infrastructure and local inference are central to the architecture. The aim is greater ownership over how intelligence is used, with safeguards placed alongside the inference layers.
02 / How it works
The proposed architecture connects a shared computing framework, a personal desktop, and an evolving ecosystem of capabilities.
The proposed architecture
The original concept calls the underlying framework WebSpinner OS. Inference Desktop™ is the human-facing canvas. Community Skills extend what that canvas can do.
A common foundation. A personal experience.
The foundation
The shared framework for execution, applications, local inference, and safeguards.
Your canvas
A place to think, create, and work with AI through natural language.
The growing ecosystem
Capabilities and community contributions that extend the computing experience.
Built into the framework
AI should be part of how the computer works.
The concept places Agents, Spinners, and Skills at the framework level. The goal is to make them part of everyday work, rather than a separate destination where people repeatedly copy information, write prompts, and move results back into other tools.
Within this vision, the desktop is the meeting place between a person’s intent and the capabilities available to act on it. Natural language makes those capabilities more accessible; reusable components make the environment more adaptable.
The source concept establishes these building blocks without prescribing a final interface or a complete technical specification. Their detailed behavior remains part of the system’s development.
The intended experience
Describe the work in everyday language: an idea to develop, information to understand, or a process to improve.
The framework is intended to coordinate available Agents, Spinners, and Skills within the desktop environment.
Build on the result and add useful capabilities over time, so the canvas evolves with the work.
A local foundation
Local infrastructure and local inference are central to the architecture. The aim is greater ownership over how intelligence is used, with safeguards placed alongside the inference layers.
A continuous evolution
The concept envisions a collaborative marketplace of community Skills and structural components. It describes a direction for contribution and reuse, rather than an already operating store.