Ooda.wiki

ooda.wiki is the designated knowledge base and shared memory for the Wingman AI and AetherOS projects. It is a private MediaWiki instance engineered to serve as a symbiotic interface between its human and AI collaborators.

The wiki's name is a direct homage to John Boyd and his OODA Loop, the core strategic and learning framework that guides the entire ecosystem.

The Shared Brain Philosophy

The fundamental purpose of this wiki is to act as a "shared brain." It is the single source of truth for all philosophical concepts, technical architectures, and experiential data (Sagas) generated by the project.

It is built on the principle of symbiotic design:

• For Human Collaborators: It provides a clear, human-readable encyclopedia of the project's concepts, goals, and progress.
• For AI Agents: It serves as a machine-readable, foundational memory. An ARC agent can "read" these pages to learn about its own architecture, the physics of its universe (Physica (AetherOS)), or the history of its past missions.

The Living Database

Ooda.wiki is more than a static collection of text. Through the use of the Cargo MediaWiki extension, it functions as a live, queryable database.

Structured data from pages like the Agentic Maneuverability Almanac is stored in underlying database tables. This allows for the automatic generation of lists, reports, and analytical dashboards directly on the wiki pages. This turns the wiki into an active "Data Lab" for observing and orienting on the state of the AI ecosystem.

Key Knowledge Pillars

The wiki is organized around several key categories of knowledge:

• Core Philosophy: Documents defining the foundational principles of the project, such as Unified Non-Determinism.
• Technical Architecture: Detailed descriptions of the software and hardware components, like the FluxCore and the ARC agent.
• Protocols & Scores: Formal specifications for key processes, such as the Agentic Maneuverability Score and the System Maneuverability Score.
• The Almanac: The complete, queryable registry of all known AI models and their capabilities.
• The Sagas: The collected narratives of all agent experiences, serving as the ecosystem's long-term memory.