Foundations of Strategic Computing in AI Systems: OS2x2 Whitepaper (v2.7)
This whitepaper introduces Strategy Knowledge Science (SKS) as a formal framework for representing strategic environments as computable state-spaces. It presents the OS2x2 architecture as a strategic computing system for positioning, feasibility analysis, trajectory computation, verified strategic decision-making, and continuous strategic memory. The paper defines the core layers of strategic computation — Strategic Geometry, Strategic Algebra, Strategic Mechanics, Strategic Topology, and Strategic Field Theory — and shows how they are translated into an applied computational architecture for AI-assisted strategic reasoning. It also introduces the Strategy Knowledge Model (SKM) as a new class of strategic-native artificial intelligence aligned with strategic state-spaces, constraints, and trajectories rather than linguistic plausibility alone. This document serves as the theoretical and architectural foundation of the OS2x2 platform and the broader category of computed strategy. What’s new in v2.7 Added three formal case studies: The Asymmetric Acceleration of OpenAI vs. Incumbents The Narrative Hallucination of WeWork Real-Time Strategic Positioning — Humans.ai Expanded the practical integration layer across BI, ERP, CRM, knowledge systems, telemetry pipelines, and planning tools Website: https://os2x2.com
Authors
- Igor Binom
Institutions
- BC Platforms (Finland) (FI)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-03-22
- DOI
- https://doi.org/10.5281/zenodo.19172587
- Primary Topic
- Cognitive Science and Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00