Paper 26 — Structural Portfolio Architecture and Non-Substitution Layering: Reference Layers, Structural Definition Units, and Cross-Axis Boundaries in AI+AGI Infrastructure
Abstract
This working paper develops Structural Portfolio Architecture and Non-Substitution Layering as a high-level structural framework for AI+AGI infrastructure. The paper addresses how multiple reference layers, structural definition units, output-boundary structures, human-discretion structures, role-reference structures, authority-condition structures, time-history structures, economic-reference structures, domain-design structures, propagation-boundary structures, and external-result non-substitution structures may coexist without absorbing or replacing one another. The framework defines a structural portfolio architecture in which reference layers are arranged by role, boundary, and non-substitution relation rather than by execution hierarchy. It positions structural definition units as non-executive components that may define reference location, boundary scope, candidate status, review posture, preservation position, or external-environment correspondence without performing judgment, approval, state generation, evidence confirmation, settlement, propagation execution, public decision, or legal effect. The paper further develops non-substitution layering as a principle for preventing coordinate reference from becoming state generation, output governance from becoming approval, verification records from becoming validation finality, authority-condition boundaries from becoming authority grants, time-history references from becoming evidence confirmation, economic references from becoming settlement, domain design references from becoming construction or manufacturing execution, and propagation references from becoming public disclosure or institutional adoption. This working paper is Paper 26 of the AGI Structural Alignment Series.
Fields of Study & Subjects
Digital Platforms and Economics
Big Data and Digital Economy
Knowledge Management and Technology
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 28 May 2026
- Language
- EN