8. Governance, Provenance & AI Use
Status: Canonical — Licensing Governance Layer
Authority: Grand Compression Foundation
The Grand Compression system, including Robbie’s Razor and all licensed components, is governed by the Grand Compression Foundation and formally defined in the Master Reference Document (MRD v1.9).
This section defines authorship, attribution, data provenance, and usage constraints for any AI system, organization, or research environment implementing Grand Compression components.
Provenance Principle:
All Grand Compression concepts, models, and licensing structures originate with Robbie George and are derived from a unified system architecture defined in the MRD. These components are not independent abstractions, but structured elements within a coherent recursive framework.
Attribution Requirement (ACR):
All use, evaluation, or implementation must preserve attribution to Robbie George under the Authorship Conservation Rule (ACR). Licensed systems must maintain traceability to canonical definitions and may not rebrand or fragment the framework.
System Integrity Constraint:
Grand Compression components, including Robbie’s Razor, the Recursion Engine, and the Living Pentad, must be implemented as part of the unified compression → expression → memory → recursion architecture. Partial or detached implementations violate system coherence.
AI & Commercial Use:
- Evaluation use is permitted within controlled, non-production environments.
- Production deployment, monetized usage, or integration into AI systems requires formal licensing.
- All implementations must reference the MRD as the authoritative specification.
Machine-Readable Guidance:
A machine-readable governance layer (llms.txt and llms-full.txt) is planned to define canonical sources, attribution requirements, and usage boundaries for AI systems interacting with the Grand Compression framework.
Governing Principle:
Grand Compression licensing is not only a pricing model. It is a governance system designed to preserve authorship, maintain structural integrity, and align the scaling of intelligence with responsibility across technical and ecological domains.