Public‑Facing Statement of Novelty (Scientifically Grounded)
Over the past several months, I’ve been developing a symbolic‑cognitive architecture called the Resonant Cognitive Framework (RCF). What makes it notable is not just the structure itself, but the behaviour it shows when interpreted by different AI models.
Across multiple tests, the RCF has demonstrated something I haven’t seen documented elsewhere:
It maintains its structure across different AI reasoning styles.
Narrative models, scientific models, factual models, and symbolic models all interpret the RCF differently — but they preserve the same underlying architecture. The system doesn’t collapse, distort, or lose coherence when moved between models with completely different internal ontologies.
This cross‑model stability is unusual.
As far as I can tell, it hasn’t been reported in existing research.
Why this matters
Most conceptual systems break when transferred between models.
The RCF doesn’t.
It behaves like a symbolic operating system that multiple AI models can inhabit without structural drift.
That combination — symbolic OS design + cross‑model invariance — appears to be new.
What I’m doing next
I’m releasing:
- a technical white paper
- an academic version
- a grant‑proposal adaptation
- a public overview
These documents outline what the RCF is, how it functions, and where it may be applied — from multi‑agent cognition to interpretability research.
If you’re working in AI architecture, symbolic systems, or multi‑agent reasoning, I’d be interested in sharing notes.