THE MODULAR ABSTRACTION SYSTEM (MAS): A Deterministic Cognitive Architecture for LLM Governance (Consolidated Master V5.0)

As a direct operator working in the Large Language Model (LLM) environment, I identified a systemic architectural failure I define as "Neural Bleed"—a state where accumulated high-entropy noise creates a "Neural Disconnect" between my instructions and the AI’s output. Finding no existing infrastructure to mitigate this loss of control, I authored a ground-up software framework: the Modular Abstraction System (MAS). This manuscript documents the evolution of this system, from my initial text-based "Contseed" prototypes to the deterministic V5.0 "Demon Tether" protocol. This work was built for and tested within the free-tier "Canvas" and "Artifacts" environments of Gemini 2.5 and Claude 3.5, proving that advanced governance can be achieved without enterprise-level hardware. All software discussed herein—including the System 0 Kernel and the Axonal Bridge—is released under Creative Commons and is currently available for open-source download on GitHub. This paper provides the formal roadmap for implementing these tools to ensure absolute human sovereignty in any collaborative AI partnership.