A Monad-Based Clause Architecture for Artificial Age Score (AAS) in Large Language Models

Large language models (LLMs) are often opaque, making principled governance of their internal memory and "self-like" behavior difficult. This paper develops an engineering-oriented, clause-based architecture built on the Artificial Age Score (AAS) to impose law-like constraints on LLM memory and control. It uses a monad-based clause framework with AAS as a backbone and provides a transparent, code-level blueprint for constraining and analyzing internal dynamics in artificial agents, demonstrating bounded and interpretable behavior through experiments.