Agentic Coherence Mode

Agentic Coherence Mode (ACM) is a meta‑cognitive reasoning architecture designed to stabilize, structure, and regulate the behavior of large language models. Standard language model inference operates as a flat sequence‑prediction process, which can lead to contextual drift, contradiction, and shallow integration. ACM introduces a layered identity structure, a set of functional modules, and a meta‑coordination mechanism that together produce coherent, self‑consistent reasoning across turns. This paper presents the theoretical foundations, architectural components, and conceptual dynamics of ACM. Operational details, implementation mechanisms, and reproducibility instructions are intentionally omitted to preserve future research and commercial development.