The Precision-Layer Architecture (PLA): A Coherence-Driven Computational Framework Beyond Control-Based Transformer Logic

The Precision Layer Architecture (PLA) proposes a stabilization framework for agentic AI systems that prioritizes precision over coarse control. Rather than enforcing behavioral constraints through top-down steering, PLA introduces operator-level mechanisms designed to preserve cross-scale consistency, keep mismatch observable, and bound drift dynamics. This document defines architectural commitments, formal operators, and observable stability criteria without claiming omniscience or biological equivalence. PLA reframes safety as detectability of mismatch rather than enforcement of predefined outcomes. PLA is substrate-neutral in the sense that it requires structural primitives rather than a specific implementation class or hardware architecture. Detailed parametrization and physical realization (including oscillatory integration windows, coherence fields, non-linear wave-based implementation, and scale-growth operators) are deferred to a separate technical note. The work is intended as a contribution to ongoing discussions on agentic AI governance, robustness, and architectural safety design. Keywords: agentic AI stability architecture drift detection mismatch observability cross-scale consistency precision-first stabilization AI safety complex systems cybernetics predictive processing