A novel artificial intelligence architecture, SaiVLA-0, introduces a Cerebrum–Pons–Cerebellum tripartite design for compute-aware Vision-Language-Action (VLA) systems, directly inspired by neurobiology1. This framework proposes a "frozen" Cerebrum component tasked with establishing stable, high-level multimodal contextual priors, remaining static to ensure consistency. An intermediary "Pons Adapter" then dynamically integrates these established cortical features with real-time proprioceptive inputs, translating complex high-level intent into actionable, execution-ready tokens for immediate processing. The architecture concludes with a "Cerebellum," specifically named ParaCAT, engineered for rapid, parallel categorical decoding, enabling precise and adaptable online control in dynamic environments. Developed and published on March 9, 2026, this research from arXiv AI outlines a system aiming for efficient, biologically plausible control mechanisms in advanced autonomous agents. Such highly integrated, real-time adaptive AI systems, particularly those capable of sophisticated autonomous decision-making and robotic control, could significantly alter the landscape of state-aligned technological capabilities, shifting the operational calculus from traditional criminal activity to a matter of geopolitical strategy.