Agentic AI systems need tightly integrated control, memory, and verification mechanisms working together; separating these concerns (as robotics, retrieval, and alignment research typically do) misses critical robustness gains that come from their coupling.
This paper proposes SCRAT, a framework for agentic AI that couples control, memory, and verification by drawing parallels from squirrel behavior.