This paper proposes a foundational model in which tension is treated as the primaryprimitive underlying physical, informational, and computational structure. Themodel assumes a finite capacity for memory and local state updates, from whichform, time, and causality emerge as secondary effects. Unlike prevailing frameworksthat rely on continuous global states or infinite precision, this approach constrainsall evolution to discrete, local interactions governed by informational cost.In this framework, time is not a fundamental dimension but the result of irreversiblestate transitions under memory limitation. Space arises as relational structurewithin a graph of interacting states. Particles and fields are stable or quasi-stableconfigurations of tension gradients, maintained through constrained update rules.Observation corresponds to selective state coupling rather than externalmeasurement.The theory aims to reconcile elements of physics and computation by modelingreality as a locally updating system with bounded memory, avoiding the need forglobal wave functions, continuous manifolds, or observer-dependent collapse. Itprovides a basis for simulation-first physics, where predictions are derived fromexecutable rules rather than closed-form solutions.The paper outlines core postulates, formal definitions, and a minimal state-transition model, then demonstrates how known physical phenomena can emergefrom these constraints. Finally, it identifies testable predictions and open problems,positioning the theory as a candidate framework for unifying physical law withinformation-theoretic limits.