The Central Dogma has provided a foundational framework for biological information flow, yet it does not fully explain how living systems preserve stable identity, functional robustness, and recoverability under continuous molecular noise and environmental perturbation. Here, I propose the Central Homeostatic Principle (CHP) as a complementary first-principle framework that shifts the explanatory center from information execution alone to the physical constraint architecture that makes biological execution possible. The CHP posits that, in living cells, a central homeostatic state functions as a system-level coordinating layer that defines the feasible state space within which genetic and biochemical programs can operate.This framework is motivated by convergent evidence across mechanical confinement, electrophysiological coupling, membrane contact-site transduction, phase-state regulation, and non-genetic phenotypic heterogeneity, all of which indicate that global physical states can gate, reshape, or buffer molecular outcomes. Building from systemic prerequisites and material constraints, I further argue through an exclusionary first-principle analysis that lipid-organized boundary systems occupy a near-irreplaceable physical position in implementing this central homeostatic constraint in aqueous cellular life-not as exclusive causal authors, but as the dominant substrate of feasibility control.To render the theory scientifically actionable, this manuscript provides a formal articulation of CHP, a three-tier realization model, operational corollaries, and a rule typology that distinguishes stronger and weaker forms. It then derives a set of falsifiable hypotheses spanning temporal commitment dynamics, non-genetic resistance, aging-related resilience loss, state-engineering-based reprogramming, and evolutionary primacy in prebiotic systems. By reframing life as a problem of constrained state maintainability rather than information flow alone, the CHP offers a testable theoretical scaffold for integrating molecular biology, biophysics, systems biology, and translational state engineering.