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Abstract: In the fiercely competitive landscape of product-oriented operating systems, including the IOT, efficiently managing a substantial stream of real-time tasks, coexisting with resource-intensive user applications embedded in constrained hardware presents a significant challenge. Bridging the gap between embedded and general-purpose operating systems, we introduce XIRAC, an optimized operating system shaped by information theory principles. XIRAC leverages Shannon's Information Theorem to regulate processor workloads, minimize context switches, and preempt processes by maximizing system entropy tolerance. Unlike prior approaches that apply information theory to task priority alignment, the proposed method integrates maximum entropy into the core of the real-time operating system and scheduling algorithms. Subsequently, we optimized numerous system parameters by shifting and integrating commonly used unlimited tasks from the application layer to the kernel. This paper describes the many advantages ushered in by this paradigm shift, offering improved system performance, scalability, and adaptability. A new application-programming paradigm, termed ”object emulated programming” has emerged from this integration. Practical implementations of XIRAC in diverse products have revealed additional benefits, including an enhanced learning curve, elimination of library functions and threading dependencies, optimized chip capabilities, and increased competitiveness in product development. We provide a comprehensive explanation of these benefits and explore their impact through various real-world use cases and practical applications.