The Thermodynamics of Temporal Endurance: Why "Built to Last" Wasn't Built to Endure

This working dissertation preprint advances Knowledge Thermodynamics as a formal planning science for understanding organizational survival, decline, and collapse in the AI era. It challenges the foundational assumption popularized by Built to Last (Collins & Porras, 1994): that organizations achieve enduring excellence by discovering and preserving stable core principles. Through a thermodynamic analysis of recursive meaning systems, the paper demonstrates that organizational endurance is not cultural or normative, but temporal and governed by lawful constraints on semantic stability, correction capacity, and recursion velocity. Re-examining the original Built to Last companies reveals a consistent pattern: founding at peak semantic integrity, entropy accumulation through growth, transition across critical velocity thresholds, and eventual collapse when semantic degradation outpaces corrective capacity. The work introduces collapse velocity (Vᴄ) as the governing variable of organizational survivability and reframes success from permanence to temporal endurance—the ability to manage semantic degradation slowly enough to accomplish meaningful objectives before thermodynamic dissolution. Drawing on six prior empirical studies, the paper formalizes four axioms of semantic systems and five original mathematical constructs within the Katzian Thermodynamic Model of Meaning (KTMM). Rather than treating failure as managerial error or cultural deviation, the paper establishes organizational collapse as a predictable outcome of operating beyond thermodynamic limits—limits that accelerate sharply under AI-mediated decision recursion. It proposes velocity-aware governance as an alternative paradigm, integrating strategic planning, scientific assessment, and operational oversight to manage entropy, drift, and interpretive capacity across organizational scales. This preprint positions temporal endurance—not permanence—as the upper bound of organizational achievement, with particular urgency for AI-augmented institutions where recursion rates compress organizational lifespans and render principle-based frameworks insufficient. Keywords Knowledge Thermodynamics; organizational theory; semantic entropy; collapse velocity; recursive systems; AI governance; planning science; institutional endurance