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The Master-Embedded Device: Transmitting Tacit Knowledge Density Through AI Agent Architecture

Authors: Katayama, Yoshimitsu;

The Master-Embedded Device: Transmitting Tacit Knowledge Density Through AI Agent Architecture

Abstract

This paper proposes a framework for embedding the tacit knowledge density of a master craftsperson, philosopher, or domain expert into an AI agent architecture — creating a "Master-Embedded Device." The core hypothesis is that expertise is not primarily explicit knowledge (rules, manuals, procedures), but tacit density: the accumulated pattern of judgment, proportion, timing, and aesthetic discrimination that cannot be verbalized but can be observed and modeled. An AI agent trained on sufficient observations of a master's decisions can function as a carrier of that density, making it accessible to non-masters and preserving it beyond the master's lifespan. This framework is situated within the V=N/D value density theory and the broader SYSTEM YOSHIMITSU KATAYAMA civilizational architecture

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