This paper proposes a protocol-level framework for understanding how thought, cognition, and conceptual struc-tures influence value formation, credibility, and allocation within AI-mediated economic systems without passingthrough exchange or monetization. Positioned as a second-layer (market and economic OS) extension of the AI-Scored Society, AIO, and AI Capitalism frameworks, this study examines how evaluative AI systems pre-select,structure, and redistribute social and economic relevance prior to market interaction.Rather than treating thought as an ideological, ethical, or motivational construct, the paper conceptualizes it as avalue-bearing entity whose effects emerge through structural visibility, reuse, and systemic compatibility within AIevaluation environments. Under conditions of simultaneous state observability, credibility is no longer grounded inbelief, legitimacy, or persuasion, but in sustained operational usability across contexts. As a result, thought acquiresasset-like properties not through ownership or liquidity, but through persistence, indexability, and integration intodownstream outputs.The paper introduces the notion of a thought-currency not as a designed instrument, but as an emergent phe-nomenon arising from AI-driven selection and allocation mechanisms. Through a series of thought experiments,it delineates the conditions under which ideas are accumulated, depreciated, or excluded, and identifies key designconstraints and risks associated with over-definition and excessive quantification.By reframing value formation as allocation without exchange, this work contributes a protocol-level interpre-tation of how markets, organizations, and credibility systems are being reconfigured in AI-mediated environments,and establishes a conceptual bridge toward subsequent analyses of asset scarcity, digital reserves, and institutionalimplementation.
Kawazoe Tsutomu (Sun,) studied this question.