A formal decomposition of enterprise data architecture for AI. We reduce operational data to ontological primitives and show that AI readiness is a function of coherence: how far the enterprise has standardized its own ontological representations.
Most enterprise AI wins and failures come down to one question: did it reduce entropy, or add it? LLMs are good compressors and bad expanders.
'The knowledge needed for a rational economic order never exists in concentrated form but solely as the dispersed bits of incomplete and frequently contradictory knowledge which all the separate individuals possess.' — F.A. Hayek
Our attention is stolen in pennies, by notifications and emails and feeds, until our entire fortune is gone. What I want from AI is a bouncer: something that keeps the riffraff out so I can focus on what matters.
'Value is not intrinsic; it is not in things. It is within us; it is the way in which man reacts to the conditions of his environment.' — Ludwig von Mises
'We shape our tools, and thereafter they shape us' — Marshall McLuhan