All three stories are variations on the same underlying question: what happens when you consolidate AI infrastructure into fewer, faster, larger systems? The NBER paper gives you the theoretical answer (feedback loops corrupt at scale), the GEO piece gives you the market answer (consolidation creates exploitable fragility), and the Codex pricing move shows you the commercial logic that's driving consolidation anyway. The economics and the epistemics are pulling in opposite directions.