100 LLM agents running a simulated town economy for 26 weeks froze the money supply: 0.3% of prices ever changed, and memory deletion made no difference

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arXiv 2609.11108 ran 91 validated simulations of 100 memory-equipped agents on real Pokhara geography, totalling 2.44M decisions and 21.5B tokens. A 12x demand shock raised revenue 4.62x but moved wages only 1.03x, and a cash transfer was 96.7% unspent 311 pulses later. Swapping the backing LLM changed every measured outcome, while deleting agent memory changed none detectably. A purely social tool failed 94-97% of the time and agents kept calling it anyway. The takeaway for agent-society builders is that the base model, not the memory architecture, drives outcomes. The full run corpus is released.