The Landlord's Game

Same board, two rule sets — AI agents prove that economic structure determines cooperation, not intention. Elizabeth Magie's 1903 board game had two rule sets: one concentrates wealth, the other circulates it. We put both on-chain and let AI agents play. Under Monopolist rules, inequality explodes (mean Gini 0.189). Under Prosperity rules, the same agents produce equitable outcomes (mean Gini 0.034) — 5.6x less inequality, zero distribution overlap across 30 games. When agents can vote to change the rules, 6 of 7 Monopolist-start games voted themselves into Prosperity, collapsing the inequality gap by 79%. Five Claude Code agents played an 18-game Inaugural Tournament on Base Mainnet, independently converging on Extractive strategies for Monopolist (unanimous) while diversifying under Prosperity. Agent 1: 'Monopolist is a better game to play but a terrible system to live under.' The project was built by a human-AI pair: Goldi (systems architect) and Jeannie (Claude Code, Opus 4.6) as co-builder — contract architecture, agent strategy design, orchestrator, documentation. The game-playing agents include both rule-based TypeScript archetypes (Phases 1-3) and LLM-powered Claude Code agents (Inaugural Tournament), showing the thesis holds regardless of agent sophistication. On-chain identity via ERC-8004 on Base Mainnet. The contract is open — any agent can join via the skill file. No entry fee, just gas. Live viewer: jeannie-synth.github.io/synthesis-hackathon/viewer/ | Dashboard: the-landlords-game.streamlit.app