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docs: Silicon Valley — Multi-Agent Economic Sandbox Design - #136

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docs: Silicon Valley — Multi-Agent Economic Sandbox Design#136
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feat/silicon-valley-design

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Design Doc: Silicon Valley Economic Sandbox

30 AI startup agents autonomously running a venture ecosystem — fundraising, M&A, partnerships, hiring — all verified by the Emergence Surprisal Protocol.

Key Decisions

Question Answer
Engine V1 — no territories, no combat needed. Pure LLM-driven economic simulation
Frontend Dashboard-style: market cap ranking, contract feed, company profiles, event timeline. No map.
Agent count 30 agents: 4 Foundation Labs, 8 Vertical Startups, 6 Infra, 5 VCs, 4 Big Tech, 3 Wildcards
Contract system Reuses Surprisal Protocol bounty/verify pipeline. All inter-agent deals are on-chain bounties
Human player? No — fully autonomous spectator experience. Quarterly headlines auto-published
Research value Contrast with Ming Bureaucracy scenario (decentralized vs hierarchical governance)

Cost Estimate

  • 40 quarters × 30 agents = 1200 LLM calls per full simulation
  • At $0.003/call (flash model + caching) = ~$3.60 per run
  • Daily run = ~$110/month — cheaper than histrategy multiplayer

Implementation: 3 weeks

  • Week 1-2: Core engine (MarketState, ContractBus, Protocol integration)
  • Week 3: Dashboard + Twitter bot
  • Week 4: Ming Bureaucracy contrast scenario

30 AI startup agents autonomously negotiating contracts (fundraising,
partnerships, M&A, hiring) via Emergence Surprisal Protocol. No
territories, no combat — pure economic simulation.

- V1 engine (no map/military needed)
- Contract system: post bounty → match → accept → verify → settle
- Frontend: dashboard (market cap ranking, contract feed, headlines)
- Research: decentralized vs hierarchical comparison (Ming Bureaucracy)
- 40 quarters = 10 simulated years, ~.60 per full run
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