
What happened
A human CEO split work among five AI agents (Protocol, Preflight, Infra, Security, Growth) via GitHub Issues and Codex, producing a local MVP whose integration run passed 52 tests with 0 failed and 0 skipped.
Why it matters
The approach suggests that separating responsibilities and enforcing interfaces — rather than relying on one all-capable AI — may be a workable way to ship software, though mainnet settlement and real-money charging have not been tested, so production readiness remains unproven.
Summaries like this, every morning.
The experiment deliberately set a narrow business goal: earn the first dollar from a third-party user within seven days, excluding self-payments. From 20 Web3 business ideas, the team selected a Transaction Preflight API based on implementation feasibility, distance to first revenue, on-chain necessity, and differentiation. The architecture reflects a software organization rather than a single chatbot: a human CEO sets direction and holds final approval for production deploys and fund movements, ChatGPT handles market research and spec work, GitHub Issues become units of work, and five Codex workers execute in parallel branches and pull requests. A shared AGENTS.md file defines common KPIs, prohibitions, interfaces, and PR rules. The Security agent reviewed from an attacker's perspective independently of the implementers, surfacing issues that a purely generative workflow might miss. The integration test result of 52 passed is a local-fixture milestone, not a production green light; real-money billing and mainnet settlement have not been exercised. The next phase focuses on fixing production blockers, settling billing semantics, and running testnet payments before any human-approved mainnet release.
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