AI Multi-Agent System Completes Urban Flood Research Paper from Scratch

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A researcher acting as Principal Investigator used a custom AI framework called tanaike-lab, powered by Google Gemini on the Antigravity CLI, to conduct and publish a full scientific study on urban torrential rain fluid dynamics. The resulting paper, focused on using citizen-science sensor networks for high-resolution rain prediction, was published on ESS Open Archive. The tanaike-lab system coordinates 22 AI subagents alongside tools like Model Context Protocol and Agent-to-Agent protocols to handle tasks such as numerical modeling, data processing, and manuscript drafting. The project was designed to address a core bottleneck in modern research: the operational overhead that slows down scientific output, without resorting to generic AI-generated content. The creator plans to open-source the framework once it reaches full maturity, with the goal of making virtual R&D labs accessible to the broader research community.

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