As conversations regarding AI in Architecture evolve, cultural representation remains a critical point of discussion. This course examines AI as a practical design tool that draws on indigenous spatial intelligence, including water-harvesting traditions such as South Asian stepwells, to generate new design logics, examined through the design of a cultural and community center where collecting water becomes a shared, identity-forming act.

The investigation develops datasets that inform new typologies, reanalyzing traditional water collection systems as vernacular precedents for addressing contemporary water scarcity in underserved communities. The cultural center reimagines these systems, including cisterns, catchment courtyards, and shaded thresholds, as architecture that convenes a community.

Applied methodologies include generative AI tools such as Stable Diffusion with ControlNet and Adobe Firefly, guided by spatial and modelling techniques such as Depth Map Reconstruction, Common Sense Machines, and Meshy, to translate historical data into spatial and environmental design logics. The study demonstrates that AI can produce culturally responsive, community-centered frameworks for socially informed futures. Participants will be able to describe how AI generates datasets from historical imagery and archival documentation to produce culturally grounded design frameworks.