Our team explored how semantic models, computational structures, and artificial intelligence can together form a reasoning pipeline that reads space not just as geometry, but as behavior, constraint, and opportunity. Grounded in real-world contexts but abstracted through spatial theory, we built a prototype AI system that reflects and tests our spatial hypothesis through simulation and inference. This work is both a technical experiment and a conceptual proposition for how AI might help designers observe, interpret, and intervene in complex spatial environments.