In the current architectural imagination, “Geospatial Intelligence” has become the mot du jour–a term often deployed by emerging tech platforms to describe the transformative power of Large Language Models (LLMs) and their world-building generative capabilities. Yet, for designers, the intelligence of space is an age-old inquiry. Every era is marked by the aesthetic and spatial trace of its tools; if the LLM is our tool du jour, this course interrogates the specific architectural trace it leaves behind.

This class will move through three modules that introduce students to a suite of tools for AI-enabled spatial production, investigate spatial glitches as a design site, and revisit the foundational texts and design practices that predate neural networks but confront the same core concepts.

The final deliverable for the semester will be a collective contribution to a volume–a manual of experiments, drawings, and texts that seek to provide rigorous, designer-led definitions of and positions on Geospatial Intelligence.