Generative artificial intelligence is increasingly embedded in architectural practice and education, yet its role often remains confined to image production or optimization tasks. This study situates generative AI within a broader design ecology. It examines how structured human–AI interaction can support environmentally oriented architectural thinking in design education. The article presents an international design workshop as a research setting in which architecture students engaged with AI through a multi-agent workflow. This workflow combined large language models, diffusion-based image generation, 2D–3D translation tools, parametric modeling, and clay-based 3D printing. Central to the methodology is the concept of prompt choreographies. These are deliberate dialogs between human and AI agents, based on a language of prompts and AI-generated outcomes. Through this process, the design concept moves toward a final architectural proposal. The workshop addressed complex ecological challenges emerging from interactions among Earth’s spheres. These were conceived as environmental interfaces defined by behavioral continuity rather than typological form. Using qualitative, design-based evaluation criteria focused on environmental, spatial, and material aspects, the study identifies recurring patterns of human–AI collaboration. The findings indicate that generative AI supports architectural ideation most effectively when embedded in structured workflows that emphasize curatorial decision-making and reduce generative overproduction. While limited to a workshop-based educational context, the research offers transferable methodological insights for architectural pedagogy and conceptual practice. It proposes a process-oriented framework for designing with generative AI and outlines an emerging form of architectural literacy and multi-agent collaboration that warrants further empirical validation.
Uhrík et al. (Wed,) studied this question.