  Recent advances in Machine-Learning have led to the development of models
that generate images based on a text description.Such large prompt-based text
to image models (TTIs), trained on a considerable amount of data, allow the
creation of high-quality images by users with no graphics or design training.
This paper examines the role such TTI models can playin collaborative,
goal-oriented design. Through a within-subjects study with 14 non-professional
designers, we find that such models can help participants explore a design
space rapidly and allow for fluid collaboration. We also find that text inputs
to such models ("prompts") act as reflective design material, facilitating
exploration, iteration, and reflection in pair design. This work contributes to
the future of collaborative design supported by generative AI by providing an
account of how text-to-image models influence the design process and the social
dynamics around design and suggesting implications for tool design
