Prompting for Discovery: Flexible Sense-Making for AI Art-Making with DreamSheets

Design space exploration (DSE) for Text-to-Image (TTI) models entails navigating a vast, opaque space of possible image outputs, through a commensurately vast input space of hyperparameters and prompt text. Perceptually small movements in prompt-space can surface unexpectedly disparate images. How can interfaces support end-users in reliably steering prompt-space explorations towards interesting results? Our design probe, DreamSheets, supports user-composed exploration strategies with LLM-assisted prompt construction and large-scale simultaneous display of generated results, hosted in a spreadsheet interface. Two studies, a preliminary lab study and an extended two-week study where five expert artists developed custom TTI sheet-systems, reveal various strategies for targeted TTI design space exploration-such as using templated text generation to define and layer semantic "axes" for exploration. We identified patterns in exploratory structures across our participants' sheet-systems: configurable exploration "units" that we distill into a UI mockup, and generalizable UI components to guide future interfaces.