  Conditional generative models such as DALL-E and Stable Diffusion generate
images based on a user-defined text, the prompt. Finding and refining prompts
that produce a desired image has become the art of prompt engineering.
Generative models do not provide a built-in retrieval model for a user's
information need expressed through prompts. In light of an extensive literature
review, we reframe prompt engineering for generative models as interactive
text-based retrieval on a novel kind of "infinite index". We apply these
insights for the first time in a case study on image generation for game design
with an expert. Finally, we envision how active learning may help to guide the
retrieval of generated images.
