  Generative AI models are increasingly powering software applications,
offering the capability to produce expressive content across varied contexts.
However, unlike previous iterations of human-AI design, the emerging design
process for generative capabilities primarily hinges on prompt engineering
strategies. Given this fundamental shift in approach, our work aims to
understand how collaborative software teams set up and apply design guidelines
and values, iteratively prototype prompts, and evaluate prompts to achieve
desired outcomes. We conducted design studies with 39 industry professionals,
including designers, software engineers, and product managers. Our findings
reveal a content-centric prototyping approach in which teams begin with the
content they want to generate, then identify specific attributes, constraints,
and values, and explore methods to give users the ability to influence and
interact with those attributes. Based on associated challenges, such as the
lack of model interpretability and overfitting the design to examples, we
outline considerations for generative AI prototyping.
