  The emergence of Generative AI is catalyzing a paradigm shift in user
interfaces from command-based to intent-based outcome specification. In this
paper, we explore abstract-to-detailed task transitions in the context of
frontend code generation as a step towards intent-based user interfaces, aiming
to bridge the gap between abstract user intentions and concrete
implementations. We introduce Frontend Diffusion, an end-to-end LLM-powered
tool that generates high-quality websites from user sketches. The system
employs a three-stage task transition process: sketching, writing, and coding.
We demonstrate the potential of task transitions to reduce human intervention
and communication costs in complex tasks. Our work also opens avenues for
exploring similar approaches in other domains, potentially extending to more
complex, interdependent tasks such as video production.
