  As neural language models grow in effectiveness, they are increasingly being
applied in real-world settings. However these applications tend to be limited
in the modes of interaction they support. In this extended abstract, we propose
Wordcraft, an AI-assisted editor for story writing in which a writer and a
dialog system collaborate to write a story. Our novel interface uses few-shot
learning and the natural affordances of conversation to support a variety of
interactions. Our editor provides a sandbox for writers to probe the boundaries
of transformer-based language models and paves the way for future
human-in-the-loop training pipelines and novel evaluation methods.
