The development of IDN authoring tools remains fragmented, with no shared standard for terminology, structure, or workflow. An answer to this problem might be an open, community-centered AI-supported authoring environment that adapts to an author’s intentions, skills, and knowledge. This study uses a Research through Design approach to explore how authors perceive and engage with such a model. We conducted user research and developed a prototype not as a functional interface but as a probe to provoke reflection and capture insights into the values, needs, and challenges of the authors. Findings highlight enthusiasm for structural support features like knowledge graphs and moodboards but also reveal resistance to AI as a creative collaborator and confusion around theoretically grounded language. These results underscore the critical tensions between system adaptability and authoring practice.