In client-AI expert collaborations, the planning stage of AI application development begins from the client; a client outlines their needs and expectations while assessing available resources (pre-collaboration planning). Despite the importance of pre-collaboration plans for discussions with AI experts for iteration and development, the client often fails to reflect their needs and expectations into a concrete actionable plan. To facilitate pre-collaboration planning, we introduce PlanTogether, a system that generates tailored client support using large language models and a Planning Information Graph, whose nodes and edges represent information in the plan and the information dependencies. Using the graph, the system links and presents information that guides client's reasoning; it provides tips and suggestions based on relevant information and displays an overview to help understand the progression through the plan. A user study validates the effectiveness of PlanTogether in helping clients navigate information dependencies and write actionable plans reflecting their domain expertise.
https://dl.acm.org/doi/10.1145/3706598.3714044
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)