Co-Ideation Across Time: Revitalizing Legacy Design Sketchnotes with Conversational AI Agents to Foster Intergenerational Collaboration

While legacy sketchnotes capture rich design rationales and inspirations, they are rarely reused in contemporary practice. We present Co-Ideation Across Time (CIAT), utilizing Large Language Models (LLMs) to transform decades-old design sketchnotes into interactive "AI-augmented Knowledge Objects". Our system digitizes over 2,000 pages of alumni sketchnotes and connects them with conversational agents trained on corresponding theses and publications, enabling current and future students to engage in multimodal dialogue with past ideas and researchers. An exploratory evaluation with 12 participants showed that interacting with the system stimulated deeper understanding of abstract concepts, idea diversity, and fostered a stronger sense of continuity with the community’s legacy. Our contributions are threefold: (1) a method for integrating design legacies with LLM-driven conversational agents; (2) an empirical study demonstrating how this approach supports learning and intergenerational knowledge sharing; and (3) a conceptual framing of AI-Augmented Knowledge Objects as active participants in design ideation.