DesignManager: An Agent-Powered Copilot for Designers to Integrate AI Design Tools into Creative Workflows

工作流程 计算机科学 系统工程 人机交互 软件工程 工程类 数据库
作者
Weitao You,Yinyu Lu,Zhipeng Ma,Nan Li,Mingxu Zhou,Xue Zhao,Pei Chen,Lingyun Sun
出处
期刊:ACM Transactions on Graphics [Association for Computing Machinery]
卷期号:44 (4): 1-26
标识
DOI:10.1145/3730919
摘要

Creative design is an inherently complex and iterative process characterized by continuous exploration, evaluation, and refinement. While recent advances in generative AI have demonstrated remarkable potential in supporting specific design tasks, there remains a critical gap in understanding how these technologies can enhance the holistic design process rather than just isolated stages. This paper introduces DesignManager, a novel AI-powered design support system that aims to transform how designers collaborate with AI throughout their creative workflow. Through a formative study examining designers' current practices with generative AI, we identified key challenges and opportunities in integrating AI into the creative design process. Based on these insights, we developed DesignManager as an interactive copilot system that provides node-based visualization of design evolution, enabling designers to track, modify, and branch their design processes while maintaining meaningful dialogue-based collaboration. The system offers two collaboration modes: DesignManager-guiding and Designer-guiding. Designers can engage in conversational interactions with the DesignManager to obtain design inspiration and tool recommendations, and proactively advance the design progress. The system employs an agent framework to manage decoupled contextual information emerged during the design process, facilitating deep understanding of designers' needs and providing context-aware assistance. Our technical evaluation validated the effectiveness of context decoupling and the use of agent framework, while the open-ended user study with experts demonstrated that DesignManager successfully supports intuitive intention expression, flexible process control, and deeper creative articulation. This work contributes to the understanding of how AI can evolve from task-specific tools to collaborative partners in creative design processes.

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