QuerySwitch: Supporting the Design Process by Balancing Vagueness through Large Language Models

Abstract

Designers often regard vagueness as an essential aspect of creative work, as it fosters diverse interpretations and helps prevent fixation. Although large language models (LLMs) are increasingly viewed as a promising creative partner, designers struggle to productively incorporate vagueness into AI-supported workflows. To address this challenge, we present QuerySwitch, an interactive prototype that enables fashion designers to manage vagueness by flexibly switching between two distinct query-output modes. Findings from a user study show that QuerySwitch helps fashion designers balance vagueness, enhances the usability of LLMs in design tasks, and promotes creative exploration. This work contributes to HCI by (1) foregrounding a critical construct in human–AI collaboration, (2) demonstrating how interaction mechanisms can scaffold designer agency in LLMs use, and (3) articulating design principles—structuring exploration and preserving key query formulations—that extend to creativity-driven domains.