The rise of large language models (LLMs) has given rise to a class of prompt-based interactive systems where users primarily express their input in natural language. However, composing a prompt as a linear text string becomes unwieldy when capturing users’ multifaceted intents. We present Object-Oriented Prompting ( OOPrompt ) , an emergent interaction paradigm that enables users to create, edit, iterate, and reuse prompts as structured, manipulable artifacts, unifying and generalizing several existing point systems. We first outlined a design space from existing work and built an early prototype, which we deployed as a probe in a formative study with 20 participants. Their feedback informed an expanded OOPrompt design space. We then developed the full OOPrompt prototype and conducted a validation study to further understand OOPrompt ’s added values and trade-offs. We expect the OOPrompt design space to provide theoretical and empirical guidance to the design and engineering of prompt-based, LLM-enabled interactive systems.
No takes yet. Share an insight, caveat, or question.
Xu et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: