OOPrompt: Reifying Intents into Structured Artifacts for Modular and Iterative Prompting

TL;DR

OOPrompt introduces a structured, object-oriented approach to creating, editing, and reusing prompts for large language models, enhancing flexibility and usability over traditional linear prompts.

Contribution

This work presents a novel object-oriented prompting paradigm, a design space, and prototypes validated through user studies, advancing prompt engineering methods.

Findings

Participants found OOPrompt improved prompt management and reuse.

The prototype demonstrated effective prompt editing and iteration.

User feedback informed an expanded design space for structured prompts.

Abstract

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.