mlsanityData to 7 Oct 2026

PromptInfuser: How Tightly Coupling AI and UI Design Impacts Designers' Workflows

arXiv 2310.15435 ↗First posted 24 Oct 2023cs.HC cs.AIcited by 8

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Abstract (arXiv)

Prototyping AI applications is notoriously difficult. While large language model (LLM) prompting has dramatically lowered the barriers to AI prototyping, designers are still prototyping AI functionality and UI separately. We investigate how coupling prompt and UI design affects designers' workflows. Grounding this research, we developed PromptInfuser, a Figma plugin that enables users to create semi-functional mockups, by connecting UI elements to the inputs and outputs of prompts. In a study with 14 designers, we compare PromptInfuser to designers' current AI-prototyping workflow. PromptInfuser was perceived to be significantly more useful for communicating product ideas, more capable of producing prototypes that realistically represent the envisioned artifact, more efficient for prototyping, and more helpful for anticipating UI issues and technical constraints. PromptInfuser encouraged iteration over prompt and UI together, which helped designers identify UI and prompt incompatibilities and reflect upon their total solution. Together, these findings inform future systems for prototyping AI applications.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 13 of its 56 references that are in the map. First posted on arXiv 24 Oct 2023.

Builds on

13 of 56 references.

References · 13

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  3. 2022Social Simulacra: Creating Populated Prototypes for Social Computing Systemscited by 300
  4. 2021AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptscited by 265
  5. 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 216
  6. 2022PromptChainer: Chaining Large Language Model Prompts through Visual Programmingcited by 134
  7. 2021Sparks: Inspiration for Science Writing using Language Modelscited by 80
  8. 2022Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Modelscited by 70
  9. 2022Opal: Multimodal Image Generation for News Illustrationcited by 36
  10. 2021PopBlends: Strategies for Conceptual Blending with Large Language Modelscited by 22
  11. 2023ScatterShot: Interactive In-context Example Curation for Text Transformationcited by 20
  12. 2023Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experiencecited by 18
1 more
  1. 2023fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Taskscited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 2.

8 papers.