Gradual Generation of User Interfaces as a Design Method for Malleable Software

2026-01-25

AI Summary

This work addresses the challenge that existing generative user interfaces (GenUIs) struggle to support effective discovery of diverse customization options while maintaining expressive power. To overcome this, the paper proposes a progressive GenUI approach that introduces a structured intermediate UI layer into the AI generation pipeline, incrementally exposing customization capabilities along specific dimensions and enabling users to backtrack through the generation process to explore and refine designs. By decomposing the interface generation into traceable, intermediate representations—a novel contribution—the method effectively balances system expressiveness with the discoverability of customization features. A prototype system implementing this approach integrates generative AI, interaction design, and hierarchical customization mechanisms. Evaluations across three case studies demonstrate its ability to significantly enhance users’ exploration of complex customization spaces while preserving visual simplicity, offering a new paradigm for malleable software design.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Natural Language Processing: Generation
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• User Modeling, Personalization and Recommendation: Explainable and interpretable methods for personalization
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

AI is growing increasingly capable of automatically generating user interfaces (GenUI) from user prompts. However, designing GenUI applications that enable users to discover diverse customizations while preserving GenUI's expressiveness remains challenging. Current design methods -- presenting prompt boxes and leveraging context -- lack affordances for customization discovery, while traditional menu-based approaches become overly complex given GenUI's vast customization space. We propose Gradually Generating User Interfaces -- a design method that structures customizations into intermediate UI layers that AI gradually loads during interface generation. These intermediate stages expose different customization features along specific dimensions, making them discoverable to users. Users can wind back the generation process to access customizations. We demonstrate this approach through three prototype websites, showing how designers can support GenUI's expanded customization capabilities while maintaining visual simplicity and discoverability. Our work offers a practical method for integrating customization features into GenUI applications, contributing an approach to designing malleable software.

Problem

• Generative User Interfaces
• Customization Discovery
• Malleable Software
• User Interface Design
• AI-generated UI

Innovation

• Gradual Generation
• User Interface Customization
• Generative UI
• Malleable Software
• Discoverability