# Design Generative AI for Practitioners: Exploring Interaction Approaches Aligned with Creative Practice

arXiv: https://arxiv.org/abs/2603.03074 · HTML: https://mlsanity.com/paper/2603.03074/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 22 references that are in the map.
- First posted on arXiv 3 Mar 2026.

## Builds on (most cited first, 8 of 8)

- [CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AI](https://mlsanity.com/paper/2312.11949/) (2023)
- [MagicQuill: An Intelligent Interactive Image Editing System](https://mlsanity.com/paper/2411.09703/) (2024)
- [GANSlider: How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Information](https://mlsanity.com/paper/2202.00965/) (2022)
- [Inkspire: Supporting Design Exploration with Generative AI through Analogical Sketching](https://mlsanity.com/paper/2501.18588/) (2025)
- [Demystifying Tacit Knowledge in Graphic Design: Characteristics, Instances, Approaches, and Guidelines](https://mlsanity.com/paper/2403.06252/) (2024)
- [Block and Detail: Scaffolding Sketch-to-Image Generation](https://mlsanity.com/paper/2402.18116/) (2024)
- [DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Design](https://mlsanity.com/paper/2502.09867/) (2025)
- [How Interaction Designers Use Tools to Manage Ideas](https://mlsanity.com/paper/2002.08139/) (2020)

## Abstract (arXiv)

Design is a non-linear, reflective process in which practitioners engage with visual, semantic, and other expressive materials to explore, iterate, and refine ideas. As Generative AI (GenAI) becomes integrated into professional design practice, traditional interaction approaches focusing on prompts or whole-image manipulation can misalign AI output with designers' intent, forcing visual thinkers into verbal reasoning or post-hoc adjustments. We present three interaction approaches from DesignPrompt, FusAIn, and DesignTrace that distribute control across intent, input, and process, enabling designers to guide AI alignment at different stages of interaction. We further argue that alignment is a dynamic negotiation, with AI adopting proactive or reactive roles according to designers' instrumental and inspirational needs and the creative stage.