# From Prompts to Worlds: How Users Iterate, Explore, and Make Sense of AI-Generated 3D Environments

arXiv: https://arxiv.org/abs/2603.13233 · HTML: https://mlsanity.com/paper/2603.13233/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 25 references that are in the map.
- First posted on arXiv 24 Jan 2026.

## Builds on (most cited first, 7 of 7)

- [Design Guidelines for Prompt Engineering Text-to-Image Generative Models](https://mlsanity.com/paper/2109.06977/) (2021)
- [Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy](https://mlsanity.com/paper/2002.04087/) (2020)
- [Design Principles for Generative AI Applications](https://mlsanity.com/paper/2401.14484/) (2024)
- [3DALL-E: Integrating Text-to-Image AI in 3D Design Workflows](https://mlsanity.com/paper/2210.11603/) (2022)
- [WorldGen: From Text to Traversable and Interactive 3D Worlds](https://mlsanity.com/paper/2511.16825/) (2025)
- [Text-to-3D Gaussian Splatting with Physics-Grounded Motion Generation](https://mlsanity.com/paper/2412.05560/) (2024)
- [Generative AI and Creative Work: Narratives, Values, and Impacts](https://mlsanity.com/paper/2502.03940/) (2025)

## Abstract (arXiv)

Text-to-3D generative AI systems create navigable environments from natural language prompts, but unlike text-to-image generation, evaluation requires embodied exploration of spatial coherence, scale, and navigability. We present the first empirical study of a commercial text-to-3D platform, combining think-aloud protocols, behavioral observation, and validated measures of usability, presence, and engagement. We report three findings. First, asymmetric expressibility: users readily convey semantic intent (themes, atmosphere) but struggle to specify spatial structure (layout, scale), reflecting a language-to-space limitation rather than a skill deficit. Second, episodic presence: immersion arises when expectations align with outputs but does not accumulate into sustained place illusion. Third, structural iteration breakdowns: refinement fails due to interaction barriers - poor discoverability, opaque feedback, and high temporal costs - rather than user limitations. Together, these dynamics form a reinforcing cycle in which spatial mismatches persist, producing episodic presence and ongoing sensemaking. We reframe text-to-3D interaction as negotiated meaning-making rather than linear prompting, and argue that effective systems require hybrid input modalities, transparent feedback, and low-cost iteration.