Original document
GPT Image 2 · en
Scene:
Design a square near-future living environment study that feels immediately usable as a brand-inspiration image or speculative editorial visual. The scene should show one complete routine surface, not just decorative furniture styling. Compose a bright shared laundry lounge with folding counters, seating niches, clean storage walls, and quietly automated machines integrated into one room.
Subject:
Focus on a believable room or shared domestic node where human habits, object placement, and light all imply how the space is used every day. Technology should feel embedded in materials, fixtures, and workflows instead of floating as abstract holograms. The space should feel used by neighbors and families, not merely styled, with clear workflows for washing, sorting, waiting, and light social interaction.
Important details:
Keep the design humane, tactile, and slightly imperfect so it reads as lived-in. Surfaces, storage, and appliance behavior should all support a credible near-future domestic routine. Show how good lighting, acoustics, and materials can turn a utility room into a credible community amenity. Preserve habitual realism in object placement, cleaning, storage, and circulation so every room feels actually inhabited.
Use case:
Future Domestic single study 1/5, designed as a self-contained support image for this topic.
Constraints:
No readable text, no watermark, no logos, preserve exact 1:1 aspect ratio, no generic smart-home wallpaper, no unrealistic levitating furniture, no fashion-shoot posing, no readable packaging copy, no luxury spa cues.How to use
- Copy the complete original prompt, including any parameters.
- Replace the subject, text and composition with your own requirements.
- Use a compatible external tool; check its current access conditions and review the result.
Before you start
- Check whether a reference image is required. A compatible model label does not mean this example was generated with that model.
- Keep names, figures and visible text accurate; results can vary between model versions.
