Competition Use-Case: AI Rendering for Early Architectural Design

Q: What prompts work best for early-stage architectural AI rendering?

Start broad and directional—for example: "rainy mood, Yakushima vegetation, keep the architecture as-is." As design decisions solidify, make prompts more specific: "water droplets on glass roof, warm interior light, dead leaves on terrace." RenderAI reaches its full potential when prompts reflect a clear creative intent.

AI , Rendering , Use Cases
Agustin
27 Feb, 2026

Competition Use-Case: AI Rendering for Early Architectural Design

In this post, I want to share my personal experience using RenderAI throughout the entire design process for an architecture competition—from the very first sketches to the final submission renders.

RenderAI was part of the workflow from week one and accompanied me all the way to the final images included in the deliverables. As an architect, designer, and 3D artist, I’m used to working with traditional modeling and rendering tools, and I feel comfortable handling them with professional fluency. However, in this particular competition I faced a very common situation: tight deadlines, overlapping projects, and the need to make fast decisions without sacrificing design quality. That’s when I decided to explore RenderAI.

From the start, I understood this wasn’t just a visualization tool—it was a real support for the creative process. My goal was to shorten architectural exploration time while expanding the range of possibilities: from form and site placement to materials, details, and the overall atmosphere of the project. Very quickly I confirmed that RenderAI could enhance both early-stage design explorations and final image quality, even when combined with photorealistic rendering workflows.

The experience I describe here is based on the design of a house for a competition in Japan, where I used different real-time and AI visualization tools from the beginning as an active part of the design workflow. The project was highlighted as Best 30 Finalist among 1058 submissions from 112 countries.

Table of Contents

Challenges of Early-Stage Architectural Ideation
From Simple Renders to AI-Enhanced Images
Materiality and Textures as Part of the Design Process
Mood and Visual Language from Day One
Conclusion: AI Rendering as a Design Thinking Tool
Frequently Asked Questions
References

Challenges of Early-Stage Architectural Ideation

In a traditional design process, early stages present a series of recurring challenges. In this project, I can summarize them as follows—and analyze how RenderAI helped me address each one.

Placing the Project in Context

Inserting a project into its real-world context isn’t always possible during early stages—either due to lack of information or the time required to model the surrounding environment in 3D. Even when the necessary data is available, integrating context meaningfully can be extremely time-consuming. This becomes even more critical when the context is a defining factor from the very beginning, as in this project, where the Yakushima forest was a central element of both the analysis and the architectural proposal.

High-Precision Post-Production with Render AI to place the project in context

High-Precision Post-Production with Render AI to add ambience and people in seconds

Exploring Mood and Atmosphere

Decisions related to mood are often postponed to the late stages of a competition. This limits the early interaction between architecture, materiality, and context, and frequently leads to underdeveloped images or processes that never reach the depth they deserve.

Two AI rendering mood explorations of the Yakushima house competition project using RenderAI

Real-time rendering base view of Yakushima house exterior used as input for RenderAI mood exploration

RenderAI output of the Yakushima house exterior with rainy forest mood and warm interior light

High-Quality image post-production using RenderAI, the Yakushima forest mood, exploration 1

High-Quality image post-production using RenderAI, the Yakushima forest mood, exploration 2

High-Quality image post-production using RenderAI, the Yakushima forest mood, exploration 3

Rapid Material and Texture Exploration

Exploring materials, placing the project in its specific context, working with the right vegetation, and testing different moods can require many hours of work. In a competition setting, finding the balance between design, representation, and the rest of the submission is complex. Traditional rendering workflows amplify this problem: materials require maps, adjustments, and constant testing, and it’s not uncommon that after achieving a good result in one view, changing the camera angle means practically starting over.

AI rendering exploration of roof textures and finishes for the Yakushima house competition

Natural and Artificial Lighting

Another common challenge is being able to quickly evaluate a project under different lighting conditions: various times of day, natural and artificial light, and their interaction within a specific context that often isn’t even fully modeled in 3D.

In short, addressing all these challenges through traditional methods requires significant time and creates a heavy additional workload—while the project must also advance on its technical and conceptual fronts.

Natural and Artificial Lighting Exploration using AI Rendering, two examples

Natural and artificial lighting comparison for the Not a Hotel house: daytime vs interior-lit evening using RenderAI

Natural and artificial lighting comparison for the Not a Hotel house: rainy day vs regular daytime using RenderAI

From Simple Renders to AI-Enhanced Images

In my case, the creative process was structured from the start around modeling and real-time rendering tools, deliberately avoiding photorealism in the early stages due to time and resource constraints.

Unlike more realistic programs that require a larger time investment, this type of workflow provides quick access to key information:

Point of view and camera composition
General material intent and color direction
Solar lighting and orientation
Furniture and human scale reference

Even though I’m accustomed to working with highly realistic images from early stages, I confirmed that simple images generated in tools like Enscape or D5 Render already provide enough information for solid design conclusions. From these base images—simple but loaded with conscious decisions—I began working with RenderAI, exploring different options and engines.

The method that helped me most at this stage was Creative–Editor.

Workflow for Early-Stage Exterior Images

Method: Creative–Editor
Style Enhance: Realistic
Description approach: Initially, descriptions were mostly ambiguous—for example: “Make the stone more realistic, rainy mood, add people, keep the architecture as-is.” As the design progressed and the exploration margin narrowed due to decision-making, prompts became more precise: “Add dead leaves on the glass roof, water droplets after rain, use Yakushima vegetation, create a rainy mood with warm interior light.”

Beyond the tool itself, what proved essential at this stage was having a clear composition in mind and a precise vision of where I wanted to guide the exploration. RenderAI reaches its full potential when used consciously and with clear architectural intent.

During this process, I explored materials on the project’s surfaces, different finishes and appearances—variations in rock texture, reflections, roughness, and stone types—without needing to commit the project too early.

High-Precision Post-Production with RenderAI to explore materials and textures, before and after example

High-Precision Post-Production with RenderAI to explore materials and textures, winter snow mood presentation ready AI Rendering

Exploring Creative-Quality AI method with Realistic Style Enhance on the Not a Hotel house

Final mood AI rendering example created with RenderAI, using Creative-Quality AI method with Realistic Style Enhance

Materiality and Textures as Part of the Design Process

With RenderAI, material explorations don’t have to wait until the final stage of the creative process.

One of the biggest advantages of this approach was being able to work on volumetry, space, and textures simultaneously. Massing studies were directly informed by material explorations: the veining of the rock, the tones, and the surfaces evolved at the same time as the architectural form.

Real-time design tools offer fast results but often with limited expressive character and realism. In this case, I used those quick images as a base to define viewpoints, basic furniture, and initial decisions, then turned to RenderAI to explore new material possibilities with a level of realism that would have otherwise required several days of work.

Material Exploration Workflow

Method: Creative–Editor
Style Enhance: Realistic
Description approach: Descriptions focused on defining the material along with its spirit—for example: “Make the rock like the one found in Yakushima forests, use the same granite.” At the same time, I would ask the geometry to adopt more natural forms inspired by the site’s context, softening the architecture to make it more coherent with the environment.

Another key advantage of using RenderAI in early stages is that material explorations happen directly within the real context where they will be implemented. In this project, the island of Yakushima has a rainy climate, and it was essential for me to visualize materials under those conditions: the light, reflections, water, and forest.

I also explored how materials reacted to different lighting conditions and the presence of water, introducing interior lights to understand their behavior in various environments.

This preliminary work was extremely helpful in anticipating the final submission images, allowing me to envision from the very start what I wanted to show and how to refine it over time.

AI rendering exploration of stone flooring materials and surface finishes for the Yakushima house interior

Final AI rendering of the Yakushima house applying material and texture decisions from early explorations

Mood and Visual Language from Day One

From the beginning, mood and visual language stopped being a late consequence of the project and became an active design tool. RenderAI allowed me to test atmospheres, climates, and emotions without closing decisions too early, keeping the process open and flexible.

Rather than “locking in” the design, these explorations helped keep ideas alive, allowing me to iterate, adjust, and refine both the architecture and its representation simultaneously.

More than a rendering tool, RenderAI became a medium for thinking about the project, understanding its relationship with the context, and building a coherent visual language from the earliest stages of design. I especially value having been able to work with the complexity of the context in a fluid and precise way from day one.

Mood board showing different atmospheric variations of the same Yakushima house: Rainy and misty moods AI Rendering

Mood board showing different atmospheric variations of the same Yakushima house: Snow AI Rendering

Conclusion: AI Rendering as a Design Thinking Tool

Using RenderAI from the earliest stages of design significantly changed how I approached the creative process in a competition context. More than accelerating image production, the tool allowed me to integrate decisions about context, materiality, light, and atmosphere from the very beginning—preventing these aspects from being relegated to a rushed final phase.

This approach didn’t just reduce time and friction within the workflow—it also kept the project open, flexible, and in constant dialogue with its environment. Images stopped being a final output and became an active instrument for thinking, exploration, and decision-making.

I especially value the ability to have incorporated the complexity of the context at every stage of the design, from the first ideas to the final project definition. RenderAI allowed me to build a coherent, sensitive, and context-respectful proposal, reinforcing the relationship between architecture, place, and atmosphere as an integral part of the design process.

Ready to integrate AI rendering into your early-stage architectural workflow? Try RenderAI and discover how it can transform your design process from the very first sketch.

Frequently Asked Questions

How can AI rendering speed up architecture competition workflows? By integrating AI rendering from the first week, you can iterate on context, materials, and atmosphere in minutes rather than days. RenderAI lets you generate multiple high-quality visualizations from simple base renders, freeing time for design decisions instead of production work—as demonstrated in this competition that reached the Best 30 Finalist out of 1058 submissions.

Can I use AI rendering without a finished 3D model? Yes. RenderAI works effectively with quick base renders from tools like Enscape or D5 Render—even early, non-photorealistic outputs. The Creative–Editor method interprets geometry, materials, and lighting intent from your base image, so you don’t need a polished model to start exploring.

What prompts work best for early-stage architectural AI rendering? Start broad and directional—for example: “rainy mood, Yakushima vegetation, keep the architecture as-is.” As design decisions solidify, make prompts more specific: “water droplets on glass roof, warm interior light, dead leaves on terrace.” RenderAI reaches its full potential when prompts reflect a clear creative intent.

How does RenderAI handle material exploration in architecture? RenderAI lets you test stone types, reflections, surface roughness, and finishes directly on your renders—without building material maps or restarting for each camera angle. Material explorations happen in the actual project context and lighting conditions, giving results that are immediately relevant to design decisions. Learn more about comparing RenderAI methods to find the right approach for your workflow.