Generative Artifacts

Roles

Visual Director, Prompt Engineer,

Image Series Prompt Iteration Sheets Artifact Catalog High-resolution Exports

Midjourney v6, DALL·E 3, Visual Electric, Hautech, Kling, Sora, Runway, Chat GPT 4.o

Explored speculative product aesthetics using AI tools to rapidly prototype visual form studies. Focused on style variation, material simulation, and lighting logic across categories like tools, furniture, and appliances.

Generative Artefacts is a visual experiment series exploring AI as a co-creator. Without a fixed brief or medium, the project focuses on generating visual outputs that evoke tactile form, synthetic texture, and surreal function. These images are not final products—they’re provocations.

Intent

This project blurs the line between author and algorithm. By combining prompt engineering, material imagination, and visual composition, the goal is to generate forms that suggest utility without defining it.

Scope

Material Illusions: Metallic fibers, translucent mesh, woven carbon, iridescent ceramics—all created digitally.
Ambiguous Objects: Artifacts that look manufacturable but serve no defined use.
Prompt-Driven Evolution: Each image iteration builds from the failures and strengths of the last—trials in language become trials in form.
Context-Free Display: No environments, no backstories—just raw surface, light, and silhouette.

Process Flow

1. Prompt Engineering
Constructed layered prompt structures for tools like Midjourney, DALL·E, and others to control texture, lighting, and structural intent.

2. Visual Curation
Filtered hundreds of outputs—selecting based on narrative ambiguity, material tension, and formal intrigue.

3. Iteration Loops
Used outputs as input references to further evolve the object language—layering AI-on-AI feedback.

Result

Generative Artefacts exists between concept art and product speculation. It serves as a future-facing sketchbook—one that questions authorship, process, and the aesthetics of machine-made imagination.