TEXT-SVG-IMAGE GENERATION ITERATION PLATFORM
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Role: Sr. Product Designer
Team: Machine Learning Engineer, Founding Frontend Developer
This image-generating platform reimagines how users engage with generative art by merging intuitive creation tools with a transparent ecosystem for attribution, discovery, and iteration.
While generative tools often obscure the labor behind machine-made art, this platform foregrounds the time, iteration, and inspiration behind each piece.
WELCOME
The welcome flow is intentionally minimal — a three-screen sequence consisting of a logo splash, followed by sign-up or sign-in. In a product that leverages complex machine learning systems and layered image iteration, the introduction is deliberately pared back.
DISCOVER
A scrollable feed surfaces trending and curated generative works. Clicking into any image reveals its creation journey — including iterations, total time, prompt history, and credited inspiration. Featured artists are showcased with bio blurbs and linked works.
CREATE + ITERATE
Users generate images using a smart fill-in-the-blank prompt system, with controls for style, influence, and vibe. Outputs are editable as SVGs with a Figma-like toolbar, making it easy to tweak, remix, and iterate. Time and edit history are tracked to reflect effort.
RESPECTING ARTISTIC LINEAGE
This platform doesn’t erase the origin of visual inspiration. It actively surfaces the artists, styles, and practices that shape generative works. Every image carries a thread back to its non-AI source.
Original artists are credited throughout. Their profiles feature original works, a tab of inspired creations, and short bios with imagery — reinforcing transparency and showing their influence across the platform.
MACHINE LEARNING FOUNDATIONS
The creative engine is powered by a few key ML-driven features that enhance control and transparency throughout the generation pipeline:
Prompt Temperature
Controls allow users to modulate the randomness and creative looseness of their image generations, from structured to wildly abstract.
SVG-Based Output & Iteration Tracking
Each visual is editable post-generation. Users can fine-tune details, mask out elements, and re-generate parts, creating a clear history of iterative effort.
Artist Influence Matching
Leverages similarity search across training embeddings to surface likely inspirations behind generated works. These matched artists are credited, and users can explore their original pieces — spotlighting the real creatives behind the data.
USER PROFILE
Each user has a profile with tabs for created, liked, saved, and reposted work. The UI encourages identity-building and creative exploration, while tracking iteration timelines to celebrate the craft of generative art.
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