What happens when AI pulls you into a field you know nothing about

I started this project knowing nothing about chemistry. I finished it reading molecular structures.

VALENCE is a speculative fragrance brand, but really it was an experiment: can AI help you go deeper into a concept, not just faster to a pretty image?

Every perfume is a formula, a handful of real molecules with real shapes. So instead of inventing a "scientific look," I built the whole brand from the actual chemistry. Three scents, nine molecules, all verified in PubChem. Geosmin, the molecule behind the smell of rain on dry earth, gave the scent Petrichor its name.

The process went one way only: from real data to image, never the other way round. Molecular geometry calculated in RDKit, molecules rendered as glass sculptures with a Python path tracer built together with Claude, and those renders used as references for AI-generated campaign visuals, motion and packaging. The bottle went through many iterations before it landed on one calm form: clear glass, a chrome sphere, each scent told apart only by its colour.

What I took away: an AI workflow can connect design with fields that seem far from it, and turn that connection into a campaign.

Tools: RDKit, Python, Claude, Midjourney, Flora, Kive