An AI sustainability product for Accenture, showcased at Web Summit 2026
The AI needs precise garden data. The user doesn't have it.
I designed the system that bridges that gap. A site assessment that turns uncertain homeowners into confident gardeners.
Wildlight is an AI-powered web app that helps homeowners plan and maintain sustainable gardens.
As lead product designer, I built the core of the experience: the site assessment conversation, a map-based measuring tool, the AI's teaching moments, and onboarding. Launched at Accenture's Season of Impact, now pitched to retailers including Home Depot.
ROLE
Lead Product Designer
Team
1 Product Manager ● 1 Brand Designer
2 Product Designers ● 3 Developers
Timeline
January - April, 2026
Why we committed to AI-first
The original approach assumed people already knew their garden: site size, soil type, sun exposure, drainage.
But people open a gardening app because they can't answer those questions, and a form can't answer back.
So we replaced it with a conversation.
One question at a time, each one shaped by the last.
Generative research
Building AI-first only works if the AI asks the right questions. So we didn't guess.
We went where gardeners start. Nurseries and greenhouses, watching how people read plant tags and where they get stuck.
Then we brought in Accenture's subject matter expert to separate what beginners actually need to know from what only sounds important.
Designing for people who don't garden yet
Translating research into structure
Everything we learned in the field led to one question:
How do you help someone reach the right answer when they know nothing about their garden?
From what we learned to how it works
The solution wasn't another form.
It was a conversation.
Usability testing
Testing the first build
We put the conversation in front of 20 people.
18 made it through on their own.
Moderated, think-aloud sessions, with us sitting beside each person.
What they said out loud is how we found the details that didn't work yet.
The flow was right.
The details weren't.
Three problems surfaced. Here's how I solved each.
01
Plant cards that actually tell you something
Testing made one thing clear beautiful cards weren't enough. People still didn't have the confidence to choose a plant.
The answer was already in the nursery.
A seed packet puts the essentials on the front and the growing details on the back.
I brought that same pattern into the app: a scannable front for choosing, and a flip for everything else.
In the retest, people chose their plants without second-guessing.
02
Measuring without a measuring tape
The assessment needed the garden's size, but almost no one can estimate square footage by eye.
So we didn't ask for a number. We let people draw one: trace your boundary on the map, and the system calculates the area for you.
Questions should be answered, not blocked
03
People guessed on questions like soil type, and one wrong guess throws off everything after it. A form leaves you stuck there. A conversation doesn't: ask, and the AI explains it, shows a visual, and teaches you enough to answer honestly.
In the retest, people stopped guessing once they understood the question.
Outcome
Shipped and showcased
The AI-first site assessment shipped as the core of Wildlight and was showcased at both Accenture's Season of Impact event and Web Summit 2026, where the team demoed it publicly. It was also pitched to major retailers including Home Depot, and Accenture continues to build on the foundation we designed.
What this taught me
The sharpest design decision in this project didn't come from a screen. It came from standing in a greenhouse, watching how people read a plant tag. When the product felt stuck, the answer was to go look at how the real world had already solved the same problem — and translate it, rather than invent something new.