AI-powered wayfinding experience for grocery shoppers, from research to prototype.

ROLE

Solo designer + developer

METHODS

Competitive analysis, prompt engineering, prototyping

FOCUS

Interaction design, UX for generative interfaces

CONTEXT

2026 · Personal concept

Aisle Assist grocery shopping interface mockups
Aisle Assist grocery shopping interface mockups

OVERVIEW

An AI shopping assistant that plans the trip around the store.

A concept for grocery shoppers that turns a list into a route. It acts as a companion through the trip, handling the small, invisible hurdles that slow shoppers down.

CONTEXT

2023 · Concept · Self-directed

ROLE

Solo UX Designer

FOCUS

Mobile UX, AI feature design

OVERVIEW

An AI shopping assistant that plans the trip around the store.

A concept for grocery shoppers that turns a list into a route. It acts as a companion through the trip, handling the small, invisible hurdles that slow shoppers down.

FOCUS

Mobile UX, AI feature design

ROLE

UI/UX Designer

YEAR

2023

PROBLEM

A quick grocery run usually involves an invisible mental overhead.

Shoppers have to remember what they need, pick a store, and work through a list that knows nothing about the store’s layout or what’s in stock.

RESEARCH

Shoppers want to find things faster, not get more suggestions.

A survey of 14 grocery app users showed where to put the design effort and what to cut.

Discoverability came first.

[12 of 14] put search and filtering at the top of their list.

The list is the product.

[9 of 14] wanted better list management, so the list became the core surface.

Content has to keep up.

[9 of 14] valued item descriptions and images as much as features.

Recommendations could wait.

Only [5 of 14] wanted personalized suggestions, so that feature was cut.

Discoverability came first.

[12 of 14] put search and filtering at the top of their list.

The list is the product.

[9 of 14] wanted better list management, so the list became the core surface.

Content has to keep up.

[9 of 14] valued item descriptions and images as much as features.

Recommendations could wait.

Only [5 of 14] wanted personalized suggestions, so that feature was cut.

IDEATE

Design opportunities centered on the shopping context

01

Context-aware list

Reorder the list automatically based on the store layout, so the shopper follows one path instead of backtracking.

02

Low-friction input

Voice, recents, and smart suggestions reduce the cost of keeping the list current.

03

Cross-store memory

Adapt to different store layouts and inventory without asking shoppers to manage the differences.

IDEATE

Design opportunities centered on the shopping context

01

Context-aware list

Reorder the list automatically based on the store layout, so the shopper follows one path instead of backtracking.

02

Low-friction input

Voice, recents, and smart suggestions reduce the cost of keeping the list current.

03

Cross-store memory

Adapt to different store layouts and inventory without asking shoppers to manage the differences.

DESIGN

Help at the three moments shoppers get stuck.

Three screens, each covering a distinct moment of friction: arriving at a new store, routing through it efficiently, and getting help mid-trip without losing your place.

Before the trip

Items are added one by one; the assistant fills in details you’d otherwise have to look up yourself.

Choosing a store

The AI looks at what you’re buying and recommends where to get it, so you’re not choosing blind.

Mid-aisle

The assistant answers mid-shop questions about aisle locations, stock, and substitutes without pulling you out of your list.

REFLECTION

Design for the failures first.

I designed this in 2023, before AI and UX had much shared vocabulary. I built the happy path first and caught the gaps late: what happens when an item is out of stock, or the assistant gets an aisle wrong. Today I’d start with the failure cases and build on existing AI/UX frameworks instead of designing from scratch.

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