An AI shopping tool that knows the store as well as the list.

CONTEXT

2023 · Concept · Self-directed

ROLE

Solo UX Designer

METHODS

Competitive audit, user surveys, interviews, prototyping

FOCUS

Mobile UX, AI feature design

ROLE

Solo designer + developer

METHODS

Competitive analysis, prompt engineering, prototyping

FOCUS

Interaction design, UX for generative interfaces

CONTEXT

2026 · Personal concept

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

PROBLEM

A quick grocery run usually involves an invisible mental overhead. Remembering everything, choosing the right store, then navigating a list that doesn’t consider the context of the store and the shopper.

DISCOVER

Research revealed that users want tools that match real shopping.

Fourteen grocery app users ranked discoverability and list management far ahead of personalization. That decided what stayed and what got cut from v1.

87%

Prioritized search and filtering, making discoverability the dominant bet.

64%

Wanted better list management, confirming the list as the core surface.

64%

Valued descriptions and images, so content quality had to match feature quality.

37%

Wanted personalized recommendations. Lowest priority, first thing cut.

DISCOVER

Design opportunities centerd 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.

DISCOVER

Design opportunities centerd 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

Prototypes

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.

Building a list before you arrive

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

Picking the right store for your list

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

Questions without leaving your list

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

REFLECTION

This project is from 2023, before AI and UX had much of a shared vocabulary. I designed the happy path and caught the gaps late. Today I’d start with failure cases and lean on existing AI/UX frameworks rather than designing from first principles.