Product / Functional beta

Neighbr.ly

I researched, designed, and built a neighborhood tool-sharing app with AI-assisted development, taking it from an early question to a functional beta.

MY ROLE

Founder / Product Designer

TIMEFRAME

2025

STATUS

Functional beta

From finding a nearby tool to planning a hand-off: the Neighbr.ly app experience.

01 / THE CHALLENGE

A little more neighbor. A lot less stuff.

Could neighbors borrow tools instead of buying equipment they might only use once or twice? The opportunity depended on trust, clear expectations, and an experience that worked beyond the listing screen.

Early Neighbr.ly wireframes with notes connecting discovery, requests, loans, and returns — Early wireframes mapped the borrowing journey and its supporting states before the interface took shape.

02 / THE DECISIONS

Start with the people, not the platform.

I started with a survey of 100+ participants to understand what people needed and what might make them hesitate to lend or borrow. Those findings shaped the initial product and borrowing workflows.

Welcome screen explaining community, sharing, and safety — Introduce the value of sharing before asking people to join.

Onboarding form collecting name and neighborhood location — Collect the information needed for nearby discovery.

Community guidelines covering respect, returns, safety, and timely replies — Make community expectations explicit during onboarding.

Design the whole borrowing loop.

The experience connects profiles, listings, nearby discovery, requests, approvals, messaging, active loans, and returns. Pending requests and unavailable items matter just as much as the happy path.

Borrowing request with project description and pickup location choices — 1 / Explain the project and choose a hand-off spot.

Borrowing request with pickup and return dates and times — 2 / Set the pickup and return window.

Borrowing agreement explaining returns, care, compensation, and risk — 3 / Review expectations before confirming the request.

Find a nearby tool. Keep home addresses private.

Public discovery shows approximate item locations. Precise pickup details are reserved for accepted transactions, balancing nearby discovery with personal privacy.

Nearby tool feed with radius control, category filters, and tool listings — Discovery combines distance, categories, and recognizable tool listings.

Tool details with description, condition, lender information, and pickup options — The listing brings tool details and hand-off choices into one view.

Exchange location settings with saved hand-off spots and home-address privacy guidance — Choose convenient hand-off spots, with home-address privacy explained in context.

THE EXPERIENCE

Keep the conversation close to the loan.

Messaging keeps coordination connected to the item being borrowed. Unread-message indicators draw attention to updates, while current and past conversations retain the context of each borrowing request.

Conversation attached to a socket and ratchet set borrowing request — Coordinate the hand-off in the context of the tool.

Navigation showing an unread-message notification beside Messages — An unread-message indicator brings attention to new conversations.

Message history grouped into current and past conversations with request statuses — Keep current and past conversations organized by their borrowing status.

THE EXPERIENCE

Give trust a place in the experience.

Profiles, community badges, and transaction feedback make participation visible. These screens show how the product supports reputation alongside the borrowing flow.

Community badges and member profiles make participation visible.

Transaction review shown as an overlay in the Neighbr.ly app — Close the loop with feedback after a transaction.

Let members manage their profile and preferences.

03 / HOW I USED AI

Building with AI.
Learning as I go.

I used Base44 and AI-assisted development to turn requirements into a working application. When generated interfaces began to drift, I recreated core tokens and reusable components in Figma to regain control of consistency and responsive behavior. I also set up the third-party services behind the beta: mapping for nearby discovery, Cloudinary for uploaded images, and transactional email and SMS notifications. Connecting these services was part of taking the experience from designed screens to a usable product.

04 / OUTCOME & LEARNING

What came out of it.

I launched a local beta to test the complete borrowing experience. Building it taught me about the service connections, notifications, and less tidy states that a screen prototype can miss. A borrowing request is only the start; the tool still has to get home.

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