Lent With Love

I assumed the friction was logistical: tracking who had what, setting due dates, sending reminders. I almost built Venmo for books.

Living in New York, books take up space I don't have, and mine sat unread on a shelf instead of with friends who'd want them. That became my prompt for Coding It Forward's Hack Your Summer, a free four-week production sprint.

My question was: how might I make lending easier? I assumed people wanted inventory tracking and reminders, and that the physical handoff was the pain point. I went in to validate that.

I was wrong.

So I widened the question: not just how people lend books, but how they discover them, decide what to read next, and decide whose taste to trust. That wider lens surfaced the real insight.

Almost no one described the handoff as a real frustration. Across five interviews and forty surveys, what people kept returning to, unprompted and in different words, was the same thing: they wanted to know what the people they trusted were reading. The patterns weren't about logistics. They were about people.

So I stopped designing a lending platform and designed a community one. Lending became a feature; community became the product. Without research, I'd have built the wrong thing.

Plenty of products force AI into every interaction. I didn't. I asked where AI actually removes friction, and it wasn't recommendations or discovery. Those are the human parts.

It was onboarding. Entering hundreds of titles by hand is enormous friction before the product is useful at all. So: photograph your shelf, and AI identifies titles, authors, and editions. After that it recedes, and people become the recommendation engine.

How to scan

Camera

Building your shelf

Confirm books

Post-scan curation

Confirmation is the highest-stakes moment: results are graded by confidence, with a clear path to fix whatever the scan got wrong. Imperfect accuracy should feel fine, not frustrating.

Curation comes last by design. Once the shelf exists, marking what you've read takes a single pass instead of leaving a library to correct book by book later.

No gamification. No algorithmic feed. No strangers. Just a warm space to see what people you trust are reading, and share what you love back.

Library

Sort & filter

Covers face forward on wooden shelves, warm and tactile. A Reading Now card surfaces what you're in the middle of, and status chips filter by read, loved, or DNF.

Your book detail

Friend's book detail

Every book detail leads with “Recommend to a friend”, not rate, not share. The north-star behaviour is built into the hierarchy. On a friend's book you see their rating, review, and saved quotes.

Feed

Conversation thread

The feed is chronological, friends-only, and cover-forward. Posts come from real reading actions: finishing a book, saving a quote, starting a buddy read. Never a composer. No like counts, no vanity metrics.