Turning daily watch wear into a collection journal

As a watch enthusiast and collector, I wanted a way to remember what I wore and see how my collection changed in use over time. I had seen collectors on Reddit tracking wears in spreadsheets, but I did not have a tracking habit myself.

I started WearLog in May 2026 as a personal side project: an opportunity to develop my UX design skills, explore working with AI, and take an iOS app from an idea toward my first independent App Store release. The core interaction was simple: choose the watch you are wearing today, optionally add a photo, and save the entry.

Over time, I wanted that history to help collectors notice favorites and overlooked watches. Streaks, milestones, and learning about watches could make the experience enjoyable enough to return to. Those ambitions gave me a direction, but I needed a smaller version I could actually use.

The original 13-week rotation view used a GitHub-style contribution grid, with colors showing the watch brands worn each day. I liked how much history it fit into one view and the sense of progress as the grid filled in. It was a pattern I already knew how to read.

When I showed it to my wife, who also collects watches, she had no idea what she was looking at and found it overwhelming. Her reaction made the problem clear: I had brought my own familiarity with a technical tool into an app for watch collectors. The interface depended on knowledge I could not assume other people shared.

I replaced the grid with an Active days calendar. Weekday labels and numbered dates give the activity a familiar structure, while brand colors preserve the rotation history. A split circle shows days with watches from two brands, and activity totals and streaks summarize progress below. This change came from one informal feedback session; broader collector testing is still ahead.

I began by talking through the concept with Gemini, then used it to organize the ideas into epics and user stories. I brought that backlog into Claude to explore branding and initial screens, using references from Peloton and Instagram to explain the tracking and photo-journal experiences I had in mind.

I reviewed those explorations and iterated on what belonged on each screen. The resulting designs gave me a starting point for implementation with Antigravity. I owned the product direction, priorities, interface decisions, and testing, while AI helped generate designs and code.

The initial prototype felt too angular. I asked for a direction built around rounded cards, using Peloton’s home screen as a reference. Later iterations introduced red insight cards to give the screen more contrast and brought more activity metrics into the layout.

Each exploration also gave me something to reject. I liked how the gradient made the collector insight stand out, but the metallic Momentum card, protruding milestone circle, and khaki tones pulled the next version away from the direction I wanted. Those reviews led to the simpler surfaces and stronger red accents in the current implementation.

I also removed active days from Momentum because the monthly recap already showed that information. Redesigning Momentum to reduce its unused space remains on my backlog.

As the app grew, I used ChatGPT to help prioritize the backlog, prepare implementation prompts, and review Antigravity's proposed and completed work. I reviewed and revised those prompts before passing them along. When a layout overlapped or an implementation stalled, sharing the Swift code and a screenshot with another model sometimes helped identify the issue.

The reviews also surfaced cases I had not initially considered, such as deleting an entry without an internet connection and later syncing. My own testing caught other problems, including a feature-image change that made previous wear photos disappear from the interface and needed to be fixed. The workflow depended on reviewing the output and using the app, then feeding those findings back into the next iteration.

Working with AI gave me an initial version I could use. Living with that version helped me decide what deserved space, where the interface felt inconsistent, and what would make logging worth returning to. Refinement became a cycle of noticing a problem, reviewing it with AI, and testing the result myself.

Letting the watch box lead

The early Collection drafts put a featured watch above the watches I owned. But Today already showed the watch I was wearing and how close it was to its next milestone. I did not need Collection to repeat that moment. I wanted to open it and see my watch box.

I removed the featured watch and shortened the cards. Labels such as “Weekend favorite” and observations such as “Usually leaves the box on Saturdays” took space without helping me browse. The current cards keep the photo, brand, model, and last-worn label, with Add Watch at the top and archived watches below the active collection.

Using native behavior, then testing the fit

I had asked for Apple’s standard interface elements from the start. During iOS beta testing, changes in translucency and the feel of navigation made me question whether the implementation actually followed that direction. Switching tabs felt less fluid than the native interfaces I was seeing in other apps.

I gave ChatGPT Apple’s official documentation and asked it to audit the code. The review identified a custom tab bar, title treatments, and spacing in places where I expected standard components. I then used that audit to guide an implementation pass and manually tested the changes in the app.

The pass also introduced default Apple forms into wear logging. In use, those screens felt too generic. I kept the native navigation behavior while bringing back selected custom buttons and treatments so the app still felt like WearLog. The audit gave me a starting point; using the result helped me decide where to stop.

Giving the first version a reason to return

The same process helped round out the app beyond the current day. The earlier move from a contribution grid to an active-days calendar made wear history easier to revisit. Today now provides immediate context, while You brings together a broader view of the collector’s activity.

These additions are intended to make continued logging rewarding and give the collection a sense of history. They round out the first version; whether they encourage a lasting habit still needs feedback from more collectors.