A wardrobe-based weather app that recommends outfits from your own closet, redesigned in 2026 with an e-ink display that shows the day's outfits before you pick up your phone.

Context

I designed and built Fit for the Weather with two classmates for the Full Stack Web Programming course at Yale University in 2023, and redesigned it in 2026.

The course focused on building software through programming and system design, and our final group project was to build a web application from scratch.

Although the assignment was graded on its technical requirements, I approached it as a product rather than just a web application. I started from specific pain points that I, along with other classmates, had at Yale, and designed the software around how people would actually use it.

Problem

Coming from Texas, I often found it hard to read information from weather apps and translate it into an outfit. Dallas was mostly warm, so I wasn't used to the cold weather of New England. I was often either underdressed or overdressed, and felt frustrated that I couldn't get it right.

This pain point was shared by students across Yale. Many from outside the East Coast felt the same frustration, and I thought it would be a fun experience to build a relatable solution we could keep using outside of the course.

Process

I looked at existing solutions

There were weather apps and outfit recommendation apps, but none made a clear connection between the weather and the user's own wardrobe.

I designed within the course requirements

The assignment rubric required a backend database, a frontend design and implementation, and a server connection. Rather than treating these as separate checkboxes, I designed the product around them; the database stored images of each user's closet items, and the frontend was designed around deciding which of those images to show, based on calculations and interpretations of the weather.

I interviewed students for insight and inspiration

I interviewed around 20 students on campus about how they chose their outfits around the weather, and whether they felt "fit for the weather."

• Even New Haven locals were often under- or overdressed. Weather apps gave numbers rather than tangible guidance, so each person had to interpret them, and their interpretations weren't always accurate.

• Fits needed to account for the entire day. Weather in New Haven changes frequently throughout the day, regardless of season, so layering became an important feature to implement.

• Students had more limited wardrobes than typical recommendation apps assume. They wanted recommendations specific to their own closets.

I designed it to be practical and enjoyable

A key design principle was making the product fun to use, with quirks that add to the experience of building outfits and getting creative with them. Clothes are a form of self-expression, so instead of making the product purely practical, I used it to explore different ways to see and experience outfits, through a more modern style of UI and new technology like e-ink readers.

I revisited the product in 2026

In 2026, I looked more closely at how to make recommendations more personalized, and how the product could help users start their day. Observing the existing layout, I noted where usability could be improved and intuitive. I also approached the product to be more mobile-friendly so users could access the product more quickly.

In 2026, I became interested in the trend of apps using physical devices, like e-ink readers, to help users get information faster. I decided to experiment with implementing an e-ink reader into the project as a conscious choice for users who don't want to look at a screen as soon as they wake up.

I decided to use the e-ink reader as the main outfit recommendation feature. The web application was then designed as a companion to the reader for users to customize, edit, and archive outfits.

Solution

2023: a desktop web-app that recommends outfits from your own closet

• Personalized recommendations. Outfits were built from the items each user added to their closet, rather than from generic clothing suggestions.

• Outfits shown as images. Each recommendation displayed the items as images, visually showing how they work together as an outfit.

• A one-liner for everything else. A short line of advice covered extra items the user hadn't saved, but that might still apply to the weather.

• Layering for changeable days. Not every day is fully sunny or fully cold. The recommendations included layering options, and the one-liner suggested layering when the weather was expected to change.

• Useful tips. Popovers like "Don't forget your umbrella!" appeared on rainy days, for users who might not know it would rain.

2026 Redesign: E-Ink Display + Companion Web App

Outfit slides from your own closet. The reader shows a randomized series of outfits that fit the day's weather, arranged scrapbook-style. Users can assess which items are appropriate, and combine them in their own way. Even if they don't strictly follow the recommendations, they can get inspired and visually learn what type of clothing fits the day.

Compact weather personalizations. The bottom of the screen shows a pixelated black-and-white image of the weather, the temperature, wind, and humidity, and the date and time, so users can make sense of the weather alongside the outfits. The header also includes a one-liner, like "Don't forget your umbrella!", so users know to watch for certain weather conditions.

NFC tap. Tapping a phone on the reader opens the web app instantly.

Companion Web App

Today's Fit

Users select items shown as thumbnails. Once they've made an outfit of at least two items that fit the outfit criteria, the save button at the bottom is enabled.

Closet

Users can add, remove, and edit their clothing items, organized into Tops, One-Pieces, Bottoms, and Accessories. Each item has detailed information and an image.

Archive.

A calendar-style archive marks each day an outfit was saved with a circle. Users can tap a day to see what they wore, as a way to keep track of their outfits over time.

Outcome

Voted Best Project by classmates. We presented the product along with how it was built, and how it could make our daily lives easier.

Still in use today! Fit for the Weather continues to have active users, including myself.