Bringing mood-based meal planning from Figma to iOS.
PlanEat
An AI meal planner that suggests meals and snacks based on mood. I designed the interface and built the SwiftUI front end, including account screens and the states around loading and generated content.
At a glanceFigma → SwiftUI · Mood-based suggestions · Account flows & loading states
01 / Background & problem
Start meal suggestions with how someone feels.
PlanEat explored an iOS meal-planning experience built around mood. The app presents meal and snack suggestions with calories and ingredients, combining text and images in the recommendation experience.
My responsibility was to design the UI in Figma and carry it into the SwiftUI front end. That meant designing both the recommendation screens and the account flows needed to use them.
02 / Design decisions & execution
Design the states around the main experience.
I designed the interface in Figma and implemented the SwiftUI front end. The app displayed generated text from GPT-4o mini and images from DALL-E 3 through the OpenAI API, alongside meal and snack details such as calories and ingredients.
I built the sign-up, login, password-reset, and profile screens using Firebase Auth and Firestore. I also implemented loading, fallback, and cached-image states so the interface could account for waiting and unavailable content as well as successful responses. Teammates developed the back end.
03 / Results & reflection
Carry the design through to a working iOS front end.
From May to July 2025, I delivered the Figma UI and SwiftUI front-end implementation for mood-based meal suggestions and the app’s account flows. My work included the loading, fallback, and cached-image states around generated content.
PlanEat taught me to treat those supporting states as part of the product experience. Working in SwiftUI also helped me understand how interface decisions become implementation details, experience I later brought to my company internship.