Outfit Matcha
Client:
Me
Role:
Designer
Service:
Vibe Coding
Year:
2026
Overview
Outfit Matcha is a web-based, responsive platform designed to help users journal and track their outfits based on different moods or “vibes.”
This was a personal project built using Loveable as an AI agent, where I translated my ideas, rough designs, and requirements into structured prompts, and the system implemented them. The focus was on creating a simple, intuitive experience that allows users to easily remember what they wore, what suited them, and in which context.
Choosing outfits is often influenced by mood, occasion, and past experiences, but:
Users don’t remember which outfits worked well in specific situations
There is no simple, lightweight way to log and revisit outfit choices
Existing solutions are either too complex or not focused on personal reflection
Tracking outfits is not treated as a quick, everyday activity
This results in repeated uncertainty and inefficiency in daily outfit decisions.
A minimal, responsive web platform that enables quick outfit journaling.
Users can log in and upload or capture an outfit image
Select a “vibe” (e.g., casual, formal, chill)
Optionally add notes for context
Save entries for future reference
The experience is designed to be completed in a few steps, reducing friction and encouraging regular use.
The platform works seamlessly across desktop and mobile, ensuring accessibility and flexibility.
The project resulted in a simple, functional system that:
Helps users track and organize their personal style
Enables quick recall of past outfit decisions
Improves confidence in choosing outfits based on context
Demonstrates an efficient workflow of combining design thinking with AI-assisted development
