UX research is one of the most valuable activities in product development — and one of the easiest to lose in the chaos of shipping. This project set out to fix that: a clean, minimal web platform that gives teams a dedicated space to document findings, communicate design rationale, and keep research visible across the whole product lifecycle. No bloated tools, no steep learning curves. Just clarity, fast.
Client
Role
Product Design UX/UI Design Development & Deployment
Industries
Blockchain
Date
2025
Role & Team
Solo-led from concept to launch. I owned product definition, UX, visual design, and deployment — using AI-assisted tools to move quickly without cutting corners on quality.
Project Goal
The brief was simple: build something that actually gets used. Most research documentation ends up in a Notion page nobody revisits or a Figma file that only the designer understands. UX Research was designed to be the opposite — structured, shareable, and frictionless enough that teams keep coming back to it throughout the product development lifecycle.
Design Approach
The design is intentionally minimal. Strong hierarchy, clean typography, and generous whitespace keep the focus on the content rather than the interface. Every decision — from the information architecture to the content entry flow — was made with one question in mind: does this make research easier to share and act on? The visual system was built to support clarity across different types of research outputs, from insight summaries to design rationale documents. The build used a modern AI-assisted workflow: MVP and content structure defined first, then translated into a working interface via Builder.io, refined iteratively with Cursor, and shipped on Vercel. This let me move from concept to live product in a fraction of the usual time while keeping design intent intact.
Project Learnings
Tight deadlines clarify priorities fast. Delivering a fully functional web app solo in a compressed timeframe reinforced the value of clear scope, strong design fundamentals, and knowing exactly when AI tools help versus when they slow you down. The biggest lesson: shipping a focused, well-executed product beats a feature-rich one that takes three times as long.