Exploring emerging technology through action
I tend to learn new technology by moving through three stages:
Challenge assumptions: conduct research to understand what a technology can & cannot do.
Apply it to real products: look for opportunities where new technology creates workflows that were previously impossible.
Rethink my own workflow: experiment with how I research, design, prototype, and communicate ideas.
These projects are independent explorations rather than one continuous product. Together, they represent how I approach learning in rapidly changing technology landscapes.
01
CHALLENGE ASSUMPTIONS
Researching 100 AI-native products with 20 UX designers
When generative AI rapidly emerged in 2024, 20 UX designers organized a four-month research initiative to better understand its impact on creative work.
Working in 6 research groups, we evaluated approximately 100 AI-native products based on product maturity, industry influence, and investment momentum. My group focused on how generative AI could reshape creative professions through image generation, video creation, UI generation, and multimodal design tools.
My biggest question was simple: Would AI eventually replace creative expertise?
Surprisingly, my research led me to the opposite conclusion. While AI dramatically accelerated execution, the quality of the outcome still depended heavily on human judgment—defining problems, evaluating solutions, making trade-offs, and deciding what was worth building.
That insight has influenced how I approach both product design and my own career ever since.
Deliverables
Four-month collaborative research with 20 UX designers, met weekly
Evaluation of 100 AI-native products
Research blog summarizing key findings
Output Quality Comparison: Same Prompt to Image Generation by 3 Products
02
APPLY NEW TECHNOLOGY
Designing AI-native workflows at InspectMind.ai
As the first and only product designer at InspectMind ai, I worked closely with founders and engineers to build AI-powered software for structural inspection professionals.
The product uses generative AI to transform field observations into structured engineering documentation—unlocking workflows that were previously impractical without modern AI. As an ex-architect with over a decade of practice, I bridged the deep domain expertise with product design.
I designed features that helped engineers organize, manage, and review highly technical inspection data in ways that matched their existing mental models. One example was a scalable labeling system connecting field observations to broader project information, making complex engineering reports easier to navigate and manage.
The feature was presented to customers and received highly positive feedback, reinforcing another lesson from my research: AI creates new possibilities, but meaningful products still depend on understanding people and their work.
Labels Design with Scaling Opportunity for InspectMind ai
03
RETHINK MY WORKFLOW
From Figma prototypes to working applications
Before vibe coding era, many of my concepts stopped at Figma because I didn’t have the engineering skills to build them. As a weekend experiment, I used Claude Code to build a working prototype for a virtual fashion try-on experience. Instead of creating a static prototype, I was able to iterate with AI and produce an interactive application running in Expo Go after only a few hours of collaboration.
The project was an opportunity to understand how AI changes the relationship between designers and software development. The experience reinforced an important shift in my workflow: AI now enables me to test ideas beyond traditional prototypes, allowing product conversations to happen around working experiences instead of static screens.
Fashion Try-on Mockup. Built with Claude Code
What I believe today
With such exploration, I see AI as technology that compresses execution while increasing the value of human judgment. The ability to ask better questions, understand complex domains, challenge assumptions, and make thoughtful product decisions has become even more important.
That’s why I continue exploring emerging technologies—not to chase new tools, but to become a better designer for whatever comes next.
BACK TO