My story began in Seoul, Korea, and my roots took hold across the Pacific, shaped by a childhood spent between cultures and a lifelong curiosity about how different worlds connect. My academic path eventually led me to the University of Michigan in Ann Arbor, where that curiosity only deepened.
For the last decade, I’ve channeled that curiosity into Web Design and SEO. I see websites as digital front doors — and my job is to make sure they’re welcoming, easy to find, and built to last. I love the moment when a business owner sees their vision finally come to life online, and I take pride in building the kind of technical foundation that can grow with them.
This blog is where I explore the next frontier: A.I. implementation and agentic workflows. We’re living through a fundamental shift in how work gets done, and I’m fascinated by how intelligent agents can handle the heavy lifting — freeing us up for the creative, human-centered work we actually enjoy. My goal here is to demystify AI and share practical strategies for building workflows that think, learn, and grow with you. Consider me your guide through this new landscape: someone who’s been on the ground floor of enough transitions to know that the best technology never loses its human touch.
Your AI agent’s hallucinations aren’t random bugs—they’re predictable failures caused by three architectural mistakes I see repeatedly across production deployments. After debugging dozens of agent
Zapier’s AI Actions processed 2.3 billion workflow automations last quarter, while most enterprise AI pilots never make it past proof-of-concept. The difference? These seven AI
LangChain’s vector database queries started returning empty results at 3:47 AM on a Tuesday, cascading through Zapier’s automated customer support workflows and leaving 12,000 helpdesk