My story and inspiration in life

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.

Popular Posts:

Popular

Why Your RAG System Needs an Agentic Memory Layer: Building AI That Learns From Every Query

Stop starting from zero. Traditional RAG systems treat every query like a first date, forgetting everything the moment a session ends. By implementing an Agentic Memory Layer, you can transform your AI from a stateless search tool into a truly evolving assistant—one that learns from every interaction, masters your organization’s unique terminology, and builds a deep contextual understanding over time.

A.I. Workflows

Beyond ‘Fire and Forget’: The Art of Building Robust, n8n Agentic Workflows

Most people design for the ‘happy path’—the sequence where everything works perfectly. But in the real world, APIs fail and data is messy. A truly agentic workflow doesn’t just execute; it reasons. By building ‘critique loops’ in n8n, you move from simple automation to a system that can peer-review its own work, catching errors before they ever reach your customer.

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