Early curiosity

I started learning code around 12 or 13 while growing up in Virginia. My first real doorway into technology was not a classroom or a textbook. It was game hacking, private servers, scripts, forums, and the early internet culture that made computers feel like something you could explore from the inside.

I spent a lot of time around communities like HackersBlackBook, experimenting with games like GunZ: The Duel, running private World of Warcraft servers with friends, and trying to understand why systems worked the way they did.

That period shaped me. It taught me that software is not magic. It is a system of rules, incentives, constraints, and hidden surfaces. Once you understand even one small part of a system, you can start to change how it behaves.

The practical middle

My path was not a straight line from teenage curiosity to engineering. I spent years in retail, operations, project management, and leadership roles. That chapter gave me a different kind of education.

I learned how to ship under pressure, communicate across messy human systems, manage deadlines, lead teams, and turn unclear requirements into real outcomes. I also learned how quickly a tool fails when it does not respect the person using it.

A lot of my engineering taste comes from that experience. I believe good software should reduce friction, make work easier to understand, and continue functioning when the environment is imperfect. Elegant systems matter, but practical systems matter more.

Returning to engineering

Around 2021, I went deep into blockchain infrastructure, open-source engineering, and protocol systems. That work pulled me back into the kind of systems thinking that originally made technology feel exciting to me.

By 2022 and 2023, artificial intelligence became the center of gravity. I began focusing more seriously on AI agents, automation, memory systems, research workflows, and interfaces that help people work with increasingly complex systems.

AI felt familiar to me because it connected many of the threads I had been following for years: systems talking to systems, information becoming action, tools coordinating across context, and software beginning to operate more like a collaborator than a static interface.

How I think about AI

I see AI agents as more than productivity tools. At their best, they can become durable memory systems, research partners, creative collaborators, and extensions of human intent.

I am especially interested in agents that preserve context over time. Systems that can help individuals, families, teams, and communities carry forward knowledge, decisions, lessons, and taste in a way that is useful rather than extractive.

As a father, this idea matters to me personally. I think a lot about what we leave behind for our children. Not just photos or stories told secondhand, but the actual shape of our thinking: what we cared about, what we were trying to build, what we believed, and what we learned the hard way.

That long-term view shapes how I think about technology. I want to build systems that extend capability without replacing judgment, preserve memory without flattening humanity, and help people act with more clarity in a world that keeps accelerating.

What I build

My work usually lives between research and shipping. I build agentic systems, AI-native tools, open-source infrastructure, protocol-shaped products, automation workflows, and interfaces that make complex machinery feel more understandable.

I care about systems that are useful in the real world, not just impressive in a demo. The best tools should feel powerful without becoming fragile. They should make complexity legible. They should help people move from thought to action with less noise in the way.

Why this site exists

This site is a home for my work, writing, research, experiments, and public memory. It is part blog, part portfolio, part lab notebook, and part record of the things I am learning as I go.

I write here because I want to document the journey while I am still inside it. The systems are changing quickly. AI is changing what it means to build, learn, remember, and create. I want a place where I can think out loud, share useful work, and leave behind something honest.