A kid from Alabama who went all-in on AI.

I bet on AI before it was the obvious bet

I grew up in Alabama and earned an associate degree in computer science. I was on the traditional path — and then I saw where AI was heading. So I left college and went all-in instead of finishing the degree. It was the hardest call I’ve made, and I’d make it again.

For the last ~3 years I’ve been building and learning agentic AI systems hands-on — no bootcamp, no big company behind me, just the real work, every day. Self-taught, in public, one shipped thing at a time. That’s how I learned what actually holds up and what falls apart the moment it meets reality.

I’m telling you this because if you don’t have a fancy degree, I want you to know it isn’t the thing standing between you and building real things with AI. The tools are here. The door is open. I walked through it from Alabama with an associate degree and a lot of stubbornness — and so can you.

What Yotta Byte Labs is

Yotta Byte Labs is my company — a one-person AI company. Two things happen here. First, I help people and businesses put AI to work: AI consulting, private 1-on-1 sessions, team and business training, hands-on workshops, and speaking. Second, I build my own AI products — the first is Journal Genie, a private, source-grounded AI workspace.

It’s just me, leaning hard on AI agents to do the work of a much larger team. That’s the point: the same approach I use to build my own products is the approach I bring to yours.

A written operating system, not vibes

The way I get one person’s worth of hours to do a team’s worth of work is discipline I actually wrote down — roles, guardrails, and an evidence habit the agents follow. Three parts hold it together:

• Constitution a written document the agents follow, so the rules don’t live only in my head.
• Roles an engineering agent that owns the code; an operations agent that owns everything else.
• Evidence every claim backed by a real command, file, or test. “Done” means proven, not plausible.

Journal Genie runs on this, and so does everything I build. It’s the highest-leverage discipline I have — and it’s the heart of what I teach when I help a team work with AI.

What I believe about building with AI

• You don’t need a fancy degree to build real things with AI — you need to start.
• AI output is only as good as the operating system around it.
• Trust comes from provenance and honesty about limits — not from confidence.
• One person, with the discipline built in, can ship and operate real software.

What I’m focused on

June 2026 — building Journal Genie, helping people and businesses put AI to work, and writing up how the work actually gets done. I update this when it changes.

Let’s put AI to work for you

If you want help getting fluent with AI — for yourself, your team, or your business — I’d love to hear what you’re working on. Every engagement starts with a discovery call: we map exactly what you need, then scope it to fit. You can also follow along in the writing, where I share the stories and lessons as they happen.