The beginning was a farm, a father who let me figure things out, and the realization that a system tells you things if you learn how to listen.
A first-person account. Linked public records support the specific details identified alongside them.
I grew up on a hog farm near Geneseo, Illinois. Everything depended on something else.
Feed and water depended on pumps, lines, electrical power, and people. The animals depended on ventilation, water and an environment that stayed within workable limits.
You learned what normal sounded like. A ventilation fan’s motor changing pitch could be an early warning that something was beginning to fail.
Breathing, coughing, changes in behavior. Sometimes the first clue came from the pigs themselves. You looked for a pattern, considered its possible causes, and asked what would happen next if you were wrong.
The chain was immediate: power, ventilation, air quality, temperature, animal distress. A small change could affect everything depending on it.
One family story has me trying to make a hot dog as a small child. The bread needed to be flatter. Two heavy books seemed like a reasonable solution.
Dad was watching from around the corner, close enough to help and willing to let me work it out. That’s the part that stayed with me: having room to try, see what happened, and adjust.
As a young teenager responsible for the farm buildings, a power outage meant getting the tractor-driven generator connected so ventilation and other critical systems could run.
I learned to ask what had to remain true, restore the dependency supporting it, then check what else had changed. Restoring power and confirming recovery were separate tasks.
Later conversations with my Aunt Mary about her teaching helped me recognize the same pattern: clear objectives, room to explore, an explanation of what happened, and a willingness to revise.
That shapes how I collaborate today. Make the objective understandable, give people room to contribute, and use what the work shows to improve the next version.
These family scenes and conversations are my recollections, drawn from my family-lineage account.
My father, Roy, explained mechanisms and gave me room to reason through them. A pump or motor was part of something larger: power, lines, equipment, and the people and animals depending on it.
I learned to ask what a piece of equipment was supposed to do, what it depended on, and what would happen if it stopped.
My father designed an animal-feed management system that automated an established physical process. I helped put it together as he explained how the pieces should work and why.
The public patent record captures his invention. My participation is my recollection. The lasting lesson was seeing an everyday operation decomposed, measured, and redesigned.
In the mid-1980s, I was using a TRS-80 Model 4. Dan Duncalf showed me BASIC, screen coordinates, and games he was building. Someone had described the behavior precisely enough for a machine to produce it.
Dan later co-founded Pipeworks Studios. His career is publicly documented; that early scene with the TRS-80 is my memory of encountering computing.
Around 1990, a family Packard Bell 386SX became the machine behind Grounded Zero, my dial-up bulletin board. I remember using Wildcat! software, with my parents supporting a second phone line. Other people dialed into the menus, messages and files I maintained; access, storage, configuration and uptime became my responsibility.
From there, it was a short step into the telephone network itself. What does the network know, and what signal does it trust? That question became part of a broader security mindset.
Early professional work meant entering unfamiliar telephony and predictive-dialing systems, learning the stack, and making incomplete pieces work together. Later came enterprise infrastructure, payments, cybersecurity, audit programs, and controls.
A payment-system failure can expose customers or interrupt critical operations without an obvious physical signal. Understanding the dependencies still matters.
Today those questions inform my work in integrations, applied AI, and assurance: What should remain true? What changed? Which observations support the conclusion? Who can act?
The move into AI follows the same curiosity. The signals are harder to read, but a useful answer still needs a connection to the system behind it.
See how that appears in the work →That is how I describe compliance: make the actual state visible, keep proof close to its source, and make ownership and recovery paths understandable to the people who need them. The farm stories and early-computing scenes are my recollections; linked public records support only the details identified alongside them.