If you’ve spent any amount of time reading my content, you’ll probably realize something pretty quickly:
I’m not the average AI user.
I know I’m not the average AI user because what most people consider a simple conversation often turns into thousands of tokens for me. Most people ask a question, get an answer, and move on.
I don’t.
Usually, I’m trying to answer a question for myself. The problem is that I rarely know exactly what question I’m trying to answer when I start. My brain tends to wander from one subject to another, circle back to the original topic, discover a connection to something else, and then head off in an entirely new direction before eventually finding its way back home.
That’s just how I think.
For me, AI isn’t about replacing thought. It’s about keeping up with thought.
The conversations aren’t long because I’m trying to generate content. They’re long because I’m trying to understand something. Sometimes I’m exploring technology. Sometimes it’s business. Sometimes it’s transportation, media, history, politics, psychology, manufacturing, or some random idea that popped into my head while driving down the road.
The reality is that AI has become one of the few tools capable of following those jumps without immediately losing the thread.
That doesn’t mean I blindly trust it.
Far from it.
I question it constantly. I challenge answers. I cross-reference information. I ask follow-up questions. I intentionally push discussions in different directions just to see where the weak spots are. The conversation isn’t the destination—it’s part of the process.
Because of that, I decided I might as well document what I’m doing.
This category is going to be a running journal of AI development, experimentation, successes, failures, strange discoveries, and the occasional moment where I realize I’ve spent three hours investigating a problem that didn’t actually need solving.
Along the way, you’ll see discussions about local AI systems, infrastructure, hardware, software, workflows, automation, and whatever else catches my attention.
One thing you’ll notice is that I’m actively working toward running more of my AI tools locally.
People often talk about cloud costs, resource usage, subscriptions, and dependency on large platforms. Those are valid concerns.
That’s one of the reasons I’m building my own local AI environment.
I’m running tools like Llama models, Open WebUI, Tailscale, and other self-hosted services on hardware I already own. In fact, much of it is running on an old gaming PC.
Why an old gaming PC?
Simple.
I’m rarely home long enough to play games anymore.
So instead of letting the hardware sit there collecting dust, it might as well do something useful.
That approach also lets me learn how these systems actually work instead of treating them like a magic box on the internet.
And if you’ve followed me elsewhere over the years, none of this should surprise you.
Whether it’s Thingiverse, Facebook, websites I’ve built, comic strips I’ve created, 3D printing projects, electronics experiments, server infrastructure, content creation, or whatever else I’ve gotten myself involved in, you’ll notice a pattern:
I don’t stay in one corner.
Honestly, I find it boring to stare at a corner.
I’ve always been interested in solving problems, learning new skills, and exploring whatever catches my attention next. AI is simply the latest tool in that journey.
This section of The GigMan’s Life is where I’ll document that journey.
Some of it will be technical.
Some of it will be philosophical.
Some of it will probably be ridiculous.
But all of it will be real.
Welcome to the AI Development section.