Summary

AI is everywhere. Tools launch daily. Everyone’s suddenly an expert. It’s easy to get lost in the noise. But behind the hype, there’s real leverage, if you’re willing to go deep. This is how I stopped chasing and started building.

I Didn’t Start With Code

My entry point wasn’t programming, it was exploration.

I was a student, curious how things worked behind the scenes. Maple, LaTeX, Ubuntu, I didn’t just install software, I pulled it apart. Sometimes things broke. I learned by fixing them.

I spent hours inside cracked apps, not to use them, to understand them. How they bypassed rules. Where the logic lived. That’s how I got into reverse engineering, before I knew the term.

I didn’t need clean documentation to start. I just needed a mess, and a reason to solve it.

That mindset never left.

The AI Overwhelm Is Real

When AI took off, I felt the same pressure as everyone else:

“I need to catch up.”

I downloaded tools. Tried them all. Watched too many videos. Drowned in newsletters and prompts. It didn’t help. It just added noise.

At some point, I stepped back and asked myself: Where’s the actual friction in my day?

That’s where I focused. One use case. One tool. One system at a time.

I Don’t “Learn AI”, I Work With It

I don’t study AI like it’s a subject. I use it to think.

I don’t need help with answers. I need a second brain to organize what I already know. Writing SOPs, documenting internal systems, untangling ideas, that’s where it shines.

I treat AI like a sparring partner. I throw prompts, challenge assumptions, push for clarity.

“Don’t just answer, think with me.”

I Work In Rhythm, Not in Hype Cycles

I don’t try every tool. I don’t jump on every trend.

Every morning, same spot, same flow: I open Obsidian and work through prompts. It’s part of how I think now. No effort. No friction.

Every month, I review:

  • What drains me?
  • What’s repeatable?
  • What got easier since last quarter?

If AI helps, I automate. If not, I move on.

Simple.

What I’m Optimizing For

I’m not trying to “do more.” I’m trying to build better systems, and do less, with more clarity.

That means:

  • Seeing what matters before it’s obvious
  • Recognizing quality when it shows up
  • Building tools that serve people, not just impress them

I don’t want busy. I want leverage.

The NavNab Way

I break systems to understand them. I rebuild them to see what actually holds. Then I write down what worked, and what didn’t.

NavNab is just the byproduct of that process. If you like thinking in systems and building with intention, you’ll feel at home here.

Final Thought

AI won’t replace you. But if you’re stuck doing shallow work, it might outpace you.

The edge isn’t in knowing every tool. It’s in knowing what matters, and building systems around it.

That’s the game. And I’m here to play it well.

Have questions about building your own AI systems? Feel free to reach out via LinkedIn or Twitter. I’d love to hear about the friction points you’re solving.