Blogs

When I first heard “machine learning,” I pictured some sci-fi robot uprising.
Turns out, it’s less Terminator, more intel analyst on steroids.

If you’re a veteran trying to understand what machine learning really is, think of it like recon—but with data instead of drones.

What Is Machine Learning, Really?

At its core, ML is about teaching machines to recognize patterns, make decisions, and learn from experience—just like we did during fire missions.

When you’ve been trained to make decisions under fire, tech feels… calm.

But that doesn’t mean it’s easy. Tech teams hit roadblocks. They deal with pressure, deadlines, and breakdowns—just like any unit in the field.

And that’s exactly why I believe the military mindset belongs in tech.

Mission > Ego

In the Army, the mission came first. Always.
That same mentality helps in the digital world. I don’t care who wrote the broken code—I care how we fix it together.

When I left the military, I expected the silence. What I didn’t expect was the noise in my own head.

No mission. No orders. No structure. Just... stillness. And if you’ve served, you know that kind of silence can be loud.

I struggled with anxiety, restlessness, and moments I couldn’t explain. I didn’t want to admit it, but I needed help.
That help came with four legs, droopy ears, and a heart bigger than mine.

When people hear “cybersecurity,” they think hoodie-wearing hackers in dark rooms.

But I see something different: a digital battlefield. Threats. Defense. Strategic operations.

Sounds a lot like the military, doesn’t it?

That’s why I believe veterans are perfect for cybersecurity roles—and most don’t even realize it.

The Overlap Is Real

Think about it:

People assume leadership comes from rank. In the military, sure—rank opens the door. But real leadership? That’s earned in the dirt, not on paper.

I was a 13B in the Army. Our job? Move fast, fire faster, and stay alive. Every fire mission depended on precision, trust, and execution under pressure.

That’s where I learned the truth about leadership.

The AI Coalition Network has developed a comprehensive educational resource titled “Pricing Strategies for AI Products and Services.” This initiative seeks to demystify the monetization strategies employed in the AI industry, providing learners with a foundational understanding of how AI products are priced and sold in the market.

When I first stood behind a 155mm howitzer, I never imagined I’d one day stand behind a keyboard writing Python code.

I served as a 13B Cannon Crew Member in the U.S. Army’s 2/3 Armored Cavalry Regiment. My job? Precision destruction. I was trained to fire accurately, adapt quickly, and function under intense pressure. At the time, I didn’t realize those very same traits would lead me into the world of cybersecurity and machine learning.

But here we are.

I used to operate artillery systems.
Now I operate terminal windows.

That may sound like a wild shift—from field manuals to machine learning, from radios to regex—but really, the mindset stayed the same.

The journey from tactical to technical wasn’t easy. But it made sense the more I leaned into the skills I already had.

Here’s what that transition looked like—step by step.

Step 1: Recognizing the Crossover

At first, I didn’t see the link. I thought:

No matter how tough you are, tech interviews hit different.

I’ve been through field missions, fire missions, and late-night movement under pressure—but walking into my first technical interview?

I was sweating like I was back in MOPP gear.

The truth is, tech interviews don’t just test your skills—they test your mindset. And for self-taught developers and veterans like me, they can feel like a whole new battlefield.

But the fear is beatable. Here’s how I approached it like a mission—and won.

I didn’t start coding to get a job.
I started because I needed something to keep me from falling apart.

Life after the Army hit me hard.
No structure. No squad. No mission.
Just too much silence—and way too many thoughts.

PTSD doesn’t always show up as flashbacks.
Sometimes it looks like restlessness, avoidance, anxiety.
Sometimes it looks like nothing at all—until it all hits you.

And weirdly enough, code helped me cope.

Startups move fast.
One minute you're coding a new feature, the next you're fixing a fire in prod at 2 a.m.

That kind of chaos?

Veterans were built for it.

As a former 13B turned tech builder, I’ve seen firsthand how well vets fit into the startup ecosystem.

We bring grit, urgency, and calm under fire—things that can’t be taught in a coding bootcamp.

Here’s why every startup should hire a vet.

1. We Thrive in Uncertainty

Startups are messy. Roles shift. Priorities change. Systems break.

No one warned me that learning to code would bring up so much... self-doubt.

Sure, I expected the hard concepts. The long hours. The Google rabbit holes.
But I didn’t expect to question if I even belonged in this industry.

“Am I smart enough?”
“Who am I to call myself a developer?”
“I’m too late. Too old. Too different.”

These voices hit hard—especially for veterans. We’re trained to execute missions. To move with confidence. But in tech? We start at square one.

And that can shake you to your core.