Human Deep Learning in the Age of AI
AI can do a lot—but not the deep work. Here’s why the next edge is learning how to actually
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Over the last few years, we’ve all been living through this massive shift—AI is now a PhD in everything. It knows the answer to almost anything, one prompt away. It can write your code, draft your content, summarize your notes, and even explain your own job back to you.
But if AI already knows it all, then what do we actually need to learn anymore?
That question has been sitting with me lately, and I’ve started calling the answer “human deep learning.”
It’s this idea that as AI takes over more surface-level tasks, our job is to move up—to think more strategically, more deeply, and more creatively than before. Every time AI gets better at doing your job, you get promoted. Your role shifts. You go from doing the work to understanding the work.
If you’re a developer, you start thinking more like a product manager.
If you’re in operations, you start thinking like a systems designer.
AI fills in behind you. You move up the stack.
The pilot lesson that changed everything
A few years ago, I decided to get my pilot’s license. I’ve always loved aviation—it’s been this dream tucked away for years. But I realized something as life got busier (marriage, kids, building businesses): margin disappears over time. If you don’t make time for certain things now, you probably never will.
So I finally started flight school.
And I quickly learned something—there are no hacks in flying.
You can’t Google your way to a pilot’s license. You can’t “prompt” your way through turbulence. You either know it, or you don’t. You either pass your check ride, or you don’t. There’s no shortcut.
For the first few years, I was dabbling. Doing a few lessons here, studying there, then taking months off. I was enjoying the fun parts of it—flying—but I wasn’t actually learning deeply enough to finish.
And that’s exactly what a lot of us do with work right now. We skim. We prompt. We half-learn. We get familiar with topics, but we don’t master them.
This year, I decided to go all in—to actually go deep. I started studying seriously, drilling hundreds of note cards, learning regulations, weather systems, mechanics, aerodynamics—all of it.
That process of going deep reminded me what real learning feels like again. The kind where you’re not memorizing for a test—you’re understanding because lives literally depend on it.
How this ties into building products
At Inovo, we had a similar wake-up moment with our process.
We’d been using Shape Up for a while—loved it, taught it, built with it. We thought we were really good at it. Like, 9 out of 10 good.
Then we started doing sessions with Ryan Singer, the guy who actually created Shape Up.
He spent three hours with us shaping one small feature. Just one.
And it hit us—we weren’t 90% there. We were 9% there.
We realized the difference between knowing about a process and mastering it. Between learning it from a book and internalizing it at a craft level. It required slowing down, thinking deeply, asking better questions, and zooming way into the details.
And the crazy part? It didn’t make things slower. It made everything faster.
Once you understand something at that level, decisions come quicker, tradeoffs are cleaner, and your output gets sharper.
That’s human deep learning in action.
Depth is the new edge
In this AI era, surface-level learning is cheap.
Everyone can “vibe code.” Everyone can throw something into ChatGPT, get a working prototype, and feel productive.
But what separates builders now is depth.
The people who understand how and why something works—those are the ones who will keep creating value long-term. They don’t just know how to use the tools; they know when not to.
So when you’re building products—or learning a new stack, or leading a project—don’t just copy-paste what works. Go a few layers deeper:
- Learn the language of that domain.
- Understand the mechanics behind it.
- Ask the dumb questions until it finally makes sense.
- And when it does, turn around and teach it to someone else.
Learning vs. understanding
When you train to become a pilot, you take two major tests:
- A knowledge test—a multiple-choice exam that checks if you’ve memorized the material.
- A check ride—where an examiner actually grills you for hours and then watches you fly.
That’s the part that matters. And it’s the same in tech, business, design—everything.
AI can pass the knowledge test for you. But it can’t take the check ride.
Going deep in your own work
Here’s what I’ve learned from both flying and building:
- Slow down. Take the time to really shape things before you build.
- Ask why. Don’t stop at “that’s how it works.”
- Study long-form content. Read the manuals, watch the 3-hour breakdowns.
- Use AI to learn smarter. Let it quiz you, explain, or walk through concepts step-by-step.
- Get curious. Go down rabbit holes. Learn the parts no one else bothers to.
You stop guessing. You stop rebuilding. You start creating things that actually last.
The real difference-maker
Everyone has access to AI now.
The playing field is flat.
But depth—that’s what sets people apart.
Depth gives you judgment.
It gives you creativity.
It gives you leverage.
You can fake “smart” with AI for a while, but you can’t fake mastery.
Depth is what keeps you from being replaced by the tools you use.