Junior Developers Are Coding, But Are They Learning?

The Speed Trap: Code Without Comprehension

There’s something unsettling happening in software development. A quiet erosion of knowledge disguised as progress.

Every junior dev I meet has Copilot, Claude, or GPT humming in the background, shipping code at a pace that would’ve been unthinkable a decade ago. But the moment you scratch beneath the surface, the illusion shatters.

Ask why the code works? Silence. Ask about edge cases? Blank stares. Ask about trade-offs? A confused shrug.

It’s like watching a chef assemble a five-star meal using YouTube tutorials—looks great, but don’t ask them what “deglazing” means. We’re churning out code faster than ever, but at what cost? The struggles that once built strong engineers, the hard-earned lessons from debugging, refactoring, and breaking things—that process is disappearing. And with it, the depth that separates great developers from those who just move text around.

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When We Had to Actually Think

There was a time—not that long ago—when developers lived on Stack Overflow. If you hit a problem, you Googled it. If you were lucky, you’d land on a post where a seasoned dev had taken the time to not just solve the issue but break it down in a way that made you understand it.

I still remember a question I asked 12 years ago. The top answer? A masterclass from a developer who didn’t just tell me what to do but expanded my thinking. I learned things I wasn’t even looking for. Some of those insights are still burned into my brain today.

And here’s the kicker: That answer was written for free. No AI, no automation—just one developer passing knowledge to another.

Meanwhile, junior devs today:

👶 “I don’t know how to fix this error.” 🤖 types vague question into AI ✨ Magically gets working code 🙌 Pushes to production without reading a single line 💥 Production explodes 2 hours later

Back in our day, if you had a question and no Stack Overflow answer existed, well… tough luck. You had to suffer. And suffering built character.

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AI Is Fast, But It’s Shallow

Here’s the tradeoff we don’t talk about enough:

• AI gives instant answers—but shallow understanding.

• Stack Overflow and deep research take longer—but build real knowledge.

Think of it like fitness: Using AI is like taking steroids—you’ll get results fast, but without the fundamental strength. Stack Overflow was like old-school weightlifting. Painful. Slow. But you actually got stronger.

Great developers aren’t just people who write code. They’re people who think in systems, understand trade-offs, and can troubleshoot at a fundamental level. That skill isn’t built by copying answers. It’s built by struggling through problems and coming out smarter on the other side.

I’m not anti-AI—I use it every day, and I’m even building AI-driven tools. But let’s be real: The way we’re using AI is making us worse engineers.

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How to Actually Learn in the Age of AI

AI isn’t the enemy. The way we use it is. So how do we fix this?

1. Interrogate AI, don’t just accept its answers. Ask why a solution works. Push for explanations. Make the tool teach you instead of just handing you a fix.

   Think of it like that one strict professor who always answered your questions with another question. Annoying? Yes. Effective? Absolutely.

2. Seek out real discussions. Reddit, Discord, forums—anywhere seasoned devs talk. The gold isn’t just in answers but in how experienced engineers think.

3. Reinvent code reviews. Don’t just check if the code runs—ask why a certain approach was taken. What other options were considered? The best teams treat reviews as mentorship, not just debugging.

4. Build things from scratch. AI can generate an authentication system in seconds. But do it yourself at least once. Yes, it’ll take longer. Yes, your first version will be worse. But that process builds intuition—and intuition compounds over time.

   It’s like cooking: You can DoorDash every meal and survive. But until you burn a few pancakes yourself, you’ll never really know how to cook.

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The Future: Choose Depth Over Convenience

AI isn’t slowing down. Open-source models are accelerating, and we’ll have AGI in our pockets before long. But the real question isn’t whether we use AI—it’s how we use it.

We’re already seeing the consequences of shallow learning. Junior devs who can ship code but can’t explain it. Engineers who can debug only when the solution is spoon-fed to them. Companies hiring “fast” developers, only to watch their projects turn into technical debt nightmares.

This is our moment to decide: Do we want to be button-pushers or problem-solvers?

If we get this wrong, we’ll end up with an entire industry full of developers who can copy-paste solutions but have no idea what they’re doing. And that’s a disaster waiting to happen.

So tell me—have you found a way to balance AI-driven speed with deep learning? Or am I just an old dev yelling at clouds? Either way, let’s figure this out together.