AI is Raising a Generation of Copy-Paste Coders

The Illusion of Speed

Something has been gnawing at me for a while, and I need to say it out loud: We’re at a turning point in software development, and not necessarily for the better.

Every junior developer I meet is shipping code at lightning speed, powered by Copilot, Claude, or GPT running 24/7. On the surface, it looks like a golden age of productivity. But scratch beneath the surface, and you’ll find something troubling—many of them don’t actually understand what they’re building.

Sure, their code works. But ask why it works one way instead of another? Silence. Ask about edge cases? Blank stares.

The foundational struggle that used to define early programming experiences—the deep, sometimes painful learning that comes from debugging, refactoring, and truly understanding—is vanishing. We’re trading mastery for quick fixes. And while that feels good in the moment, we’ll pay the price later.

The Lost Art of Learning

I recently realized there’s an entire generation of developers who don’t even know what Stack Overflow is.

There was a time—before chatbots handed out answers like candy—when debugging meant diving deep. First, you’d Google your problem, hoping some poor soul had encountered it before. If you were lucky, you’d land on a Stack Overflow page where a seasoned developer had taken the time to craft a detailed, thought-provoking response.

I still remember one of my own Stack Overflow questions from 12 years ago. The top answer? A brilliantly written breakdown by a veteran dev—someone who not only answered my query but expanded my understanding beyond what I even knew to ask.

Can you imagine that level of detail, freely given, without AI in the middle? Someone sharing their expertise, not just solving the problem but teaching the principles behind it?

That experience shaped how I think about coding. And it’s something we’re rapidly losing.

AI Is Fast, But It’s Shallow

AI makes coding convenient, no doubt. Why wrestle with a problem when you can copy-paste a solution in seconds? But here’s the thing—convenience isn’t the same as competence.

Take a look at this tradeoff:

• AI gives you instant answers, but shallow understanding.

• Stack Overflow and deep research take longer, but they build true knowledge.

Think about the best developers you know. Did they get there by copying solutions? Or did they get there by struggling, experimenting, and learning from the wisdom of others?

I’m not anti-AI—I use it every day, and I’m even building AI-driven tools myself. But we need to be brutally honest about what we’re losing in this shift.

What Can We Do About It?

AI isn’t going away, and honestly, it shouldn’t. But if we want to produce developers who actually know what they’re doing, we need to rethink how we use it. Here are some ways to fix this:

1. Use AI as a teacher, not a crutch. When AI gives you an answer, don’t just accept it. Ask why it works. Push for explanations. Challenge it.

2. Engage in real discussions. Find places where smart developers hang out—Reddit, Discord, Mastodon, wherever—and participate. Read debates, ask questions, and absorb knowledge beyond just “what works.”

3. Change how we do code reviews. Don’t just check if the code runs. Start a conversation: What alternatives were considered? Why this approach over another? Make the process of thinking as important as the result.

4. Build things from scratch—sometimes. Yes, AI can generate an authentication system in seconds. But force yourself to build one manually at least once. You’ll write worse code, but you’ll actually understand it. And that understanding will pay dividends.

The Future: Balancing Speed with Depth

We’re already past the point of no return. AI models are advancing rapidly, and soon enough, AGI will be in our pockets. But the future of coding isn’t about whether we use AI—it’s about how we use it.

If we’re not careful, we’ll end up with a generation of developers who can produce endless lines of code but have no real understanding of what they’re doing. And that’s a problem waiting to explode.

So, what’s your take? Have you found ways to balance AI-driven efficiency with real learning? Or am I just an old developer yelling at clouds? Let’s figure this out together.