The Decline of Real Coding: Why New Programmers Can’t Code Without AI

The Google Generation of Coders

Back when I first started coding, we didn’t have AI assistants to autocomplete our code or Stack Overflow to hand us ready-made solutions. We had to actually figure things out. That meant digging through documentation, experimenting with different approaches, and learning through trial and error. Today, though, I see a new wave of programmers who rely so heavily on Google and AI that if you took away their internet access, they’d be completely lost.

Coding Without Understanding

The biggest issue isn’t just the reliance on external sources—it’s the lack of deep understanding. Many newcomers see coding as a process of copying and pasting rather than problem-solving. They find a snippet online, tweak it just enough to make it work (often without fully understanding it), and move on. But the moment they’re placed in a situation where they can’t look up a solution, they freeze.

1. The Copy-Paste Epidemic

I’ve worked with junior developers who don’t even try to understand what their code is doing. The second they hit an error, their instinct isn’t to debug—it’s to Google the exact error message and copy whatever answer they find. Instead of learning why something isn’t working, they rely on quick fixes. And the worst part? They don’t even test alternative solutions; they just assume the first answer is correct.

2. The Rise of AI Coding Assistants

AI tools like GitHub Copilot and ChatGPT are great, but they’ve become a crutch. I’ve seen developers use them to generate entire codebases without actually understanding how the code works. It’s scary because while AI can help speed up development, it’s no replacement for knowing how to think through a problem. If you can’t write a simple function without AI, are you really coding?

3. Lack of Fundamentals

A lot of new programmers struggle with the basics, and it shows. Ask them to write a sorting algorithm from scratch, and they’ll look at you like you’re speaking another language. Here are a few areas where I see major gaps:

• Data structures and algorithms – If you don’t understand how an array or a linked list works, you’re going to struggle down the road.
• Memory management – Languages like Python and Java handle this for you, but that doesn’t mean you shouldn’t know how it works.
• Debugging skills – I’ve met programmers who don’t know how to read a stack trace. Instead of stepping through their code logically, they just Google for solutions.

The Importance of Independent Problem-Solving

Programming is about problem-solving. If you strip away Google, a good programmer should still be able to break down a problem, write functional code, and debug errors logically. The issue isn’t that programmers are using tools—everyone does—but that many new developers don’t know how to function without them.

How Can We Fix This?

• Focus on learning the fundamentals – Stop jumping straight into frameworks and libraries without understanding the core concepts first.
• Practice coding without searching online – Try solving problems without immediately looking for an answer. Struggle a little—it’s part of the learning process.
• Get better at debugging – Instead of pasting an error message into Google, read it, understand it, and debug it yourself.
• Use AI as a tool, not a crutch – AI is helpful, but don’t let it do all the thinking for you.

Conclusion

The modern programming world has made coding more accessible, but it’s also created a generation of developers who struggle to code independently. Google and AI should be tools, not a substitute for real knowledge. If you want to be a competent programmer, don’t just memorize answers—learn how to think through problems, experiment, and actually understand what’s happening under the hood. Because at the end of the day, if you can’t code without the internet, can you really call yourself a programmer?