Top Programmers Are Going Back to Hand-Coding

Yeah. That Arnold Schwarzenegger.

So do Codie Sanchez, Scott Galloway, Colin & Samir, Shaan Puri, and Jay Shetty. And none of them are doing it for fun. They're doing it because a list you own compounds in ways that social media never will.

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For the last two years, the story was simple: AI will write most of the code. Tools got better, faster, and more popular. Big companies pushed hard in this direction. At Google, leaders said around 75% of new code is now generated by AI. At Anthropic, estimates go even higher, between 70% and 90%.

On the surface, it looks like AI has already won.

But inside developer communities, something different is happening.

Top programmers are starting to go back to hand-coding.

The conversation picked up after comments from Sam Hogan, CEO of Inference.net. He shared that many elite engineers are choosing to write more code themselves again.

Not because AI is useless.

But because it is not perfect.

Many developers say AI-generated code often looks correct at first. But once you dig deeper, problems appear. Bugs, edge cases, messy logic, and unclear structure. Developers sometimes call this “slop” code that works a little, but not cleanly.

And fixing that slop can take more time than writing the code from scratch.

AI promises speed. And in many cases, it delivers.

You can generate hundreds of lines of code in seconds. You can build a basic app in a day. You can move faster than ever before.

But speed is not everything.

Developers are now talking about the hidden cost: debugging.

When AI writes code, it does not truly “understand” the system like a human does. It predicts patterns. It guesses what looks right. That works well for simple tasks. But in complex systems, small mistakes can create big problems.

So developers spend hours:

In some cases, using AI actually slows them down.

There is also a human side to this story.

Many programmers say they simply enjoy writing code.

Hand-coding gives a sense of control. You know why every line exists. You can design clean systems. You can think deeply about problems.

Languages like Rust and Zig are often mentioned in this context. They are powerful, precise, and require careful thinking. Developers who use them often care about performance, safety, and clarity.

For these programmers, coding is not just output. It is craft.

AI, on the other hand, can feel like copy-paste at scale.

This does not mean developers are rejecting AI completely.

In fact, most are doing the opposite.

They are using AI in a more balanced way.

AI is great for:

But when it comes to core logic, architecture, and critical systems, many developers prefer to write code themselves.

This hybrid approach is becoming more common.

Think of AI as an assistant, not a replacement.

AI is very good at scale.

It can generate code faster than any human. It can help teams move quickly. It can reduce the effort needed for routine tasks.

But coding is not only about speed.

It is also about understanding.

Good software requires:

These are areas where humans still have a strong advantage.

AI can suggest. Humans decide.

Another issue is experience.

Junior developers often rely heavily on AI. It helps them get unstuck. It helps them learn faster.

But senior developers see the gaps more clearly.

They can spot weak logic. They can see when code will break later. They know when something “feels wrong,” even if it works today.

That intuition is hard for AI to match.

So experienced programmers are more selective. They use AI carefully. And sometimes, they avoid it completely for important work.

What we are seeing is not a rejection of progress.

It is a correction.

The early excitement around AI coding tools created a belief: everything will be automated soon.

Now reality is setting in.

AI is powerful, but not perfect.

And programming is more than just producing code.

It is about building systems that last.

That is why many top developers are returning to fundamentals:

In short, they are treating coding as a craft again.

So what happens next?

Most likely, we will not see a world where AI replaces programmers.

Instead, we will see a new kind of developer.

Someone who:

Companies will still push AI adoption. The numbers will keep growing. More code will be generated by machines.

But the best engineers will stand out even more.

Because they will not just generate code.

They will understand it.

AI changed how we write code.

But it did not change what good code means.

Clean, reliable, and well-designed software still requires human thinking.

That is why, even in an AI-first world, many top programmers are going back to basics.

Not because they have to.

Because they want to.

AI can write code fast.

But humans still write it best.

—Sushila

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