C in the Times of AI Link to heading

The AI coding revolution Link to heading

AI coding agents are everywhere. In just a couple of years they went from novelty to necessity in many software teams. Tools like Copilot, Cursor, Kiro, and a growing list of alternatives promise to write code faster than any human could. And they deliver — sort of.

Teams are shipping features at record speed. But there’s a catch. Without a structured approach, without someone who actually understands what the generated code is doing, quality drops fast. You end up with a codebase that looks impressive on the surface but crumbles the moment you need to debug it, scale it, or explain it to someone else.

Here’s the lesson many of us have learned the hard way: AI is not a shortcut to learning. It’s a tool to automate things you’re already good at. If you don’t understand the fundamentals, no amount of generated code will save you. You can’t prompt your way out of ignorance — the machine just gives you confident-sounding nonsense faster.

Deep knowledge still matters Link to heading

This points to something that should be obvious but often gets lost in the hype: having a deep technical background, following proven design patterns, and accumulating real experience still matter. A lot.

AI amplifies what you already know. If your foundation is solid, AI makes you faster and more productive. If your foundation is weak, AI just helps you produce bugs at scale. There’s no shortcut through the desert — you have to walk it.

Computers haven’t changed underneath Link to heading

Here’s the thing people forget when they get excited about the latest model or framework: the underlying workings of computers have not changed. Underneath all the layers of abstraction, it’s still binary code and raw math. CPU cycles, memory addresses, instruction sets — none of that cares about your shiny new framework nor prompt engineering skills.

The machine does what the machine has always done. It moves bits around according to very specific rules. If you want to write good software — or guide an AI to write good software — you need to understand those rules.

Why C: proximity to the machine Link to heading

This is where C comes in.

C gives you proximity to the hardware in a way that few other languages do. When you write C, you deal directly with memory management, data layout at the byte level, pointers, and the process of compiling and linking your code into actual machine instructions. There’s nowhere to hide. No garbage collector to save you, no runtime to paper over your mistakes.

Writing C is like taking the red pill. You see the machine for what it really is. And once you see it, you can’t unsee it. Every piece of software you write afterwards — in any language — benefits from that understanding.

Better foundations, better prompts Link to heading

All that low-level knowledge changes how you think about software design at every level. You start asking better questions. You notice when something is wasteful or fragile. You understand trade-offs that are invisible to someone who has only worked with high-level abstractions.

And here’s the practical payoff in the age of AI: developers with a strong systems background write better prompts. They provide better context, better constraints, and better guidance to AI coding agents. The result is higher quality generated code. You become a better director of the machine because you understand what the machine is actually doing.

C is still critical in production Link to heading

Beyond the educational value, C is far from a relic. It provides fast runtime performance that matters for critical software. The Linux kernel is written in C. Embedded devices run C. Real-time systems, networking stacks, database engines — C is everywhere in the infrastructure that the modern world runs on.

These domains aren’t shrinking. If anything, with the explosion of IoT devices and the growing demand for performance-sensitive AI inference at the edge, C is more relevant than ever. The language has been around for over fifty years and it’s still standing. Long after the hype cycle moves on, C will still be there, quietly running the world.

AI lowers the barrier to learn C Link to heading

Here’s the good news: AI also makes learning C more accessible than it used to be. What once required thick textbooks, cryptic man pages, and hours of staring at segfaults can now be supplemented with AI-assisted learning. You can ask an AI to explain what a pointer is, walk you through memory allocation, or help you understand why your program just crashed.

The barrier to entry is lower than ever. The excuses are running out.

Conclusion Link to heading

In the times of AI, I’m learning C, and you should too.

Not because AI is going away — it’s not. But because investing in deep, foundational knowledge is the best way to stay relevant and produce quality software. Whether you write it by hand or guide an AI to write it for you, understanding the machine underneath makes all the difference.

The future belongs to developers who can think at every level of the stack. C is how you get there.