You’ve probably seen the headlines lately, maybe even from big names like the CEO of NVIDIA: “Coding is dead.” The idea is that AI will soon do all the work, so there’s no need for kids—or anyone, for that matter—to learn how to code.
When I first heard this, a part of me felt a jolt. Is the career I’ve dedicated myself to about to become obsolete? But after taking a breath and looking at the bigger picture, I realized this isn’t the death of coding. It’s the next step in its evolution, a pattern that has been repeating for decades.
We’ve Been Here Before
The way we write code today is nothing like how our seniors did it. The generation before us didn’t have the high-level languages and sophisticated tools we take for granted. In the early days of computing, programming was a grueling, manual process. Think of loading programs from cassette tapes or using low-level Assembly language, where you had to communicate almost directly with the computer’s hardware.
Then came the evolution. High-level languages like C appeared, which were then improved upon by object-oriented languages like C++. Later, scripting languages like Python made complex tasks, especially in machine learning, much more accessible.
Each step in this journey was about one thing: abstraction. We’ve consistently built tools and languages to make programming easier, allowing us to focus more on solving the problem and less on the nitty-gritty details of the machine. AI is simply the next, most powerful layer of abstraction we’ve ever had.
The Reality of “AI Doing the Work”
The sensational claim is that AI will replace programmers entirely. But in reality, the headlines often leave out the most important part: the crucial need for human intervention.
Yes, AI can generate code. It can build a basic website from a prompt. But what it often produces is a starting point, not a final product. I’ve seen AI-generated code that is inefficient, buggy, or what I’d call “digital waste.” It gets the job done on the surface, but it’s not optimized, secure, or scalable.
Why? Because these AI models learn from the vast amount of publicly available code on the internet—tutorials, forums like Stack Overflow, and open-source projects. They aren’t learning from the highly-optimized, proprietary, production-level code that powers companies like Microsoft, Google, or Apple. That code is private.
The result is that someone still needs to debug the AI’s output, optimize it, ensure it’s secure, and integrate it properly into a larger system. That someone is a skilled developer.
An Opportunity, Not a Threat
Instead of seeing AI as a threat, I see it as a powerful assistant. A project that might have taken me ten days to build from scratch can now be prototyped in three or four days with the help of AI tools. This doesn’t make me obsolete; it makes me more efficient and valuable.
Furthermore, this trend is creating a new type of demand. As more people use AI to “vibe code”—creating applications without deep technical knowledge—there will be an explosion of software that needs fixing, maintaining, and scaling. And who will do that? Experienced developers who understand the fundamentals. Fixing buggy, AI-generated code is often much harder than writing clean code from scratch, and that’s a skill that will be in high demand.
So, What’s the Takeaway?
Don’t panic. Programming isn’t going anywhere. The need to create software, build websites, and solve complex problems with technology is only growing.
What is changing is the way we do it. The future isn’t about being replaced by AI; it’s about partnering with it. Our job as developers is to adapt, just as it has always been. Learn how to use these AI tools effectively. Master the art of prompt engineering. But most importantly, strengthen your core understanding of problem-solving, system architecture, and clean coding principles.
Because when the AI gets stuck, or when its code breaks, they’ll still need a human to figure out why. And that human could be you.