New Delhi, April 16 -- Remember the days, not too long ago, when we'd wave frantically at a yellow taxi, hoping it would stop? Today, we just open an app, tap a few buttons, and a cab pulls up to our doorstep. No need to explain directions or argue about the route-the app handles it all. That's how quickly things have changed.

With the rapid advancements of AI, careers are also no longer straight lines. They're more like zigzags filled with diverse roles and industries. The ones who keep evolving with the times are the ones who stay in the game.

Now take coding. When Amjad Masad, the CEO of Replit, said AI might eventually take over what coders do, it set off alarm bells. And sure, that's a scary thought. But as someone who works closely with students and young professionals, I'd say-don't panic. Of course, the statement is bold and reflects a growing sentiment in the industry: AI tools like GitHub Copilot, ChatGPT, and Replit Ghostwriter are becoming more capable, raising the question-is traditional coding becoming obsolete? There's no doubt that AI is changing how software is written. But then, let's make it clear that coders will evolve and not disappear in the age of AI. To answer that, we need to unpack both the promise and the limitations of AI in software development.

Rise of AI-assisted coding

There's no doubt that AI is changing how software is written. Tools powered by large language models can now write boilerplate code, fix bugs, suggest entire functions, and even generate basic applications from plain English instructions. These developments have drastically lowered the barrier to entry for many tasks that once required deep technical knowledge.

Startups and individual developers are already reporting increased productivity. In some cases, companies have accelerated product timelines because AI tools took over repetitive tasks. This shift is comparable to how calculators changed math education or how Google changed the way we remember facts-not by eliminating the need for human intelligence, but by redefining what skills are most valuable.

AI vs humans

While it's tempting to imagine AI writing flawless code and rendering coders jobless, reality is more nuanced. Software engineering is not just about typing code-it's about understanding problems, designing systems, managing trade-offs, testing solutions, and communicating with stakeholders. These are human tasks.

Moreover, AI models, for all their brilliance, are still prone to hallucinations, bias, and logical errors. They generate code based on patterns seen in their training data, not a true understanding of logic or intent. This means that human oversight remains critical-especially in high-stakes areas like cybersecurity, healthcare, or finance.

Coding as foundational skill

Even if AI writes most of the code in the future, understanding how code works will still be an essential skill-much like how understanding math is still important, even if you use Excel or a calculator. Learning to code builds computational thinking, logical reasoning, and structured problem-solving. These skills are transferable and increasingly relevant in fields beyond traditional software development-such as biology, marketing, logistics, and policy design.

Rather than fearing redundancy, coders should embrace the shift. Learn how to collaborate with AI tools, not compete against them. Build a strong foundation in logic, systems thinking, and ethics. Stay curious, and treat AI as a co-pilot rather than a replacement. Ultimately, technology is always evolving. And so must we.

The author is the Group CEO of Techno India Group, a visionary and an educator. Beyond his corporate role, he is also a mentor who guides students towards resilience and self-discovery

Published by HT Digital Content Services with permission from Millennium Post.