AI can already write functions, scaffold projects, fix bugs, even suggest entire architectures. And it’s getting better all the time.
So what’s the point of learning how to write a loop? Or manage memory? Or reason through system design?
Will any of that still matter in a year?
It’s a fair question. And one a lot of developers are quietly asking. If AI can already do so much (and is improving so quickly), what’s the value of investing in foundational skills?
It’s not that fundamentals have stopped mattering—it’s that their role has changed.
They’re no longer solely about executing tasks by hand. They’re about understanding how things work deeply enough to collaborate with the machine: to guide it, correct it, and shape its output into something truly useful.
Better inputs, better outcomes
Fundamentals sharpen your prompts. They help you translate intent into instruction. Developers with a strong grasp of core concepts, whether in syntax, architecture, or systems thinking, are better equipped to tell AI exactly what they want. They know the right terms to use, the edge cases to account for, the structure to aim toward.
And when AI gives an incomplete or flawed response (as it often does), those same fundamentals make it easier to debug, iterate, and keep moving. You don’t just get better output: you get there faster, with fewer misfires.
As Andrew Ng recently said:
“Learn about AI and take control of it, because one of the most important skills in the future will be the ability to tell a computer exactly what you want, so it can do that for you.”
It’s like sitting two people down with the same AI music generator. Both should be able to produce something. But the person who’s steeped in music theory and composition? They’ll prompt with more nuance, recognize when the harmony clashes or the tempo drags, and refine the result into something truly impressive. More importantly, they’ll get to what they envisioned faster, because they can shape the tool instead of just reacting to it.
Tools assist, but knowledge directs
That’s what knowledge does in the AI era. It becomes a creative and corrective force. It puts developers in control: not just accepting what the system offers, but pushing it somewhere better.
It’s also how developers scale responsibly. Fundamentals equip you to make smarter decisions around performance, security, cost, and complexity. When AI gives you five ways to solve a problem, they’re how you choose the right one.
The ground is shifting, but the ceiling is rising
And fundamentals keep you adaptable. As AI abstracts away more of the tactical layer, the value of experience rises toward judgment, systems thinking, and problem framing. The baseline is changing, but the ceiling is rising, too.
So yes, the ground is shifting. But if developers are going to guide where this goes, not just ride along, then the fundamentals still matter.
They just matter differently now.