There’s a question we’re hearing more and more from parents, and it’s a fair one: “If AI can write code now, does my child really need to learn it?”

It usually comes with a story attached. A colleague who builds apps by describing them to a chatbot. A news segment about AI replacing programmers. And underneath it, a genuine worry — am I signing my child up to learn a skill that will be obsolete before they finish school?

We think about this question a lot. Not just because we teach coding, but because we use AI every week — our students learn alongside an AI tutor as part of their program. So here is our honest answer.

Coding was never really about typing code

Here’s the part that often gets missed: the point of learning to code was never the syntax. Nobody’s life was improved by memorising where the semicolons go.

What coding actually teaches is a way of thinking. Taking a big, messy problem and breaking it into small, solvable pieces. Following logic through to its consequences. Testing an idea, watching it fail, working out why it failed, and trying again. Sticking with a problem that doesn’t give up its answer in the first five minutes.

Educators call this computational thinking. We’d call it the most transferable skill a child can build — and AI hasn’t made it obsolete. It’s made it more valuable.

The calculator question

We’ve been here before. When calculators arrived, some people asked why children still needed to learn arithmetic. But the kids who understood numbers were the ones who could use calculators powerfully — they knew what to ask, and they could tell instantly when an answer didn’t make sense. The kids who didn’t understand numbers just trusted whatever the screen said.

AI is the same story at a much bigger scale. AI can produce code, essays, designs and answers in seconds — and it is often wrong in ways that look completely convincing. The question is no longer “can you produce the answer?” It’s “can you tell whether the answer is right?”

Children who understand how code works — how logic flows, where things break, what a sensible solution looks like — will be the ones directing AI: setting the problem, judging the output, catching the mistakes. Children who don’t will be limited to accepting whatever the machine gives them. That’s the real divide the next generation faces, and it has nothing to do with who can type the fastest.

What this looks like in our workshops

This is why our programs have evolved into a STEM School model rather than a “coding class.” Our students build capabilities across coding, robotics, electronics and engineering — and yes, they work with AI as part of that. They learn to use our AI tutor the way a good engineer uses any tool: ask sharp questions, check the answers, and understand what’s happening underneath.

We’re not preparing children for a world without AI. We’re preparing them to be the ones in charge of it.

That’s what we mean when we say we take students from curiosity to capability.