The tools that define professional software development are changing faster than most school curricula can follow. For parents raising children in Singapore today, that gap is more than academic — it is personal.

Something has been shifting quietly inside the world’s most valuable technology companies. Not a reorganisation, not a product launch, but something more structural than either. In April 2025, speaking at Meta’s LlamaCon conference, Microsoft chief executive Satya Nadella said that between 20 and 30 percent of the code his engineers work with is now written by Artificial Intelligence.

Around the same time, Google’s Sundar Pichai told investors that AI was generating more than 30 percent of Google’s new code — up from 25 percent just six months earlier. Meta’s Mark Zuckerberg went further, projecting that within a year, AI might handle roughly half of all engineering output on his company’s AI development. These were not speculative forecasts. They were operational reports from the people running three of the largest software organisations on earth.

What is less often discussed is the downstream implication — the one that does not land in earnings calls but sits in the back of every parent’s mind when they enrol their child in a coding class: if AI is writing the code, what exactly are we preparing our children for?

For most of the past two decades, the pathway into a technology career was legible and widely understood. Study computer science. Learn to write code in Python, JavaScript, or another mainstream language. Graduate. Get hired as a junior developer. Build up experience from there. That pathway is not broken. But it is bending.

Data from SignalFire, a San Francisco-based venture capital firm, found that fresh graduates represented just 7 percent of new hires at large technology companies in recent years — a significant reduction from prior cycles. A 2025 survey by LeadDev found that 54 percent of engineering managers believed that in the long term, junior developer hiring would drop as a direct result of the rise of AI coding tools. Entry-level job postings in technology fell noticeably between 2022 and 2024 across multiple major markets.

The evidence, overall, points not to the disappearance of technology careers but to their restructuring: the tasks that used to define entry-level work — writing boilerplate code, building basic features, debugging routine errors — are increasingly being handled by AI tools. What employers now want from early-career hires is something different. The rungs of the ladder that once existed — the slow accumulation of simpler tasks that built competency over time — are fewer than they used to be.

The World Economic Forum’s Future of Jobs Report 2025, which draws on surveys of more than 1,000 major employers representing over 14 million workers across 55 economies, found that nearly 40 percent of core job skills are expected to change by 2030. At the top of the list of skills growing in importance: AI and big data literacy. Alongside them: analytical thinking, creative thinking, resilience, and the ability to work alongside and direct intelligent systems.

The consensus among technology leaders, even as they accelerate AI adoption, is that the premium has moved: from the ability to produce code to the ability to think clearly about what to build and why.

Curriculum development is slow by design. Educational systems are built to be stable, broadly transferable, and resistant to short-term disruption. But the pace of change in the technology sector over the past three years has been genuinely unusual. Most children’s technology programmes were built around assumptions that made sense five years ago: that learning Python or JavaScript was a durable investment, that syntax fluency was a meaningful differentiator, and that the ladder from junior developer to senior engineer remained intact. Those assumptions are not wrong, exactly. They are increasingly incomplete.

Singapore’s government has been alert to parts of this. From 2025, new AI for Fun modules — covering generative AI, prompt engineering, and smart robotics — are being introduced across government and government-aided schools. Singapore’s National AI Strategy 2.0 commits to building a pipeline of AI-fluent talent. The framing, from government, is already shifting. The question is whether the broader education ecosystem is shifting with it.

For parents in Singapore choosing technology education for children aged four to nineteen, the landscape can feel bewildering. Some programmes are genuinely rethinking their approach. Others have added AI-themed content onto existing frameworks without changing the underlying logic of what is being taught. Children who learn to code in any language are building logical reasoning skills that transfer. The concern is more specific: that children who spend years memorising syntax rules may be investing in a skill that, by the time they enter the workforce, has become a smaller part of what employers actually need.

The skills that do appear to be durable — based on employer surveys, workforce data, and the stated priorities of technology companies — are the ability to think clearly about problems, to understand how systems interact, to direct technology towards meaningful ends, and to adapt when the tools change.

Empire AI — formerly Empire Code, a Singapore-based technology education school for children from age four to nineteen — is one of the more deliberate examples of an institution attempting to respond to these shifts in a structured way. The school’s recent curriculum overhaul started from a question: does what we are teaching still reflect how technology is actually built and used today?

Robotics remains central and is expanding, now incorporating AI-enabled tools. Block programming remains, but with a shift in emphasis — less time on the mechanics of making code execute, more time on the reasoning behind it. Game development continues, now incorporating entrepreneurship. App development for older students is being redesigned around how applications are actually built today, including working with AI tools, connecting to live data sources, and deploying functioning projects online.

Traditional syntax-heavy programming in languages like Python and JavaScript is being retired as a core curriculum focus. In its place: learning to build using AI as a creative and technical partner — understanding how to describe what you want to create, how AI interprets and executes those instructions, how to evaluate and refine the results, and how to bring working projects into the real world.

Children who are ten today will enter the job market in the mid-2030s. The skills that will matter to them then are being shaped, in part, by the education choices made now. The World Economic Forum’s research is unambiguous on one point: the skills gap is the single biggest barrier to workforce transformation, cited by 63 percent of employers in its 2025 survey. Closing that gap requires decisions made when children are young enough for learning to feel like play.

When my child is an adult, will they feel capable? Will they understand the technology around them well enough to shape it, not just use it? Will the years they spent learning have given them something that transfers — not just to the jobs that exist today, but to the ones that will exist when they get there? Those are not questions with clean answers. But they are the right questions to be asking.

Empire AI is headquartered in Singapore and serves students across the region.

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