Coding is being automated at a frenetic pace, and there’s much uncertainty about coding jobs a few years down the line, but some tech leaders believe that it is still valuable for students to study programming.
In a landscape filled with anxiety about the future of traditional technical roles, Demis Hassabis, the influential CEO of Google DeepMind, offers a clear piece of advice for the next generation: don’t abandon the fundamentals. He argues that even as artificial intelligence automates complex tasks, a solid grounding in programming and STEM fields will be the critical differentiator for those who want to thrive in the coming decade.
When asked what advice he would give a graduate today for a lifetime of work in the age of AI, Hassabis offered a nuanced and optimistic perspective. “My view currently, and of course this is changing all the time with the technology developing, but right now, if you think of the next five to 10 years, the most productive people might be 10x more productive if they are native with these tools,” he explained.
His primary encouragement for students is to dive headfirst into the new wave of AI systems. “I think kids today, students today, my encouragement would be to immerse yourself in these new systems. Understand them,” Hassabis urged. He emphasized that foundational knowledge remains key. “I think it’s still important to study STEM and programming and other things so that you understand how they’re built. Maybe you can modify them yourself on top of the models that are available. There are lots of great open-source models and so on.”
Beyond understanding how the models are built, Hassabis points to a new layer of skills that will define expertise. He advises students to “become incredible at things like fine-tuning, system prompting, and system instructions. All of these additional things that anyone can do, and really know how to get the most out of those tools.” He recommends applying these skills immediately: “Do it for your research, work, programming, things that you are doing on your course. And then come out of that being incredible at utilizing those new tools for whatever it is you’re going to do.”
Hassabis envisions this synergy between human expertise and AI tools leading to a period of unprecedented individual capability. “I think for the next few years, it’s most likely to be that we’ll have these incredible tools that supercharge our productivity and make us really useful for creative tools, and actually almost make us a little bit superhuman in some ways in what we’re able to produce individually,” he elaborated. “So I think there’s going to be a kind of golden era of the next period of what we’re able to do.”
Hassabis’s advice cuts through the narrative of pure job displacement and instead outlines a pathway to augmentation. The “10x programmer” of the past was an individual with exceptional innate talent; the 10x programmer of the future, as he sees it, will be the one who can masterfully wield AI. This mastery isn’t about simply using a chatbot to write code; it’s a deeper, more technical skill set. Understanding programming allows a user to craft more effective “system prompts” that set the context for an AI model, while knowledge of STEM principles enables them to critically evaluate the output. The ability to “fine-tune” open-source models like Google’s Gemma or Meta’s Llama on specific datasets is becoming a crucial skill that elevates a generic tool into a specialized, high-performance assistant.
We are already seeing this “golden era” begin to dawn in various fields. Google DeepMind’s own breakthroughs, such as using AI to discover new math equations or solve complex biological problems like protein folding with AlphaFold, exemplify this human-AI collaboration. In these scenarios, scientists and researchers who understand the underlying principles of their domain can use AI to explore possibilities at a scale and speed that was previously unimaginable. For students, the message is clear: the path to becoming “superhuman” in the age of AI isn’t to abandon technical knowledge but to fuse it with a deep, practical mastery of the new tools it has created.