There was a time when saying “I studied at Stanford” worked almost like a magic spell in tech. Doors opened, interviews happened, trust was assumed. It wasn’t arrogance, it was just how the system worked. If you made it through the gates of an elite university, especially one sitting in the heart of Silicon Valley, your future looked… safe. That story is slowly falling apart. Not with drama, not with rebellion, but with quiet, factual statements from people who helped build the tech world as we know it. Sergey Brin is one of them. And when he talks about education, hiring, and artificial intelligence, he’s not speculating. He’s describing what’s already happening. --- ## Why Sergey Brin chose computer science During a talk with students at Stanford, Brin shared something that feels almost countercultural today. He didn’t choose computer science because it was the “right move” or a guaranteed career path. He chose it because he was genuinely curious. He wanted to understand computers, how they worked, and what they could become. That detail matters more than it seems. Today, many students pick fields based on fear. Fear of automation. Fear of AI. Fear of choosing something that might not “pay off.” Brin’s perspective goes in the opposite direction. He argues that choosing a field just to avoid automation doesn’t really make sense, because AI is advancing everywhere, not only in programming. If your motivation is only safety, you’re likely to end up disengaged. Curiosity, on the other hand, keeps people learning even when tools change, and they always do. That ability to keep learning turns out to be far more durable than any single technical skill. --- ## What Google’s hiring practices quietly reveal One of the most striking points Brin has made recently is that Google hires a large number of people without university degrees. Not as an experiment. Not as a statement. Simply because they’re good. Many of these candidates are self-taught. They learned through documentation, online communities, open-source projects, and years of trial and error. When they sit down for interviews, what stands out isn’t where they studied, but what they can actually do. This shift didn’t happen because Google decided degrees don’t matter. It happened because degrees stopped being the best signal of ability. The internet changed access to knowledge, and practical proof of skill became easier to show than ever before. From a hiring perspective, this creates a very real question. If someone can solve the problems, collaborate with the team, and learn quickly, what exactly does a diploma add to that evaluation? --- ## When elite degrees stop being a guarantee This change goes beyond Google. As AI reshapes the labor market, even degrees from top universities are no longer a guaranteed entry ticket into elite tech jobs. For decades, companies used academic pedigree as a shortcut. It was efficient. It reduced risk. But AI has exposed how limited that shortcut really was. As machines handle more routine tasks, companies are rethinking what they actually need from humans. The answer is rarely “someone who passed the right exams.” It’s someone who can think clearly, adapt fast, and work with tools that didn’t exist a year ago. That’s why companies like Google, Microsoft, Apple, and Cisco have reduced or removed degree requirements for many roles. Not because education is worthless, but because credentials alone don’t predict performance very well anymore. --- ## AI didn’t lower standards, it moved them There’s a common fear that AI is making hiring easier, that the bar is dropping. In reality, the opposite seems to be happening. The bar hasn’t disappeared. It’s just moved. Tasks that can be automated are no longer where human value lies. What matters now is judgment, problem framing, creativity, and the ability to learn continuously. Those qualities are hard to capture on a transcript. This is where Brin’s emphasis on curiosity becomes very concrete. Curious people experiment earlier. They adapt faster. They see AI as a tool to explore, not a threat to avoid. In an environment where change is constant, that mindset becomes a competitive advantage. --- ## What this means if you’re just starting out For students and early-career professionals, this new reality can feel unsettling. The old path was stressful, but clear. Study hard, get into the right university, follow the pipeline. The new path is messier. More open, but also more demanding. There’s no single formula anymore. What’s expected is evidence. Projects. Real work. Proof that you can learn on your own and keep learning. Universities still matter. They offer structure, mentorship, deep theory, and networks. What they no longer offer is certainty. A degree can help, but it doesn’t finish the story for you. --- ### Education didn’t lose value, credentials lost exclusivity One important distinction runs through all of this. Learning itself hasn’t been devalued. What’s changed is the monopoly that formal credentials once had. Knowledge can now be demonstrated in many ways. Through open-source contributions, startups, research, products, or years of hands-on experience. The signal has diversified. Sergey Brin’s comments resonate because they align with what many people already feel. The system didn’t collapse. It evolved. And it’s still evolving. --- ### Sources https://www.yahoo.com/news/articles/google-cofounder-reveals-tons-recent-231500103.html https://timesofindia.indiatimes.com/technology/tech-news/google-founder-sergey-brin-i-chose-to-study-computer-science-because-i-had-/articleshow/126640658.cms https://www.storyboard18.com/trending/as-ai-reshapes-hiring-even-stanford-degrees-are-no-longer-a-guaranteed-ticket-to-top-tech-jobs-87591.htm In the end, what’s left isn’t panic or nostalgia. It’s a quieter realization. The ladder didn’t disappear. It just stopped being vertical.