College Students: Learn AI or Fundamentals?

I've been a software engineer for around 15 to 20 years, and I wanted to address a question I keep hearing a lot, especially from college students. If AI can write code now, do we even need to learn programming anymore? Now, I'm going to talk mainly about software engineering and computer science because that's my field, but I honestly think this advice applies to a lot of knowledge work and creative professions that are being transformed by AI. First of all, let's acknowledge reality. The AI revolution is real in the software engineering field. If you've been following the news, you've probably seen headlines saying that companies are generating 50%, 75%, or even 90% of their code with AI. From my own experience, I can tell you those headlines aren't as crazy as they sound. Today, I do most of my coding with AI coding agents. I describe what I want, I review what they generate, I ask them to improve it, and together we build software much faster than I ever could by myself. AI has completely changed the way I work, and honestly, I don't think we're going back. If you're graduating over the next few years, there's a very good chance that using AI will simply be part of your daily job. Companies aren't going to tell you not to use AI. In many cases, they're going to expect you to use it because it makes you more productive. So this isn't a video telling you to avoid AI. It's actually the opposite. Learn how to use AI. Use it every day. Experiment with it. Become really good at working with it. But here's the part that I think a lot of students are missing. I actually feel incredibly fortunate that I started my career before AI became this capable. For most of my career, if I wanted software to work, I had to write the code myself. I had to spend hours debugging problems. I had to learn why one solution was better than another. I had to understand algorithms, data structures, software architecture, design patterns, debugging techniques, and all the little best practices that experienced engineers eventually develop over time. Sometimes it was frustrating. Sometimes it took days to solve a problem. But looking back, those struggles were actually the reason I learned. Today, AI writes a lot of my code. But the reason I'm comfortable letting AI do that is because I have years of experience reviewing what it produces. I can usually tell when something looks wrong. I know when the architecture doesn't make sense. I know when the code might work today but become difficult to maintain six months from now. I know which suggestions are genuinely helpful and which ones should never make it into production. That judgment didn't come from AI. It came from years of learning the fundamentals. And that's the difference. AI is doing much more of the typing. I'm still doing the thinking. Now imagine you're a college student watching experienced software engineers use AI every day. It's easy to look at that and think, well, if professionals are letting AI write their code, why shouldn't I let AI do my homework? At first, that seems like a logical conclusion. But those two situations are completely different. The professional already has the foundation. They're using AI to become faster. You're still building that foundation. If AI builds it for you, you never actually build it yourself. Think about a typical programming assignment. Your professor asks you to solve a problem. Instead of working through it yourself, you paste the question into ChatGPT or another AI tool. A few seconds later, you have a working solution. Maybe you read through it. Maybe you don't. You submit it. You get a good grade. Everything looks great. But what did you actually learn? Did you understand why that algorithm was chosen? Did you understand why one data structure was better than another? Did you understand why the solution was efficient? Or did you simply submit code that happened to work? There's a huge difference between getting the right answer and understanding why it's the answer. The scary part is that your grades might look great while your actual understanding quietly falls behind. And you may not notice until you're sitting in your first internship or your first software engineering job. This is why I believe the fundamentals are actually becoming more important, not less. People often say that AI is replacing programming. I don't think that's what's happening. I think AI is replacing the repetitive parts of programming. The thinking still matters. The judgment still matters. The problem solving still matters. In fact, those things matter even more now. Because AI isn't always right. Sometimes it misunderstands your requirements. Sometimes it introduces subtle bugs. Sometimes it generates code that's inefficient. Sometimes it confidently explains something that's simply incorrect. If you don't understand the fundamentals, how will you know? How will you know whether the code is secure? Whether it's scalable? Whether it's maintainable? Whether it's solving the right problem? You can't review something you don't understand. That's why I think of AI as an amplifier. If you have strong knowledge, AI amplifies your productivity. If your knowledge is weak, AI amplifies your mistakes. One of the biggest advantages of learning programming the traditional way is that you develop intuition. You start recognizing patterns. You know when something feels off. You learn how to debug. You learn how to break a big problem into smaller ones. You learn how to think like an engineer. Those skills don't come from copying answers. They come from struggling with problems, making mistakes, fixing those mistakes, and gradually improving over time. Those moments can feel frustrating when you're in college. But they're also where the real learning happens. And that brings me to what I think is probably the most important point in this entire video. College may be the last time in your life where your primary job is simply to learn. Once you start working, everything changes. There are deadlines, customers, meetings, production issues, features that need to ship this week. Your employer isn't paying you to slowly explore computer science fundamentals. They're paying you to deliver software. Ironically, AI makes this even more true. Because AI helps developers move faster, expectations are increasing. Companies expect more output in less time. That means there may actually be less opportunity to slowly learn the basics once you're already in the workforce. That's why I think college is such a unique opportunity. Take advantage of it. Learn the concepts. Understand why things work. Ask questions. Struggle a little. Build that foundation while you still have the time. And yes, absolutely use AI. Ask it to explain concepts. Ask it to review your code. Ask it why your solution doesn't work. Ask it to compare different approaches. Use it as a tutor. Use it as a mentor. Use it as a learning partner. Just don't let it become a replacement for your own thinking. Before I finish, I want to go back to something I mentioned at the beginning. I've been talking about software engineering because that's my profession. But I really don't think this lesson stops there. If you're studying accounting, AI can help prepare reports and analyze financial data. If you're studying law, AI can summarize cases and draft contracts. If you're studying marketing, AI can generate campaigns, write content, and help analyze customer trends. If you're studying business, AI can build presentations, analyze spreadsheets, and help make strategic recommendations. If you're studying filmmaking, AI can help write scripts, create storyboards, edit footage, and generate visual effects. If you're studying music, AI can compose melodies, suggest chord progressions, generate backing tracks, and even help with mixing and mastering. If you're studying 3D animation, AI can generate concepts, create textures, assist with rigging, animate scenes, and speed up parts of the production process. No matter what field you're going into, AI is becoming another tool you'll probably use every day. But the people who stand out won't simply be the people who know how to ask AI for answers. They'll be the people who understand the fundamentals well enough to ask better questions. The people who know when the answer is incomplete. The people who recognize when it's wrong. And the people who can take a decent first draft from AI and turn it into something exceptional. AI is changing the way we work. I don't think there's any question about that. But it's not changing the importance of understanding the work itself. So if you're in college today, don't waste this opportunity. Build your foundation. Master the fundamentals. Then let AI make you faster. Because the strongest professionals in the future won't be the ones who rely on AI the most. They'll be the ones who understand their craft so well that AI becomes a force multiplier instead of a crutch.