“Do fundamentals still matter?” The moral high ground says - they do, and I agree. But the motivation loop that made people great at fundamentals is broken.
Fundamentals were rewarding because we immediately applied them to solve problems better and, more importantly, gave us an edge over others. Say we write a wire protocol - then concepts like endianness come in handy when we serialize the data and solve our problem. That tight feedback loop is what drove curiosity.
But with AI handling the implementation, we skip from “I have a problem” straight to “it’s solved,” without the middle step where understanding actually forms. We can still force ourselves to study the output afterward, but reviewing someone else’s (AI) solution is very different from building it ourselves.
Honestly, some fundamentals will be valuable to understand conceptually, but rarely practiced. Others will become even more critical because they are what you need to evaluate AI output and catch what it gets wrong.
The hard part is that we are living through the transition. Nobody knows which fundamentals will fade and which will become indispensable.
But until that becomes clear, I would still bet on building strong fundamental muscles for problem-solving.