Maybe the real threat is that our industry has been stalled for years, or to put it more politely, that it has been mature for a while. Back before 2010 or so,

Maybe the real threat is that our industry has been stalled for years, or to put it more politely, that it has been mature for a while. Back before 2010 or so, people actually read books like The Art of Computer Programming, the Dragon Book on compilers, and the Lions’ Book on Unix, or followed sites like lambda-the-ultimate.org. Then sites like High Scalability became popular. Not that everyone studied them cover to cover, but plenty of engineers considered them essential reading. Yet long before LLMs came along, that kind of depth had clearly become niche. The creator of High Scalability even put the site up for sale. Whenever someone posts an article titled "Top X Data Structures for Y," every single structure mentioned was invented decades ago. If most of what we do now is just slice and dice abstractions created and refined by previous generations, we are really just relying on our once-unique ability to transfer knowledge - something AI is rapidly replacing. This isn't unique to software engineering. In Renaissance Italy, mathematicians like Tartaglia and Fior hoarded cubic formula shortcuts like proprietary algorithms and challenged rivals to public math duels. Today, we solve cubic equations without a second thought. Special functions used to be a staple college course for physics and engineering majors. Are they still? The US military used to employ thousands of people just to calculate PDEs by hand. Do we need anyone doing that today? Our only hope is that our society moves fast enough to create new demands and problem domains that genuinely require new systems and algorithms. Look at AI: it’s evolving rapidly, driving massive demand, and forcing the development of new systems and architectures. As a result, the lucky few[1] working at that frontier are having rewarding careers. Without frontiers like that, the rest of us risk becoming irrelevant. [1] One unfortunate factor is that building AI now requires lots of capital for accessing GPUs, which means individuals in the open source community have a hard time working on it.