Also: Will AI steal your job? It's complicated, new survey reveals A significant percentage of GPUs fail each year, so "we're constantly replacing those things," McNeill explained. "When you replace them, you have to re-synch them, and get the networking software working again with the high-band memory chips. All this stuff adds up to big demand for people, and I don't see that going away anytime soon -- with all the complexity of these clusters and server farms." Along with that, "demand for inference is going to continue to drive demand for infrastructure," he added. "That's really good news for IT infrastructure professionals." Computer science and software are different story On the computer science and software side, a different story unfolds, with a call for code writers, software engineers, and developers to move to a higher level of skills, McNeill said. "They have this layer cake of these different architectural approaches, and smart computer scientists are figuring that out," he noted. "Yes, I can vibe code an app on one single layer. If I have six or seven different models coming together and working together, I can keep them synced agentically. But the invention of the architecture is human -- probably well into the foreseeable future." The most durable software companies now emerging "are being created with a bunch of layers," he illustrated. "They attack a very complex problem. They'll say, 'Hey, one layer of this problem can be solved by simple search index. Another layer of this problem can be solved by ML.' So I wouldn't spend money on tokens to solve those pieces of the problem. Other pieces of the problem can be solved by small models, maybe another part of the problem by large models."