The computer science major is in trouble. At Berkeley, it's complicated
alumni.berkeley.edu
alumni.berkeley.edu
Personally, I think current LLMs have clear limits, so would engineering majors be at risk? That's a bit of a difficult point.
Because LLMs are good at writing code, but as complexity increasingly grows, if a person handles it, the number of lines one individual has to deal with will grow exponentially. To maintain that or find bugs, you'd need major-specific knowledge. After all, building a program is fundamentally about controlling complexity.
There's a slightly difficult point here. It's true that frontier AIs are good at coding, but once you start running agents at a large scale, token efficiency varies depending on whether a human intervenes or not. Ultimately, if you compare current token costs, isn't hiring a junior person cheaper? Is the US a different situation? Thinking about the API prices of GPT 6 or Fable makes me think that even more.
In a capitalist world, do the same, but in other currency.
Taking extra steps (but fewer than you and many propose, which includes paying academics, university HR, test-providers, career advisors, recruiters, board members, grant-reviewers etc etc), the... LLM simply charges the productive engineers more per token.. if you suck, you get proportionately more tokens until you don't, then you pay back.
If there isn't a helpful joke in that, find it