| TL;DR: AI's recent advancements make me want to change careers from SWE or math. I feel completely lost and struggle to predict what future is best and "ai proof". I want any advice. I feel completely lost both career and identity-wise. I think I should pivot careers. Engineering? Trade school? Law school? Medicine? Who knows. The problem is, any, high paying, knowledge related field seems under threat. It feels impossible to predict the future and so I am not comfortable putting my chips anywhere. On the other hand, I could try to improve my CS skills (as depressing as the field feels right now), hope that AI slows down and I get a job so I can go back to a masters program in god-knows-what that is "ai proof". Any advice is appreciated. I hope that this post can be useful for others in my situation because finding good resources that are not extremely biased seems hard. --------------Here is why I believe what I believe--------------------- Seeing the rapid pace at which AI is improving, I have little hope that SWE (or math) is a viable a career path. If you asked me a year ago, I would never have thought AI would have gotten this good. The big moments for me have been the release of Fable/Mythos 5 and OpenAI's disproof of the unit distance conjecture (and yes I know, disproofs using counterexamples are less impressive that proof). I subscribe to the idea that anything AI can do well or okay at now, it will be excellent at in the near future. Although somewhat unfalsifiable, we have seen examples of this such as in writing or art and I see no reason for this to not happen to computer science and math (if we haven't already seen it with Mythos and OpenAI's disproof). I expect mass layoffs in SWE around when I graduate (2028). |
First, costs and ROI of AI are on a collision course and companies are finding they can't simply lay off smart people and replace them with "vibe-working" employees. Secondly, not only will more junior workers adapt to new hybrid human/AI workflows better than more senior workers, they're likelier to apply them to parts of the job that are low-value, routine. Third, the next frontier for agents and models is within very narrow domains where more junior AI-savvy workers are in a great position to collect, capture and refine the data models from subject matter experts. Who better to ask "What about X ...?" and "How do you know Y...?" from experts?