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Everyone and their dog has been told in the last decade that learning to code is important. I've grown up hearing that sentiment consistently and I'm sure it contributed a lot to me falling in love with this field.
However, coding (at least in its current form) seems like one of the most at-risk forms of work in terms of AI automation. I love writing code and I think I'm good at it, but I'm not so sure I'll be able to compete long-term with AI. I'm sure there'll be a few "John Henry"s, but many devs will probably change. Keep in mind, I'm thinking on the scale of length of a whole career and not saying this is happening already. However, with LLM context lengths increasing and special hardware made for ML inference (like groq), it feels like we're not far out from repo-level AI coding. At this rate of development, I could imagine a decade of progress might transform many aspects of day-to-day work for software development.
With all that being said, what advice would you give to someone just starting their career who wants to avoid shorter-term local maxima? I've heard lots of mixed reviews on PhDs and advanced degrees compared to working in industry, but should that calculus change with AI? Thank you!