(I am not sure whether questions like these are allowed here)
Hi everyone.
What is our opinion on the future of scientific computing careers? Given that AI has become so good at writing code, finding bugs, and optimizing performance, and it is likely to get better, what should a STEM student or an early-career computing researcher focus on to stay relevant?
Is learning a programming language to the deepest level (Julia, C++, Python) still a sure way to a lucrative career? Or is that somewhat obsolete because one can use the AI output to learn stuff “on the fly”, via prompts like “What does this syntax mean? Why is it better to do it like this rather than…”
Should one focus more on software design principles or system’s architecture?
Should one focus more on the science, eg., to be able to read and understand research papers to certain topics (and do research oneself)?
Good questions, and I don’t have an answer to them. Just my personal experience and comments.
At the moment, AI is a great tool for developing software, but in my opinion it’s just that: a tool.
And as with any other craft, new tools may greatly change parts of the process, may make some steps obsolete, and may require a new set of skills to use them effectively. But learning how to use the tool doesn’t replace learning the craft itself, if that analogy makes sense…
Learning about the fundamentals of software and programming (regardless of the language) is still nontrivial and in my experience you need to have a good enough understanding of those fundamentals to judge if the approach an AI would suggest is really going in the right direction – not just in programming, but with all other prompts as well. My guess (and indeed hope) is that programmers who have this kind of understanding will stay in demand in the foreseeable future.