Which languages, frameworks, infrastructure, etc. is set to become more useful and important, and what is potentially less relevant due to advancements in how software products and systems could be developed with the assistance of AI?
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Top comments (5)
I think it will be hard to see how things shake out.
Ecosystems which emphasize human readability, i.e. Python might become less valuable if the AI can help directly generate more machine-ready code (i.e. better performance). If the AI is also doing de-bugging, how much "human-readable" code do we need?
On the other hand, if the AI is generating code for less technical developers to gut check and work with, you want very human-readable code.
I really think it will be hard to figure out for sure.
Good thinking!
That would pop up another thinking for myself, about less "human-readable" thing more the security problem. I cannot say how much influence range can be under control by us human being, if there are a lot of unreadable codes for us in the future. Of cause, what I'm saying depends on how many people will maintain the basic level of those AIs in the future.
Getting worse?
Any place where you're trying to learn how to programme. Will teachers need to include prompt writing in the syllabus? Is coursework going to be plagued with generated code?
Also cowboys are bad now, what about when they just put in what the AI spits out?
Getting better?
I guess it can shave some time of writing simple stuff you're sure you can validate.
In today's iteration of AI, I think the best ecosystem would be where the entire intents of the program are spit out more in line vs separated into files throughout a codebase, just because that's a little easier to manage for the AI.
But any advantage like that will be short-lived, I'd imagine.
Python?