That's not the same thing. LLMs don't just obscure low-level technical implementation details like Python does, they also obscure your business logic and many of its edge cases.
Letting a Python interpreter manage your memory is one thing because it's usually irrelevant, but you can't say the same thing about business logic. Encoding those precise rules and considering all of the gnarly real-world edge cases is what defines your software.
There are no "higher level details" in software development, those are in the domain of different jobs like project managers or analysts. Once AI can reliably translate fuzzy natural language into precise and accurate code, software development will simply die as a profession. Our jobs won't morph into something different - this is our job.
>There are no "higher level details" in software development, those are in the domain of different jobs like project managers or analysts. Once AI can reliably translate fuzzy natural language into precise and accurate code, software development will simply die as a profession. Our jobs won't morph into something different - this is our job.
I'm the non-software type of Engineer. I've always kind of viewed code as a way to bridge mathematics and control logic.
When I was at university I was required to take a first year course called "Introduction to Programming and Algorithms". It essentially taught us how to think about problem solving from a computer programming perspective. One example I still remember from the course was learning how you can use a computer solve something like Newton's Method.
I don't really hear a lot of software people talk about Algorithms but for me that is where the real power of programming lives. I can see some idealized future where you write programs just by mix and matching algorithms and almost every problem becomes essentially a state machine. To move from state A to State B I apply these transformations which map to these well known algorithms. I could see an AI being capable of that sort of pattern matching.
the hard thing is to define what State A and State B means Also to prepare for State C and D, so that it doesn’t cost more to add to the mix. And to find that State E everyone is failing to mention,…
> "Once AI can reliably translate fuzzy natural language into precise and accurate code, software development will simply die as a profession."
One-shotting anything like this is a non-starter for any remotely complex task. The reason is that fuzzy language is ambiguous and poorly defined. So even in this scenario you enter into a domain where it's going to require iterative cycling and refinement. And I'm not even considering the endless meta-factors that further complicate this, like performance considerations depending on how you plan to deploy.
And even if language were perfectly well defined, you'd end up with 'prompts' that would essentially be source codes in their own right. I have a friend who is rather smart, but not a tech type - and he's currently working on developing a very simple project using LLMs, but it's still a "real" project in that there are certain edge cases you need to consider, various cross-functionality in the UI that needs to be carried out, interactions with some underlying systems, and so on.
His 'prompt' is gradually turning into just a natural language program, of comparable length and complexity. And with the amount of credits he's churning through making it, in the end he may well have been much better off just hiring some programmers on one of those 'gig programming' sites.
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And beyond all of this, even if you can surmount these issues - which I think may be inherently impossible - you have another one. The reason people hire software devs is not because they can't do it themselves, but because they want to devote their attention to other things. E.g. - most of everybody could do janitorial work, yet companies still hire millions of janitors. So the 'worst case' scenario would be that you dramatically lower the barriers to entry to software development, and wages plummet accordingly.
Letting a Python interpreter manage your memory is one thing because it's usually irrelevant, but you can't say the same thing about business logic. Encoding those precise rules and considering all of the gnarly real-world edge cases is what defines your software.
There are no "higher level details" in software development, those are in the domain of different jobs like project managers or analysts. Once AI can reliably translate fuzzy natural language into precise and accurate code, software development will simply die as a profession. Our jobs won't morph into something different - this is our job.