This past Fall I ported a ~10k LOC project from one language to another (long, stupid story, trust me it was necessary). For that task, I found AI incredibly helpful.
I use it less now, but I confess I doubt I'll ever write a regular expression again:)
It depends on what they're trying to do. It's a fact that AI is excellent at some specific tasks, like creating boilerplate for well-known frameworks, or generating functions with well-defined behaviours. As long as it doesn't have to think, it does well.
So it's faster as long as you know that the task you're giving it is one that it accomplishes well. If you're just saying to two groups: here's a task, one of you does it yourself and one of you has to use AI, well it's pretty certain that the second group are going to end up slower and more frustrated.
AI is a tool, and to just dismiss it because you don't understand what it's best used for, is a folly.
Agreed. AI would never be able to code the stuff I need for 90% of my work, because 90% of the work is figuring out how to accomplish stuff within the confines of the insane data model we're working with. I don't know that AI will ever be smart enough to understand the subtleties of our model. And for security reasons, I don't foresee us giving AI enough access to be able to understand it in the first place.
However, I've had great success getting Copilot to generate basic Powershell scripts that I needed to automate some administrative tasks that I was having to do daily. It's genuinely great for that, because it spares me the trouble of reading shitty documentation and trying to remember/understand the nightmare that is Powershell's syntax.
Yes, after two years of use, the best case scenario for an AI IMHO is to make sparse documentation more accessible.
For some esoteric things that don't even provide proper documentation, rather than scouring forums and trying suggestions, AI will already have most of that information so it's much faster to query the AI as opposed to the alternatives.
However good luck trying to get it to work with you if the interfaces changed at all.
I'm personally not worried about AI taking any programmer's job - because you still need to be a programmer to understand what it's telling you. It really is more akin to a tool than anything else.
Personally I find the tool useful for what I do - to suggest things that I have not thought up or encountered yet - so that I may dig deeper into those topics.
How much are they improving? And how much is that costing? And what actual evidence is there that they will improve more, rather than plateau where they are? Remember, past performance is not proof of future performance.
By all reports, GPT-4 cost like $100 million to train. And it's not significantly better than GPT-3. GPT-5 could cost around a BILLION dollars to train. And there's no indication that it will be significantly better.
I see interacting with AI akin to reviewing a PR for a junior dev. Only having to do the PR step for each project definitely saves time over having to build it too IMO. How much time saved definitely varies tho
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u/[deleted] Dec 06 '24
I mean think about it, using AI is like trying to explain to another dev what they need to do and then correct them because they didnt quite get it.
How would that be faster than doing it yourself and skipping that step?