this post was submitted on 24 May 2024
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[–] [email protected] 91 points 1 month ago (13 children)

Yeah, but the non-tech savvy business leaders see they can generate code with AI and think 'why do I need a developer if I have this AI?' and have no idea whether the code it produces is right or not. This stat should be shared broadly so leaders don't overestimate the capability and fire people they will desperately need.

[–] [email protected] 4 points 1 month ago (6 children)

Programming jobs will be safe for a while. They've been trying to eliminate those positions since at least the 90s. Because coders are expensive and often lack social skills.

But I do think the clock is ticking. We will see more and more sophisticated AI tools that are relatively idiot-proof and can do things like modify Salesforce, or create complex new Tableau reports with a few mouse clicks, and stuff like that. Jobs will be chiseled away like our unfortunate friends in graphic design.

[–] [email protected] 13 points 1 month ago (5 children)

You, along with most people, are still looking at automation wrong. It's never been about removing people entirely, even AI, it's about doing the same work with less cost.

If you can eliminate one programmers from your four person team by giving the other three AI to produce the same amount of work, congrats you've just automated one programming job.

Programming jobs aren't going anywhere, but either the amount of code produced is about to skyrocket, or the number of employed programmers is going to drop (or most likely both of those things).

[–] [email protected] 5 points 1 month ago (1 children)

I wonder if this will also have a reverse tail end effect.

Company uses AI (with devs) to produce a large amount of code -> code is in prod for a few years with incremental changes -> dev roles rotate or get further reduced over time -> company now needs to modernize and change very large legacy codebase that nobody really understands well enough to even feed it Into the AI -> now hiring more devs than before to figure out how to manage a legacy codebase 5-10x the size of what the team could realistically handle.

Writing greenfield code is relatively easy, maintaining it over years and keeping it up to date and well understood while twisting it for all new requirements - now that's hard.

[–] [email protected] 0 points 1 month ago

AI will help with that too, it's going to be able to process entire codebases at a time pretty shortly here.

Given the visual capabilities now emerging, it can likely also do human-equivalent testing.

One of the biggest AI tricks we haven't started seeing much of yet in mainstream use is this kind of automated double-checking. Where it generates an answer, and then validates if the answer is valid before actually giving it to a human. Especially in coding bases, there really isn't anything stopping it from coming up with an answer compiling, running into an error, re-generating, and repeating until the code passes all unit tests or even potentially visual inspection.

The big limit on this right now is sheer processing cost and context lengths for the models. However, costs for this are dropping faster than any new tech we've seen, and it will likely be trivial in just a few years.

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