Yeah, I think it depends a lot on the problem as well. Some problems in industry are largely solved, so it’s just reapplying tried and true patterns to accomplish something we’ve done before, but there are usually turn-key or off-the-shelf solutions to those problems (Wordpress for the CMS example).
It seems like LLMs are very well-suited to these kinds of “solved” problems. But that’s not what engineers get hired to do. Companies don’t hire engineers to solve problems that have turn-key solutions. They hire us to find new solutions to problems that don’t yet have good or feasible solutions. Or to figure out how to keep the lights on when the last engineer created a really bad solution that is crushing the company under the weight of unrecoverable tech debt. Or to create a better experience to an already solved problem.
LLMs can be helpful if used as a tool that fits into the workflow, but I think a lot of devs are resistant to it just because it’s constantly being forced down our throats. I know that’s the main reason I tend to roll my eyes at AI stuff at least. Some of it is pretty cool, but I’d prefer to wait until the tools become more established rather than being forced to be an early adopter of something that is situationally (un)helpful. Though, they have gotten a lot better over the last year.
Seems like once the hype cycle concludes and the bubble pops, LLMs will find their place in everyone’s workflows, because then everyone will be able to utilize them based on their actual benefits to the particular problem being solved, but right now it seems like there is an unrealistic amount of pressure on devs to use AI even if it’s not all that helpful for the task at hand.
That’s the part that’s weird to me. I’m new to the tech industry, but I’m a computing history nerd, so I’ve read about most of the major technology cycles we’ve been through since the 50s, and it seems like this is the first time that the entire industry is pushing people to use a single tool without really considering the merits of it at all. Even people that have no vested interest in it. I guess if we compare AI to a programming paradigm and not a tool, then it makes more sense. Everyone had to know OOP in the early 2000s even if they were applying for a job that was doing something like data analytics that makes no sense to use OOP for. And the dominance of OOP in the early 2000s is also eyebrow-raising because OOP is a pretty bad model to use for HTTP 1-based applications since HTTP 1 is stateless. FP actually fits much nicer with traditional web apps, but OOP dominated right after the web took over as the next big thing. We also started switching over to primarily Functional-style stuff (React Function Components, Elixir, ect) after stateful connections (HTTP2/3, websockets) started becoming commonplace, which is really weird because stateful connections are actually a pretty good fit for OOP patterns (though I still prefer immutability everywhere personally). 
