Writing code with an LLM is often actually less productive than writing without.

Sure for some small tasks it might poop out an answer real quick and it may look like something that's good. But it only looks like it, checking if it is actually good can be pretty hard. It is much harder to read and understand code, than it is to write it. And in cases where a single character is the difference between having a security issue and not having one, it's very hard to spot those mistakes. People who say they code faster with an LLM just blindly accept the given answer, maybe with a quick glance and some simple testing. Not in depth code review, which is hard and costs time.

Then there's all the cases where the LLM messes up and doesn't give a good answer, even after repeated back and forth. Once the thing is stuck in an incorrect solution, it's very hard to get it out of there. Especially once the context window runs out, it becomes a nightmare after that. It will say something like "Summarizing conversation", which means it deletes lines from the conversation that are deemed superfluous, even if those are critical requirement descriptions.

There's also the issue where an LLM simply can't do a large complex task. They've tried to fix this with agents and planning mode and such. Breaking everything down into smaller and smaller parts, so it can be handled. But with nothing keeping the overview of the mismatched set of nonsense it produces. Something a real coder is expected to handle just fine.

The models are also always trained a while ago, which can be really annoying when working with something like Angular. There are frequent updates to Angular and those usually have breaking changes, updated best practices and can even be entire paradigm shifts. The AI simply doesn't know what to do with the new version, since it was trained before that. And it will spit out Stackoverflow answers from 2018, especially the ones with comments saying to never ever do that.

There's also so much more to being a good software developer than just writing the code. The LLM can't do any of those other things, it can just write the code. And by not writing the code ourselves, we are losing an important part of the process. And that's a muscle that needs flexing, or skills rust and go away.

And now they've poisoned the well, flooding the internet with AI slop and in doing so destroying it. Website traffic has gone up, but actual human visits have gone down. Good luck training new models on that garbage heap of data. Which might be fine for now, but as new versions of stuff gets released, the LLM will get more and more out of date.