[codexon]

Top AI researchers like Yann LeCunn have said that LLMs are a dead end.

It seems to me that LLM performance is plateuing and not improving exponentially anymore. This recent hubbub about rewriting a worse GCC for $20,000 is another example of overhype and regurgitating training data.

You don't know for sure if it is going to "snow" (AI reaches general intelligence) Snow happens frequently, AI reaching general intelligence has never happened. If it ever happens, 99% of jobs are gone and there is really nothing you can do to prepare for this other than maybe buy guns and ammo, and even that might not do anything to robotic soldiers.

People were worried about AI taking their jobs 60 years ago when perceptrons came out, and anyone who avoided a tech career because of that back then would have lost out majorly.

[bossyTeacher]

There is no reason why an AI model capable of pushing a significant chunk of devs into lower paid and highly competitive dev jobs as a result of automation needs to be a general artificial intelligence. There is a lack of nuance that comes with thinking that either AI is dumb or it has human level general intelligence. As much as devs hate to admit it, you don't need that much of what we understand as general intelligence to write software. Only a portion of your intelligence is needed and arguably not all of it at the same time.

While general purpose models might be plateauing soon (arguably they have for a while). Highly specialised models (especially for programming) haven't necessarily plateaud yet. And anyway, existing functionality seem like a good foundation to build upon systems that remove the need of hiring as many devs. It's not the "being out of a job" that should worry you. Open up your binary thinking and consider that facing a 08 job market for the rest of your career is not the same permanent unemployment but it is not a market you would like to have.

That is the real concern.

[codexon]

You don't need to be a genius or rocket scientist to write code, but llm don't even reach the bar for anything but the most simple things. Take a look at the video I posted earlier for an example.

And specialised models for programming HAVE plateaued.

https://livebench.ai/#/?sort=Agentic+Coding+Average

From Claude 4.1 to 4.5 was only an 18% gain, and from 4.5 to 4.6 it even DECLINED. Codex 5.1 to 5.2 also shows a decline.

[codexon]

https://arxiv.org/abs/2510.26787

Testing the top llms on wework, the highest performing one only succeeded with a rate of 2.5%

Can you imagine not being fired when you can only do 2.5% of all tasks?

This study is dated October 30th, very recent.