this post was submitted on 27 Aug 2026
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I'm very AI-skeptical in terms of the incredibly negative societal impacts of it, but as least in the field that I most associate myself with (software engineering, but I've been unemployed for more than 2 years), they're somewhere between very useful and wildly useful. Most of my friends who are employed in this field haven't written a single like of code by hand in months, and spend at least $1000/month on behalf of their company on tokens (per engineer). It's the single biggest change to the field that has happened in at least 20 years.
I think that a big part of the crazy valuations come from the idea that this will be able to replace lots of labor, as least in the tech sector, if not more broadly in other blue collar sectors. In terms of software engineering, at least, I don't think it works to replace engineers wholesale, but I do think that it can work as a productivity multiplier, where now one engineer can do the work of what used to take five to ten.
(I think the valuations of the AI companies are still completely ridiculous, because they all rely on the idea that one of these companies, i.e. Anthropic or OpenAI, will achieve a monopoly on having the useful model, which, outside of AGI
, will never happen. Firstly, I think that currently they are both top tier models, so one would have to extinguish the other, and secondly, the Chinese AI labs are pretty close behind, or in some cases even better, and they release their weights so there's no lock-in.)
Outside of tech, I'm a lot less sure. Right now, writing software is the main thing they're being trained on, and they're getting better and better with each release. Once they hit a wall with that, these companies might focus their training efforts on other tasks, and it would likely get better at those too. I'm not sure what areas would come next (I'm sure it would be based off of a combination of what they think will make them the most money and what is easiest to get large amounts of training data for), but it has the potential to do a lot of white collar computer jobs in the near-ish future imo.
I agree with a lot of other points in the thread, but I think they do correspond to a pretty substantial shift in the field of tech, which is a big part of the US's economy.
I very much doubt that it can be used for things other than software and perhaps physical simulation applications. In software, it either works or it doesn't, and you can build it around working and optimizing certain metrics. Literally just optimization of automation. I can see it coming for alot of ME and data entry jobs.
Once you get out into the more vague aspects of engineering and social science, or even something as basic as factory management, the level and ability to do experimentation and replication studies plummets, which means the advice and solutions that it comes up with are going to be based entirely on what the user thinks work, or based on the 'scientific consensus' is. It is a much more difficult issue to tackle epistemologically, like, what is the best spice to add to broast chicken?
Not super complex, but i think it works well at topics pertaining to language and linguistics (which are closely related to software, computer science, and formal logic anyway)