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LLMs are eroding my software engineering career and I don't know what to do
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this post was submitted on 09 Jun 2026
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Programming
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I think the author is mostly right about the current state of AI, but his future predictions (or worries) are based on a false premise: that the massive LLMs will keep improving in the future.
As far as I have seen the improvements have clearly slowed down, while the energy consumption is rising linearly (or worse). It's like the energy (money) vs. performance graph is logarithmic, and the companies are expending double the energy to get a 10% improvement. Something like that is not sustainable, and the money seems to indicate so.
I really think that LLMs are a dead-end for AI. A really useful dead-end, once the bubble pops and with time, we get a useful working model for them, probably based mostly on local LLMs, maybe using specialized training data.
Energy efficiency has improved by orders of magnitude - leading to much higher energy use. It's the Jevons paradox and it's as old as coal-gas lighting. Last year some guy recreated GPT2 for twenty bucks. Corpus to model in one hour. OpenAI never said how much the original cost, but there was at least one comma.
But yeah, LLMs are fundamentally limited, because 'what's the next word' shouldn't work. The fact it's accidentally this flexible and powerful, even with its many infamous fuckups, is a reminder that neural networks in general will permanently alter computing. Models trained on supercomputers can run on any potato. Any problem with good examples can be addressed, without first being solved.
Yes, you're right. However, for fear of coming off as an AI sycophant (I've yet to sacrifice my brain at the altar of our future AI overlords), LLMs aren't the whole picture. Plenty of research is dedicated to essentially combining the best of each class of AI algorithms into a composite model of intelligence. For instance, "Neuro-Symbolic AI" is really just the result of giving an LLM (good at translation, search, synthesis, bad at symbolic reasoning) a symbolic inference engine like Prolog (good at symbolic reasoning, no native ability for translation/search/synthesis). I've been coding for over 20 years, and I'm impressed at its results for software development.
This all is reminiscent of Moore's Law; even though we keep running into the physical limits of CPU clock speeds, transistor size, etc. we keep finding clever ways to work around those limits.
Of course I'm not saying we should; these models are, after all, models of intelligence, not wisdom.
Edit: fix apostrophe splice
Being reasonable about the tech is kind of a pain, here. At least we only got one flavor of campist, so anyone seeing outright "boosters" is jumping at shadows. I just think the chatbot that can code is neat. Maybe we can do stuff with it. Maybe it doesn't need to spy on everyone forever.
We accidentally invented p-zombies and they're already more intelligent than script kiddies. Once the grifters move on we can see what that's good for.
Agreed. The bubble has to pop eventually... Or not, and we really are marching towards our own obsolescence as a species.
I mean, AGI is inevitable, but it's never gonna come from these dinguses. They can't even look past LLMs far enough to pursue text diffusion.
To imagine we cannot possibly build a mind, or that it cannot possibly improve that same effort, is baffling. It changes the shape of the universe.
Just because it's possible does not mean it's inevitable. It's incredibly optimistic to think that we can get our shit together enough to pull it off before we destroy all our productive capacity through hubris.
Nothing's inevitable. And as for "building a mind", while it depends on precisely what you mean by "mind", it's totally possible that only a biological brain can produce minds as we understand the word "mind". Building AGI doesn't necessarily mean building a mind. And since thoughts seem to be properties of "matter", and there seem to be rules about which configurations of matter produce mind, we don't necessarily know that there are other configurations that can produce minds. We might produce something else equally interesting which still is not a mind.
Bollocks. Thought is a process, like math. Nothing meat does with signals is impossible in other substrates.
At the utmost extreme: surely we can simulate physics at whatever level is necessary for virtual brains to function. Physical neurons are not gonna rely on quantum chromodynamics. Mere chemistry will probably suffice.
And hand-waving things that are like-minds-but sounds like Chinese Room nonsense.
You're making a baseless assumption about the inner being of every process. If you simulate physics then you're actually doing different physics, where the map is not the terrain. If the hardware is different then the inner being of the thing may very well be different.
You're actually displaying a lack of imagination here. You're not considering things other than consciousness. If you simulate the processes which on the surface resemble the processes that you see in the brain when observing from the outside, what you produce may be something equally interesting and yet totally different in-itself from subjective experience.
You don't know as much as you think you know.
You say that, and GAs were used decades ago to design FPGAs to a spec. The evolved design worked perfectly on the test chip, so the design was copied onto a second chip and it failed. The logic gates were identical but the GA had utilised microscopic differences in the substrate and there were large areas of programmed chip totally unconnected to the main circuit. Without them, the first chip didn’t work any more.
There are likely quantum effects available at the size / scale of neurons, and it’s brave to say evolution wouldn’t exploit them if there was some benefit.
Yeah yeah yeah, probably exploiting capacitance instead of on-spec functionality, I'm well familiar with this example. It's not relevant - there's eight billion human brains in the world, and they generally still function despite the wild shit we put them through. They are not fragile.
A human mind is not balanced on a knife-edge, where one tiny difference breaks everything. They're complex enough that sometimes blowing a railroad spike clean through just alters functionality. It's still a mind. Subatomic interactions surely cannot be crucial here.
And again, this is only the extreme example. Y'think all known laws of the universe are mandatory? Great, simulate those too. Same answer: meat has no monopoly on thought because metal can fake the meat. There is no philosophical basis for even suggesting AGI is impossible, unless you start talking about souls.
The scale of neurons is too big for quantum effects, but that's contemporary understanding that may change in the future. We're really far from understanding both what mind is and how to make one
I'd be curious why you think LLMs are dead ending? Is it that you think the Jepa models are likely to find success and win out or do you think the LLMs in generally are just hitting their peaks?
Your point on power usage is interesting, although I think that is mostly on training not usage correct?
I think they're a dead-end mostly because of the exponential cost vs. performance. The decreasing returns are obvious, and the companies are trying to adapt by raising token prices, but that will not be enough with the current user numbers (or even double or triple, if we believe the analysts). I think that, at least with these large LLM companies, we're actually beyond the point of economic equilibrium with this technology, at current energy and water prices.
And yes, training is more expensive than usage. That's probably the reason why Anthropic suggested a pause in LLM development (training), supposedly because of the fear that AI could become Skynet, but really because they are getting an IPO soon and if people see their current balance numbers, the IPO would fail and the bubble would probably pop. Which really proves my point a little: the economics of these companies "improving their LLMs" (training) don't make sense at current energy prices.