What a fuckin’ clown circus…
this post was submitted on 25 Jun 2026
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If you just throw every task at it, I can completely imagine that it'll cost you more than any gain in efficiency. To some degree I think this is true of some coding tasks (not all, most are pretty efficient pattern matches, and that's what it does well).
But using LLMs to build tools and pipelines that stand alone (no AU built into it) and enable human productivity seems like a far higher leverage use.
The programming version is building the libraries and abstractions that are robust and well tested, so that regular developers can quickly build and refine the features.
Or building the reporting dashboard. Or whatever.
The cost is only going to go up, and the companies that lock in some non-AI process improvements before the hike will likely be smiling
Especially because a statistical model of language has very limited valid usecases. Many tasks that people use LLM for do not make any sense and cannot be accomplished by a statistical model of language. It can only output a statistical approximate of what a solution to the task might look like, not an actual solution.
It constructed an entire feature-full library for a UV sensor that just came on the market, by me just throwing the PDF datasheet at it and saying "make library pls".
It's the actual solution. Maybe the statistical approximate just coincidentally lined up with the actual solution? Either way, works for me. Second time it did that, too. Worked for a LiDAR sensor earlier.
Maybe the statistical approximate just coincidentally lined up with the actual solution?
Yes, right, and this can happen. I didn't say they are a bad approximation. LLMs may be the most advanced and sophisticated statistical models ever created (if there are other examples of statistical models that are more sophisticated, I would love to learn about them). But given what an LLM actually objectively is, a statistical model of the next token to follow from a sample of language, what other explanation could there be?
We need to keep in mind what the tools that we are working with actually are.
As a code generator, they can produce great results, especially simple stuff like generating a script or some function implementation. Once you get to software engineering tasks like designing system architecture and designing maintainable code, it starts to fall apart really fast. You end up doing all of the work for it in natural language and just using the LLM for a usecase that it is actually great for: translation, from detailed spec to code.
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LLMs as a technology are incredibly powerful tools that have so many useful applications. The issue is trying to turn them into this all powerful omnitool that could do everything, and then shoving that product up everyone's ass at every turn.
There was always bound to be a correction to this bubble, because the current model is unsustainable. You can only keep making unreasonable moves for so long before everything starts to crumble and your forced to scale back.
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All this money that is being spent, where does it end up?
Trump and his cronies, probably
Various designing firms.
After the bubble bursts, law firms, because everyone starts suing everyone to get back money they didn't necessarily have, but still spent, because somebody will soon sue them.
Well at least there's a happy ending
Nvidias pocket maybe. CEOs? Billionares?
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converting pdfs to presentation
I don't get this, We've had OCR for a while. All around San Francisco Ive been seeing ads for "llamaparse" with the tagline "we parse pdfs", like is that all you do? How do you afford this marketing budget?
PDFs are so shitty to work with, it's like translating them, it's impossible without using a tool like Google translate.
I fucking hate PDFs as much as I hate Adobe.
I HATE PDFS TOO. I hate them! 99.999% of the time I'm given a PDF file it would be more useful as an HTML file.
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Can't read the whole article bc paywall... But if they are really worried about token cost for converting PDF to a Powerpoint, they ain't seen nothing yet. Agentic coding the way AI companies push it (multiple agents in parallel with Claude, looping etc) uses way way wayyyyy more tokens than this.
Have you used Opus 4.8 at API costs? Without using agents, I can burn $20 an hour no problem. I use Kimi K2.6 and GLM 5.2 these days.
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I used to understand what computers were for and how they worked.
