“Top-down mandates to use large language models are crazy,” one employee told Wired. “If the tool were good, we’d all just use it.”
Yep.
Management is often out of touch and full of shit
This is a most excellent place for technology news and articles.
“Top-down mandates to use large language models are crazy,” one employee told Wired. “If the tool were good, we’d all just use it.”
Yep.
Management is often out of touch and full of shit
You wanna know who really bags on LLMs? Actual AI developers. I work with some, and you've never heard someone shit all over this garbage like someone who works with neural networks for a living.
There's this great rage blog post from 1.5 years ago by a data scientist
Missed this one, thanks
Oh, the guy from Hermit Tech! He's great, and his blog is hilarious and poignant in turns (though sometimes both at the same time).
That's me, but for QA...
Management: "No, that doesn't work, because employees spend so much time doing the actual work that they lack the vision to know what's good for them. Luckily for them I am not distracted by actual work so I have the vision to save them by making them use AI."
If the tool were good, we’d all just use it.”
Eggs-mothafucking-zackly!!!
There are no daily pressure campaigns to convince you to use a laptop or a smartphone. The value of those are self-evident.
AI on the other hand... -_-
At work today we had a little presentation about Claude Cowork. And I learned someone used it to write a C (maybe C++?) compiler in Rust in two weeks at a cost of $20k and it passed 99% of whatever hell test suite they use for evaluating compilers. And I had a few thoughts.
I think this is a cool thing in the abstract. But in reality, they cherry picked the best possible use case in the world and anyone expecting their custom project is going to go like this will be lighting huge piles of money on fire.
Agree with all points. Additionally, compilers are also incredibly well specified via ISO standards etc, and have multiple open source codebases available, eg GCC which is available in multiple builds and implementations for different versions of C and C++, and DQNEO/cc.go.
So there are many fully-functional and complete sources that Claude Cowork would have pulled routines and code from.
The vibe coded compiler is likely unmaintainable, so it can't be updated when the spec changes even assuming it did work and was real. So you'd have to redo the entire thing. It's silly.
A C compiler in two weeks is a difficult, but doable, grad school class project (especially if you use lex and yacc instead of hand-coding the parser). And I guarantee 80 hours of grad student time costs less than $20k.
Frankly, I'm not impressed with the presentation in your anecdote at all.
It's even simpler than that: using an LLM to write a C compiler is the same as downloading an existing open source implementation of a C compiler from the Internet, but with extra steps, as the LLM was actually fed with that code and is just re-assembling it back together but with extra bugs - plagiarism hidden behind an automated text parrot interface.
A human can beat the LLM at that by simply finding and downloading an implementation of that more than solved problem from the Internet, which at worse will take maybe 1h.
The LLM can "solve" simple and well defined problems because its basically plagiarizing existing code that solves those problems.
Hey, so I started this comment to disagree with you and correct some common misunderstandings that I've been fighting against for years. Instead, as I was formulating my response, I realized you're substantially right and I've been wrong — or at least my thinking was incomplete. I figured I'd mention because the common perception is arguing with strangers on the internet never accomplishes anything.
LLMs are not fundamentally the plagiarism machines everyone claims they are. If a model reproduces any substantial text verbatim, it's because the LLM is overtrained on too small of a data set and the solution is, somewhat paradoxically, to feed it more relevant text. That has been the crux of my argument for years.
That being said, Anthropic and OpenAI aren't just LLM models. They are backed by RAG pipelines which are verbatim text that gets inserted into the context when it is relevant to the task at hand. And that fact had been escaping my consideration until now. Thank you.
https://harshanu.space/en/tech/ccc-vs-gcc/ has a good overview how bad it really is
Also, software development is already the best possible use case for LLMs: you need to build something abiding by a set of rules (as in a literal language, lmao), and you can immediately test if it works.
In e.g. a legal use case instead, you can jerk off to the confident sounding text you generated, then you get chewed out by the judge for having hallucinated references. Even if you have a set of rules (laws) as a guardrails, you cannot immediately test what the AI generated - and if an expert needs to read and check everything in detail, then why not just do it themselves in the same amount of time.
We can go on to business, where the rules the AI can work inside are much looser, or healthcare, where the cost of failure is extremely high. And we are not even talking about responsibilities, official accountability for decisions.
I just don’t think what is claimed for AI is there. Maybe it will be, but I don’t see it as an organic continuation of the path we’re in. We might have another dot com boom when investors realize this - LLMs will be here to stay (same as the internet did), but they will not become AGI.
I also often get assigned projects where all the tests are written out beforehand and I can look at an existing implementation while I work…
Don't forget that there are tons of C compilers in the dataset already
I can’t wait until billionaires realize how worthless they actually are without people doing everything for them
They will never realize that, they will blame any failures on others naturally. They truly believe they are better than everyone else, that their superior ability led them to invest in a company that increased in value enough for them to become filthy rich.
Surrounded by yes men and woman that agree with everything they say and tell them what a genius they are. Of course any ill outcome isn't their fault.
Eh, as the world goes to shit there will always be desperate people willing to work for them, probably cheaper than before even with the AI failures, so they wouldn't care.
Might be a minute. The brain damage that lets them think they've "earned" those billions kinda hides the work of others. Especially the poors.
We can't to wait for them to realize this themselves. We need to demonstrate this by actively creating a society which excludes them.
I had a meeting with my boss today about my AI usage. I said I tried using Claude 4.5, and I was ultimately unimpressed with the results, the code was heavy and inflexible. He assured me Claude 4.6 would solve that problem. I pointed out that I am already writing software faster than the rest of the team can review because we are short staffed. He suggested I use Claude to review my MRs.
One big problem with management is their inability to listen. Folks say shit over and over but management seems deaf because we're not people to be listened to. We're the help. And management acts like they know better.
If you were so smart you'd have wads of cash like them. They got where they are through sheer grit and bootstraps and a paltry $50 million from their family.
The trick is to tell them you've been using it more than they have and that it's not as good as chatGPT for task A, but that for task B claude does okay 25% of the time so we'll need to 4x the timeline in order to get a good claude output based on that expected value.
But not as good as your personal local LLM that you've been training on company data. No one else can use it because it's illegal to clone. (your personal local LLM is your brain)
Telling your boss you trained a personal LLM with company data will lead to nothing but you holding a box full of your stuff about 10 minutes later.
Ralph Wiggum loop that shit
Numbers go up, Claude won’t bother you 👍🏻
From reading all the comments from the community, it’s amazing (yet not surprising) that all these managers have fallen for the marketing of all these LLMs. These LLMs have gotten people from all levels of society to just accept the marketing without ever considering the actual results for their use cases. It’s almost like the sycophant nature of all LLMs has completely blinded people from being rational just because it is shiny and it spoke to them in a way no one has in years.
On the surface level, LLMs are cool no doubt, they do have some uses. But past that everyone needs to accept their limitations. LLMs by nature can not operate the same as a human brain. AGI is such a long shot because of this and it’s a scam that LLMs are being marketed as AGI. How can we attempt to recreate the human brain into AGI when we are not close to mapping out how our brains work in a way to translate that into code, let alone other more simple brains in the animal kingdom.
I don't think LLMs will become AGI, but... planes don't fly by flapping their wings. We don't necessarily need to know how animal brains work to achieve AGI, and it doesn't necessarily have to work anything like animal brains. It's quite possible if/when AGI is achieved, it will be completely alien.
Aircraft wings operate on pretty much the same principle as bird wings do. We just used a technology we had already developed (fans, essentially) to create the forward movement necessary to create the airflow over the wings for lift. We know how to do it the bird way too, but restrictions in material science at scale make the fan method far easier and less error prone.
One of the best written comments I've seen about this. LLMs are cool for what they can do, but anyone comparing them to AGI is just shilling and trying to make a fortune off of selling pickaxes in a gold rush with the only gold being fools gold.
From reading all the comments from the community, it’s amazing (yet not surprising) that all these managers have fallen for the marketing of all these LLMs
This is probably related to automation bias and wishful thinking
I agree with almost all of your comment. The only part I disagree on is:
How can we attempt to recreate the human brain into AGI when we are not close to mapping out how our brains work in a way to translate that into code, let alone other more simple brains in the animal kingdom.
An implementation of AGI does not need to be inspired from the human brain, or any existing organic brain. Nothing tells us organic brains are the optimal way to develop intelligence. In fact, I'd argue it's not.
That being said, it doesn't change the conclusion: We are nowhere near AGI, and LLMs being marketed as such is absolutely a scam.
Man, corporate layoffs kill productivity completely for me.
Once you do layoffs >50% of the job becomes performative bullshit to show you’re worth keeping, instead of building things the company actually needs to function and compete.
And the layoffs are random with a side helping of execs saving the people they have face time with.
Who?
The original creator of Twitter and now creator of Bluesky and whatever this thing that's falling off the rails is.
Basically another billionaire living in his own little bubble and huffing his own farts too much.
He also had a lot to do with Nostr, early on.
Jack Dorsey, has endorsed and financially supported the development of Nostr by donating approximately $250,000 worth of Bitcoin to the developers of the project in 2023,[13][15] as well as a $10 million cash donation to a Nostr development collective in 2025.
What?
Oops I mistread my source. Have updated my comment.
he left Bluesky around 2 years ago
Uhhh, Block is the the parent company of Square (formerly known as Square Up). This is actually a huge company, not some little side thing.
Yeah, the sellout.