It’s very good at a fuzzy great answer, not a precise one. You have to really use this thing all the time and pick up on stuff like that.
> why don´t we stop pretending that we as users are stupid and don´t know how to use them
This is in response to someone who saw a bunch of URLs coming out of it and was surprised at a bunch of them being wrong. That's using the tool wrong. It's like being surprised that the top results in google/app store/play store aren't necessarily the best match for your query but actually adverts!
If you're trying to one shot stuff with a few sentences then yes you might be using these things wrong. I've seen people with PhDs fail to use google successfully to find things, were they idiots? If you're using them wrong you're using them wrong - I don't care how smart you are in other areas. If you can't hand off work knowing someones capabilities then that's a thing you can't do - and that's ok. I've known unbelievably good engineers who couldn't form a solid plan to solve a business problem or collaboratively work to get something done to save their life. Those are different skills. But gpt5-codex and sonnet 4 / 4.5 can solidly write code, gpt-5-pro with web search can really dig into things, and if you can manage what they can do you can hand off work to them. If you've only ever worked with juniors with a feeling of "they slow everything down but maybe someday they'll be as useful as me" then you're less likely to succeed at this.
Let's do a quick overview of recent chats for me:
* Identifying and validating a race condition in some code
* Generating several approaches to a streaming issue, providing cost analyses of external services and complexity of 3 different approaches about how much they'd change the code
* Identifying an async bug two good engineers couldn't find in a codebase they knew well
* Finding performance issues that had gone unnoticed
* Digging through synapse documentation and github issues to find a specific performance related issue
* Finding the right MSC for a feature I wanted to use but didn't know existed - and then finding the github issue that explained how it was only half implemented and how to enable the experimental other part I needed
* Building a bunch of UI stuff for a short term contract I needed, saving me a bunch of hours and the client money
* Going through funding opportunities and matching them against a charity I want to help in my local area
* Building a search integration for my local library to handle my kids reading challenge
* Solving a series of VPN issues I didn't understand
* Writing a lot of astro related python for an art project to cover the loss of some NASA images I used to have access to.
> the folks pushing or better said
If you don't want to trust them, don't. Also don't believe the anti-hype merchants who want to smugly say these tools can't do a god damn thing. They're trying to get attention as well.
> Trust me, it sucks
Ok. I'm convinced.
> and under-delivers.
Compared to what promise?
> I am sure we will see those 10x apps rolling in soon, right?
Did I argue that? If you want to look at some massive improvements, I was able to put up UIs to share results & explore them with a client within minutes rather than it taking me a few hours (which from experience it would have done).
> It's only been like 4 years since the revolutionary magic machine was announced.
It's been less than 3 since chatgpt launched, which if you'd been in the AI sphere as long as I had (my god it's 20 years now) absolutely was revolutionary. Over the last 4 years we've seen gpt3 solve a bunch of NLP problems immediately as long as you didn't care about cost to gpt-5-pro with web search and codex/sonnet being able to explore a moderately sized codebase and make real and actual changes (running tests and following up with changes). Given how long I spent stopping a robot hitting the table because it shifted a bit and its background segmentation messed up, or fiddling with classifiers for text, the idea I can get a summary from input without training is already impressive and then to be able to say "make it less wanky" and have it remove the corp speak is a huge shift in the field.
If your measure of success is "the CEOs of the biggest tech orgs say it'll do this soon and I found a problem" then you'll be permanently disappointed. It'd be like me sitting here saying mobile phones are useless because I was told how revolutionary the new chip in an iphone was in a keynote.
Since you don't seem to want to read most of this, most isn't for you. The last bit is, and it's just one question:
Why are you paying for something that solves literally no problems for you?
The CEO of Anthropic said I can fire all of my developers soon. How could one possibly be using the tool wrong? /s
Perhaps you’ve been sold a lie?
You have to be able to see what this thing can actually do, as opposed to what it can’t.
But all code is "long precise strings".
On the other hand, I've had them easily build useful code, answer questions and debug issues complex enough to escape good engineers for at least several hours.
Depends what you want. They're also bad (for computers) at complex arithmetic off the bat, but then again we have calculators.
We have OpenAI calling gpt5 as having PhD level of intelligence and others like Anthropoc saying it will write all our code within months. Some are claiming it’s already writing 70%.
I say they are being sold as a magical do everything tool.
Did the LLM have this?
Also there's a huge gulf between "some people claim it can do X" and "it's useful". Altman promising something new doesn't decrease the usefulness of a model.
"This isn't how humans work. Einstein never saw ARC grids, but he'd solve them instantly. Not because of prior knowledge, but because humans have consistent reasoning that transfers across domains. A logical economist becomes a logical programmer when they learn to code. They don't suddenly forget how to be consistent or deduce.
But LLMs have "dead reasoning zones" — areas in their weights where logic doesn't work. Humans have dead knowledge zones (things we don't know), but not dead reasoning zones. Asking questions outside the training distribution is almost like an adversarial attack on the model."
The things they're saying are technically correct, the best kind of correct. The models beat human PhDs on certain benchmarks of knowledge and reasoning. They may write 70% of the easiest code in some specific scenario. It doesn't matter. They're useful tools that can make you slightly more productive. That's it.
When you see on tv that 9 out of 10 dentists recommend a toothpaste what do you do? Do you claim that brushing your teeth is a useless hype that's being pushed by big-tooth because they're exaggerating or misrepresenting what that means?
Only after schizophrenic dentists go around telling people that brushing their teeth is going to lead to a post-scarcity Star Trek world.
Sadly it seems the best use-case for LLMs at this point is bamboozling humans.
They're useful, but you must verify anything you get from them.
Edit: I think I'm just regurgitating the article here.
> You can never trust the LLM to generate a url
This is very poorly worded. Using LLMs more wouldn't solve the problem. What you're really saying is that the GP is uninformed about LLMs.
This may seem like pedantry on my part but I'm sick of hearing "you're doing it wrong" when the real answer is "this tool can't do that." The former is categorically different than the latter.
> I'm sick of hearing "you're doing it wrong"
That's not what they said. They didn't say to use LLMs more for this problem. The only people that should take the wrong meaning from this are ones who didn't read past the first sentence.
> when the real answer is "this tool can't do that."
That is what they said.
Sure, but conceivably, you could also be informed of this second hand, through any publication about LLMs, so it is very odd to say "you don't use them enough" rather than "you're ignorant" or "you're uninformed". It is very similar to these very bizarre AI-maximalist positions that so many of us are tired of seeing.
> Sure, but conceivably, you could also be informed of this second hand, through any publication about LLMs, so it is very odd to say "you don't use them enough" rather than "you're ignorant" or "you're uninformed".
But this is to someone who is actively using them, and the suggestion of "if you were using them more actively you'd know this, this is a very common issue" is not at all weird. There are other ways they could have known this, but they didn't.
"You haven't got the experience yet" is a much milder way of saying someone doesn't know how to use a tool properly than "you're ignorant".