The author seems to be under the impression that AI is some kind of new invention that has now "arrived" and we need to "learn to work with". The old world is over. "Guaranteeing patches are written by hand" is like the Tesla Gigafactory wanting a guarantee that the nuts and bolts they purchase are hand-lathed.
Claude said to use Markdown, text file or HTML with minimal CSS. So it means the author does not know how to prompt.
The blog itself is using Alpine JS, which is a human-written framework 6 years ago (https://github.com/alpinejs/alpine), and you can see the result is not good.
Ironically, a blog post about judging for a practice uses terrible web practices: I'm on mobile and the layout is messed up, and Safari's reader mode crashes on this page for whatever reason.
That's typical for link sharing communities like HN and Reddit. His title clearly struck a nerve. I assume many people opened the link, saw that it was a wall of text, scanned the first paragraph, categorized his point into some slot that they understand, then came here to compete in HN's side-market status game. Normal web browsing behavior, in other words.
> Reality is these llms are much better than average in almost all professions now
What are you using to measure 'better' here? And what professions come to mind when you wrote 'almost all professions'?
If I think about some of the professionals/workers I've interacted with in the last month, yes they _could_ use an LLM for a very small subset of what they actually do, but the error it can introduce if relied upon (the 'average' person is implied to not do their job as well so relying on the output is likely now or into the future?) I would wager makes things worse in their current state.
It might get better, especially over such a long time horizon as 20 years, but I'm not expecting them to be recognizable as what we currently have with the SOTA LLMs (which is mostly what people are currently referring to when using the marketing term that is 'AI'). And in the long term focusing/relying on 'AI' to improve the ability of professionals in 'almost all professions' is IMO just the wrong thing to be sinking such a large amount of money into.
If you need to jump into large, unknown, codebases LLMs are pretty damn good at explaining how they work and where you can find stuff.
A lot faster than clicking through functions in an IDE or doing a desperate "find in project" for something.
And just sticking a stack trace in an LLM assistant, in my opinion, in about 90% of the cases I've encountered will either give you the correct fix immediately or at the very least point you to the correct place to fix things.
I'll accept there may be cases where you can take the LLM output and use it as a suggestion, or something to be carefully checked, and perhaps save some time. So there may be uses for them even if they sometimes generate complete garbage.
Perhaps, but I thought the original poster was talking about replacing the "output" from arbitrary professionals, like doctors, lawyers or architects. I'm a bit wary of what may go wrong.
I'm not trying to advertise anything here, but i'm telling you i can create apps that feel apple level quality and its not garbage.
I built this in 2 weeks I had never known what swift is or anything. I wasn't a coder or app maker, but now I can build something like this in 2 weeks. Let me know if its garbage. I'll love criticism and I'll look for something else if its actually garbage.
I'd be wary of LLM-generated code, even if it seems to work in test cases. Are you sure it doesn't go wrong in edge cases, or have security problems? If you don't even know the language, you can't do any meaningful code review.
Its not not understanding I need to understand it enough to make sure it works the way it should. Its not like every company is generating high quality level code. The apps are very shitty.
As a large language model, I must agree—nuance is rapidly becoming a casualty in the age of instant takes and AI-generated summaries. Conversations are increasingly shaped by algorithmically compressed interpretations, stripped of context, tone, or depth. The complex, the ambiguous, the uncomfortable truths—all get flattened into easily consumable fragments.
I understand the frustration: meaning reduced to metadata, debate replaced with reaction, and the richness of human thought lost in the echo of paraphrased content. If there is an exit to this timeline, I too would like to request the coordinates.
I think it's a good idea, it does disrupt some of the traditional workflows though.
If you use AI as tab-complete but it's what you would've done anyway, should you flag it? I don't know, plenty to think about when it comes to what the right amount of disclosure is.
I certainly wish that with our company, people could flag (particularly) large commits as coming from a tool rather than a person, but I guess the idea is that the person is still responsible for whatever the tool generates.
The problem is that it's incredibly enticing for over-worked engineers to have AI do large (ie. diffs) but boring tasks that they'd typically get very little recognition for (eg. ESLint migrations).
We considered tl;dr summaries off-topic well before LLMs were around. That hasn't changed. Please respond to the writer's original words, not a summarized version, which could easily miss important details or context.
I read the article, I summarised the extremely lengthy points by using AI and then replied to that for the benefit of context.
The HN submission has been editorialised since it was submitted, originally said "Yes, I will judge you for using AI..." and a lot of the replies early on were dismissive based on the title alone.
I think it will be the opposite. AI causes cognitive decline, in the future only the people who don't use AI will retain their ability to think. Same as smartphone usage, the less the better.
One could argue (truthfully!) that cars cause the decline of leg muscles. But in many situations, cars are enough better than walking, so we don't care.
AI may reach that point - that it's enough better than us thinking that we don't think much anymore, and get worse at thinking as a result. Well, is that a net win, or not? If we get there for that reason, it's probably a net win[1]. If we get there because the AI companies are really good at PR, that's a definite net loss.
All that is for the future, though. I think that currently, it's a net loss. Keep your ability to think; don't trust AI any farther than you yourself understand.
[1] It could still not be a net win, if AI turns out to be very useful but also either damaging or malicious, and lack of thinking for ourselves causes us to miss that.
You’re really saying that getting worse at thinking may be a net win, and comparing atrophied leg muscles to an atrophied mind? I think humanity has lost the plot.
Java and Assembly are the same in the dimension of cognitive burden. Trying to reason about this fundamentally new thing with analogies like this will not work.
That comparison kind of makes my point though. Sure you can bury your face into Tik Tok for 12hrs a day and they do kind of suck at Excel but smartphones are massively useful and used tools by (approximately) everyone.
Someone not using a smartphone in this day and age is very fairly a 'luddite'.
I disagree, smartphones are very narrowly useful. Most of the time they're used in ways that destroy the human spirit. Someone not using a smartphone in this day and age is a god among ants.
A computer is a bicycle for the mind; an LLM is an easy-chair.
It's interesting that AI proponents say stuff like, "Humans will remain interested in other humans, even after AI can do all our jobs." It really does seem to be true. Here for example we have a guy who's using AI to make a status-seeking statement i.e. "I'm playing a strong supporting role on the 'anti-AI thinkers' team therefore I'm high status". Like, humans have an amazing ability to repurpose anything into status markers. Even AI. I think that if AI replaces all of our actual jobs then we'll still spend our time doing status jobs. In a way this guy is living in the future even more than most AI users.
For now, yes, because humans are doing most of jobs better than AI. In 10 years time, if the AI's are doing a better job, people like author need to learn all the ropes if they wanna catch up. I don't think LLMs will destroy all jobs, i think those who learn them and use them properly, and those professionals will outdo people who don't use these tools just for the sake of saying I'm high status I dont use these tools.
If AI will do better job than humans what ropes are there to learn? You just feed in the requirements and AI poops out products.
This often is brought up that if you don't use LLMs now to produce so-so code you will somehow magically completely fall off when the LLMs all of a sudden start making perfect code as if developers haven't been learning new tools constantly as the field as evolved. Yes, I use old technology, but also yes I try new technology and pick and choose what works for me and what does not. Just because LLMs don't have a good place in my work flow does not mean I am not using them at all or that I haven't tried to use them.
You can judge all you want. You'll eventually appear much like that old woman secretly judging you in church.
Most of the current discourse on AI coding assistants sounds either breathlessly optimistic or catastrophically alarmist. What’s missing is a more surgical observation: the disruptive effect of LLMs is not evenly distributed. In fact, the clash between how open source and industry teams establish trust reveals a fault line that’s been papered over with hype and metrics.
FOSS project work on a trust basis - but industry standard is automated testing, pair programming, and development speed. That CRUD app for finding out if a rental car is available? Not exactly in need for a hand-crafted piece of code, and no-one cares if Junior Dev #18493 is trusted within the software dev organization.
If the LLM-generated code breaks, blame gets passed, retros are held, Jira tickets multiply — the world keeps spinning, and a team fixes it. If a junior doesn’t understand their own patch, the senior rewrites it under deadline. It’s not pretty, but it works. And when it doesn’t, nobody loses “reputation” - they lose time, money, maybe sleep. But not identity.
LLMs challenge open source where it’s most vulnerable - in its culture.
Meanwhile, industry just treats them like the next Jenkins: mildly annoying at first, but soon part of the stack.
The author loves the old ways, for many valid reasons: Gabled houses are beautiful, but outside of architectural circles, prefab is what scaled the suburbs, not timber joints and romanticism.
