The anti-LLM arguments aren't just "hand tools are more pure." I would even say that isn't even a majority argument. There are plenty more arguments to make about environmental and economic sustainability, correctness, safety, intellectual property rights, and whether there are actual productivity gains distinguishable from placebo.
It's one of the reasons why "I am enjoying programming again" is such a frustrating genre of blog post right now. Like, I'm soooo glad we could fire up some old coal plants so you could have a little treat, Brian from Middle Management.
I beg to differ. There are a whole lot of folks with astonishingly incomplete understanding about all the facts here who are going to continue to make things very, very complicated. Disagreement is meaningless when the relevant parties are not working from the same assumption of basic knowledge.
There’s a lot of unwillingness to even attempt to try the tools.
There are people I work with who are deep in the AI ecosystem and it's obvious what tools they're using It would not be uncharitable in any way to characterize their work as pure slop that doesn't work, buggy, untested adequately, etc.
The moment I start to feel behind I'll gladly start adopting agentic AI tools, but as things stand now, I'm not seeing any pressing need.
Comments like these make me feel like I'm being gaslit.
If this stuff was self-evidently as useful as it's being made out to be, there would be no point in constantly trying to pressure, coax and cajole people into it. You don't need to spook people into using things that are useful, they'll do it when it makes sense.
The actual use-case of LLMs is dwarfed by the massive investment bubble it has become, and it's all riding on future gains that are so hugely inflated they will leave a crater that makes the dotcom bubble look like a pothole.
One dude with an LLM should be able to write a browser fully capable of browsing the modern web or an OS from scratch in a year, right?
Chrome took at least a thousand man years i.e. 100 people working for 10 years.
I'm lowballing here: it's likely way, way more.
If ai gives 10x speedup, to reproduce Chrome as it is today would require 1 person working for 100 years, 10 people working for 10 years or 100 people working for 1 year.
Clearly, unrealistic bar to meet.
If you want a concrete example: https://github.com/antirez/flux2.c
Creator of Redis started this project 3 weeks ago and use Claude Code to vibe code this.
It works, it's fast and the code quality is as high as I've ever seen a C code base. Easily 1% percentile of quality.
Look at this one-shotted working implementation of jpeg decoder: https://github.com/antirez/flux2.c/commit/a14b0ff5c3b74c7660...
Now, it takes a skilled person to guide Claude Code to generate this but I have zero doubts that this was done at least 5x-10x faster than Antirez writing the same code by hand.
"Being left in the dust" would also mean it's impossible for new people / graduates to ever catch up. I don't think it is. Even though I learned react a few years after it was in vogue (my company bet on the wrong horse), I quickly got up to speed and am just as productive now as someone that started a bit earlier.
There was a land rush to create apps. Basic stuff like the flash light, todo lists, etc, were created and found a huge audience. Development studios were established, people became very successful out of it.
I think the same thing will happen here. There is a first mover advantage. The future is not yet evenly distributed.
You can still start as an iOS developer today, but the opportunity is different.
The introduction of the App Store did not increase developer productivity per se. If anything, it decreased developer productivity, because unless you were already already a Mac developer, you had to learn a programming language you've never used, Objective-C, (now it's largely Swift, but that's still mainly used only on Apple platforms) and a brand new Apple-specific API, so a lot of your previous programming expertise became obsolete on a new platform. What the App Store did that was valuable to developers was open up a new market and bring a bunch of new potential customers, iPhone users, indeed relatively wealthy customers willing to spend money on software.
What new market is brought by LLMs? They can produce as much source code as you like, but how exactly do you monetize that massive amount of source code? If anything, the value of source code and software products will drop as more is able to be produced rapidly.
The only new market I see is actually the developer tool market for LLM fans, essentially a circular market of LLM developers marketing to other LLM developers.
As far as the developer job market is concerned, it's painfully clear that companies are in a mass layoff mood. Whether that's due to LLMs, or whether LLMs are just the cover story, the result is the same. Developer compensation is not on the rise, unless you happen to be recruited by one of the LLM vendors themselves.
My impression is that from the developer perspective, LLMs are a scheme to transfer massive amounts of wealth from developers to the LLM vendors. And you can bet the prices for access to LLMs will go up, up, up over time as developers become hooked and demand increases. To me, the whole "OpenClaw" hype looks like a crowd of gamblers at a casino, putting coins in slot machines. One thing is for certain: the house always wins.
I think it will make prototyping and MVP more accessible to a wider range of people than before. This goes all the way from people who don't know how to code up to people who know very well how to code, but don't have the free time/energy to pursue every idea.
Project activation energy decreases. I think this is a net positive, as it allows more and different things to be started. I'm sure some think it's a net negative for the same reasons. If you're a developer selling the same knowledge and capacity you sold ten years ago things will change. But that was always the case.
My comparison to iOS was about the market opportunity, and the opportunity for entrepreneurship. It's not magic, not yet anyway. This is the time to go start a company, or build every weird idea that you were never going to get around to.
There are so many opportunities to create software and companies, we're not running out of those just because it's faster to generate some of the code.
Returning to the iOS analogy, though, there was only a short period of time in history when a random developer with a flashlight or fart app could become successful in the App Store. Nowadays, such a new app would flop, if Apple even allowed it, as you admitted: "You can still start as an iOS developer today, but the opportunity is different." The software market in general is not new. There are already a huge number of competitors. Thus, when you say, "This is the time to go start a company, or build every weird idea that you were never going to get around to," it's unclear why this would be the case. Perhaps the barrier to entry for competitors has been lowered, yet the competition is as fierce as ever (unlike in the early App Store).
In any case, there's a huge difference between "the barrier to entry has been lowered" and "those who don't use LLMs will be left in the dust". I think the latter is ridiculous.
Where are the original flashlight and fart app developers now? Hopefully they made enough money to last a lifetime, otherwise they're back in the same boat as everyone else.
Yeah, it’s a bit incendiary, I just wanted to turn it into a more useful conversation.
I also think it overstates the case, but I do think it’s an opportunity.
It’s not just that the barrier to entry has been lowered (which it has) but that someone with a lot of existing skill can leverage that. Not everyone can bring that to the table, and not everyone who can is doing so. That’s the current advantage (in my opinion, of course).
All that said, I thought the Vision Pro was going to usher in a new era of computing, so I’m not much of a prognosticator.
> I also think it overstates the case
I think it's a mistake to defend and/or "reinterpret" the hype, which is not helping to promote the technology to people who aren't bandwagoners. If anything, it drives them away. It's a red flag.
I wish you would just say to the previous commenter, hey, you appear to be exaggerating, and that's not a good idea.
The App Store reshuffled the deck. Some people recognized that and took advantage of the decalcification. Some of them did well.
You've recognized some implications of the reshuffle that's currently underway. Maybe you're right that there's a bias toward the LLM vendors. But among all of it, is there a niche you can exploit?
What do you get from it? Say you produce more, do you get a higher salary?
What I have seen so far is the opposite: if you don't produce more, you risk getting fired.
I am not denying that LLMs make me more productive. Just saying that they don't make me more wealthy. On the other hand, they use a ton of energy at a time where we as a society should probably know better. The way I see it, we are killing the Earth because we produce too much. LLMs help us produce more, why should we be happy?
Not all that hard to learn, but waiting for things to settle down assumes things are going to settle down. Are they? When?
These are leaked implementation details that the labs are forcing us to know because these are weak, early products and they’re still exploring the design space. The median user doesn’t want to and shouldn’t have to care about details like this.
Future products in this space won’t have them and future users won’t be left in the dust by not learning them today.
Python programmers aren’t left behind by not knowing malloc and free.
"Anti-LLM sentiment" within software development is nearly non-existent. The biggest kind of push-back to LLMs that we see on HN and elsewhere, is effectively just pragmatic skepticism around the effectiveness/utility/ROI of LLMs when employed for specific use-cases. Which isn't "anti-LLM sentiment" any more than skepticism around the ability of junior programmers to complete complex projects is "anti-junior-programmer sentiment."
The difference between the perspectives you find in the creative professions vs in software dev, don't come down to "not getting" or "not understanding"; they really are a question of relative exposure to these pro-LLM vs anti-LLM ideas. Software dev and the creative professions are acting as entirely separate filter-bubbles of conversation here. You can end up entirely on the outside of one or the other of them by accident, and so end up entirely without exposure to one or the other set of ideas/beliefs/memes.
(If you're curious, my own SO actually has this filter-bubble effect from the opposite end, so I can describe what that looks like. She only hears the negative sentiment coming from the creatives she follows, while also having to dodge endless AI slop flooding all the marketplaces and recommendation feeds she previously used to discover new media to consume. And her job is one you do with your hands and specialized domain knowledge; so none of her coworkers use AI for literally anything. [Industry magazines in her field say "AI is revolutionizing her industry" — but they mean ML, not generative AI.] She has no questions that ChatGPT could answer for her. She doesn't have any friends who are productively co-working with AI. She is 100% out-of-touch with pro-LLM sentiment.)
For software the situation is different. Being opposed to LLM-generated software is just batshit crazy at this point. The value that LLMs provide to the process makes learning to use them, objectively, an absolute must; otherwise you are simply wasting time and money. Eric S. Raymond put it something like "If you call yourself a software engineer, you have no excuse not to be using these tools. Get your thumb out of your ass and learn."
I can say “learn how to use vim makeprg feature so that you can jump directly to errors reported by the build and tool” and it’s very clear where the ROI. But all the AI hypers are selling are hope, prayers, and rituals.
I'm curious about what industry you are in and the tech stack you are using?
It may take some human intervention, but the productivity results are pretty consistent: tasks that used to take weeks now take hours or days. This puts in reach the ability to try things you wouldn't countenance otherwise due to the effort and tedium involved. You'd have to be a damn fool not to take advantage of the added velocity. This is why what we do is called "engineering", not a handicraft.
> This puts in reach the ability to try things you wouldn't countenance otherwise due to the effort and tedium involved.
If you’re talking about prototypes, a whiteboard is way cheaper and less time consuming than an agent.
Strong disagree right there. I remember talking to a (developer) coworker a few months ago who seemed like the biggest AI proponent on our team. When we were one-on-one during a lunch though, he revealed that he really doesn't like AI that much at all, he's just afraid to speak up against it. I'm in a few Discord channels with a lot of highly skilled (senior and principal programmers) who mostly work in game development (or adjacent), and most of them either mock LLMs or have a lot of derision for it. Hacker News is kind of a weird pro-AI bubble, most other places are not nearly as keen on this stuff.
This is certainly untrue. I want to say "obviously", which means that maybe I am misunderstanding you. Below are some examples of negative sentiments programmers have - can you explain why you are not counting these?
NOTE: I am not presenting these as an "LLMs are bad" argument. My own feelings go both ways. There is a lot that's great about LLMs, and I don't necessarily agree with every word I've written below - some of it is just my paraphrasing of what other people say. I'm only listing examples of what drives existing anti-LLM sentiment in programmers.
1. Job loss, loss of income, or threat thereof
These two are exacerbated by the pace of change, since so many people already spent their lives and money establishing themselves in the career and can't realistically pivot without becoming miserable - this is the same story for every large, fast change - though arguably this one is very large and very fast even by those standards. Lots of tech leadership is focusing even more than they already were on cheap contractors, and/or pushing employees for unrealistic productivity increases. I.e. it's exacerbating the "fast > good" problem, and a lot of leadership is also overestimating how far it reduces the barrier to creating things, as opposed to mostly just speeding up a person's existing capabilities. Some leadership is also using the apparent loss of job security as leverage beyond salary suppression (even less proportion of remote work allowed, more surveillance, worse office conditions, etc).
2. Happiness loss (in regards to the job itself, not all the other stuff in this list)
This is regarding people who enjoy writing/designing programs but don't enjoy directing LLMs; or who don't enjoy debugging the types of mistakes LLMs tend to make, as opposed to the types of mistakes that human devs tend to make. For these people, it's like their job was forcibly changed to a different, almost unrelated job, which can be miserable depending on why you were good at - or why you enjoyed - the old job.
3. Uncertainty/skepticism
I'm pushing back on your dismissal of this one as "not anti-LLM sentiment" - the comparison doesn't make sense. If I was forced to only review junior dev code instead of ever writing my own code or reviewing experienced dev code, I would be unhappy. And I love teaching juniors! And even if we ignore the subset of cases where it doesn't do a good job or assume it will soon be senior-level for every use case, this still overlaps with the above problem: The mistakes it makes are not like the mistakes a human makes. For some people, it's more unnatural/stressful to keep your eyes peeled for the kinds of mistakes it makes. For these people, it's a shift away from objective, detail-oriented, controlled, concrete thinking; away from the feeling of making something with your hands; and toward a more wishy-washy creation experience that can create a feeling of lack of control.
4. Expertise loss
A lot of positive outcomes with LLMs come from being already experienced. Some argue this will be eroded - both for new devs and existing experienced devs.
5. The training data ownership/morality angle
> A lot of positive outcomes with LLMs come from being already experienced. Some argue this will be eroded - both for new devs and existing experienced devs.
This is true, but the pace of progress is so mind blowing the experts we have now might just be enough until the whole industry becomes obsolete (10-20 years assuming the lower bound of the trend line holds?)
I like this. What's more, while AI-generated art has a characteristic sameyness to it, the human-produced art stands out in its originality. It has character and soul. Even if it's bad! AI slop has made the human-created stuff seem even more striking by comparison. The market for human art isn't going anywhere, just like the audience for human-played chess went nowhere after Deep Blue. I think people will pay a premium for it, just to distinguish themselves from the slop. The same is true of writing and especially music. I know of no one who likes listening to AI-generated music. Even Sabrina Carpenter would raise less objection.
The same, I'm afraid, cannot be said for software—because there is little value for human expression in the code itself. Code is—almost entirely—strictly utilitarian. So we are now at an inflection point where LLMs can generate and validate code that's nearly as good, if not better, than what we can produce on our own. And to not make use of them is about as silly as Mel Kaye still punching in instruction opcodes in hex into the RPC-4000, while his colleagues make use of these fancy new things called "compilers". They're off building unimaginably more complex software than they could before, but hey, he gets his pick of locations on the rotating memory drum!
I'm one of the nonexistent anti-LLMers when it comes to software. I hate talking to a clanker, whose training data set I don't even have access to let alone the ability to understand how my input affects its output, just to do what I do normally with the neural net I've carried around in my skull and trained extensively for this very purpose. I like working directly with code. Code is not just a product for me; it is a medium of thought and expression. It is a formalized notation of a process that I can use to understand and shape that process.
But with the right agentic loops, LLMs can just do more, faster. There's really no point in resisting. The marginal value of what I do has just dropped to zero.
I see it all the time in professional and personal circles. For one, you are shifting the goalpost on what is “anti-llm”, two, people are talking about the negative social, political and environmental impacts.
What is your source here?