I somewhat agree with this poster. However, I think the unfortunate reality of programming for money is that a mediocre programmer that pumps out millions of lines of slop that seems to drive the business forward and manages to hide disastrous bugs until after the contract / promotion cycle is over will get further ahead than the more competent programmer that delivers better, less buggy, less spaghetti code.
Most of us are paid to solve problems and deliver features, not craft the most perfect code known to man.
If the slop-o-matic next to you is delivering 5 features a week without tripping up QA and you do one every two weeks - which one will the company pick when layoffs hit again?
Hearing people on tech twitter say that LLMs always produce better code than they do by hand was pretty enlightening for me.
LLMs can produce better code for languages and domains I’m not proficient in, at a much faster rate, but damn it’s rare I look at LLM output and don’t spot something I’d do measurably better.
These things are average text generation machines. Yes you can improve the output quality by writing a good prompt that activates the right weights, getting you higher quality output. But if you’re seeing output that is consistently better than what you produce by hand, you’re probably just below average at programming. And yes, it matters sometimes. Look at the number of software bugs we’re all subjected to.
And let’s not forget that code is a liability. Utilizing code that was “cheap” to generate has a cost, which I’m sure will be the subject of much conversation in the near future.
> These things are average text generation machines.
Funny... seems like about half of devs think AI writes good code, and half think it doesn't. When you consider that it is designed to replicate average output, that makes a lot of sense.
So, as insulting as OP's idea is, it would make sense that below-average devs are getting gains by using AI, and above-average devs aren't. In theory, this situation should raise the average output quality, but only if the training corpus isn't poisoned with AI output.
I have an anecdote that doesn't mean much on its own, but supports OP's thesis: there are two former coworkers in my linkedin feed who are heavy AI evangelists, and have drifted over the years from software engineering into senior business development roles at AI startups. Both of them are unquestionably in the top 5 worst coders I have ever worked with in 15 years, one of them having been fired for code quality and testing practices. Their coding ability, transition to less technical roles, and extremely vocal support for the power of vibe coding definitely would align with OP's uncharitable character evaluation.
LLMs are not "average text generation machines" once they have context. LLMs learn a distribution.
The moment you start the prompt with "You are an interactive CLI tool that helps users with software engineering at the level of a veteran expert" you have biased the LLM such that the tokens it produces are from a very non-average part of the distribution it's modeling.
If firing up old coal plants and skyrocketing RAM prices and $5000 consumer GPUs and violating millions of developers' copyrights and occasionally coaxing someone into killing themselves is the cost of Brian Who Got Peter Principled Into Middle Management getting to enjoy programming again instead of blaming his kids for why he watches football and drinks all weekend instead of cultivating a hobby, I guess we have no choice but to oblige him his little treat.
LLMs are really great at copy/pasting answers from stack overflow and fitting them to work in a given system. If your work is outside what is answerable on stack overflow you're going to end up fighting the results constantly.
Front end pages like a user settings page? Done. One shottable.
Nuanced data migration problems specific to your stack? You're going to be yelling at the agent.
> LLM evangelists - are you willing to admit that you just might not be that good at programming computers? Maybe you once were. Maybe you never were.
A bit harsh considering that many of us used knowledge bases like SO for so long to figure out new problems that we were confronting.
> Front end pages like a user settings page? Done. One shottable.
This is only one shottable if you are high paced startup or you don't care enough. In real world software, you would need to make it accessible, store data in a complaint way, hook up translations, make sure all inputs are validated and do some usability testing.
I see it only as a threat to those who have a deep hook into their role as a SWE.
If as a SWE you see the oncoming change and adapt to it, no issue.
If as a SWE you see the enablement of LLMs as an existential threat, then you will find many issues, and you will fail to adapt and have all kind of issues related to it.
If a company wants to cut a lot of SWE it wouldn't matter if you have adapted or not, they will just cut as much as they can. How can you adapt more than another SWE? These tools seem easy to learn and there isn't a massive learning curve if you're a programmer. I wonder if changing to a different role would work but I would be skeptical, because after SWEs they will try to cut the other jobs and if there is no one at the bottom, middle management doesn't make sense.
> And then, inevitably, comes the character evaluation, which goes something like this:
I saw a version of this yesterday where a commenter framed LLM-skepticism as a disappointing lack of "hacker" drive and ethos that should be applied to making "AI" toolchains work.
As you might guess, I disagreed: The "hacker" is not driven just by novelty in problems to solve, but in wanting to understand them on more than a surface layer. Messing with kludgy things until they somehow work is always a part of software engineering... but the motive and payoff comes from knowing how things work, and perceiving how they could work better.
What I "fear" from LLMs-in-coding is that they will provide an unlimited flow of "mess around until it works" drudgery tasks with none of the upside. The human role will be hammering at problems which don't really have a "root cause" (except in a stochastic sense) and for which there is never any permanent or clever fix.
Would we say someone is "not really an artist" just because they don't want to spend their days reviewing generated photos for extra-fingers, circling them, and hitting the "redo" button?
> What I "fear" from LLMs-in-coding is that they will provide an unlimited flow of "mess around until it works" drudgery tasks with none of the upside.
I feel like its very true to the hacker spirit to spend more time customizing your text editor than actually programming, so i guess this is just the natural extension.
There’s plenty of understanding we need to get in order to learn to steer the agents precisely, rather than, as you put it, mess around until it works. Some people are actively working on it, while others make a point of looking the other way.
I said this elsewhere. The whole argument is so boring. There are people trying to make money by pushing the tech (annoying videos I come across), but the most vehement side on HN are the anti-LLM.
Within five years I think the debate will be over, and I think I know what the outcome will be.
Can we just agree that both the pro- and anti-llm faction mostly contribute noise? And go back to discuss actual achievements?
It's trivial to share coding sessions, be they horrific or great. Without those, you're hot air on the internet, independent of whatever specific opinions on LLMs you voice.
"And it made me think - why are these people so insistent, and hostile? Why can't they live and let live? Why do they need to convince the rest of us?"
Same could be said about the anti-AI crowd.
I'm glad the author made the distinction that he's talking about LLMs, though, because far too many people these days like to shout from the rooftops about all AI being bad, totally ignoring (willfully or otherwise) important areas it's being used in like cancer research.
"I find LLMs useful as a sort of digital clerk - searching the web for me, finding documentation, looking up algorithms. I even find them useful1 in a limited coding capacity; with a small context and clear guidelines."
I am curious why the author doesn't think this saves them time (i.e. makes them more productive).
I never had terribly high output as a programmer. I certainly think LLMs have helped increased the amount of code that I can write, net total, in a year. Not to superhuman levels or even super-me levels, just me++.
But, I think the total time spent producing code has gone down to a fraction and has allowed me more time to spend thinking about what my code is meant to solve.
I wonder about two things:
1. maybe added productivity isn't going to be found in total code produced, because there is a limit on how much useful code can be produced that is based on external factors
2. do some devs look at the output of an LLM and "get the ick" because they didn't write it and LLM-code is often more verbose and "ugly", even though it may work? (this is a total supposition and not an accusation in any way. i also understand that poorly thought out, overly verbose code comes with problems over time)
See for some, "over time" means "the next guy's problem". That is true before LLMs of course. And that's even the prevailing school of thought in most organizations. And to some extent it is correct to accept some tech debt because otherwise you'll never get anything done.
For those who have been around a while, dealing with the "over time" of yesteryear is a daily occurrence. So naturally they are more averse to it. And LLMs seem to dramatically shorten the duration of "over time".
Simon Wilson (known for Django) has been doing a lot of LLM evangelism on his blog these days. Antirez (Redis) wrote a blog post recently with the same vibe.
I doubt they are not good programmers. They are probably better than most of us, and I doubt they feel insecure because of the LLMs. Either I'm wrong, or there's something more to this.
edit: to clarify, I'm not saying Simon and Antirez are part of the hostile LLM evangelists the article criticizes. Although the article does generalize to all LLM evangelists at least in some parts and Simon did react to this here. For these reasons, I haven't ruled him out as a target of this article, at least partly.
Simon just explores stuff and writes about them. Doesn't mean he uses LLMs for everyting.Antirez likes to question stuff and make them better. Doesn't mean he uses LLMs for everything.
Also their experience is not my experience. I will make my own choices.
Came here to comment on this line: it completely changes the tone of the article. It's fairly reasonable and neutral until we get here, upon which the antagonism is jarringly clear.
In fact I would posit this is the central crux of the post: OP does not believe those LLM evangelists were ever good programmers.
As others have already noted[1], many well-known excellent programmers - including yourself! and now even Linus! - would beg to differ.
I like OP's representation, but I feel like a lot of people arent saying 'LLMs are the bomb dot com _right now_' (though some are), but rather the trend is evident: these things will keep getting better, and the writing is on the wall.
Personally I think the rate of improvement will plateau: in my experience software inevitably becomes less about tech and more about the interpersonal human soup of negotiating requirements, needs, contradiction, and feedback loops, at lot of which is not signal accessible to a text-in-text-out engine.
Until some days / weeks ago, LLM's for coding was more hype than actually real code producing. That is gone now. They clearly leveled up, things will not be the same anymore. And of course this is not just for coding, this is just the beginning. A month ago it really seemed that the models were hitting a complexity wall and that the architecture would need to be improved. Not anymore.
I'm dubbing this "podcast driven development" because so many of them aren't building things to build things, they just want to _have built something_ so they can go on podcasts and talk about how great it is.
For what it's worth, I think most of them are genuine when they say they're seeing 10X gains,they just went from, like, a 0.01X engineer (centi-swe) to to a 0.1X engineer (deci-swe).
I feel no strong need to convince others. I've been seeing major productivity boosts for myself and others since Sonnet 3.5. Maybe for certain kinds of projects and use cases it's less good, maybe they're not using it well; I dunno. I do think a lot of these people probably will be left behind if they don't adopt it within the next 3 years, but that's not really my problem.
What's there to be left behind on? That's like arguing people who stick to driving cars with manual transmissions are going to get left behind when buses "inevitably get good."
The whole point of the AI coding thing is that it lets inexperienced people create software. What skill moat are you building that a skilled software developer won't be able to pick up in 20 minutes?
You need to be fairly smart to be in tech. People who grew up smart and were told they were tend to view it as part of their self worth. If someone disagrees with this person later on, their self with has been attacked so of course they are going to lash out.
The worst thing you can say to a dev is they are wrong. Most will do everything in their power to prove otherwise, even on the dumbest of topics.
Keep in mind that anyone posting on a forum (just like this), or so much more, anyone blogging about something is already a huge selection bias for people who believe that their opinion needs to be shared.
You don't hear from all the people who don't feel that others must know their opinion.
Lurkers always outweigh posters.
Don't ever make the mistake of believing that a sample of posts is a sample of people
> You see a lot of accomplished, prominent developers claiming they are more productive without it.
Demonstrably impossible if you’re actually properly trying to use them in non-esoteric domains. I challenge anyone to very honestly showcase a non-esoteric domain in which opus4.5 does not make even the most experienced developer more productive.
"LLM evangelists - are you willing to admit that you just might not be that good at programming computers? Maybe you once were. Maybe you never were."
lol. is this supposed to be like some sort of "gotcha"! yes? like maybe i am a really shitty programmer and always just wanted to hack things together. what it has allowed me to do is prevent burnout to some extent, outsource the "boring" parts and getting back to building things i like.
also getting tired of these extreme takes but whatever, it's #1 so mission accomplished. llms are neither this or that. just another tool in the toolbox, one that has been frustrating in some contexts and a godsend in others and part of that process is figuring out where it excels and doesn't.
I think it goes further than this. Some people - some developers, even - do not _like_ programming computers. In fact, many hate it. Those people welcome the LLM agent stuff because it delivers the end product without going through the necessary pain (from their pov) of programming.
This is a fun piece to dissect because it's self-aware about being uncharitable, yet still commits the very sin it's criticizing.
The author's central complaint is that LLM evangelists dismiss skeptics with psychological speculation ("you're afraid of being irrelevant"). Their response? Psychological speculation ("you're projecting insecurity about your coding skills").
This is tu quoque dressed up as insight. Fighting unfounded psychoanalysis with unfounded psychoanalysis doesn't refute anything. It just levels the playing field of bad arguments.
The author gestures at this with "I am still willing to admit I am wrong" but the bulk of the piece is vibes-based counter-psychoanalysis, not engagement with evidence.
It's a well-written "no u" that mistakes self-awareness ("I know this isn't charitable") for self-correction.
I see a lot more insecurity from people who refuse to use AI coding tools. My teammates amd I use this stuff all the time, and it's not making a statement, it's just an easier path sometimes.
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[ 5.3 ms ] story [ 92.0 ms ] threadIf the slop-o-matic next to you is delivering 5 features a week without tripping up QA and you do one every two weeks - which one will the company pick when layoffs hit again?
LLMs can produce better code for languages and domains I’m not proficient in, at a much faster rate, but damn it’s rare I look at LLM output and don’t spot something I’d do measurably better.
These things are average text generation machines. Yes you can improve the output quality by writing a good prompt that activates the right weights, getting you higher quality output. But if you’re seeing output that is consistently better than what you produce by hand, you’re probably just below average at programming. And yes, it matters sometimes. Look at the number of software bugs we’re all subjected to.
And let’s not forget that code is a liability. Utilizing code that was “cheap” to generate has a cost, which I’m sure will be the subject of much conversation in the near future.
Funny... seems like about half of devs think AI writes good code, and half think it doesn't. When you consider that it is designed to replicate average output, that makes a lot of sense.
So, as insulting as OP's idea is, it would make sense that below-average devs are getting gains by using AI, and above-average devs aren't. In theory, this situation should raise the average output quality, but only if the training corpus isn't poisoned with AI output.
I have an anecdote that doesn't mean much on its own, but supports OP's thesis: there are two former coworkers in my linkedin feed who are heavy AI evangelists, and have drifted over the years from software engineering into senior business development roles at AI startups. Both of them are unquestionably in the top 5 worst coders I have ever worked with in 15 years, one of them having been fired for code quality and testing practices. Their coding ability, transition to less technical roles, and extremely vocal support for the power of vibe coding definitely would align with OP's uncharitable character evaluation.
The moment you start the prompt with "You are an interactive CLI tool that helps users with software engineering at the level of a veteran expert" you have biased the LLM such that the tokens it produces are from a very non-average part of the distribution it's modeling.
Front end pages like a user settings page? Done. One shottable.
Nuanced data migration problems specific to your stack? You're going to be yelling at the agent.
> LLM evangelists - are you willing to admit that you just might not be that good at programming computers? Maybe you once were. Maybe you never were.
A bit harsh considering that many of us used knowledge bases like SO for so long to figure out new problems that we were confronting.
This is only one shottable if you are high paced startup or you don't care enough. In real world software, you would need to make it accessible, store data in a complaint way, hook up translations, make sure all inputs are validated and do some usability testing.
If as a SWE you see the oncoming change and adapt to it, no issue.
If as a SWE you see the enablement of LLMs as an existential threat, then you will find many issues, and you will fail to adapt and have all kind of issues related to it.
I saw a version of this yesterday where a commenter framed LLM-skepticism as a disappointing lack of "hacker" drive and ethos that should be applied to making "AI" toolchains work.
As you might guess, I disagreed: The "hacker" is not driven just by novelty in problems to solve, but in wanting to understand them on more than a surface layer. Messing with kludgy things until they somehow work is always a part of software engineering... but the motive and payoff comes from knowing how things work, and perceiving how they could work better.
What I "fear" from LLMs-in-coding is that they will provide an unlimited flow of "mess around until it works" drudgery tasks with none of the upside. The human role will be hammering at problems which don't really have a "root cause" (except in a stochastic sense) and for which there is never any permanent or clever fix.
Would we say someone is "not really an artist" just because they don't want to spend their days reviewing generated photos for extra-fingers, circling them, and hitting the "redo" button?
I feel like its very true to the hacker spirit to spend more time customizing your text editor than actually programming, so i guess this is just the natural extension.
We're well past ad nauseum now. Let's talk about anything else.
Within five years I think the debate will be over, and I think I know what the outcome will be.
It's trivial to share coding sessions, be they horrific or great. Without those, you're hot air on the internet, independent of whatever specific opinions on LLMs you voice.
Same could be said about the anti-AI crowd.
I'm glad the author made the distinction that he's talking about LLMs, though, because far too many people these days like to shout from the rooftops about all AI being bad, totally ignoring (willfully or otherwise) important areas it's being used in like cancer research.
I am curious why the author doesn't think this saves them time (i.e. makes them more productive).
I never had terribly high output as a programmer. I certainly think LLMs have helped increased the amount of code that I can write, net total, in a year. Not to superhuman levels or even super-me levels, just me++.
But, I think the total time spent producing code has gone down to a fraction and has allowed me more time to spend thinking about what my code is meant to solve.
I wonder about two things: 1. maybe added productivity isn't going to be found in total code produced, because there is a limit on how much useful code can be produced that is based on external factors 2. do some devs look at the output of an LLM and "get the ick" because they didn't write it and LLM-code is often more verbose and "ugly", even though it may work? (this is a total supposition and not an accusation in any way. i also understand that poorly thought out, overly verbose code comes with problems over time)
For those who have been around a while, dealing with the "over time" of yesteryear is a daily occurrence. So naturally they are more averse to it. And LLMs seem to dramatically shorten the duration of "over time".
Simon Wilson (known for Django) has been doing a lot of LLM evangelism on his blog these days. Antirez (Redis) wrote a blog post recently with the same vibe.
I doubt they are not good programmers. They are probably better than most of us, and I doubt they feel insecure because of the LLMs. Either I'm wrong, or there's something more to this.
edit: to clarify, I'm not saying Simon and Antirez are part of the hostile LLM evangelists the article criticizes. Although the article does generalize to all LLM evangelists at least in some parts and Simon did react to this here. For these reasons, I haven't ruled him out as a target of this article, at least partly.
most top engineers will have their best work locked up in their employer's private repositories
simonw and antirez have an advantage here, and at least the former is very good at self-promotion
Also their experience is not my experience. I will make my own choices.
Here have some actual skill
https://github.com/PCBox/PCBox
This guy is half his age and keeps to himself. Pure quality.
No.
In fact I would posit this is the central crux of the post: OP does not believe those LLM evangelists were ever good programmers.
As others have already noted[1], many well-known excellent programmers - including yourself! and now even Linus! - would beg to differ.
[1] https://news.ycombinator.com/item?id=46610143
Personally I think the rate of improvement will plateau: in my experience software inevitably becomes less about tech and more about the interpersonal human soup of negotiating requirements, needs, contradiction, and feedback loops, at lot of which is not signal accessible to a text-in-text-out engine.
For what it's worth, I think most of them are genuine when they say they're seeing 10X gains,they just went from, like, a 0.01X engineer (centi-swe) to to a 0.1X engineer (deci-swe).
The whole point of the AI coding thing is that it lets inexperienced people create software. What skill moat are you building that a skilled software developer won't be able to pick up in 20 minutes?
And there it is, the insecure evangelism.
"Why are you using Go? Rust is best! You should be using that!" "Don't use AWS CDK, use Terraform! Don't you know anything?"
The worst thing you can say to a dev is they are wrong. Most will do everything in their power to prove otherwise, even on the dumbest of topics.
You don't hear from all the people who don't feel that others must know their opinion.
Lurkers always outweigh posters.
Don't ever make the mistake of believing that a sample of posts is a sample of people
Demonstrably impossible if you’re actually properly trying to use them in non-esoteric domains. I challenge anyone to very honestly showcase a non-esoteric domain in which opus4.5 does not make even the most experienced developer more productive.
lol. is this supposed to be like some sort of "gotcha"! yes? like maybe i am a really shitty programmer and always just wanted to hack things together. what it has allowed me to do is prevent burnout to some extent, outsource the "boring" parts and getting back to building things i like.
also getting tired of these extreme takes but whatever, it's #1 so mission accomplished. llms are neither this or that. just another tool in the toolbox, one that has been frustrating in some contexts and a godsend in others and part of that process is figuring out where it excels and doesn't.
The author's central complaint is that LLM evangelists dismiss skeptics with psychological speculation ("you're afraid of being irrelevant"). Their response? Psychological speculation ("you're projecting insecurity about your coding skills").
This is tu quoque dressed up as insight. Fighting unfounded psychoanalysis with unfounded psychoanalysis doesn't refute anything. It just levels the playing field of bad arguments.
The author gestures at this with "I am still willing to admit I am wrong" but the bulk of the piece is vibes-based counter-psychoanalysis, not engagement with evidence.
It's a well-written "no u" that mistakes self-awareness ("I know this isn't charitable") for self-correction.