> how every new iteration is going to spell doom/be a paradigm shift/change the entire tech industry etc.
It's much the dynamic between parents and a child. The child, with limited hindsight, almost zero insight and no ability to forecast, is annoyed by their parents. Nothing bad ever happens! Why won't parents stop being so worried all the time and make a fuss over nothing?
The parents, which the child somewhat starts to realize but not fully, have no clue what they are doing. There is a lot they don't know and are going to be wrong about, because it's all new to them. But, what they do have is a visceral idea of how bad things could be and that's something they have to talk to their child about too.
In the eyes of the parents the child is % dead all the time. Assigning the wrong % makes you look like an idiot and not being able to handle any % too. In the eyes of the child actions leading to death are not even a concept. Hitting the right balance is probably hard, but not for the reasons the child thinks.
Disagree - we’re being told on one hand that we are 6 months away from AI writing all Code, and 3 months into that the tools are unusable for complex engineering [1]. Every time I mention this I’m told “but have you tried the latest model and this particular tool” - yes I have, but if I need to be on the hottest new model for it to be functional that means the last time you claimed it was solved, it wasn’t solved.
I feel like there’s a bunch of factors for why it will never be the same for many folks, from the models and harnesses, to the domains and existing tests/tooling.
I feel bad for the people for whom it doesn’t work, but Claude Opus has written most of my code in 2026 so far. I had to build some tools around linting entire projects and most of my tokens are probably referencing existing stuff and parallel review iterations and tests, but it’s pretty nice and even seeing legacy code doesn’t make me want move to a farm and grow potatoes.
It might be counter productive to be like: "Oh, just do X!" which works for the person suggesting it, and then have to do "But have you tried Y?" when it doesn't for the other person, if it just keeps being a never ending string of what works for one person not working for another.
> I feel like there’s a bunch of factors for why it will never be the same for many folks
Yeah, and the problem arises simply because some people are unable to accept the fact. They insist that if LLM-assisted coding doesn't work for one, it's because “you're holding it wrong”.
> I feel like there’s a bunch of factors for why it will never be the same for many folks, from the models and harnesses, to the domains and existing tests/tooling.
If the argument is “you have to use the right model, harness, test and tooling for it to work” then it’s not replacing software engineers any time soon.
The other thing is - where are all the web apps, mobile apps, games, desktop apps, from these 100x productivity multipliers. we’re 1-2 years into these tools being widely mainstream and available and I’m not seeing applications that took years to ship before appear at 100x the rate, or games being shipped by tiny teams, or new ideas of mobile apps coming out at 100x the rate. What we do see is vibe coded slop, stability issues with massive companies (windows, AWS for example), and mass layoffs back to pre-covid levels blamed on AI but everyone knows it’s a regression to the mean after a massive over hiring when money was cheap.
It’s like the emperor has no clothes on this topic to me.
I’m an indie developer and I see the explosion in apps in my niche (creative tools for photography/videography).
They wouldn’t have taken years to ship before, but easily a couple months.
Now the moment any app with any value gets popular, the App Store gets flooded with quick vibe coded copycat clones (very recognizable AI generated icon included).
The quality is low, but the impact this flood has on the market is real.
I wouldn't paint the image in such black terms. LLMs can be good in finding bugs and potential issues. And if you like, they can be like IntelliSense on steroids. Even agentic workflows can be good, e.g. for an initial assessment of a new large codebase. And potentially millions of other small tasks like writing one-off helper scripts etc.
So which apps are seeing 10x the bug fixes and improvements in stability and quality? From my side, I see one shot CRUD apps, platforms like AWS and windows actively deteriorating, to the point of causing massive outages and needing to have development processes changed [0]. Who is actually shipping 10x more stuff, or fixing 10x more bugs?
I "pair" with claude-code and still write 30% by hand, with additional review with gpt-5.4, but I definitely write fewer bugs than before. I'd estimate my speedup to be 2x.
The Automation bias issue is something that has been raised by many people like myself but mostly ignored. The better models get the worse that problem with get, but IMHO the implications of the claims are not on the code generation side.
The sandwich story in the model card is the bigger issue.
LLMs have always been good at finding a needle in a haystack, if not a specific needle, it sounds like they are claiming a dramatic increase in that ability.
This will dramatically change how we write and deliver software, which has traditionally been based on the idea of well behaved non-malfeasant software with a fix as you go security model.
While I personally find value in the tools as tools, they specifically find a needle and fundamentally cannot find all of the needles that are relevant.
We will either have to move to some form of zero trust model or dramatically reduce connectivity and move to much stronger forms of isolation.
As someone who was trying to document and share a way of improving container isolation that was compatible with current practices I think I need to readdress that.
VMs are probably a minimum requirement for my use case now, and if verified this new model will dramatically impact developer productivity due to increased constraints.
Due to competing use cases and design choice constraints, none of the namespace based solutions will be safe if even trusted partners start to use this model.
How this lands in the long run is unclear, perhaps we only allow smaller models with less impact on velocity and with less essential complexity etc…
But the ITS model of sockets etc.. will probably be dead for production instances.
I hope this is marketing or aspirational to be honest. It isn’t AGI but will still be disruptive if even close to reality.
It depends on the use, I'm not fixed on "productivity" measured by LoC but on code quality. So when using LLMs to challenge my code I'm less productive but the quality of my code increases.
Where are all the apps?
It's mostly visible in AI tooling itself. Harnesses, vibe coding tools and stuff with "claw" in the name saw a cambrian explosion.
And maybe using AI to use AI better is just masturbatory. But coders want interesting problems to solve. Pros also need software ideas they can monetize. And what problem is attracting more investment in money, time and neurons than the problem of making AI productive? (I am referring only to problems that can be solved in software....)
So the thing with AI is that right now it is both a tool AND a potentially very valuable problem to solve, that's why most of the AI "productivity" gains go into AI itself.
At one point this self-refetential phase will have to end and people are going to see if these new AI tools, harnesses.claw-things are actually applicable to things people are willing to pay the real prices for (not the subsidized ones).
And thus the goalpost was shifted. The first question was "where are all the AI coded apps?" And once this was answered, the subject is immediately switched to quality.
> I had to build some tools around linting entire projects
OK, everybody is doing that. And everybody is doing their best at making LLMs more reliable when working on non-trivial tasks. Yet, it looks like nobody came up with a universal solution yet. This is particularly true for non-trivial projects.
It’s because the models response is conditioned on the prompt. They are as intelligent as the person using them
In some sense it’s a lot like a google search. There’s this big box of knowledge and you are choosing tokens to pluck out of it. The quality of the tokens depends on how intelligent you are.
The irony here is that even if one is extracting legitimate value from LLMs because they are that much smarter than their peers, the process of using LLMs to perform all of their skilled labor makes them less intelligent.
Trade volume and buying API credits are very dissimilar ways of measuring value. One can be wash traded into oblivion, the other is burning a hole in corporate accounts.
> “I think… I don’t know… we might be six to twelve months away from when the model is doing most, maybe all of what SWEs (software engineers) do end to end.”
I think it's disingenuous (as disingenuous as you're accusing these marketing teams of being) to paraphrase that as "being told on one hand that we are 6 months away from AI writing all Code". It's merely stating that it's a real possibility. (It's also disingenuous to use a post complaining about a behavioral regression bug as evidence that it's not progressing)
Dismissing it as impossible is silly, considering how close it already is to a junior dev. Keep in mind that 14 months prior to that statement was before we even had any public reasoning models. Things really are moving that fast, it's just, at the moment, unclear how fast.
We’ve been suggesting that programmers are going to be replaced by simpler programming languages, gui programming tools, no code tools, low code tools, and now AI. The real big step was when Claude code came out and introduced the agentic loop where it could self validate against tests/linters/tooling, but everything after that had been penned as miraculous when IME it’s a new iteration of the same thing - wild hallucinations, getting stuck in deep loops, ignoring explicit instructions and guard rails, wild tangents and just generating stuff that doesn’t work or solve the problem.
> I think it's disingenuous (as disingenuous as you're accusing these marketing teams of being) to paraphrase that as "being told on one hand that we are 6 months away from AI writing all Code". It's merely stating that it's a real possibility
No - you don’t get to make wild predictions and say “oh I didn’t actually mean that, look how succesful we are though”. These teams aren’t saying “hey we think we’re going to majorly influence programming in 6-12 months”, they’re saying “we’re going to replace programmers”. If you can’t stand over your claims, don’t make them. _That’s_ disingenuous.
> We’ve been suggesting that programmers are going to be replaced by simpler programming languages, gui programming tools, no code tools, low code tools, and now AI.
The difference is that it's actually working this time. Non-programmers are writing full apps. Sure, they're simple ones, often just CRUD and UI, but it actually is changing things in a way it never has before. You can't assert something is the same as everything previous when there's already evidence that it's different.
> No - you don’t get to make wild predictions and say “oh I didn’t actually mean that, look how succesful we are though”.
Except that's not what's happening here. I'm criticizing you for misrepresenting what claim was made in the first place. No where in your evidence have you shown anyone "walking the claim back". If anything, TFA is claiming evidence of an LLM doing "most" of what SWEs do "end to end" three months ahead of schedule.
If you want to present evidence Dario (or another CEO -- I'm sure Sama has made much more fantastic claims that you could falsify) made claims that didn't pan out, be my guess, but don't tell falsehoods about the evidence you are presenting.
(And no, I'm not counting breathless tech reporters -- everyone knows how much to trust them when they report a cure for cancer -- they'll say everything is a miracle cure. But the fact that hundreds of "miracle weight loss cures" that never panned out made the new in the past several centuries didn't make GLP1s fake just because they had the same type of hype.)
> The difference is that it's actually working this time. Non-programmers are writing full apps
You can say this about every step along the way. C programmers replaced assembly programmers. Python programmers replaced C programmers. low code tools replaced interal tools teams.
> I'm criticizing you for misrepresenting what claim was made in the first place. No where in your evidence have you shown anyone "walking the claim back".
The claim is that SWES will have their work done by models in 6-12 motnhs. We are _nowhere near_ that 9 months on to it. That's all there is to say it.
> If anything, TFA is claiming evidence of an LLM doing "most" of what SWEs do "end to end" three months ahead of schedule.
TFA based on a model that is so good that it has to be kept from us? from the company that literally can't keep their app up? From the company who shipped an update that didn't launch?
> be my guess, but don't tell falsehoods about the evidence you are presenting.
I mean, I literally posted a quote from the CEO of one of the two major companies saying that SWEs are 6-12 months away from being replaced. This is fantasy talk from a guy who is incentivised to have you believe this. If the claims are that software is changing, and how we're building/deploying software is adapting to that new world then yeah that's fair enough. But the current models, harnesses and tooling are not replacing an SWE unless there's a paradigm shift in the next 3 months. And my point is that we appear t be going backwards, not forwards.
> didn't make GLP1s fake just because they had the same type of hype.
> I mean, I literally posted a quote from the CEO of one of the two major companies saying that SWEs are 6-12 months away from being replaced.
Even ignoring the other ways you're misrepresenting the, there's a huge difference between "might be" and "are going to be".
I'm sorry if English isn't your first language, but we're going to have to agree on basic grammar or else it's not going to be productive for me to continue responding to the flaws in your argument.
That feels like a very complex way of looking at it. Another way would be to say “potentially profit seeking companies have an incentive to oversell products even if they’re good”.
March 2025, Anthropic was claiming that 90% of code would be written by LLMs in three to six months, and "essentially all" code within twelve months. This was one week after closing a Series E round for $3.5 billion. When they began working on their Series F round for $13 billion. You shouldn't need more than that to understand what's going on here.
The Claude Code leak revealed that Anthropic runs Claude-operated bots on the internet. One should be very cautious in getting swept up in the fund-raising process if they are not seeing first-hand the fruition of all of the flattering claims being presented by strangers on the internet.
>March 2025, Anthropic was claiming that 90% of code would be written by LLMs in three to six months, and "essentially all" code within twelve months.
There's a pretty big difference between "We predict in X time frame our model will be capable of Y" and "Our model did Y."
This is like watching someone measure the size of an object and saying "I don't believe you because you guessed it was X before you pulled out your tape measure."
Homie chill. I use Opus every day and I love it. I’m not saying it’s all hype, just that these companies are here to make money and that every advertisement should be taken with salt yeah?
Also maybe consider what this kind of visceral reaction indicates on a personal level :/
I mean if it helps I support the move to not release mythos right off the bat yeah? That makes sense, treat new models like new vulnerabilities and give companies time to scan with them etc.
But you have to admit it does serve a savvy business purpose of creating a moat where one wasn’t by getting these tech companies on board and the threat does make for good marketing yeah?
We have been hearing this since GPT-2. They’ve been crying wolf for too long, that’s on them (the model providers).
That and the fact they never publish anything interesting around their claims. It’s the ffmpeg thing all over again (very old bug in a decoder for a format used by one game from the early 90’s sold as some major breakthrough).
I feel like you’re muddying 2 different arguments here. Or rather, 2 different positions.
You’re asserting that people who are tired of this line being wheeled out hold a position analogous to “what’s the big deal, nothing bad happens, just relax”. In reality, that’s only 1 position. The other position is “I understand fully, the consequences, but the relentless doomer language is tiring in the face of continuing-to-not-eventuate”.
What do you think of people that say that about climate change? It seems you don't understand fully. This is not the time go get tired, right before this actually starts impacting jobs and people in other ways.
It’s more like the abusive parents telling the child that they’ll sell him to the scary man at the bus stop every time they want to coerce the child into doing what they want.
Eventually the child develops disrespect for authority.
This is just a really bad analogy. It doesn't addresses that there are multiple sources, the incentives to be telling us about it, and the spectrum between disaster-mitigation heroes and snake-oil salesmen.
Did you compare AI companies to parents and engineers actually delivering value to toddlers? AI companies cannot, in any capacity, be regarded as caretakers.
Don’t take it personally but this amount of fear and paranoia about death on every corner sounds like a mental illness to me. Generalised Anxiety disorder to be precise. Maybe I am just not a parent.
In any case there are substances and realiable methods that fix whatever paralyzing existential dread anyone struggles with daily.
Probably best to use conventional route but I personally use special low thc, high cbg weed once a week with a medical grade vaporizer and once a year (early autumn) a moderate dose of golden teacher mushrooms. Although I understand that most people perhaps couldn’t due to not managing their own business but on a strict employment contract with urine tests.
Are you suggesting these researchers somehow have wisdom and aren’t just guessing, and that everyone else are children too naive to understand the technology? It certainly sounds that way from the description you are attempting to apply.
This is two parents disagreeing on whether their child will automatically grow up to be a psychopath with one parent constantly remarking “if you teach that child how to cut bread, they will stab everyone later. If you teach that child to drive, they will run over everyone later”, not the “parents know better” situation you describe.
This is literally one the most infantilizing and simultaneously insulting analogies I've ever come across on this site. Do you really think consumers of the latest AI tools have no ability to forecast? The parents in this analogy have every incentive to lie
It's much the dynamic between parents and a child. The child, with limited hindsight, almost zero insight and no ability to forecast, is annoyed by their parents. Nothing bad ever happens! Why won't parents stop being so worried all the time and make a fuss over nothing?
The parents, which the child somewhat starts to realize but not fully, have no clue what they are doing. There is a lot they don't know and are going to be wrong about, because it's all new to them. But, what they do have is a visceral idea of how bad things could be and that's something they have to talk to their child about too.
In the eyes of the parents the child is % dead all the time. Assigning the wrong % makes you look like an idiot and not being able to handle any % too. In the eyes of the child actions leading to death are not even a concept. Hitting the right balance is probably hard, but not for the reasons the child thinks.