[0] https://www.entrepreneur.com/business-news/ai-ceo-says-softw...
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.
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”.
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.
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.
[0] https://arstechnica.com/ai/2026/03/after-outages-amazon-to-m...
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.
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).
> I’m not seeing applications that took years to ship before
> What we do see is vibe coded slop
My company for example has gotten 500% better at creating productivity tools.
Further, i don't trust code anymore that hasn't been reviewed 3x or more by co-pilot.
If you have asked me 6 months ago I wouldn't have expected this change so soon.
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.
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 less complex the work and the less experienced the operator means more perceived “wow” factor :)
There’s definitely an aspect of how you use it though. In my work it’s mostly been chaining to reduce non-determinism.
Take a snapshot and check again in a few months. It's not perfect but it's much more falsifiable than a lot of the noise.
How many crypto exchanges were pulling in hundreds of millions in funding and doing billions in trades in 2021/2022?
That blog post is… really something, I’ll give you that. Im not entirely sure what else to say about it other than that.
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.
> 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.
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.)
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.
No, GLPs work and that's the difference.
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.