When people suggest to use AI for open-source projects, what exactly are they advocating for given that the median open-source project budget is pretty much $0/month? Maybe $1/month if the maintainer likes to have a website for the project.
IMO around December of last year LLM output (for coding at least, not for everything) went from "almost 100% certainly slop" to "probably not slop, if you asked for the right thing while being aware of context limitations".
A lot of people seem stuck with their older (correct at the time) views of them still always producing slop.
FWIW I am more of an AI doomer (in the sense that I think the economic results from them will be disastrous for knowledge workers given our political realities) than booster, but in terms of utility to get work done they did pass a clear inflection point quite recently.
I think LLMs currently need to be used by someone who knows what they are doing to produce value, but the jump they made from being endless slop machines to useful tools in the right hands is enough for me to assume it is only a matter of time until they will be useful tools in the hands of even the untrained masses.
I wish this wasn't true because I think it will economically upend the industry in which I have a career, but sadly the universe doesn't care what I wish.
> assume it is only a matter of time until they will be useful tools in the hands of even the untrained masses.
IMO this vastly overestimates how good the "untrained masses" are at thinking in a logical, mathematical way. Apparently something as basic as Calculus II has a fail rate of ~50% in most universities.
Most people on here don’t belong to that group of people. So ofc they can find a way to create value out of a thing that requires some tinkering and playing with.
The question is can the techniques evolve to become technologies to produce stuff with minimal effort - whilst only knowing the bare minimum. I’m not convinced personally - it’s a pipe dream and overlooks the innate skill necessary to produce stuff.
If they truly did, there wouldn't be a huge amount of humans whose role is basically "Take what users/executives say they want, and figure out what they REALLY want, then write that down for others".
Maybe I've worked for too many startups, and only consulted for larger companies, but everywhere in businesses I see so many problems that are basically "Others misunderstood what that person meant" and/or "Someone thought they wanted X, they actually wanted Y".
The multi-decade existence of roles like "business analysts" and "product owners" (and sometimes "customer success") is pretty strong evidence that this is not the case.
> I wish this wasn't true because I think it will economically upend the industry in which I have a career, but sadly the universe doesn't care what I wish.
I mean, yes. I'm worried about my career too, but for different reasons. I don't think these things are actually good enough to replace me, but I do think it doesn't matter to the people signing the cheques.
I don't believe LLMs are producing anything better than slop. I think people's standards have been sinking for a long time and will continue to sink until they reach the level LLMs produce
The problem isn't just LLMs and the fact they produce slop, it's that people are overall pretty fine with slop
I'm not though, so there's no place for me in most software business anymore
>TLDR: Greg Kroah-Hartman says that last month something magical happened and AI output is no longer "slop".
Opus 4.6 has been a step change. It's simply never wrong anymore. You may need to continue giving it further clarification as to what you want, but it never makes mistakes with what it intends to do now.
> What happened? Kroah-Hartman shrugged: "We don't know. Nobody seems to know why. Either a lot more tools got a lot better, or people started going ..."
Odd sentiment. It's pretty clear the tools crossed a threshold last year (in April as I recall) where they became good enough to actually write entire applications, and just accelerated from there. Today they're amazing and no-one I know is writing artisanal code anymore (at least, not at work).
gotta love a site that hijacks your back button and makes you hit it 3 times.
Doesn't for me until I scroll past the end of the article to read the next one. To get 3 you'd have to scroll through multiple articles.
On mobile you get a little 1.5” strip to read. Rest of the screen is autoplaying ads. No, I didn’t suffer through that to read the article.
I'm thinking of Debian and how much effort it takes to maintain stability and security over time.
I can't imagine we'll really be able to trust AI without it's use in open source software where we can see how reliable it is.
If AI works, imagine 10 years of security updates and possibly 10 years of full OS upgrades for Android phones.
How many year's end have to pass?
Previously: https://news.ycombinator.com/item?id=47547849
When people suggest to use AI for open-source projects, what exactly are they advocating for given that the median open-source project budget is pretty much $0/month? Maybe $1/month if the maintainer likes to have a website for the project.
See also: https://news.ycombinator.com/item?id=47547849
AI bug reports went from junk to legit overnight, says Linux kernel czar (theregister.com)
58 points by amarant 4 days ago
TLDR: Greg Kroah-Hartman says that last month something magical happened and AI output is no longer "slop".
I noticed it last December.
paradigm shift, bro.
IMO around December of last year LLM output (for coding at least, not for everything) went from "almost 100% certainly slop" to "probably not slop, if you asked for the right thing while being aware of context limitations".
A lot of people seem stuck with their older (correct at the time) views of them still always producing slop.
FWIW I am more of an AI doomer (in the sense that I think the economic results from them will be disastrous for knowledge workers given our political realities) than booster, but in terms of utility to get work done they did pass a clear inflection point quite recently.
> if you asked for the right thing while being aware of context limitations
So, still pretty likely to produce slop in a large majority of cases
If the most useful place for them is where you've already specced things out to that degree of precision then they aren't that useful?
Speccing things to that precision is the time consuming and difficult work anyways, after all.
I think LLMs currently need to be used by someone who knows what they are doing to produce value, but the jump they made from being endless slop machines to useful tools in the right hands is enough for me to assume it is only a matter of time until they will be useful tools in the hands of even the untrained masses.
I wish this wasn't true because I think it will economically upend the industry in which I have a career, but sadly the universe doesn't care what I wish.
> assume it is only a matter of time until they will be useful tools in the hands of even the untrained masses.
IMO this vastly overestimates how good the "untrained masses" are at thinking in a logical, mathematical way. Apparently something as basic as Calculus II has a fail rate of ~50% in most universities.
That’s why you can’t generalise opinions on here.
Most people on here don’t belong to that group of people. So ofc they can find a way to create value out of a thing that requires some tinkering and playing with.
The question is can the techniques evolve to become technologies to produce stuff with minimal effort - whilst only knowing the bare minimum. I’m not convinced personally - it’s a pipe dream and overlooks the innate skill necessary to produce stuff.
Who cares? People know what they want and need and AI is increasingly able to take it from there.
> People know what they want and need
If they truly did, there wouldn't be a huge amount of humans whose role is basically "Take what users/executives say they want, and figure out what they REALLY want, then write that down for others".
Maybe I've worked for too many startups, and only consulted for larger companies, but everywhere in businesses I see so many problems that are basically "Others misunderstood what that person meant" and/or "Someone thought they wanted X, they actually wanted Y".
> People know what they want and need
The multi-decade existence of roles like "business analysts" and "product owners" (and sometimes "customer success") is pretty strong evidence that this is not the case.
What they want? Sometimes. What they need? Almost never.
Right… people knew they wanted an iPhone before it was conceived, right? Lmao
The arrogance of people like you is astonishing.
> I wish this wasn't true because I think it will economically upend the industry in which I have a career, but sadly the universe doesn't care what I wish.
I mean, yes. I'm worried about my career too, but for different reasons. I don't think these things are actually good enough to replace me, but I do think it doesn't matter to the people signing the cheques.
I don't believe LLMs are producing anything better than slop. I think people's standards have been sinking for a long time and will continue to sink until they reach the level LLMs produce
The problem isn't just LLMs and the fact they produce slop, it's that people are overall pretty fine with slop
I'm not though, so there's no place for me in most software business anymore
>TLDR: Greg Kroah-Hartman says that last month something magical happened and AI output is no longer "slop".
Opus 4.6 has been a step change. It's simply never wrong anymore. You may need to continue giving it further clarification as to what you want, but it never makes mistakes with what it intends to do now.
It’s wrong. It made large mistakes on my code literally yesterday.
Wrong context
No. Aside from just making an algorithm that didn’t even run, it refused to use an MCP that it had registered in the same context session.
Yo, just because you can't tell when Claude is wrong, doesn't mean it's right.
I do agree that the Q1 2026 models in general have passed a threshold, but goodness almighty Opus 4.6 still screws up a lot.
> Yo, just because you can't tell when Claude is wrong, doesn't mean it's right.
Just because you can't tell when Claude is right, doesn't mean that you are.
This shit is AGI, with decades + billions of dollars of research and development behind it.
So don't get all high and mighty now, acting like you know better than Claude.
> What happened? Kroah-Hartman shrugged: "We don't know. Nobody seems to know why. Either a lot more tools got a lot better, or people started going ..."
Odd sentiment. It's pretty clear the tools crossed a threshold last year (in April as I recall) where they became good enough to actually write entire applications, and just accelerated from there. Today they're amazing and no-one I know is writing artisanal code anymore (at least, not at work).