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.
AI bug reports went from junk to legit overnight, says Linux kernel czar (theregister.com)
58 points by amarant 4 days ago
supernes 2 hours ago [-]
TLDR: Greg Kroah-Hartman says that last month something magical happened and AI output is no longer "slop".
throwaway2027 34 minutes ago [-]
I noticed it last December.
ramesh31 1 hours ago [-]
>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.
binarymax 57 minutes ago [-]
It’s wrong. It made large mistakes on my code literally yesterday.
brcmthrowaway 46 minutes ago [-]
Wrong context
binarymax 21 minutes ago [-]
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.
Balinares 12 minutes ago [-]
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.
georgemcbay 1 hours ago [-]
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.
bluefirebrand 1 hours ago [-]
> 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.
georgemcbay 1 hours ago [-]
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.
mjr00 45 minutes ago [-]
> 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.
isueej 3 minutes ago [-]
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.
xyzelement 23 minutes ago [-]
Who cares? People know what they want and need and AI is increasingly able to take it from there.
mjr00 34 seconds ago [-]
> 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.
embedding-shape 5 minutes ago [-]
> 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".
PhilipRoman 4 minutes ago [-]
What they want? Sometimes. What they need? Almost never.
pbiggar 28 minutes ago [-]
> 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).
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.
AI bug reports went from junk to legit overnight, says Linux kernel czar (theregister.com)
58 points by amarant 4 days ago
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.
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.
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.
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 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.
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.
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.
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".
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).