[etamponi]

I spent the last 14 days chasing an issue with a Spark transform. Gemini and Claude were exceptionally good at giving me answers that looked perfectly reasonable: none of them worked, they were almost always completely off-road.

Eventually I tried with something else, and found a question on stackoverflow, luckily with an answer. That was the game changer and eventually I was able to find the right doc in the Spark (actually Iceberg) website that gave me the final fix.

This is to say that LLMs might be more friendly. But losing SO means that we're getting an idiot friendly guy with a lot of credible but wrong answers in place of a grumpy and possibly toxic guy which, however, actually answered our questions.

Not sure why someone is thinking this is a good thing.

[specproc]

What I always appreciate about SO is the dialogue between commenters. LLMs give one answer, or bullet points around a theme, or just dump a load of code in your IDE. SO gives a debate, in which the finer points of an issue are thrashed out, with the best answers (by and large) floating to the top.

SO, at its best, is numerous highly-experienced and intelligent humans trying to demonstrate how clever they are. A bit like HN, you learn from watching the back and forth. I don't think this is something that LLMs can ever replicate. They don't have the egos and they certainly don't have the experience.

Whatever people's gripes about the site, I learned a hell of a lot from it. I still find solutions there, and think a world without it would be worse.

[NewJazz]

The fundamental difference between asking on SO and asking an LLM is that SO is a public forum, and an LLM will be communicated with in private. This has a lot of implications, most of which surround the ability for people to review and correct bad information.

[dbobbitt]

The other major benefit of SO being a public forum is that once a question was wrestled with and eventually answered, other engineers could stumble upon and benefit from it. With SO being replaced by LLMs, engineers are asking LLMs the same questions over and over, likely getting a wide range of different answers (some correct and others not) while also being an incredible waste of resources.

[nprateem]

Surely the fundamental difference is one asks actual humans who know what's right vs statistical models that are right by accident.

[ijidak]

Providing context to ask a Stack Overflow question was time-consuming.

In the time it takes to properly format and ask a question on Stack Overflow, an engineer can iterate through multiple bad LLM responses and eventually get to the right one.

The stats tell the uncomfortable truth. LLMs are a better overall experience than Stack Overflow, even after accounting for inaccurate answers from the LLM.

Don't forget, human answers on Stack Overflow were also often wrong or delayed by hours or days.

I think we're romanticizing the quality of the average human response on Stack Overflow.

[matt_kantor]

The purpose of StackOverflow was never to get askers quick answers to their specific questions. Its purpose is to create a living knowledge repository of problems and solutions which future folk may benefit from. Asking a question on StackOverflow is more like adding an article to Wikipedia than pinging a colleague for help.

If someone doesn't care about contributing to such a repository then they should ask their question elsewhere (this was true even before the rise of LLMs).

StackOverflow itself attempts to explain this in various ways, but obviously not sufficiently as this is an incredibly common misconception.

[fireflash38]

That's only because of LLMs consuming pre-existing discussions on SO. They aren't creating novel solutions.

[specproc]

What I'm appreciating here is the quality of the _best_ human responses on SO.

There are always a number of ways to solve a problem. A good SO response gives both a path forward, and an explanation why, in the context of other possible options, this is the way to do things.

LLMs do not automatically think of performance, maintainability, edge cases etc when providing a response, in no small part because they do not think.

An LLM will write you a regex HTML parser.[0]

The stats look bleak for SO. Perhaps there's a better "experience" with LLMs, but my point is that this is to our detriment as a community.

[^0]: He comes, https://stackoverflow.com/questions/1732348/regex-match-open...

[stocksinsmocks]

Humans do not know what’s right. What’s worse is the phenomenon of people who don’t actually know but want to seem like they know so they ask the person with the question for follow up information that is meaningless and irrelevant to the question.

Hey, can you show me the log files?

Sure here you go. Please help!

Hmm, I don’t really know what I’m looking for in these. Good luck!

[andy81]

SO also isn't afraid to tell you that your question is stupid and you should do it a better way.

Some people take that as a personal attack, but it can be more helpful than a detailed response to the wrong question.

[baq]

The problem is the people who decide which questions are stupid are misaligned with the site's audience.

[zahlman]

> What I always appreciate about SO is the dialogue between commenters.

Stack Overflow is explicitly not for "dialogue", recent experiments (which are generally not well received by the regulars on the meta site) notwithstanding. The purpose of the comments on questions is to help refine the question and ensure it meets standards, and in some cases serve other meta purposes like pointing at different-but-related questions to help future readers find what they're looking for. Comments are generally subject to deletion at any time and were originally designed to be visually minimal. They are not part of the core experience.

Of course, the new ownership is undoing all of that, because of engagement metrics and such.

[specproc]

Heh, OK, dialogue wasn't the right word. I am a better informed person by the power of internet pedantry.

[djfergus]

> I don't think this is something that LLMs can ever replicate. They don't have the egos and they certainly don't have the experience

Interesting question - the result is just words so surely a LLM can simulate an ego. Feed it the Linux kernel mailing list?

Isn’t back and forth exactly what the new MoE thinking models attempt to simulate?

And if they don’t have the experience that is just a question of tokens?

[ehnto]

SO was somewhere people put their hard won experience into words, that an LLM could train on.

That won't be happening anymore, neither on SO or elsewhere. So all this hard won experience, from actually doing real work, will be inaccessible to the LLMs. For modern technologies and problems I suspect it will be a notably worse experience when using an LLM than working with older technologies.

It's already true for example, when using the Godot game engine instead of Unity. LLMs constantly confuse what you're trying to do with Unity problems, offer Unity based code solutions etc.

[sebastiennight]

> Isn’t back and forth exactly what the new MoE thinking models attempt to simulate?

I think the name "Mixture of Experts" might be one of the most misleading labels in our industry. No, that is not at all what MoE models do.

Think of it rather like, instead of having one giant black box, we now have multiple smaller opaque boxes of various colors, and somehow (we don't really know how) we're able to tell if your question is "yellow" or "purple" and send that to the purple opaque box to get an answer.

The result is that we're able to use less resources to solve any given question (by activating smaller boxes instead of the original huge one). The problem is we don't know in advance which questions are of which color: it's not like one "expert" knows CSS and the other knows car engines.

It's just more floating point black magic, so "How do I center a div" and "what's the difference between a V6 and V12" are both "yellow" questions sent to the same box/expert, while "How do I vertically center a div" is a red question, and "what's the most powerful between a V6 and V12" is a green question which activates a completely different set of weights.

[dpkirchner]

I don't know if this is still the case but back in the day people would often redirect comments to some stackoverflow chat feature, the links to which would always return 404 not found errors.

[n49o7]

This comment and the parent one make me realize that people who answer probably value the exchange between experts more than the answer.

Perhaps the antidote involves a drop of the poison.

Let an LLM answer first, then let humans collaborate to improve the answer.

Bonus: if you can safeguard it, the improved answer can be used to train a proprietary model.

[renrutal]

> This comment and the parent one make me realize that people who answer probably value the exchange between experts more than the answer.

I'm more amused that ExpertsExchange.com figured out the core of the issue, 30 years ago, down to their site's name.

[solumunus]

You can ask an LLM to provide multiple approaches to solutions and explore the pros and cons of each, then you can drill down and elaborate on particular ones. It works very well.

[bluedino]

There are so many "great" answers on StackOverflow. Giving the why and not just the answer.

[ianbutler]

It's flat wrong to suggest SO had the right answer all the time, and in fact in my experience for trickier work it was often wrong or missing entirely.

LLMs have a better hit rate with me.

[paganholiday]

The example wasn't even finding a right answer so I don't see where you got that..

Searching questions/answers on SO can surface correct paths on situations where the LLMs will keep giving you variants of a few wrong solutions, kind of like the toxic duplicate closers.. Ironically, if SO pruned the history to remove all failures to match its community standards then it would have the same problem.

[ianbutler]

"But losing SO means that we're getting an idiot friendly guy with a lot of credible but wrong answers in place of a grumpy and possibly toxic guy which, however, actually answered our questions."

> "actually answered our questions."

Read carefully.

[akoboldfrying]

Interpreting that claim as "SO users always, 100% of the time answer questions correctly" is uncharitable to the point of being unreasonable.

Most people would interpret the claim as concisely expressing that you get better accuracy from grumpy SO users than friendly LLMs.

[ianbutler]

For the record I was interpreting that as LLMs are useless (which may have been just as uncharitable), which I categorically deny. I would say they're about just as useful without wading through the mire that SO was.

[paganholiday]

>> Eventually I tried with something else, and found a question on stackoverflow, luckily with an answer. That was the game changer and eventually I was able to find the right doc

Read carefully and paraphrase to the generous side. The metaphor that follows that is obviously trying to give an example of what might be somehow lost.

[ianbutler]

This is a fair critique. I am often not generous enough with people.

[johnnyanmac]

Yes, it does answer you question, when the site lets it go through.

Note that "answers your question" does not mean "solving your problem". Sometimes the answer to a question is "this is infeasible because XYZ" and that's good feedback to get to help you re-evaluate a problem. Many LLMs still struggle with this and would rather give a wrong answer than a negative one.

That said, the "why don't you use X" response is practically a stereotype for a reason. So it's certainly not always useful feedback. If people could introspect and think "can 'because my job doesn't allow me to install Z' be a valid response to this", we'd be in a true Utopia.

[vultour]

It entirely depends on the language you were using. The quality of both questions and answers between e.g. Go and JavaScript is incredible. Even as a relative beginner in JS I could not believe the amount of garbage that I came across, something that rarely happened for Go.

[jtrn]

No point in arguing with people who bring a snowball into Congress to disprove global warming.

[solumunus]

Because what you’re describing is the exception. Almost always with LLM’s I get a better solution, or helpful pointer in the direction of a solution, and I get it much faster. I honestly don’t understand anyone could prefer Google/SO, and in fact that the numbers show that they don’t. You’re in an extreme minority.

[znpy]

> But losing SO means that we're getting an idiot friendly guy with a lot of credible but wrong answers in place of a grumpy and possibly toxic guy which, however, actually answered our questions.

Which by the way is incredibly ironic to read on the internet after like fifteen years of annoying people left and right about toxic this and toxic that.

Extreme example: Linus Torvalds used to be notoriously toxic.

Would you still defend your position if the “grumpy” guy answered in Linus’ style?

[etamponi]

> Would you still defend your position if the “grumpy” guy answered in Linus’ style?

If they answered correctly, yes.

My point is that providing _actual knowledge_ is by itself so much more valuable compared to _simulated knowledge_, in particular when that simulated knowledge is hyper realistic and wrong.

[johnnyanmac]

Sadly, an accountable individual representing an organization is different from a community of semi-anonymous users with a bunch of bureaucracy that can't or doesn't care about every semis anonymous user

[johnsmith1840]

You still get the same thing though?

That grumpy guy is using an LLM and debugging with it. Solves the problem. AI provider fine tunes their model with this. You now have his input baked into it's response.

How you think these things work? It's either a human direct input it's remembering or a RL enviroment made by a human to solve the problem you are working on.

Nothing in it is "made up" it's just a resolution problem which will only get better over time.

[nprateem]

How does that work if there's no new data for them to train on, only AI slurry?

[RobinL]

I'm hoping increasing we'll see agents helping with this sort of issue. I would like an agent that would do things like pull the spark repo into the working area and consult the source code/cross reference against what you're trying to do.

Once technique I've used successfully is to do this 'manually' to ensure codex/Claude code can grep around the libraries I'm using

[kurtis_reed]

Q&A isn't going away. There's still GitHub Discussions.