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Comment by tlogan | Hacker News Reader

The main issue with Stack Overflow (and similar public Q&A platforms) is that many contributors do not know what they do not know, leading to inaccurate answers.

Additionally, these platforms tend to attract a fair amount of spam (self promotion etc) which can make it very hard to find high-quality responses.

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I find that LLMs are precisely that: marvelous engines to explore "what you don't know that you don't know", about anything.

I’m not sure how to take you comment, but I feel the same(?) way. I love that I can use LLMs to explore topics that I don’t know well enough to find the right language to get hits on. I used to be able to do this with google, after a few queries, and skimming to page 5 hits, I’d eventually find the one phrase that cracks open the topic. I haven’t been able to do that with google for at least 10 years. I do it regularly with LLMs today.

They are extraordinarily useful for this! "Blah blah blah high level naive description of what I want to know about, what is the term of art for this?"

Then equipped with the right term it's way easier to find reliable information about what you need.

Medium is even worse about this. It's more self-promotion than it is common help.

Begin rant.

I don’t want to be that guy saying this, but 99% of the top results on google from Medium related to anything technical is literally the reworded/reframed version of the official quick start guide.

There are some very rare gems, but it is hard to find those among the above mentioned ocean of reworded quick starts disguised as “how to X”, “fixing Y”. Almost reminds me of the SEO junks when you search “how to restart iPhone” and find answers that dance around letting it die from battery drain and then charge, install this software, take it to the apple repair shop, go to settings and traverse many steps while not saying that if you are between these models use the power+volume up button trick.

End of rant.

Somebody who just summarizes tutorials can write like 10 medium posts, in the time it takes an actual practitioner to do something legitimately interesting.

Well said. Most great articles I found on Medium are actually very old hence do not rank well.

QA platforms and blogging platforms both seem to have finite lifespans. QA forums (Stack Overflow, Quora, Yahoo answers) do seem to last longer, need to be moderated pretty aggressively unless they are going to turn into homework help platforms.

Blogging platforms are the worst though. Medium looked pretty OK when it first came out. But now it is just a platform for self-promotion. Substack is like 75% of the way through that transition IMO.

People who do interesting things spend most of their time doing the thing. So, non-practicing bloggers and other influencers will naturally overwhelm the people who actually have anything interesting to report.

What you mention has been serious from day one indeed.

But to me the worst issue is it's now "Dead Overflow": most answers are completely, totally and utterly outdated. And seen that they made the mistake of having the concept of an "accepted answer" (which should never have existed), it only makes the issue worse.

If it's a question about things that don't change often, like algorithms, then it's OK. But for anything "tech", technical rot is a very real thing.

To me SO has both outdated and inaccurate answers.

I agree that "accepted answer" is a misfeature; but the default is for questions to remain open to new answers indefinitely.

On the one hand, good new answers can remain buried under mediocre and outdated answers more or less indefinitely, because they received hundreds of questionable upvotes in the past. (Despite popular perception, the average culture of Stack Overflow is very heavily weighted towards upvoting. I have statistical analysis of this on the meta site somewhere.)

On the other hand, there are tons of popular reference questions that had to be "protected" so that people couldn't just sign up and contribute the 100th answer (yes, the count really does range into triple digits in several cases, especially if you have access to deleted answers) to a question where there are maybe five actually reasonable-considered-distinct answers possible. And this protection is a quite low barrier - 10 reputation, IIRC. (I'm not sure what motivates people to write these new answers. It might have something to do with being able to point to a Stack Overflow profile which boasts that you've "reached" millions of people, due to its laughably naive algorithm for that.)

>The main issue with Stack Overflow (and similar public Q&A platforms) is that many contributors do not know what they do not know, leading to inaccurate answers.

The best Q&A platform would be the one where experts and scientists answer questions but sites like Wikipedia and Reddit showed that broad range of audience can also be pretty good at providing useful information and moderating it.

I've gotten answers from OpenAI that were technically correct but quite horrible in the longer term. I've gotten the same kinds of answers on Stack Overflow, but there other people are eager to add the necessary feedback. I got the same feedback from an LLM but only because in that case I knew enough to ask for it.

Maybe we can get this multi-headed advantage back from LLMs by applying a team of divergent AIs to the same problem. I've had other occasions when OpenAI gave me crap that Claude corrected, and visa versa.

You can usually even ask the same LLM:

- do a task

- criticize your job on that task

- redo that task based on criticism

I find giving the LLM a process greatly improves the results.

How do you know the second result is correct? Or the third? Or the fourth?

I approach it the same way as the things I build myself - testing and measuring.

Although if I’m truly honest with myself, even after many years of developing, the true cycle of me writing code is: over confidence, then shock it didn’t work 100% the first time, wondering if there is a bug in the compiler, and then reality setting in that of course the compiler is fine and I just made my 15th off-by-one error of the day :)

What’s fun is that you can skip step 1. The LLM will happily critique its own nonexistent output.

So?

I too can write made up criticism if that’s what my boss wants in the workplace — but that doesn’t suddenly invalidate my ability to criticize my own work to improve it.

That's a smart idea I didn't think of.

I've been arguing with Copilot back and forth where it gave me a half-working solution that seemed overly complicated but since I was new to the tech used, I couldn't say what exactly was wrong. After a couple of hours, I googled the background and trust my instinct and was able to simplify the code.

At that situation, where I iteratively improved the solution by telling Copilot things seem to complicated and this or that isn't working. That led the LLM to actually come back with better ideas. I kept asking myself why something like you propose isn't baked into the system.

The papers I've read have shown LLM critics to be quite bad at their work. If you give an LLM a few known good and bad results, I think you'll see the LLM is just as likely to make good results bad as it is to make bad results good.

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