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I genuinely don't understand why some people are still bullish about LLMs

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Re: I genuinely don't understand why some people are still bullish about LLMs

#51

Post by biker142541 »

doctoboggan wrote: post #28

Why do people who don't like using LLMs keep insisting they are useless for the rest of us? If you don't like to use them, then simply don't use them. I use them almost daily in my job and get tremendous use out of them. I guess you could accuse me of lying, but what do I stand to gain from that? I've also seem people claim that only people who don't know how to code or people doing super simple done a million times…

I don't think it's a matter or liking or not. The use cases just differ considerably, and tools and not as useful or applicable across those. THe OP's use case is probably one of the worst possible for LLMs right now, imo...

Re: I genuinely don't understand why some people are still bullish about LLMs

#52

Post by simonw »

ajkdhcb2 wrote: post #44
turtletontine wrote: post #30

Earlier quoted context omitted.

I literally had a developer of an open source package I’m working with tell me “yeah that’s a known problem, I gave up on trying to fix it. You should just ask ChatGPT to fix it, I bet it will immediately know the answer.” Annoying response of course. But I’d never used an LLM to debug before, so I figured I’d give it a try. First: it regurgitated a bunch of documentation and basic debugging tips, which might have ac…

My experiences have all been like this too. I am puzzled by how some people say it works for them

I wrote this article precisely for people who are having trouble getting good results out of LLMs for coding: https://simonwillison.net/2025/Mar/11/using-llms-for-code/

Re: I genuinely don't understand why some people are still bullish about LLMs

#53

Post by puppycodes »

Here's one simple reason:

I have a very specific esoteric question like: "What material is both electrically conductive and good at blocking sound?" I could type this into google and sift through the titles and short descriptions of websites and eventually maybe find an answer, or I can put the question to the LLM and instantly get an answer that I can then research further to confirm.

This is significantly faster, more informative, more efficient, and a rewarding experience.

As others have said, its a tool. A tool is as good as how you use it. If you expect to build a house by yelling at your tools I wouldn't be bullish either.

Re: I genuinely don't understand why some people are still bullish about LLMs

#54

Post by simonw »

Sohcahtoa82 wrote: post #31
MostlyStable wrote: post #4

My experience (almost exclusively Claude), has just been so different that I don't know what to say. Some of the examples are the kinds of things I explicitly wouldn't expect LLMs to be particularly good at so I wouldn't use them for, and others, she says that it just doesn't work for her, and that experience is just so different than mine that I don't know how to respond. I think that there are two kinds of people w…

> LLMs are almost perfect for this. It's generally faster than me looking up syntax/documentation, when it's wrong it's easy to tell and correct. Exactly this. I once had a function that would generate several .csv reports. I wanted these reports to then be uploaded to s3://my_bucket/reports/{timestamp}/ .csv I asked ChatGPT "Write a function that moves all .csv files in the current directory to and old_reports direc…

I've had so many cases exactly like your example here. If you build up an intuition that knows that e.g. Claude 3.7 Sonnet can write code that uses boto3, and boto3 hasn't had any breaking changes that would affect S3 usage in the past ~24 months, you can jump straight into a prompt for this kind of task.

It doesn't just save me a ton of time, it results in me building automations that I normally wouldn't have taken on at all because the time spent fiddling with os.move/boto3/etc wouldn't have been worthwhile compared to other things on my plate.

Re: I genuinely don't understand why some people are still bullish about LLMs

#55

Post by xiphias2 »

,,By my personal estimate currently GPT 4o DeepResearch is the best one. ''

If the o3 based 3 month old strongest model is the best one, it's a proof that there were quite significant improvements in the last 2 years.

I can't name any other technology that improved as much in 2 years.

O1 and o1 pro helped me with filing tax returns and answered me questions that (probably quite bad) tax accountants (and less smart models) weren't able to (of course I read the referenced laws, I don't trust the output either).

Re: I genuinely don't understand why some people are still bullish about LLMs

#56

Post by simonw »

sdenton4 wrote: post #49
turtletontine wrote: post #30

Earlier quoted context omitted.

I literally had a developer of an open source package I’m working with tell me “yeah that’s a known problem, I gave up on trying to fix it. You should just ask ChatGPT to fix it, I bet it will immediately know the answer.” Annoying response of course. But I’d never used an LLM to debug before, so I figured I’d give it a try. First: it regurgitated a bunch of documentation and basic debugging tips, which might have ac…

This morning I was using an LLM to develop some SQL queries against a database it had never seen before. I gave it a starting point, and outlined what I wanted to do. It proposed a solution, which was a bit wrong, mostly because I hadn't given it the full schema to work with. Small nudges and corrections, and we had something that worked. From there, I iterated and added more features to the outputs. At many points,…

I often wonder if people who report that LLMs are useless for code haven't cracked the fact that you need to to have a conversation with it - expecting a perfect result after your first prompt is setting it up for failure, the real test is if you can get to a working solution after iterating with it for a few rounds.

Re: I genuinely don't understand why some people are still bullish about LLMs

#57

Post by meowface »

AI coding overall still seems to be underrated by the average developer.

They try to add a new feature or change some behavior in a large existing codebase and it does something dumb and they write it off as a waste of time for that use case. And that's understandable. But if they had tweaked the prompt just a bit it actually might've done it flawlessly.

It requires patience and learning the best way to guide it and iterate with it when it does something silly.

Although you undoubtedly will lose some time re-attempting prompts and fixing mistakes and poor design choices, on net I believe the frontier models can currently make development much more productive in almost any codebase.

Re: I genuinely don't understand why some people are still bullish about LLMs

#58

Post by MostlyStable »

nonchalantsui wrote: post #33
MostlyStable wrote: post #19

Earlier quoted context omitted.

I don't know what you are doing or why it's failed. Maybe my primary use cases really are in the top whatever percentile for AI usefulness, but it doesn't feel like it. All I know is that frontier models have already been good enough for more than a year to increase my productivity by a fair bit.

Your use case is in fact in the top whatever percentile for AI usefulness. Short simple scripting that won't have to be relied on due to never being widely deployed. No large codebase it has to comb through, no need for thorough maintenance and update management, no need for efficient (and potentially rare) solutions. The only use case that would beat yours is the type of office worker that cannot write professional…

I fully believe it's far better at the kind of coding/scripting that I do than the kind that real SWEs do. If for no other reason than the coding itself that I do is far far simpler and easier, so of course it's going to do better at it. However, I don't really believe that coding is the only use case. I think that there are a whole universe of other use cases that probably also get a lot of value from LLMs.

I think that HN has a lot of people who are working on large software projects that are incredibly complex and have a huge numbers of interdependencies etc., and LLMs aren't quite to the point that they can very usefully contribute to that except around the edges.

But I don't think that generalizing from that failure is very useful either. Most things humans do aren't that hard. There is a reason that SWE is one of the best paid jobs in the country.

Re: I genuinely don't understand why some people are still bullish about LLMs

#59

Post by turtletontine »

sdenton4 wrote: post #49
turtletontine wrote: post #30

Earlier quoted context omitted.

I literally had a developer of an open source package I’m working with tell me “yeah that’s a known problem, I gave up on trying to fix it. You should just ask ChatGPT to fix it, I bet it will immediately know the answer.” Annoying response of course. But I’d never used an LLM to debug before, so I figured I’d give it a try. First: it regurgitated a bunch of documentation and basic debugging tips, which might have ac…

This morning I was using an LLM to develop some SQL queries against a database it had never seen before. I gave it a starting point, and outlined what I wanted to do. It proposed a solution, which was a bit wrong, mostly because I hadn't given it the full schema to work with. Small nudges and corrections, and we had something that worked. From there, I iterated and added more features to the outputs. At many points,…

That makes sense, and from what I’ve heard this sort of simple quick prototyping is where LLM coding works well. The problem with my case was I’m working with multiple large code bases, and couldn’t pinpoint the problem to a specific line, or even file. So I wasn’t gonna just copy multiple git repos into the chat

(The details: I was working with running a Bayesian sampler across multiple compute nodes with MPI. There seemed to be a pathological interaction between the code and MPI where things looked like they were working, but never actually progressed.)

Re: I genuinely don't understand why some people are still bullish about LLMs

#60

Post by whazor »

retrac wrote: post #3

You're using them wrong. Everyone is though I can't fault you specifically. Chatbot is like the worst possible application of these technologies. Of late, deaf tech forums are taken over by language model debates over which works best for speech transcription. (Multimodal language models are the the state of the art in machine transcription. Everyone seems to forget that when complaining they can't cite sources for s…

I think all the technology is already in place. There are already smart glasses with tiny text displays. Also smartphones have more than enough processing capacity to handle live speech transcription.
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