6 ms·

"Hey these tools are kind of disappointing" "You just need to learn to use them right" Ad infinitum as we continue to get middling results from the most overh

by __loam 2y ago

"Hey these tools are kind of disappointing" "You just need to learn to use them right" Ad infinitum as we continue to get middling results from the most overhyped piece of technology of all time.

simonw 2y ago
That's why I try not to hype it.
- mvdtnz 2y ago
  You're the biggest hype merchant for this technology on this entire website. Please.
  - simonw 2y ago
    I've been banging the drum about how unintuitive and difficult this stuff is for over a year now: https://simonwillison.net/2025/Mar/11/using-llms-for-code/ https://simonwillison.net/2025/Mar/11/using-llms-for-code/ I'm one of the loudest voices about the so-far unsolved security problems inherent in this space: https://simonwillison.net/tags/prompt-injection/ https://simonwillison.net/tags/prompt-injection/ (94 posts) I also have 149 posts about the ethics of it: https://simonwillison.net/tags/ai-ethics/ https://simonwillison.net/tags/ai-ethics/ - including one of the first high profile projects to explore the issue around copyrighted data used in training sets: https://simonwillison.net/2022/Sep/5/laion-aesthetics-weeknotes/ https://simonwillison.net/2022/Sep/5/laion-aesthetics-weekno... One of the reasons I do the "pelican riding a bicycle" thing is that it's a great way to deflate the hype around these tools - the supposedly best LLM in the world still draws a pelican that looks like it was done by a five year old! https://simonwillison.net/tags/pelican-riding-a-bicycle/ https://simonwillison.net/tags/pelican-riding-a-bicycle/ If you want AI hype there are a thousand places on the internet you can go to get it. I try not to be one of them.
    - __loam 2y ago
      The prompt injection articles you wrote really early in the tech cycle were really good and I appreciated them at the time.
    - andai 2y ago
      Could a five year old do it in XML (SVG)? Could an artist? In one shot?
    - annjose 2y ago
      I agree - the content you write about LLMs is informative and realistic, not hyped. I get a lot of value from it, especially because you write mostly as stream of consciousness and explains your approach and/or reasoning. Thank you for doing that.
  - maleldil 2y ago
    It's true that simonw writes a lot about LLMs, but I find his content to be mostly factual. Much of it is positive, but that doesn't mean it's hype.
- JohnKemeny 2y ago
  Uh... You don't do anything but hype them. I literally don't know who anyone on HN are except you and dang, and you're the one that constantly writes these ads for your LLM database product.
  - simonw 2y ago
    I think you and I must have different definitions of the word "hype". To me, it means LinkedIn influencers screaming "AGI is coming!", "It's so over", "Programming as a career is dead" etc. Or implying that LLMs are flawless technology that can and should be used to solve every problem. To hype something is to provide a dishonest impression of how great it is without ever admitting its weaknesses. That's what I try to avoid doing with LLMs.
    - bluefirebrand 2y ago
      > without ever admitting its weaknesses I don't think this part is necessary "To hype something is to provide a dishonest impression of how great it is" is accurate. Marketing hype is all about "provide a dishonest impression of how great it is". Putting the weaknesses in fine print doesn't change the hype Anyways I don't mean to pile on but I agree with some of the other posters here. An awful lot of extremely pro-AI posts that I've noticed have your name on them I don't think you are as critical of the tech as you think you are. Take that for what you will
tzumaoli 2y ago
also "They will get better in no time"
- simonw 2y ago
  That one's provably correct. Try comparing 2023-era GPT-3.5 with 2025's best models.
  - xboxnolifes 2y ago
    It's not provably correct if the comment is made toward 2025 models.
    - simonw 2y ago
      Gemini 2.5 came out just over two weeks ago (25th March) and is a very significant improvement on Gemini 2.0 (5th February), according to a bunch of benchmarks but also the all-important vibes.
torginus 2y ago
LLMs are a casino. They're probabilistic models which might come up with incredible solutions at a drop of a hat, then turn around and fumble even the most trivial stuff - I've had this same experience from GPT3.5 to the latest and greatest models. They come up with something amazing once, and then never again, leading me to believe, it's operator error, not pure dumb luck or slight prompt wording that lead me to be humbled once, and then tear my hair out in frustration the next time. Granted, newer models tend to do more hitting than missing, but it's still far from a certainty that it'll spit out something good.
pants2 2y ago
In my experience, most people who say "Hey these tools are kind of disappointing" either refuse to provide a reproducible example of how it falls short, or if they do, it's clear that they're not using the tool correctly.
- __loam 2y ago
  Ad infinitum
- sksxihve 2y ago
  I'd love to see a reproducible example of these tools producing something that is exceptional. Or a clear reproducible example of using them the right way. I've used them some (sorry I didn't make detailed notes about my usage, probably used them wrong) but pretty much there are always subtle bugs that if I didn't know better I would have overlooked. I don't doubt people find them useful, personally I'd rather spend my time learning about things that interest me instead of spending money learning how to prompt a machine to do something I can do myself that I also enjoy doing. I think a lot of the disagreements on hn about this tech is that both sides are mostly on the extremes of either "it doesn't work and at and is pointless" or "it's amazing and makes me 100x more productive" and not much discussion about the mid-ground of it works for some stuff and knowing what stuff it works well on makes it useful but it won't solve all your problems.
  - doug_durham 2y ago
    Why are you setting the bar at "exceptional". If it means that you can write your git commit messages more quickly and with fewer errors then that's all the payoff most orgs need to make them worthwhile.
    - bluefirebrand 2y ago
      > Why are you setting the bar at "exceptional" Because that is how they are being sold to us and hyped > If it means that you can write your git commit messages more quickly and with fewer errors then that's all the payoff most orgs need to make them worthwhile. This is so trivial that it wouldn't even be worth looking into, it's basically zero value
TeMPOraL 2y ago
No, it's just you and yours. IDK, maybe there's a secret conspiracy of major LLM providers to split users into two groups, one that gets the good models, and the other that gets the bad models, and ensure each user is assigned to the same bucket at every provider. Surely it's more likely that you and me got put into different buckets by the Deep LLM Cartel I just described, than it is for you to be holding the tool wrong.
KronisLV 2y ago
> "Hey these tools are kind of disappointing" > "You just need to learn to use them right" Admittedly, the first line is also my reaction to the likes of ASM or system level programming languages (C, C++, Rust…) because they can be unpleasant and difficult to use when compared to something that’d let me iterate more quickly (Go, Python, Node, …) for certain use cases. For example, building a CLI tool in Go vs C++. Or maybe something to shuffle some data around and handle certain formatting in Python vs Rust. Or a GUI tool with Node/Electron vs anything else. People telling me to RTFM and spend a decade practicing to use them well wouldn’t be wrong though, because you can do a lot with those tools, if you know how to use them well. I reckon that it applies to any tool, even LLMs.

by __loam 2y ago

"Hey these tools are kind of disappointing" "You just need to learn to use them right" Ad infinitum as we continue to get middling results from the most overhyped piece of technology of all time.

simonw 2y ago

That's why I try not to hype it.

mvdtnz 2y ago
You're the biggest hype merchant for this technology on this entire website. Please.
- simonw 2y ago
  I've been banging the drum about how unintuitive and difficult this stuff is for over a year now: https://simonwillison.net/2025/Mar/11/using-llms-for-code/ https://simonwillison.net/2025/Mar/11/using-llms-for-code/ I'm one of the loudest voices about the so-far unsolved security problems inherent in this space: https://simonwillison.net/tags/prompt-injection/ https://simonwillison.net/tags/prompt-injection/ (94 posts) I also have 149 posts about the ethics of it: https://simonwillison.net/tags/ai-ethics/ https://simonwillison.net/tags/ai-ethics/ - including one of the first high profile projects to explore the issue around copyrighted data used in training sets: https://simonwillison.net/2022/Sep/5/laion-aesthetics-weeknotes/ https://simonwillison.net/2022/Sep/5/laion-aesthetics-weekno... One of the reasons I do the "pelican riding a bicycle" thing is that it's a great way to deflate the hype around these tools - the supposedly best LLM in the world still draws a pelican that looks like it was done by a five year old! https://simonwillison.net/tags/pelican-riding-a-bicycle/ https://simonwillison.net/tags/pelican-riding-a-bicycle/ If you want AI hype there are a thousand places on the internet you can go to get it. I try not to be one of them.
  - __loam 2y ago
    The prompt injection articles you wrote really early in the tech cycle were really good and I appreciated them at the time.
  - andai 2y ago
    Could a five year old do it in XML (SVG)? Could an artist? In one shot?
  - annjose 2y ago
    I agree - the content you write about LLMs is informative and realistic, not hyped. I get a lot of value from it, especially because you write mostly as stream of consciousness and explains your approach and/or reasoning. Thank you for doing that.
- maleldil 2y ago
  It's true that simonw writes a lot about LLMs, but I find his content to be mostly factual. Much of it is positive, but that doesn't mean it's hype.
JohnKemeny 2y ago
Uh... You don't do anything but hype them. I literally don't know who anyone on HN are except you and dang, and you're the one that constantly writes these ads for your LLM database product.
- simonw 2y ago
  I think you and I must have different definitions of the word "hype". To me, it means LinkedIn influencers screaming "AGI is coming!", "It's so over", "Programming as a career is dead" etc. Or implying that LLMs are flawless technology that can and should be used to solve every problem. To hype something is to provide a dishonest impression of how great it is without ever admitting its weaknesses. That's what I try to avoid doing with LLMs.
  - bluefirebrand 2y ago
    > without ever admitting its weaknesses I don't think this part is necessary "To hype something is to provide a dishonest impression of how great it is" is accurate. Marketing hype is all about "provide a dishonest impression of how great it is". Putting the weaknesses in fine print doesn't change the hype Anyways I don't mean to pile on but I agree with some of the other posters here. An awful lot of extremely pro-AI posts that I've noticed have your name on them I don't think you are as critical of the tech as you think you are. Take that for what you will

tzumaoli 2y ago

also "They will get better in no time"

simonw 2y ago
That one's provably correct. Try comparing 2023-era GPT-3.5 with 2025's best models.
- xboxnolifes 2y ago
  It's not provably correct if the comment is made toward 2025 models.
  - simonw 2y ago
    Gemini 2.5 came out just over two weeks ago (25th March) and is a very significant improvement on Gemini 2.0 (5th February), according to a bunch of benchmarks but also the all-important vibes.

torginus 2y ago

LLMs are a casino. They're probabilistic models which might come up with incredible solutions at a drop of a hat, then turn around and fumble even the most trivial stuff - I've had this same experience from GPT3.5 to the latest and greatest models. They come up with something amazing once, and then never again, leading me to believe, it's operator error, not pure dumb luck or slight prompt wording that lead me to be humbled once, and then tear my hair out in frustration the next time. Granted, newer models tend to do more hitting than missing, but it's still far from a certainty that it'll spit out something good.

pants2 2y ago

In my experience, most people who say "Hey these tools are kind of disappointing" either refuse to provide a reproducible example of how it falls short, or if they do, it's clear that they're not using the tool correctly.

__loam 2y ago
Ad infinitum
sksxihve 2y ago
I'd love to see a reproducible example of these tools producing something that is exceptional. Or a clear reproducible example of using them the right way. I've used them some (sorry I didn't make detailed notes about my usage, probably used them wrong) but pretty much there are always subtle bugs that if I didn't know better I would have overlooked. I don't doubt people find them useful, personally I'd rather spend my time learning about things that interest me instead of spending money learning how to prompt a machine to do something I can do myself that I also enjoy doing. I think a lot of the disagreements on hn about this tech is that both sides are mostly on the extremes of either "it doesn't work and at and is pointless" or "it's amazing and makes me 100x more productive" and not much discussion about the mid-ground of it works for some stuff and knowing what stuff it works well on makes it useful but it won't solve all your problems.
- doug_durham 2y ago
  Why are you setting the bar at "exceptional". If it means that you can write your git commit messages more quickly and with fewer errors then that's all the payoff most orgs need to make them worthwhile.
  - bluefirebrand 2y ago
    > Why are you setting the bar at "exceptional" Because that is how they are being sold to us and hyped > If it means that you can write your git commit messages more quickly and with fewer errors then that's all the payoff most orgs need to make them worthwhile. This is so trivial that it wouldn't even be worth looking into, it's basically zero value

TeMPOraL 2y ago

No, it's just you and yours. IDK, maybe there's a secret conspiracy of major LLM providers to split users into two groups, one that gets the good models, and the other that gets the bad models, and ensure each user is assigned to the same bucket at every provider. Surely it's more likely that you and me got put into different buckets by the Deep LLM Cartel I just described, than it is for you to be holding the tool wrong.

KronisLV 2y ago

> "Hey these tools are kind of disappointing" > "You just need to learn to use them right" Admittedly, the first line is also my reaction to the likes of ASM or system level programming languages (C, C++, Rust…) because they can be unpleasant and difficult to use when compared to something that’d let me iterate more quickly (Go, Python, Node, …) for certain use cases. For example, building a CLI tool in Go vs C++. Or maybe something to shuffle some data around and handle certain formatting in Python vs Rust. Or a GUI tool with Node/Electron vs anything else. People telling me to RTFM and spend a decade practicing to use them well wouldn’t be wrong though, because you can do a lot with those tools, if you know how to use them well. I reckon that it applies to any tool, even LLMs.