4 ms·

When I read stories about people 10x’ing their productivity with AI, I interpret them as having the same vibe as these “solvers”.

vultour 2y ago
I think the dystopian Apple Intelligence commercials summed it up perfectly. It sure was a 10x improvement when AI generated the email for that lazy bum, but anyone who’s already bringing value will never see anywhere near those numbers.
- sejje 2y ago
  On what timeline?
  - tejohnso 2y ago
    "never"
hombre_fatal 2y ago
On the other hand, this mentality can keep you from figuring out how to use AI as a tool that works for you. You should speak to people who are using it productively since most of the time its work is verifiable.
- swatcoder 2y ago
  Discussions with the "people who are using it productively" happen all the time here on HN and among our colleages in real life. It's not like you can escape it. But those discussions don't crest the hill because the "verified" work consistently either fails to be addressing a challenge that the skeptics encounter or has qualities that the skeptics can't imagine themselves possessing. The reality is that we all approach our work differently and all carry different standards in what we accept in the work we produce. It's clear that generative AI genuinely helps some people improve their work or ease their burden of producing it, but it should also be clear at this point that the people it doesn't seem to help are not being failed for lack of having learned about its use cases. We're 2+ years in and are saturated with the hype and with such examples. It's just not as universally useful as some people (for whatever reason) want to believe.
  - hombre_fatal 2y ago
    On the flip side, I think a lot of skepticism is just cynicism, and you need to ensure that you are evaluating the tool objectively, not just doing the HN sneer the same way we dismiss Javascript or "web". It's fine if you've found a use-case that LLMs aren't so helpful, like nonfiction writing that you don't want to have to constantly verify for hallucinations. Obviously those exist. But don't forget that they are calling into question whether other people really are super productive with LLMs, and that hints at a self-limiting belief.
    - swatcoder 2y ago
      That's two different discussions. Your original comment was suggesting that people who haven't found a use-case that works for them just haven't looked hard enough, despite how inescapable the topic and tools are. Some hypothetical person that believes nobody might have a personally effective use case is a different one than what you seemed to be writing about, and completely unrelated to what I was writing about. To be fair, the distinction gets muddy in both directions because some people invest their egos into/against this kind of thing and can't just accept differences as they are. But at that point, with those people, you're just stuck in the same class of endless flamewar debate as emacs vs vim or Xbox vs Playstation and there's really no point in giving time or attention to that.
    - elicksaur 2y ago
      I reject the implication that the problem is me or other people who are critical of AI here. I’ve given it a fair shake. Why is user error or literally here a “self-limiting belief” always implied or stated? Almost like I can’t use AI because of a moral failing? C’mon… It honestly sounds like a cult where I don’t know how to read the tea leaves and believe enough. I’ll pass happily and be so self limited :) When AI is actually useful, there won’t be a debate.
      - kelseyfrog 2y ago
        Rather a virtue - the protestant work ethic is a mass.social assumption. It's assumed that hard work is a virtue and that people that find a way to cheat will justly receive their consequences. When this belief primes us to search for flaws, we of course find them. AI even with flaws is good enough. I'm happy to pick up the profit on the difference in our beliefs and behaviors. It's easy to simply out compete.
- n4r9 2y ago
  It's worth keeping a toe in the water, but for now the productivity hype seems way overblown. I recently asked Claude to help deserialize a JSON Post request in an asp.net web API so that absent or null JSON properties get set to the coded default values. They gave me what was nearly the right answer (set NullValueHandling to Ignore) but led me down a merry garden path by saying I should also set DefaultValueHandling to Populate. Every time I said it wasn't working and gave the error message, it came up with additional code to put in, which never helped. Eventually I just started toying around with it myself and realised the solution, but it was maybe half a day down the drain. Perhaps I could have taken a different approach from the start, but still, my impression is that the tools are not what they're made out to be.
  - oxidant 2y ago
    I've had similar issues and the trick I've found is to jump to Google/SO to find examples or docs as soon as Claude stops making progress. If you got NullValueHandling, jumping to the library documentation would give you immediate accurate results.
    - n4r9 2y ago
      I actually did do that, but for some reason I find Newtonsoft's documentation particularly tricky. The recent radical change in Assert formatting hasn't helped either.
olddustytrail 2y ago
That still doesn't mean it's not true...
MyOutfitIsVague 2y ago
It can 10x certain tasks. If you're making an interface to a library for a DSL and have documentation for the library, Claude 3.7 will very accurately fill that out for you extremely quickly. There are a lot of tasks that follow a pretty predictable but not automatable pattern that LLMs do a great job at, but that you couldn't leverage macros or other powerful editor tools to complete. Getting good at LLMs can greatly increase your productivity. But unless your job is just gluing well-defined interfaces together, spinning up demos, or writing documentation for existing code, you won't get 10x. 2x is very realistic for most programming jobs, though. Some tasks would potentially be below 1x, especially low level, novel, thorny logic. I'd never use it for developing new cryptographic primitives or a novel compression codec, for instance.
- elicksaur 2y ago
  I’ve tried to use LLMs for programming. They always fail in extremely predictable ways for the text prediction programs that they are. The phrasing you use is all marketing. When people share actual chat threads that they claim helped them, they always have the same issues I observe in my own use.
  - Foreignborn 2y ago
    i don’t have a stake in this at all, but i've seen dozens and dozens of comments of exactly what you’re asking here on HN. People have been sharing that, plus the problems they’ve solved or products they’ve made. Though, most of these workflows are no longer really just “chats” at like chatgpt.com. A lot of that has changed. i’m not saying you need to do it, or change anything, but… i’ve seen people do shit with a computer lately that 6 months ago would seem weird and alien.
    - jakubmazanec 2y ago
      > i’ve seen people do shit with a computer lately that 6 months ago would seem weird and alien Do you have video?
  - MyOutfitIsVague 2y ago

vultour 2y ago

I think the dystopian Apple Intelligence commercials summed it up perfectly. It sure was a 10x improvement when AI generated the email for that lazy bum, but anyone who’s already bringing value will never see anywhere near those numbers.

sejje 2y ago
On what timeline?
- tejohnso 2y ago
  "never"

hombre_fatal 2y ago

On the other hand, this mentality can keep you from figuring out how to use AI as a tool that works for you. You should speak to people who are using it productively since most of the time its work is verifiable.

swatcoder 2y ago
Discussions with the "people who are using it productively" happen all the time here on HN and among our colleages in real life. It's not like you can escape it. But those discussions don't crest the hill because the "verified" work consistently either fails to be addressing a challenge that the skeptics encounter or has qualities that the skeptics can't imagine themselves possessing. The reality is that we all approach our work differently and all carry different standards in what we accept in the work we produce. It's clear that generative AI genuinely helps some people improve their work or ease their burden of producing it, but it should also be clear at this point that the people it doesn't seem to help are not being failed for lack of having learned about its use cases. We're 2+ years in and are saturated with the hype and with such examples. It's just not as universally useful as some people (for whatever reason) want to believe.
- hombre_fatal 2y ago
  On the flip side, I think a lot of skepticism is just cynicism, and you need to ensure that you are evaluating the tool objectively, not just doing the HN sneer the same way we dismiss Javascript or "web". It's fine if you've found a use-case that LLMs aren't so helpful, like nonfiction writing that you don't want to have to constantly verify for hallucinations. Obviously those exist. But don't forget that they are calling into question whether other people really are super productive with LLMs, and that hints at a self-limiting belief.
  - swatcoder 2y ago
    That's two different discussions. Your original comment was suggesting that people who haven't found a use-case that works for them just haven't looked hard enough, despite how inescapable the topic and tools are. Some hypothetical person that believes nobody might have a personally effective use case is a different one than what you seemed to be writing about, and completely unrelated to what I was writing about. To be fair, the distinction gets muddy in both directions because some people invest their egos into/against this kind of thing and can't just accept differences as they are. But at that point, with those people, you're just stuck in the same class of endless flamewar debate as emacs vs vim or Xbox vs Playstation and there's really no point in giving time or attention to that.
  - elicksaur 2y ago
    I reject the implication that the problem is me or other people who are critical of AI here. I’ve given it a fair shake. Why is user error or literally here a “self-limiting belief” always implied or stated? Almost like I can’t use AI because of a moral failing? C’mon… It honestly sounds like a cult where I don’t know how to read the tea leaves and believe enough. I’ll pass happily and be so self limited :) When AI is actually useful, there won’t be a debate.
    - kelseyfrog 2y ago
      Rather a virtue - the protestant work ethic is a mass.social assumption. It's assumed that hard work is a virtue and that people that find a way to cheat will justly receive their consequences. When this belief primes us to search for flaws, we of course find them. AI even with flaws is good enough. I'm happy to pick up the profit on the difference in our beliefs and behaviors. It's easy to simply out compete.
n4r9 2y ago
It's worth keeping a toe in the water, but for now the productivity hype seems way overblown. I recently asked Claude to help deserialize a JSON Post request in an asp.net web API so that absent or null JSON properties get set to the coded default values. They gave me what was nearly the right answer (set NullValueHandling to Ignore) but led me down a merry garden path by saying I should also set DefaultValueHandling to Populate. Every time I said it wasn't working and gave the error message, it came up with additional code to put in, which never helped. Eventually I just started toying around with it myself and realised the solution, but it was maybe half a day down the drain. Perhaps I could have taken a different approach from the start, but still, my impression is that the tools are not what they're made out to be.
- oxidant 2y ago
  I've had similar issues and the trick I've found is to jump to Google/SO to find examples or docs as soon as Claude stops making progress. If you got NullValueHandling, jumping to the library documentation would give you immediate accurate results.
  - n4r9 2y ago
    I actually did do that, but for some reason I find Newtonsoft's documentation particularly tricky. The recent radical change in Assert formatting hasn't helped either.

olddustytrail 2y ago

That still doesn't mean it's not true...

MyOutfitIsVague 2y ago

It can 10x certain tasks. If you're making an interface to a library for a DSL and have documentation for the library, Claude 3.7 will very accurately fill that out for you extremely quickly. There are a lot of tasks that follow a pretty predictable but not automatable pattern that LLMs do a great job at, but that you couldn't leverage macros or other powerful editor tools to complete. Getting good at LLMs can greatly increase your productivity. But unless your job is just gluing well-defined interfaces together, spinning up demos, or writing documentation for existing code, you won't get 10x. 2x is very realistic for most programming jobs, though. Some tasks would potentially be below 1x, especially low level, novel, thorny logic. I'd never use it for developing new cryptographic primitives or a novel compression codec, for instance.

elicksaur 2y ago
I’ve tried to use LLMs for programming. They always fail in extremely predictable ways for the text prediction programs that they are. The phrasing you use is all marketing. When people share actual chat threads that they claim helped them, they always have the same issues I observe in my own use.
- Foreignborn 2y ago
  i don’t have a stake in this at all, but i've seen dozens and dozens of comments of exactly what you’re asking here on HN. People have been sharing that, plus the problems they’ve solved or products they’ve made. Though, most of these workflows are no longer really just “chats” at like chatgpt.com. A lot of that has changed. i’m not saying you need to do it, or change anything, but… i’ve seen people do shit with a computer lately that 6 months ago would seem weird and alien.
  - jakubmazanec 2y ago
    > i’ve seen people do shit with a computer lately that 6 months ago would seem weird and alien Do you have video?
- MyOutfitIsVague 2y ago