4 ms·

This concept won't reach that point because when you chisel too hard it crumbles. There are countless lower level tasks that typical programmers no longer learn

by xnx 6mo ago

This concept won't reach that point because when you chisel too hard it crumbles. There are countless lower level tasks that typical programmers no longer learn how to do. Our capacity for knowledge is not unlimited so we offload everything we can to move to the next level of abstraction.

ua709 6mo ago
I get your point, I just wonder how accurate it is. We basically never look at the output of the compiler, so I agree that tool allows one to operate at a higher level than assembly. But I always have to wade through the output from AI so I’m not sure I got to move to the next level of abstraction. But maybe that’s just me.
- willhslade 6mo ago
  Are compilers deterministic?
  - 23df 6mo ago
    For all intents and purposes yeh. Its really about the variance in actual outcomes vs the expected. The variance is not much is it? With LLMs that absolutely isnt the case.
  - ua709 6mo ago
    I'm sure someone, somewhere, once wrote one that wasn't but in general, yes they are. The ones I use certainly are. And with a bit of training you can reason and predict how they will respond to a given input with a large degree of accuracy without being familiar with how the particular compiler under question was implemented. Not so with the AI tools. At least with the ones I use anyway.
  - dbalatero 6mo ago
    Given the same compiler, I believe they would be the same between runs given the same inputs. I suppose that could not be true at the margins, but I would expect correctness out of whatever path it chose.
  - SkyBelow 6mo ago
    Technically LLMs can be ran in deterministic mode as well, but I don't think that is enough. Even a deterministic LLM is too chaotic, small changes in prompts or the otherwise general context can result in vastly different outputs. This makes me think we need some other factor that is stronger than (or maybe orthogonal to) determinism. A notion of being well-behaved or some other non-chaotic term, so that slightly different inputs don't lead to vastly unexpected results. Even that doesn't feel quite correct, because a compiler does seem quite chaotic. Forget a semi colon and an otherwise 99.99% code base results in a vastly different output. But it is still a very understandable output. Very predictable. So while treating both compilers and LLMs as functions that map massive input strings to massive output strings, there is some property I can't well define that compilers have that LLMs still lack (and the question is if they'll always lack it). I can't really define what it is, but it is something more than determinism.
staticshock 6mo ago
That's true, but I think it's beside the point. The flip side of that argument, which is equally true, goes something like, "not doing cognitive push-ups leads to cognitive atrophy." There are skills we're losing that are probably ok to lose (e.g. spacial memory & reasoning vs GPS, mental arithmetic vs calculators), primarily because those are well bounded domains, so we understand the nature of the codependency we're signing up for. AI is an amorphous and still growing domain. It is not a specific rung in the abstraction hierarchy; it is every rung simultaneously, but at different fidelity levels.
- koshyjohn 6mo ago
  > "not doing cognitive push-ups leads to cognitive atrophy" This is one of the points being made in the post, at least in reference to people who already have some mastery of their craft. If they outsource their thinking without elevating it, they aren't exercising that metaphoric muscle between their ears.
- kochikame 6mo ago
  > There are skills we're losing that are probably ok to lose (e.g. spacial memory & reasoning vs GPS, mental arithmetic vs calculators) I'd argue these are not at all OK to lose. You live in an earthquake zone? You sure better know which way is north and where you have to walk to get back home when all the lines are down after a big one. You need to do a quick mental check if a number is roughly where it should be? YOu should be able to do that in your head. There might be better examples that support your point more effectively e.g. cursive writing
  - staticshock 6mo ago
    Yep, there are tons. Growing food, building shelter, etc. But, for pretty much all of the skills we've allowed to atrophy in response to the advances of capitalism, technological & scientific progress, and societal changes, one COULD make the same basic argument, which is that losing that skill is detrimental to the individual, and yet here we are, not growing our own food, not building our own shelter, etc. The arguments you make ≤ the values you actually hold ≤ the actions you take in support of those values. I'm only interested in any such argument to the extent to which you've personally put it into practice. Otherwise, you're living proof of the argument's weakness. (To be fair, it's extremely hard to be internally consistent on this stuff! We all want better for ourselves than we have time and energy for. But that's my point: your fully subconscious emotional calculus will often undercut at least some of your loftier aspirations. Skills that don't matter anymore invariably atrophy due to the opportunity cost of keeping them honed.)
lsy 6mo ago
AI coding isn’t an abstraction, though. You can’t treat a prompt like source code because it will give you a different output every time you use it. An abstraction lets you offload cognitive capacity while retaining knowledge of “what you are doing”. With AI coding either you need to carefully review outputs and you aren’t saving any cognitive capacity, or you aren’t looking at the outputs and don’t know what you’re doing, in a very literal sense.
- IceDane 6mo ago
  It's staggering to me how many times I've heard this argument that LLMs are just the next level of abstraction. Some people are even comparing them to compilers.
  - girvo 6mo ago
    > Some people are even comparing them to compilers. A lot of people are using them as such too: the amount of people talking about "my fleets of agents working on 4 different projects": they aren't reviewing that output. They say they are, but they aren't, anymore than I review the LLVM IR. It makes me feel like I'm in some fantasy land: I watch Opus 4.7 get things consistently backwards at the margins, mess up, make bugs: we wouldn't accept a compiler that did any of this at this scale or level lol
    - habinero 6mo ago
      Right? People have put in decades of work to make them extremely reliable, they didn't magically start like that.
    - IceDane 6mo ago
      It's awful, and seeing even engineers I respected become so AI pilled they're shipping slop without review has made me lose respect for them. It also can't help but make me wonder: what am I missing? Am I holding it wrong? Am I too focused on irrelevant details? So far, my conclusion is that while LLMs can be s productivity boost, you have to direct them carefully. They don't really care about friction and bad abstractions in your codebase and will happily keep piling cards on top of the crooked house of cards they've generated. Just like before AI, you need a cycle of building and refactoring running on repeat with careful reviews. Otherwise you will end up with something that even an LLM will have a hard time working in.
imiric 6mo ago
The idea that a tool intended to replace all human cognitive work is the next level of abstraction is so fundamentally flawed, that I'm not sure it's made in good faith anymore. The most charitable interpretation I can think of is that it's a coping mechanism for being made redundant. Nevermind the fact that these tools are nowhere near as capable as their marketing suggests. Once companies and society start hitting the brick wall of inevitable consequences of the current hype cycle, there will be a great crash, followed by industry correction. Only then will actually useful applications of this technology surface, of which there are plenty. We've seen how this plays out a few times before already.

by xnx 6mo ago

ua709 6mo ago

I get your point, I just wonder how accurate it is. We basically never look at the output of the compiler, so I agree that tool allows one to operate at a higher level than assembly. But I always have to wade through the output from AI so I’m not sure I got to move to the next level of abstraction. But maybe that’s just me.

willhslade 6mo ago
Are compilers deterministic?
- 23df 6mo ago
  For all intents and purposes yeh. Its really about the variance in actual outcomes vs the expected. The variance is not much is it? With LLMs that absolutely isnt the case.
- ua709 6mo ago
  I'm sure someone, somewhere, once wrote one that wasn't but in general, yes they are. The ones I use certainly are. And with a bit of training you can reason and predict how they will respond to a given input with a large degree of accuracy without being familiar with how the particular compiler under question was implemented. Not so with the AI tools. At least with the ones I use anyway.
- dbalatero 6mo ago
  Given the same compiler, I believe they would be the same between runs given the same inputs. I suppose that could not be true at the margins, but I would expect correctness out of whatever path it chose.
- SkyBelow 6mo ago
  Technically LLMs can be ran in deterministic mode as well, but I don't think that is enough. Even a deterministic LLM is too chaotic, small changes in prompts or the otherwise general context can result in vastly different outputs. This makes me think we need some other factor that is stronger than (or maybe orthogonal to) determinism. A notion of being well-behaved or some other non-chaotic term, so that slightly different inputs don't lead to vastly unexpected results. Even that doesn't feel quite correct, because a compiler does seem quite chaotic. Forget a semi colon and an otherwise 99.99% code base results in a vastly different output. But it is still a very understandable output. Very predictable. So while treating both compilers and LLMs as functions that map massive input strings to massive output strings, there is some property I can't well define that compilers have that LLMs still lack (and the question is if they'll always lack it). I can't really define what it is, but it is something more than determinism.

staticshock 6mo ago

That's true, but I think it's beside the point. The flip side of that argument, which is equally true, goes something like, "not doing cognitive push-ups leads to cognitive atrophy." There are skills we're losing that are probably ok to lose (e.g. spacial memory & reasoning vs GPS, mental arithmetic vs calculators), primarily because those are well bounded domains, so we understand the nature of the codependency we're signing up for. AI is an amorphous and still growing domain. It is not a specific rung in the abstraction hierarchy; it is every rung simultaneously, but at different fidelity levels.

koshyjohn 6mo ago
> "not doing cognitive push-ups leads to cognitive atrophy" This is one of the points being made in the post, at least in reference to people who already have some mastery of their craft. If they outsource their thinking without elevating it, they aren't exercising that metaphoric muscle between their ears.
kochikame 6mo ago
> There are skills we're losing that are probably ok to lose (e.g. spacial memory & reasoning vs GPS, mental arithmetic vs calculators) I'd argue these are not at all OK to lose. You live in an earthquake zone? You sure better know which way is north and where you have to walk to get back home when all the lines are down after a big one. You need to do a quick mental check if a number is roughly where it should be? YOu should be able to do that in your head. There might be better examples that support your point more effectively e.g. cursive writing
- staticshock 6mo ago
  Yep, there are tons. Growing food, building shelter, etc. But, for pretty much all of the skills we've allowed to atrophy in response to the advances of capitalism, technological & scientific progress, and societal changes, one COULD make the same basic argument, which is that losing that skill is detrimental to the individual, and yet here we are, not growing our own food, not building our own shelter, etc. The arguments you make ≤ the values you actually hold ≤ the actions you take in support of those values. I'm only interested in any such argument to the extent to which you've personally put it into practice. Otherwise, you're living proof of the argument's weakness. (To be fair, it's extremely hard to be internally consistent on this stuff! We all want better for ourselves than we have time and energy for. But that's my point: your fully subconscious emotional calculus will often undercut at least some of your loftier aspirations. Skills that don't matter anymore invariably atrophy due to the opportunity cost of keeping them honed.)

lsy 6mo ago

AI coding isn’t an abstraction, though. You can’t treat a prompt like source code because it will give you a different output every time you use it. An abstraction lets you offload cognitive capacity while retaining knowledge of “what you are doing”. With AI coding either you need to carefully review outputs and you aren’t saving any cognitive capacity, or you aren’t looking at the outputs and don’t know what you’re doing, in a very literal sense.

IceDane 6mo ago
It's staggering to me how many times I've heard this argument that LLMs are just the next level of abstraction. Some people are even comparing them to compilers.
- girvo 6mo ago
  > Some people are even comparing them to compilers. A lot of people are using them as such too: the amount of people talking about "my fleets of agents working on 4 different projects": they aren't reviewing that output. They say they are, but they aren't, anymore than I review the LLVM IR. It makes me feel like I'm in some fantasy land: I watch Opus 4.7 get things consistently backwards at the margins, mess up, make bugs: we wouldn't accept a compiler that did any of this at this scale or level lol
  - habinero 6mo ago
    Right? People have put in decades of work to make them extremely reliable, they didn't magically start like that.
  - IceDane 6mo ago
    It's awful, and seeing even engineers I respected become so AI pilled they're shipping slop without review has made me lose respect for them. It also can't help but make me wonder: what am I missing? Am I holding it wrong? Am I too focused on irrelevant details? So far, my conclusion is that while LLMs can be s productivity boost, you have to direct them carefully. They don't really care about friction and bad abstractions in your codebase and will happily keep piling cards on top of the crooked house of cards they've generated. Just like before AI, you need a cycle of building and refactoring running on repeat with careful reviews. Otherwise you will end up with something that even an LLM will have a hard time working in.

imiric 6mo ago

The idea that a tool intended to replace all human cognitive work is the next level of abstraction is so fundamentally flawed, that I'm not sure it's made in good faith anymore. The most charitable interpretation I can think of is that it's a coping mechanism for being made redundant. Nevermind the fact that these tools are nowhere near as capable as their marketing suggests. Once companies and society start hitting the brick wall of inevitable consequences of the current hype cycle, there will be a great crash, followed by industry correction. Only then will actually useful applications of this technology surface, of which there are plenty. We've seen how this plays out a few times before already.