4 ms·

Or just write it yourself?

dukeyukey 3mo ago
If you already know what the inputs/outputs are, why should you spend days or weeks of your life typing it out rather than giving it in a well-specified and tested form to an LLM to get it done a hundred times faster?
- chasd00 3mo ago
  This is a truth that many are having a hard time accepting. Getting shoved into the light so fast is blinding.
  - anon7725 3mo ago
    We understand what you’re claiming, we just think that you are wrong.
- dosisking 3mo ago
  Because the LLM version will have countless number of bugs and security holes, which means you will spend weeks or months of your life fixing them.
- skydhash 3mo ago
  Because it’s rarely so black and white. Knowing the inputs and outputs is merely the first steps, you need to think about the transitions too as they have their own costs. Those costs don’t disappear and it’s truly naive to think they don’t matter. Take security issues, they may arise because what you thinks was the input is merely a subset of the true input range. And the extra possibilities lead to unforeseen behavior. A lot of programming is about ensuring that the input and the output are the sets defined in the specs. And the rest is that the transition/relation is the right tradeoffs of performance, correctness, and costs.
- deleted 3mo ago
  [deleted]
- JCTheDenthog 3mo ago
  >rather than giving it in a well-specified and tested form So, code?
- xigoi 3mo ago
  The behavior of an LLM is not and cannot be “well-specified”.
  - Der_Einzige 3mo ago
    trumps voice wrong https://developers.openai.com/api/docs/guides/structured-outputs https://developers.openai.com/api/docs/guides/structured-out... https://github.com/guidance-ai/guidance https://github.com/guidance-ai/guidance https://github.com/noamgat/lm-format-enforcer https://github.com/noamgat/lm-format-enforcer https://github.com/mlc-ai/xgrammar https://github.com/mlc-ai/xgrammar https://github.com/dottxt-ai/outlines https://github.com/dottxt-ai/outlines
    - JCTheDenthog 3mo ago
      Libraries like Guidance guarantee that the output of an LLM will be syntactically correct (i.e. it will be valid JSON or whatever output format you are wanting). They do not, and fundamentally cannot guarantee that the data contained in them is actually correct, and cannot make the actual behavior of the LLM "well-specified". Or, as you put it, trumps voice wrong.
whehhshs 3mo ago
Because typing “code” takes time and significant amounts of it. We are slowly waking up to the fact, which was always true, that “coding” is just a fanciful preparatory task in order to appease the spirits properly so that we may invoke the spirit of what we are actually after: a live, running process that does useful things. Code is completely useless when separated from that fact. Typing it is a complete waste of time unless getting up close and personal with it will result in some kind of useful and actionable improvement in you or your understanding. Knowing when it does and when it does not have this property is a skill of its own.
- krona 3mo ago
  The typing was never the bottleneck.
  - satvikpendem 3mo ago
    Based on what I'm using AI for these days, seems like it always was.
    - Philip-J-Fry 3mo ago
      It depends on where you're using AI. If you're working on a project for yourself or in a tiny company. Then sure, writing the code probably was your bottleneck. But at mid to large companies writing code is maybe 50% of the job, and the other 50% is the process around it. All those processes are the bottle neck, no matter how fast you can write the code. And this was a bottleneck I was hitting well before AI.
      - Izkata 3mo ago
        I'd put it even lower than that, since there's also the "understand the problem space" portion outside of the external processes and before writing the code.
    - bandrami 3mo ago
      So there are these things called "text editors"

If you already know what the inputs/outputs are, why should you spend days or weeks of your life typing it out rather than giving it in a well-specified and tested form to an LLM to get it done a hundred times faster?

chasd00 3mo ago
This is a truth that many are having a hard time accepting. Getting shoved into the light so fast is blinding.
- anon7725 3mo ago
  We understand what you’re claiming, we just think that you are wrong.
dosisking 3mo ago
Because the LLM version will have countless number of bugs and security holes, which means you will spend weeks or months of your life fixing them.
skydhash 3mo ago
Because it’s rarely so black and white. Knowing the inputs and outputs is merely the first steps, you need to think about the transitions too as they have their own costs. Those costs don’t disappear and it’s truly naive to think they don’t matter. Take security issues, they may arise because what you thinks was the input is merely a subset of the true input range. And the extra possibilities lead to unforeseen behavior. A lot of programming is about ensuring that the input and the output are the sets defined in the specs. And the rest is that the transition/relation is the right tradeoffs of performance, correctness, and costs.
deleted 3mo ago
[deleted]
JCTheDenthog 3mo ago
>rather than giving it in a well-specified and tested form So, code?
xigoi 3mo ago
The behavior of an LLM is not and cannot be “well-specified”.
- Der_Einzige 3mo ago
  trumps voice wrong https://developers.openai.com/api/docs/guides/structured-outputs https://developers.openai.com/api/docs/guides/structured-out... https://github.com/guidance-ai/guidance https://github.com/guidance-ai/guidance https://github.com/noamgat/lm-format-enforcer https://github.com/noamgat/lm-format-enforcer https://github.com/mlc-ai/xgrammar https://github.com/mlc-ai/xgrammar https://github.com/dottxt-ai/outlines https://github.com/dottxt-ai/outlines
  - JCTheDenthog 3mo ago
    Libraries like Guidance guarantee that the output of an LLM will be syntactically correct (i.e. it will be valid JSON or whatever output format you are wanting). They do not, and fundamentally cannot guarantee that the data contained in them is actually correct, and cannot make the actual behavior of the LLM "well-specified". Or, as you put it, trumps voice wrong.

whehhshs 3mo ago

Because typing “code” takes time and significant amounts of it. We are slowly waking up to the fact, which was always true, that “coding” is just a fanciful preparatory task in order to appease the spirits properly so that we may invoke the spirit of what we are actually after: a live, running process that does useful things. Code is completely useless when separated from that fact. Typing it is a complete waste of time unless getting up close and personal with it will result in some kind of useful and actionable improvement in you or your understanding. Knowing when it does and when it does not have this property is a skill of its own.

krona 3mo ago
The typing was never the bottleneck.
- satvikpendem 3mo ago
  Based on what I'm using AI for these days, seems like it always was.
  - Philip-J-Fry 3mo ago
    It depends on where you're using AI. If you're working on a project for yourself or in a tiny company. Then sure, writing the code probably was your bottleneck. But at mid to large companies writing code is maybe 50% of the job, and the other 50% is the process around it. All those processes are the bottle neck, no matter how fast you can write the code. And this was a bottleneck I was hitting well before AI.
    - Izkata 3mo ago
      I'd put it even lower than that, since there's also the "understand the problem space" portion outside of the external processes and before writing the code.
  - bandrami 3mo ago
    So there are these things called "text editors"