Only that the compiler works in a defined algorithmic way that can always be expected to work, at worst it uses more cpu registers than needed or something. AI on the other hand just spews garbage in a fundamentally statistical way and despite the enormous efforts to create tools that manipulate it into working more predictably, it still sucks so much of the time.
Another difference is that you are critically thinking when “instructing” a compiler via the code, but you only convince yourself that you think critically when you’re instructing an AI, it’s not the same and it actively makes you a worse engineer every time you decide to use it instead of thinking.
Cognitive Surrender. I can feel it happening every time I use this employer-mandated Cursor crap. I’m fighting it as hard as I can. Every AI slop pull request I have to review makes me die a little more inside.
(Edit: I’m glad this was so well received, but people are hating on my “assembler isn’t as difficult as people think” post below. Oh well.)
It’s not the form that’s the issue. It’s the required depth of that thought, when you are actually doing the work yourself you need to go all the way in your thinking otherwise it simply won’t work. When you’re vibe coding, your thinking only goes as far as you see necessary so the AI has enough context to give something useful in return. It’s like comparing the thought process of an analyst and of the engineer that implements the spec, any engineer knows that difference.
I feel like this says more about neuroscience than it does about LLMs. :D
But seriously, my teams’ and individual experiences with LLMs have been mixed, at best. Even with advanced prompt training, the tools are just not there yet for our work.
Not comparable at all. Power tools work deterministically. A powered chainsaw is not going to have a 0.1% chance of chopping a completely different tree on the other side of the forest. Of course accidents happen; your hand can slip. But a proper comparison would be if you got a computer to look at a large number of powered chainsaws and then generate its own in CAD based on what it’s seen, and then you use that generated power tool. Which, for something as potentially dangerous as a powered chainsaw, you most likely wouldn’t want to do, and would want to have careful human oversight over every part of design.
I don’t agree. LLMs are by design probabilistic. Chainsaws aren’t designed to be probabilistic, and any functionality that is probabilistic (aside from philosophical questions about what it is possible to be certain about, YKWIM) is aimed to be minimised. You’re supposed to be able to give the same model the same prompt twice and get two different answers. You’re not meant to be able to use a chainsaw the same way on the same object and have it cut significantly differently. You’re inherently leaving much more to chance by using LLMs to generate code, and creating more work for yourself as you have to review LLM code, which is generally lower quality than human-written code.
Only that the compiler works in a defined algorithmic way that can always be expected to work, at worst it uses more cpu registers than needed or something. AI on the other hand just spews garbage in a fundamentally statistical way and despite the enormous efforts to create tools that manipulate it into working more predictably, it still sucks so much of the time.
Another difference is that you are critically thinking when “instructing” a compiler via the code, but you only convince yourself that you think critically when you’re instructing an AI, it’s not the same and it actively makes you a worse engineer every time you decide to use it instead of thinking.
Cognitive Surrender. I can feel it happening every time I use this employer-mandated Cursor crap. I’m fighting it as hard as I can. Every AI slop pull request I have to review makes me die a little more inside.
(Edit: I’m glad this was so well received, but people are hating on my “assembler isn’t as difficult as people think” post below. Oh well.)
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“If you’re thinking without writing, you only think you’re thinking.”
It’s not the form that’s the issue. It’s the required depth of that thought, when you are actually doing the work yourself you need to go all the way in your thinking otherwise it simply won’t work. When you’re vibe coding, your thinking only goes as far as you see necessary so the AI has enough context to give something useful in return. It’s like comparing the thought process of an analyst and of the engineer that implements the spec, any engineer knows that difference.
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I feel like this says more about neuroscience than it does about LLMs. :D
But seriously, my teams’ and individual experiences with LLMs have been mixed, at best. Even with advanced prompt training, the tools are just not there yet for our work.
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Not comparable at all. Power tools work deterministically. A powered chainsaw is not going to have a 0.1% chance of chopping a completely different tree on the other side of the forest. Of course accidents happen; your hand can slip. But a proper comparison would be if you got a computer to look at a large number of powered chainsaws and then generate its own in CAD based on what it’s seen, and then you use that generated power tool. Which, for something as potentially dangerous as a powered chainsaw, you most likely wouldn’t want to do, and would want to have careful human oversight over every part of design.
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I don’t agree. LLMs are by design probabilistic. Chainsaws aren’t designed to be probabilistic, and any functionality that is probabilistic (aside from philosophical questions about what it is possible to be certain about, YKWIM) is aimed to be minimised. You’re supposed to be able to give the same model the same prompt twice and get two different answers. You’re not meant to be able to use a chainsaw the same way on the same object and have it cut significantly differently. You’re inherently leaving much more to chance by using LLMs to generate code, and creating more work for yourself as you have to review LLM code, which is generally lower quality than human-written code.
Removed by mod