Comment by troupo
1 day ago
> AI Is a Tool. Using It Well Takes Skill.
And that skill is? Any concrete verifiable examples? That can be replicated, repeated by others or adopted by others?
> A compiler performs substantial work without the programmer continuously directing each operation.
Yes, and the compiler produces the same output for the same input all the time. And when it doesn't, it's a bug or a specified behaviour [1]
> Picking up a saw does not guarantee a straight cut. Holding a chisel does not make you a sculptor.
Yes, but you can learn the actual techniques that let you make a straight cut 100% of the time. And make you a sculptor.
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The rest of the small article doesn't even begin to approach the premise of the title.
[1] Yes, I know it's not strictly true. But compilers are 100% predictable compared to LLMs.
> And that skill is? Any concrete verifiable examples? That can be replicated, repeated by others or adopted by others?
I learned this weekend that 1 LLM working on its own with all the context is usually better than splitting the task up into sub parts and having multiple LLMs work in parallel.
The interesting part is that I had read about this previously but it wasn't until I had seen it on something I was working on did that principle become engrained.
I'm sure there are still ways to make this work. i.e You could specify how the context should be passed between agents.
Knowing when you need to do that, what works well and what doesn't, etc., is where skill comes into play.
> Knowing when you need to do that, what works well and what doesn't, etc., is where skill comes into play.
No, it doesn't. Because this will change the next time there's an update to models (like, tomorrow). And the "handoff time" is nothing but an unverifiable gut feeling.
If LLMs reached a point where they can effectively orchestrate on their own, we would be entering a new era of progress.
And I thought we were at that phase after reading about hundreds of LLMs orchestrating the hugging face attack.
But that's not where we're at. You can read more from this 2025 article https://cognition.com/blog/dont-build-multi-agents.
>And that skill is? Any concrete verifiable examples? That can be replicated, repeated by others or adopted by others?
Writing and thinking clearly. Which is already a very useful capability across a lot of domains.
> And that skill is?
It is easy to argue otherwise, but to request a response in the form of a web app / embedded widget is at least some kind of AI proficiency that mirrors past experience having used a tool.
The result will be anyone's guess
llms work best on optimization problems. especially when wrapped in a proof system.
> Yes, but you can learn the actual techniques that let you make a straight cut 100% of the time
no you can't? not by hand? not without a jig?
LLMs won't make a straight cut no matter how many "jigs" you throw at them
I don't disagree but I don't think that matters here where we're debating whether there's a skill to be learned and you compared to something else which is not deterministic.
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