this post was submitted on 07 Mar 2026
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[–] thebestaquaman@lemmy.world 1 points 19 hours ago (2 children)

Meh, they work well enough if you treat them as a rubber duck that responds. I've had an actual rubber duck on my desk for some years, but I've found LLM's taking over its role lately.

I don't use them to actually generate code. I use them as a place where I can write down my thoughts. When the LLM responds, it has likely "misunderstood" some aspect of my idea, and by reformulating myself and explaining how it works I can help myself think through what I'm doing. Previously I would argue with the rubber duck, but I have to admit that the LLM is actually slightly better for the same purpose.

[–] _stranger_@lemmy.world 2 points 16 hours ago (1 children)
[–] thebestaquaman@lemmy.world 1 points 15 hours ago

You're absolutely right. I mostly run a pretty simple local model though, so it's not like it's very expensive either.

[–] prole@lemmy.blahaj.zone 1 points 18 hours ago (1 children)

Hooray for outsourcing of critical thinking!

What could possibly go wrong

[–] thebestaquaman@lemmy.world 1 points 18 hours ago (1 children)

I think you've misunderstood the purpose of a rubber duck: The point is that by formulating your problems and ideas, either out loud or in writing, you can better activate your own problem solving skills. This is a very well established method for reflecting on and solving problems when you're stuck, it's a concept far older than chatbots, because the point isn't the response you get, but the process of formulating your own thoughts in the first place.

[–] prole@lemmy.blahaj.zone 4 points 18 hours ago* (last edited 18 hours ago) (1 children)

Right, but a rubber duck isn't a sycophantic chatbot that isn't capable of conceptualizing anything but responding to you anyway.

[–] thebestaquaman@lemmy.world 2 points 17 hours ago (1 children)

That is correct. However, an LLM and a rubber duck have in common that they are inanimate objects that I can use as targets when formulating my thoughts and ideas. The LLM can also respond to things like "what part of that was unclear", to help keep my thoughts flowing. NOTE: The point of asking an LLM "what part of that was unclear" is NOT that it has a qualified answer, but rather that it's a completely unqualified prompt to explain a part of the process more thoroughly.

This is a very well established process: Whether you use an actual rubber duck, your dog, writing a blog post / personal memo (I do the last quite often) or explaining your problem to a friend that's not at all in the field. The point is to have some kind of process that helps you keep your thoughts flowing and touching in on topics you might not think are crucial, thus helping you find a solution. The toddler that answers every explanation with "why?" can be ideal for this, and an LLM can emulate it quite well in a workplace environment.