The original article talks about 'savvy', which is to me an essence of learning. If 'exploration' is looking at walls of code you don't understand but the linter makes them look cool, you don't need LLMs for that.

This came out a bit longer than I expected.

Depends on your usage. A rubber duck won't upheave the entire history of written human knowledge to reach for your answer. It doesn't have inherent bias, and its purpose could also be handled by a wall, or the air infront of you if you can stretch your mind a little. What I'm going for here is that as you said, its just a hack to make your brain look for answers in a more efficient manner, by clearly underlining your thought process out loud, tricking yourself into conversation mode, yada yada. Its still you doing all the work, you're just being smarter about it.

A LLM is more akin to a senior pair programmer. It may seem like a rubber duck on the surface, in the sense that you're having a conversation, but the senior programmer may come up with ideas you wouldn't think of. They may have more innate experience in the domain which might pull you away to very different implementations from what you had in mind initially. This is all good, but a common pitfall with LLMs is that they're much more conformative than a senior engineer, much faster, much more responsive. This is where it gets dangerous: they don't tell you you're wrong 80% of the time, like a rubebr duck. They also have innate experience of a domain, like a senior engineer. The result is that your brain never gets a 'hang' signal, and it doesn't feel the need to reevaluate.

> Are Rubber Ducks offloading thinking?

Just that an actual rubber duck doesn’t do anything. You solve the problem you have by talking, and in doing so, thinking, to come up with a solution, an idea, or gain better understanding.

After that you either implement something yourself or have learned something.

With an LLM you offload all of that, the only thing you still do is tell it what the problem is. The agentic duck does the rest and you look at the output.

Even if you have to argue, you argue without having gone through the steps to gain anything yourself.

I use it as a very effective learning tool, as well. To test my learning, I make sure I can code it myself after that.

> You can interrogate the LLM. You can ask it all sorts of things. Tell it to justify its decisions. Tell it to give you supporting evidence. Tell it to give you options. Tell it to explain things in detail.

Hopefully you realize that it's not actually introspecting into its previous thought process, and instead it is just making up a plausible after-the-fact explanation that matches the format of similar explanations found in its training set?

I too often find these explanations enlightening, but please don't forget that you need to read all such responses as those of a pathologically lying psychopath desparate to trick you, not as a trusted expert who actually understands its internals.