3 ms·

Agents are possible basically because the input to the LLM and the output of the LLM are both text. The loop is trivially closed. But they're universally garba

Agents are possible basically because the input to the LLM and the output of the LLM are both text. The loop is trivially closed. But they're universally garbage because they require the LLM to do a lot of things that LLMs are completely incompetent at. It's just way too early to expect to be able to remove that work and have it be done by an LLM. The fact is LLMs are useful because they easily do some work that you're terrible at, and you easily do a lot of work that it's terrible at, and this makes the LLM a good tool because you+LLM is better than either part of that equation alone. It's natural to think of the things that come effortlessly to you as easy, and to not even notice you're doing any work. But that doesn't change the fact that the LLM is completely incompetent at many of these things. It's way too early to remove the human from the loop.

furyofantares 3y ago
I just looked up a similar comment I made ~9 months ago, where I also said I thought we could probably do better than 1-to-1 prompt-to-output iteration even if we can't close the loop, and was hopeful that plugins would help compress the iteration. Looking again at it from that direction - think about plugins, functions, GPTs, custom instructions, and now memory. These are all attempts to get more out of the LLM. And they haven't really made much progress. Certainly less than I expected 9 months ago when I was hopeful the iteration loop would get compressed, even if I was highly skeptical about closing it. This is pretty conclusive to me - if it's this hard to get much more value per prompt out of current LLMs then it's really unlikely to be able to usefully close any loops.