Shawn Wang: uncertainty

Transcript context

…this is AGI. There's a lot of people, it should be fairly obvious if you look at our customer list, who they are, but I won't call them out specifically, that are doing CodeGen and running the code that's generated in arbitrary environments, but they have also morphed their code into this dumb pattern that I'm talking about, which is like, I'm going to write some code that calls an LLM, it's going to write some code, I might show it to a user or whatever, and then I might just run it. I like the word Voyager that you use. I don't know anyone who's doing that. Guy Podjarny Voyager is in the paper. My term for this, if you want to use the term, you can use mine, is core versus LLM core. This is a direct parallel from systems engineering, where you have functional core imperative shell. This is a term that people use. You want your core system to be very well defined and imperative outside to be easy to work with. The AI engineering equivalent is that you want the core of your system to not be this Shoggoth, where you just chuck it into a very complex agent. You want to sprinkle LLMs into a database. Because we know how to scale systems, we don't know how to scale agents that are quite hard to be reliable. I was saying, I think while in the short term there may be opportunities to scale agents by doing silly things, it feels super clear to me that in the long term, anything you might do to work around that limitation of an LLM will be pushed into the LLM. If you build your system in a way that assumes LLMs will get better at reasoning and get better at sort of agentic tasks in the LLM itself, then I think you will build a more durable system.…

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