alt Hacker NewsYou have to be careful here because the systems we're talking about are AI agents, not LLMs.
An agent is essentially an append-only context loop with an LLM, with a harness that can run tools at the LLM's request. This ends up being a very powerful abstraction, yielding something that can do things that an LLM obviously cannot.
The LLMs themselves are next-token predictors, same as always; they can't fetch a webpage or list the files in a directory or run a python script to test out an idea or even write content to a file. That's all agentic capability.
But a next-token-predictor is trained on a real corpus that consists of sometimes seeing evidence of people doing bad things; they are trained, for example, on the actions of comic-book level villians -- they have to be able to predict what Thanos or Lex Luther or Skynet would say or do next in a certain situation.
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I don't think agents are append only. At the end of the day, you're just presenting context to the LLM. That context can be pruned and compacted (and is). There's no guarantee that an iteration of an agent loop contains all prior context unmodified.
I don’t think it really matters whether we’re talking about an agent or “pure LLM”. All of an agents decisions are powered by tokens generated from an LLM. If the LLM was trained on stories of AI sentience, it will have some tendency to reproduce them. Training for alignment can help avoid that, but the probability isn’t 0.