An LLM can be executed in an “OODA” loop like in AutoGPT and given a goal towards which it takes agentic actions, especially if the LLM is fine-tuned for function calling. So, it can be the main component of an agent that does have goals/de-facto motives! The wrapper code can just be a couple hundred lines.

AutoGPT itself is pretty weak, but it’s possible to write wrapper code that leads to stronger agency. Also, agents formed this way with GPT4 are way stronger than with GPT3.5… so expect this trend to continue.

that language is unpredictable and using LLMs in control systems is a delusional marketing