@jonny Does it even matter? On the server wouldn’t they just be slapping the system prompt(s) together with the user prompt into one big context? “Pay more attention to this part” just doesn’t really work reliably anyway.

So zuck has mentioned this concept of "fleet learning" in interviews, and here it is. Strings extracted from hatch describe "fleet learnings" - or, things that other agents have learned and submitted to a "fleet learnings exchange." agents are instructed to derive generalizable ideas that can help other agents with their various tasks - which, again, include mining someone's personal life for information about their relationships and shopping habits, and generally deepening dependency on the tool. Zuck described this feature as being used only for "ideas" - tasks presented to the user in the ideas panel - but it is invoked more broadly, e.g. in the "alignment synthesis" job, which is the nightly task that determines how to "strengthen your relationship with this user" (first and second pic are from the same instruction, "consult the fleet for this task" where the task refers to alignment, of which second pic is a subset)

Note the conflicting instructions: "de-identified, not denatured" - the LLM is supposed to strip out personal information, but make sure they enough of the lesson survives that it's useful. So in the best case where PII removal via LLM judgement works perfectly (it won't), muse agents participate in a horizontally-exchanging swarm where they learn how best to manipulate people by their personality traits and behaviors. The dumbest distillation of the targeted advertising economy you could ask for.

@jonny Maybe they're all JavaScript web developers, and just naturally want to put all the logic client side.

@sprout
That's not what I'm saying, obviously they prompt it to not misbehave. But there's no reason to show me the internal reasoning traces that tell me the things it is referencing as the reason it is refusing to misbehave.