AI systems need both recall and precision. Low-level agents cast a wide net to find everything relevant, then a higher-level orchestrator filters and ranks the results to show only what matters most.
Chapters
And so what it ends up doing is all of these individual agents are first optimizing for coverage and recall to sort of very exhaustive find as much relevant information as it can, which obviously has the downside that precision may not be great, right? And then the orchestrator at the higher level is in charge of making sure that taking all of this sort of the high recall information that's coming in and then optimizing for precision, that that's the one assessing that like which of all of these things that have been found is relevant for the user. Um, that is what gives you You find a lot and then you trim it down and present it to the user, right? That makes sense. Yeah.