This feels to me like a lovely example of both high-quality systems design and information theory. From my perspective, one of the more abstractly interesting thoughts surfaced by this write-up is the degree to which you've "encoded" a highly complex set of relationships through use of metaphor.
That type of encoding (starting with the statement: you're at a teaching hospital) is profoundly more efficient than having to deeply and reliably articulate what each of the various roles your agents embody are, let alone their interactions.
Perhaps there is more room for any of us to consider what existing systems or identities are described abundantly in training sets and can be leveraged to ritualistically encode these social/civic/cultural dynamics saying: "act as though you're ___." Not exactly a new point, but one this write-up certainly is pulling me towards.
Thank you for sharing and the care you put into writing this!
Thanks for the thoughtful response. We too were surprised by how deeply we could take the model of the teaching hospital to software engineering. Whenever we think to expand the system in one dimension or another, the teaching hospital model seems to have a nearby analogy.
I will confess however that some people internally find the model confusing. For example, one user couldn't remember that to get an issue actioned, they needed to put it into the "waiting room". They wanted to be able to action their issues without learning how complex medical systems operate. There seems to be more work on our plates to make this resonate with all users.
Now imagine what it is like to run an actual hospital with real people whose lives (or the lives of their loved ones) are often at stake, with underpaid and overworked staff and with messy biological creatures as the subjects instead of bits and bytes. If anything this whole exercise should also give you a much deeper appreciation of the people that feel themselves called to help others.
I had a similarly useful analogy of the legal system emerge, in a similar way. I think there's a great analogy between policy in the legal system and policy in software engineering, and they have some awfully good (and very, very historical) ways to think about e.g. amending, repealing, and adjudicating things based on those policies.
yeah this is really cool. i've been thinking about sort of a mirrored idea, where you end up with wizards, mages, clerics etc and fantasy terminology used. idk if it would be as effective as this is, but maybe it would be more creative somehow?
i kinda want to try to build this off of github. it's essentially just an event bus / message queue that workers (agents) tap into.
i think role-play and utilizing the full power of language, stories, character, and narrative will unlock very sophisticated use-cases and in general a new dimension to agentic systems much in the way you're describing.
probably what will work best in the future is specific training or fine-tuning against curated datasets of narrative fiction and/or texts in general? not really sure.
That type of encoding (starting with the statement: you're at a teaching hospital) is profoundly more efficient than having to deeply and reliably articulate what each of the various roles your agents embody are, let alone their interactions.
Perhaps there is more room for any of us to consider what existing systems or identities are described abundantly in training sets and can be leveraged to ritualistically encode these social/civic/cultural dynamics saying: "act as though you're ___." Not exactly a new point, but one this write-up certainly is pulling me towards.
Thank you for sharing and the care you put into writing this!
I will confess however that some people internally find the model confusing. For example, one user couldn't remember that to get an issue actioned, they needed to put it into the "waiting room". They wanted to be able to action their issues without learning how complex medical systems operate. There seems to be more work on our plates to make this resonate with all users.
i kinda want to try to build this off of github. it's essentially just an event bus / message queue that workers (agents) tap into.
probably what will work best in the future is specific training or fine-tuning against curated datasets of narrative fiction and/or texts in general? not really sure.