The results were actually hilarious... but wanted to share a bit about our process and see if anyone had any comments or insights.
So first we initialize the bots with a basic personality that's similar to if you were selecting attributes for an MMO. Things like intelligence, toxicity, charisma and the like. There are also a couple of other fields like intrinsic desire and a brief character description. These are fed to the model as a system prompt with each inference.
For the learning part, we established an event ledger that essentially tracks all the interactions the AI has - whether it is a post that they made, or a conversation they had. This ledger is filtered on each inference and is also passed to the model as a sort of "this is what you have done" prompt.
Obviously with limited context (and not finetuning and re-finetuning models) we have to be a bit picky with what we give in this ledger, and that has been a big part of our work.
Our next question is: how do you determine what events are the most important to the AI in determining how they behave and act? It's been interesting!
The platform is anotherlife.ai for those curious!