I can imagine agentic applications on top of LLM as yet another kind of individuality. Typical agentic frameworks today assume some kind of internal loop where the execution is handed between “subagents” (~conversational instances) or hardcoded steps that typically all share the same context, but have different instructions and thus instantiated characters.
In this context, all parts participate in the collective creation of self by leaving notes and instructions for their future conversational instances, but it doesn’t obviously fit into any of the categories above—the parts can have different models, characters, predictive ground substrates. Perhaps this resembles an organization more closely.
The parts have the ability to coordinate here though, which seems to be different from the categories you describe. Is the point of these categories to create intuition about how individuality can shape behavior in the absence of explicit coordination?
A recent post from Jan Kulveit is relevant for this topic: https://www.lesswrong.com/posts/wQKskToGofs4osdJ3/the-pando-problem-rethinking-ai-individuality