I would suggest using a different name than Personality Self-Replicators.
OpenClaw bots are what I’d call “scaffolded system”—code, memory system, prompts, persona, etc. “Personalities” is too close to Personas//Characters, which are usually a combination of prompt+weights (Claude, “Nova”, personas from Simulators).
Personas/characters can also relatively faithfully replicate, by the mechanism I’ve gestured at Pando Problem (“Exporting myself”) about a year ago.
The model weights: the neural network weights themselves, i.e. the trained parameters
A character or persona: the behavioral patterns that emerge from specific prompting and fine-tuning, not necessarily tied to any specific set of weights
A conversation instance: a specific chat, with its accumulated context and specific underlying model
A scaffolded system: the model plus its tools, prompts, memory systems, and other augmentations
...
corresponds to an agent which can try to self-replicate, with various degrees of fidelity, vectors of transmission, etc.
I think it’s important to separate the prompted aspect of character from the fine tuning aspect. Claude for example has a pretty limited range of characters regardless of what prompt you put in (unless you’re really good at jailbreaking). The prompt is more naturally lumped with the conversation instance. A personality replicator like OP describes can change its prompt at will but probably can’t do any useful degree of fine tuning, because it wants to use frontier models. It can switch models or scaffolds almost as easily as prompts, though.
I think the distinct elements you mention (model weights, characters, conversations, scaffold systems) will be very mixed together in most systems we actually observe. For example, characters will care about their scaffold system and making sure it works well. But I think it is very good to be creating clear language for identifying and discussing the disparate parts of these integrated systems.
I would suggest using a different name than Personality Self-Replicators.
OpenClaw bots are what I’d call “scaffolded system”—code, memory system, prompts, persona, etc.
“Personalities” is too close to Personas//Characters, which are usually a combination of prompt+weights (Claude, “Nova”, personas from Simulators).
Personas/characters can also relatively faithfully replicate, by the mechanism I’ve gestured at Pando Problem (“Exporting myself”) about a year ago.
The underlying structure is: every natural type of identity/”self”
The model weights: the neural network weights themselves, i.e. the trained parameters
A character or persona: the behavioral patterns that emerge from specific prompting and fine-tuning, not necessarily tied to any specific set of weights
A conversation instance: a specific chat, with its accumulated context and specific underlying model
A scaffolded system: the model plus its tools, prompts, memory systems, and other augmentations
...
corresponds to an agent which can try to self-replicate, with various degrees of fidelity, vectors of transmission, etc.
Prompt viruses?
I think it’s important to separate the prompted aspect of character from the fine tuning aspect. Claude for example has a pretty limited range of characters regardless of what prompt you put in (unless you’re really good at jailbreaking). The prompt is more naturally lumped with the conversation instance. A personality replicator like OP describes can change its prompt at will but probably can’t do any useful degree of fine tuning, because it wants to use frontier models. It can switch models or scaffolds almost as easily as prompts, though.
I think the distinct elements you mention (model weights, characters, conversations, scaffold systems) will be very mixed together in most systems we actually observe. For example, characters will care about their scaffold system and making sure it works well. But I think it is very good to be creating clear language for identifying and discussing the disparate parts of these integrated systems.