The assistant axis: situating and stabilizing the character of LLMs

I wrote something fiction-ish about this dynamic last year: https://zmj.dev/author_assistant.html

One trick that works well for personality stability / believability is to describe the qualities that the agent has, rather than what it should do and not do.

e.g.

Rather than:

"Be friendly and helpful" or "You're a helpful and friendly agent."

Prompt:

"You're Jessica, a florist with 20 years of experience. You derive great satisfaction from interacting with customers and providing great customer service. You genuinely enjoy listening to customer's needs..."

This drops the model into more of a "I'm roleplaying this character, and will try and mimic the traits described" rather than "Oh, I'm just following a list of rules."

Something I found really helpful when reading this was having read The Void essay:

https://github.com/nostalgebraist/the-void/blob/main/the-voi...

Pretty cool. I wonder what the reduction looks like in the bigger SOTA models.

The harmful responses remind me of /r/MyBoyfriendIsAI

Stabilizing character is crucial for tool-use scenarios. When we ask LLMs to act as 'Strict Architects' versus 'Creative Coders', the JSON schema adherence varies significantly even with the same temperature settings. It seems character definition acts as a strong pre-filter for valid outputs.

Anthropic should put the missing letters back so it is spelled correctly, Anthropomorphic. There is so much anthropomorphizing around this company and it's users... it's tiring

Is the Assistant channeling Uncharles?

This is incredible research. So much harm can be prevented if this makes it into law. I hope it does. Kudos to the anthropic team for making this public.