(word is thrown around a lot so might be worth using a different one)
Humans, most obviously
Companies
Generally composed of humans; systems of info flow; assets; other companies
Governments
What are important properties of “agents”?
Have ties to past and future selves
Care about balance, reputation, memory
Can plan and execute
Can trade?
Can agree to contracts?
(aside: are characters in a book, agents? feels like some authors simulate the character forwards to get their actions)
What is an LLM individual?
Humans have an ego which helps maintain a narrative; some intuitive sense of “this thing in the future is me”
Gets weird when thinking about eg being split (Doris Finch)
Companies have… a single treasury? A charter, incorporation docs?
Much more of a fiction, jointly simulated by employees, users, govt, pieces of contracts
How are LLMs weird?
Can parallelize massively
More of a tool that only reacts, at the moment
How do you train a thing with proactivity?
Objective is very alien (”next token prediction”)
Can swap out computing cores/substrates — eg take the same history and run through Claude instead of o1
But: maybe we’re doing this already. Cf Emmett Shear on “Jesus is real — he’s real-ly simulated in our minds today”
Maybe better to think of even current LLMs as embedded in a system
MVP LLM individual:
Charter
Gets formed, instantiated with a purpose, a self
Can be “grown” and “raised” instead of “programmed”?
History
Keeps a major system prompt outlining who it is (kind of like “You are Claude” but instead tuned for the LLM)
Keeps a summary of recent events (short-term memory) as well as ability to read through past outputs (long-term memory)
Can rewrite its own conception, but sparingly
How to handle major value changes? Like if Bob2026 wants to throw away a lot of money earned by Bob2025 — with LLMs (unlike humans), we can still instantiate Bob2025
Balance
Maybe: spend down the balance to pay for compute (aka its life)
Maybe: get a basic handout, like UBI, so can do a bit of compute every day
Trade
Allow it to put its name down in a contract, form contracts with others; expect that those are upheld
Court for LLMs?
What kind of trade are LLMs good at?
“Remote worker” — information synthesis?
Management, planning of other LLMs?
Can simulate a lot of personalities and clone the successful ones - imagine being able to get the Steve Jobs LLM to design your products, or Elon Musk LLM to manage your workers. (Or the equivalent in from-scratch cloning)
Maybe, might start paying for exclusive use? In situations where exclusivity is especially important like zero-sum trading?
How do you differentiate LLMs?
Different prompts; finetunes; base models
Maybe: LLMs can submit to different taxation regimes
E.g. The “Bob” LLM might opt to allocate its profits as:
50% for responses using its prompt chain (its “self”)
20% among those sharing finetune
10% to base model (eg Sonnet 3.5)
10% in fees/taxes to the technical/legal infrastructure
10% in charity to all economic agents/GWWC
Misc thoughts on economy
Credit allocation as a key bottleneck towards progress & optimal economy
Right now, LLM outputs are ridiculously cheap given utility (?)
Though, is this true of electricity? of air?
Trick might be to figure out where “value” accumulates? What’s defensible?
Credit allocation in startups: Kinda broken, founders get way too much equity
Theory: leads to too many startups
Against: maybe founders are just bad at sharing power, collaborating
Investigate Jane Street model (anarchist commune)?
Big Tech, Google model (Waymo et al spun out?)
Profit/loss is a great mechanism
See: I, Pencil
Requires long-lived agents to receive the future results of a trade?
Requires contracts backed by shared fiction and use of force?
Musing: Would like to figure out what US Constitution looks like for the future country of agents.
Break down what governing structures are likely to work well, with LLM individuals
Or Catholicism!
You are shaped by your objective functions, alignment structures, role models (?, bad phrasing)
Reflecting on what to do with this essay
Could do “research” — write papers, publish, go to neurips — at extreme, Nobel
Could do “startup” — make product, sell, raise money — at extreme