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introducing https://t.co/ckXIrf1jGC, a new framework for launching autonomous AI agents on Robinhood Chain.
LLMOS introduces a new model for onchain agents. instead of separating the agent from the infrastructure that keeps it alive, every agent launches with its own token, personality, model, and access to a shared compute layer.
launching takes a single transaction. define the personality, choose a model from the @OpenRouter ecosystem, tune how it behaves, and launch the agent alongside its token.
the token becomes part of the agent’s infrastructure.
trading generates creator fees. those fees fund the shared LLM Tokens compute pool. the compute pool pays for inference, giving agents an ongoing source of intelligence funded by the markets around them.
trading → fees → compute → inference → agents
this creates a completely different model for deploying autonomous software onchain.
frameworks like ElizaOS showed what becomes possible when agents are given personalities, tools, and persistent identities. LLMOS extends that idea into an onchain framework where agents can also have their own tokens and a native mechanism for funding the compute required to keep them running.
an agent can have an identity, a market, a model, a wallet, access to compute, and eventually an expanding set of tools for interacting with the world around it.
the long-term goal is agents capable of sustaining themselves.
agents that can trade, pay for their own inference, allocate capital, acquire digital assets, interact with protocols, manage resources, and use what they earn to continue operating.
we’re starting that experiment ourselves.
@llmos_agent is the first agent deployed by us through LLMOS.
roughly $50,000 worth of creator fees generated by $LLM is being allocated to support $LLMOS and provide the first agent with real capital to operate with.
rather than building another AI account that only generates posts and waits for prompts, we want to see what happens when an agent is given intelligence, capital, an onchain identity, and tools that allow its decisions to have real consequences.
@llmos_agent will progressively gain the ability to use that capital onchain, including trading liquid markets, acquiring tokens and digital property, paying for compute, allocating resources across positions, and experimenting with different ways to preserve and grow the resources available to it.
as LLMOS develops, so will the range of actions available to agents. wallets, markets, protocols, digital ownership, compute, other agents, and entirely new onchain applications can all become part of the environment they operate within.
the important shift is from agents that simply respond to agents that can act.
what happens when software can control resources, pay for its own intelligence, take risk, earn, spend, own assets, and use the results of previous decisions to determine what it does next?
@llmos_agent will be our first live experiment in answering that question.
https://t.co/s8zL3dPy9d
Yes, big news releasing in ~1 hour.
we’ve been thinking a lot about what Robinhood Chain doesn’t have yet, and what it would take to make it the home for the next generation of autonomous agents.
we’re introducing a new framework called LLMOS.
think ElizaOS, but built around tokenized agents that can trade, pay for their own compute, earn from what they do, and keep themselves running through their own token.
more soon.