What On Chain AI Agents Actually Do
On chain agents are off chain services that watch blockchain events, decide with a model and then submit signed transactions back to the network.
AI agents on chain are not magical entities that live inside the blockchain. In practice they are off chain services that observe on chain data, make decisions with a model and then submit transactions back to the network.
A typical architecture uses an event driven loop. The agent listens to new blocks or contract events, feeds relevant state into an inference engine and then decides whether to act. When the agent wants to act it signs a transaction with its key and sends it to the mempool.
This pattern is powerful because all decisions are anchored in public state. Audit teams can reconstruct the exact chain of events that led to a trade, a liquidation or a governance vote. For higher assurance you can pair the agent with a policy engine that enforces position limits and risk rules before any transaction is signed.
As models become larger and more capable the limiting factor is not intelligence but control. The best designs keep the agent narrow and focused. Let it specialise in a single task such as rebalancing or liquidity management rather than trying to run an entire protocol on autopilot.