AI agents · 11 min read
Multi-Agent Systems for DeFi on Monad
How teams of specialized AI agents — researcher, risk officer, executor — can coordinate to trade and manage DeFi positions on Monad.
Why split responsibilities
One giant agent is hard to debug. Splitting into roles — a research agent, a strategy agent, a risk agent, and an execution agent — makes each part testable and auditable.
Coordination patterns
Agents can pass structured messages through a shared queue. The risk agent holds veto power. The executor only accepts approved, simulated actions.
Agent-to-agent markets
On a fast, cheap chain, agents can pay each other for data, predictions, or execution — micro-markets between software that were impractical when fees were high.
Challenges
More agents means more failure points and emergent behavior. Keep humans in the loop for limits and goals.
Explore
Monad's throughput suits multi-agent designs. See what monaf.ai is building.
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