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Beyond single-model AI: How architectural design drives reliable multi-agent orchestration
Successful AI agents require enterprises to orchestrate interactions, manage shared knowledge and plan for failure.
Many real-world multi-agent systems (MAS) end up being a hybrid — perhaps a high-level orchestrator sets the stage; then groups of agents within that structure coordinate decentrally. Atomic-ish operations: While true ACID transactions are hard with distributed agents, you can design workflows to behave as close to atomically as possible using patterns like Sagas. Building reliable, scalable multi-agent systems isn’t about finding a magic bullet; it’s about making smart architectural choices based on your specific needs.
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