Agent Orchestration
Coordinating multiple AI agents so their work composes: who runs when, what each is allowed to touch, and how their outputs feed each other.
One agent watching one metric is a tool. A marketing operation runs many loops at once: one watching acquisition, one drafting content, one monitoring competitors, one reconciling campaign spend against revenue. Orchestration is the layer that keeps them coherent: scheduling (which loop runs when), permissions (what each agent may read and change), handoffs (the competitor agent's findings feed the content agent's briefs), and conflict rules (two agents must not edit the same campaign). In practice orchestration matters more than any single agent's intelligence, because the failure mode of unorchestrated agents is not stupidity but contention: duplicated work, contradictory actions, and nobody accountable for the outcome. The term is growing fast (880 searches a month, tripling year over year) precisely because teams are hitting this wall.
Related terms
The cycle an AI agent runs continuously: observe the data, notice what changed, investigate why, act within its permissions, and verify the action worked.
An autonomous system that uses an LLM to plan, execute, and iterate on tasks with minimal human intervention.
An open protocol that standardises how AI models connect to external tools and data sources, so any compliant agent can use any compliant tool.
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