What is an AI Orchestrator?

As agentic systems grow beyond a single model making a single decision, something has to manage the bigger picture: which sub-task runs next, which specialized agent or tool is best suited for it, how results from parallel sub-tasks get merged, and when the overall goal is actually satisfied. The orchestrator holds that state so individual sub-agents can stay narrowly focused on their own piece without needing awareness of the whole plan. A well-designed orchestrator decomposes work into genuinely independent pieces where possible, since overlapping work wastes resources and creates conflicting edits or duplicate actions, and it tracks progress durably enough that a partially completed multi-step process can resume correctly even if something is interrupted midway. It also has to decide, sometimes dynamically, whether a task is best handled by one deep, cohesive agent or by fanning it out across several specialized ones.