A setup in which several AI agents, each with its own role or tools, work together or hand off tasks to reach a shared goal.
Rather than asking one agent to do everything, a multi-agent system divides work among specialized agents. One agent might plan the task, another might research, another might write, and a reviewer agent might check the result. An orchestrator coordinates the hand-offs.
For example, a marketing team could use a research agent to gather product facts, a drafting agent to write a product page, and a checking agent to compare claims against approved sources before a person signs off. Splitting roles can make complex workflows easier to manage and test. However, more agents mean more model calls, higher cost, and more places for errors to spread. Many teams find a single well-designed agent with good tools is enough until a workflow genuinely needs division of labour.
A software system that uses an AI model to plan and carry out multi-step tasks, often by calling tools, APIs, or other programs on its own.
Agentic AIAI systems designed to pursue goals with some autonomy, planning steps, using tools, and acting on results rather than only answering prompts.
OrchestrationAutomated coordination and management of multiple systems, services, or tasks so they work together as a complete workflow.
AI agents have moved from demos to daily operations. Here is how agentic workflows actually work, where they pay off, and how to roll them out without losing control.