Glossary

Multi-Agent Orchestration

Multi-agent orchestration is the practice of coordinating multiple specialized AI agents to accomplish a task that is too complex or too broad for a single agent.

In multi-agent systems, individual agents have narrower scopes and clearer responsibilities — one agent might handle customer triage, another might execute refunds within policy, a third might summarize and route escalations. An orchestrator agent (or a deterministic workflow engine) decides which agent handles which step.

Frameworks like CrewAI, LangGraph, and Agno provide patterns for multi-agent coordination — role definitions, message-passing, shared memory, and checkpointing. In enterprise deployments the orchestration layer also enforces governance: which agent is allowed to call which tool, which actions require approval, and how handoffs are logged.

Multi-agent designs are more maintainable than monolithic "one giant prompt" agents for non-trivial workflows, but they add operational complexity. The right cut between single-agent and multi-agent is workflow-specific.

See also
  • AI Agent— An AI agent is a software system that uses a large language model to perceive its environment, reason about tasks, and take actions in external systems on behalf of a user.
  • Agent Constitution— An agent constitution is the written policy that defines what an AI agent is authorized to do, what it must refuse, how it escalates, and how it speaks — enforced at runtime by a policy layer.
  • Tool Use (Function Calling)— Tool use — also called function calling — is the capability of a language model to emit structured calls to external tools, enabling an agent to take real actions in connected systems.
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More terms in the glossary

AI Agent

An AI agent is a software system that uses a large language model to perceive its environment, reason about tasks, and take actions in external systems on behalf of a user.

AI Voice Agent

An AI voice agent is an AI agent that interacts with users through voice — answering inbound calls, placing outbound calls, and conversing in real time.

AI Chatbot (AI Chat Agent)

An AI chatbot — more accurately, an AI chat agent — is an AI agent that interacts with users through text: web chat, WhatsApp, SMS, Slack, Teams, or social messaging.

Retrieval-Augmented Generation (RAG)

Retrieval-augmented generation (RAG) is an architecture that grounds a language model's responses in a specific knowledge base by retrieving relevant passages at inference time and conditioning the response on them.

Constitutional AI

Constitutional AI is an approach to training and deploying AI systems in which model behavior is guided by an explicit written set of principles — a "constitution" — rather than only by reinforcement from human feedback.

Model Context Protocol (MCP)

Model Context Protocol (MCP) is an open standard for connecting AI agents to the tools, data sources, and prompts they need, through a consistent client-server protocol.

See the full glossary

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