// GLOSSARY -- AGENTIC AI

What is Agent Orchestration?

2 min read Updated

Agent orchestration is the coordination of multiple AI agents working together on complex tasks, managing their execution order, communication, resource sharing, and error handling across a workflow.

WHY IT MATTERS

A single agent can handle simple tasks. Complex operations — like multi-step code refactoring involving analysis, testing, and deployment across multiple services — require multiple specialised agents working in concert.

Orchestration patterns include sequential pipelines (agent A then B then C), parallel fan-out (multiple agents work simultaneously), hierarchical delegation (a manager agent assigns work), and event-driven (agents react to triggers). The choice depends on the task structure and latency requirements.

Multi-agent orchestration amplifies the policy enforcement challenge. Each agent may connect to different MCP servers, use different tools, and operate with different authority levels. Without centralised policy enforcement, each agent is a separate attack surface.

HOW POLICYLAYER USES THIS

Intercept provides consistent policy enforcement across multi-agent orchestrations. Each agent's MCP connection can be routed through Intercept with its own YAML policy file — ensuring that a research agent has read-only tool access whilst a deployment agent has write access, and neither can exceed its authorised scope. Policies are enforced uniformly regardless of which agent in the orchestration makes the tool call.

FREQUENTLY ASKED QUESTIONS

How does Intercept handle multiple agents with different policies?
Each agent's MCP connection can be routed through a separate Intercept instance (or configuration) with its own YAML policy. This gives each agent in the orchestration its own policy scope.
How do you handle failures in orchestrated workflows?
Common strategies include retry with backoff, fallback to alternative agents, compensating actions (undo previous steps), and circuit breakers that halt the workflow when error rates spike. Intercept can enforce rate limits that prevent runaway retry loops.
Do I need an orchestration framework?
For simple sequential workflows, no — a script calling agents in order works fine. For complex workflows with branching, parallelism, and error handling, frameworks like LangGraph or Temporal save significant development time.

FURTHER READING

Enforce policies on every tool call

Intercept is the open-source MCP proxy that enforces YAML policies on AI agent tool calls. No code changes needed.

npx -y @policylayer/intercept
github.com/policylayer/intercept →
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