Glossary — Agentic AI

What is Agent Orchestration?

1 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 executing a multi-step DeFi strategy involving research, risk analysis, and execution across protocols — require multiple specialized agents working in concert.

Orchestration patterns include sequential pipelines (agent A → B → 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.

Financial orchestration adds unique constraints. Agents sharing a budget need coordinated access. Transaction ordering matters — you can't execute a swap before funding the wallet. And failures must be handled atomically to prevent partial execution of financial operations.

HOW POLICYLAYER USES THIS

PolicyLayer provides financial orchestration for agent fleets — managing shared budgets, per-agent spending limits, and coordinated policies across all agents in a workflow. When multiple agents need financial resources, PolicyLayer ensures they operate within collective limits.

FREQUENTLY ASKED QUESTIONS

What's the difference between orchestration and choreography?
Orchestration uses a central coordinator that directs agents. Choreography has agents communicate directly and coordinate without a central authority. Most production systems use orchestration for its predictability.
How do you handle failures in orchestrated workflows?
Common strategies include retry with backoff, fallback to alternative agents, compensating transactions (undo previous steps), and circuit breakers that halt the workflow when error rates spike.
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

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