Skip to content
AI Learning Playground
LinkedInX
English
English

What Is Orchestration

About 5 minutes

Shiori
Target audience: Those who want AI to handle multi-step work that a single agent cannot manage, those looking to organize how multiple agents fit together
Prerequisites: Basic understanding of What Is an AI Agent

Orchestration is the design work of coordinating multi-step workflows and multiple AI agents so that they add up to one completed job. Like a conductor holding an orchestra together, it decides the order of steps, who handles each one, and where a human reviews the result.

Why Orchestration Is Needed

An AI agent can execute tasks autonomously, but handing one agent an entire long process tends to create these problems.

ProblemDescription
Context growthMore steps mean longer history, which dilutes the important instructions
Mixed responsibilitiesCombining research, implementation, and verification in one instruction blurs the criteria
Hard to locate failuresIt becomes difficult to trace which step went wrong
Costly re-runsRedoing one part requires redoing the whole thing
This table scrolls horizontally. Keyboard users can focus the table and use the left and right arrow keys.

Splitting the work into steps, each with a suitable handler and completion condition, improves all of these considerably.

The Four Decisions Orchestration Makes

graph LR
    Split["Split the work\nwhere to draw boundaries"] --> Assign["Assign handlers\nwho does what"]
    Assign --> Flow["Control the flow\nsequential, branching, parallel"]
    Flow --> Check["Verify and recover\ncompletion conditions, failure handling"]
  1. Split the work — draw boundaries so each step has a single purpose
  2. Assign handlers — an agent, a subagent, ordinary program code, or a human
  3. Control the flow — sequential execution, conditional branching, or parallel execution
  4. Verify and recover — define completion conditions and where to fall back on failure

Do Not Hand Everything to AI

A commonly missed decision in orchestration is that deterministic work belongs in ordinary program code. File input and output, format conversion, and test execution follow fixed procedures, so running them as code is faster, more stable, and cheaper than asking an LLM to reason through them every time.

What belongs to AI is the part that cannot be reduced to a fixed procedure: judgment, summarization, generation, and handling exceptions.

Pages in This Section

PageContent
Orchestration PatternsComparison of single-agent, multi-agent, and hierarchical structures
Comparing Orchestration in Claude, ChatGPT, and CodexCompare the controls exposed by Chat, Cowork, Code, Work, and Codex
Parent-Child Agent Design in Claude CodeConcrete examples of .claude/agents/, Skills, models, effort, and worktrees
Parent-Child Agent Design in CodexConcrete examples of .codex/agents/, .agents/skills/, AGENTS.md, and reasoning effort
Agent FrameworksComparison of LangGraph, OpenAI Agents SDK, Claude Agent SDK, Google ADK, and other options
State and HandoffDesigning how information passes between steps
Failure Detection and RecoveryDetecting and recovering from mid-process failures
This table scrolls horizontally. Keyboard users can focus the table and use the left and right arrow keys.

Summary

  • Orchestration coordinates the overall flow across multiple steps and multiple agents
  • It decides four things: splitting work, assigning handlers, controlling flow, and verification with recovery
  • Fixed procedures belong in program code; AI handles the parts that require judgment