Phase 5: Agent Orchestration Patterns · 50 min · Claude Code · Python

Multi-Agent Orchestration

Multi-agent systems fail for a specific, predictable reason: agents working in isolation make locally reasonable decisions that conflict at integration time.

Real-world application: Being able to say precisely when a multi-agent design will hit Cognition's integration-conflict failure mode — and when a task is genuinely independent enough to avoid it — is sharper system-design judgment than either 'always use one agent' or 'always parallelize.'

What you will learn

Identify when a task's subtasks are independent enough to genuinely benefit from a multi-agent split
Name the three multi-agent anti-patterns: agent thrashing, hallucination propagation, context explosion
Explain Cognition's core critique of multi-agent systems and when it does and doesn't apply
Detect integration conflicts caused by specialist agents making incompatible assumptions in isolation

Introduction

Multi-Agent Orchestration

Objective

Detect when multiple specialist agents made conflicting assumptions about a shared interface, and confirm no conflict is reported when subtasks are genuinely independent.

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You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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