Phase 5: Agent Orchestration Patterns · 45 min · Claude Code · Python

Single-Agent Architecture Done Right

One well-harnessed agent with real state management beats a multi-agent system nobody needed to build yet.

Real-world application: Building a single agent with real checkpointing and recovery — not defaulting to a multi-agent system for complexity's sake — shows restraint and engineering judgment that's rarer than it should be.

What you will learn

Describe the augmented LLM pattern: a single model call augmented with retrieval, tools, and memory
Identify when a single well-harnessed agent is sufficient and preferable to a multi-agent system
Design state management for a long-running single-agent task
Implement checkpointing and recovery so an interrupted task resumes instead of restarting

Introduction

Single-Agent Architecture Done Right

Objective

Process a list of items with per-item checkpointing to durable storage, simulate an interruption partway through, and confirm a restart resumes from the last completed item instead of reprocessing everything.

Unlock the full lesson

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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