AI Engineering/Phase 14/Lesson 12

Anthropic's Workflow Patterns: Simple Over Complex

Schluntz and Zhang (Anthropic, Dec 2024) distinguish workflows (predefined paths) from agents (dynamic tool-use). Five workflow patterns cover most cases. Start with direct API calls. Add agents only when steps cannot be predicted.

Learn + Build 1 hr Python (stdlib)

Prerequisites: Phase 14 · 01 (Agent Loop)

#Learning Objectives

Name Anthropic's five workflow patterns: prompt chaining, routing, parallelization, orchestrator-workers, evaluator-optimizer.
Explain the agent-vs-workflow distinction and the engineering cost of each.
Identify when to pick a workflow over an agent (and vice versa).
Implement all five patterns in stdlib against a scripted LLM.

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The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.