Three Layers for Production-Grade Claude API Agents in Python

TL;DR Most Claude API agent tutorials show the happy path. This one focuses on the three engineering layers that make agents actually reliable in production: (1) schema discipline in tool definitions, (2) a correct agentic loop that handles tool errors gracefully, and (3) a retry wrapper with exponential backoff and jitter. Ends with a structured output boundary using Pydantic and messages.parse() . All code is runnable. No placeholder functions. The Problem With Most Agent Demos Demo agents work in notebooks because notebooks run one cell at a time, tolerate manual retries, and have a human in the loop who can interpret a malformed response. Production agents do not have those affordances. They need to handle tool exceptions without crashing, survive API rate limits without user-visible errors, and produce output that downstream systems can parse reliably. This guide walks through a complete customer order lookup pipeline that demonstrates all three layers. We use claude-sonnet-4-6 an