Prompt Engineering Patterns

If you're building production LLM apps and tired of inconsistent outputs, this handles the advanced prompt engineering patterns that actually matter. It covers structured outputs with Pydantic schemas, chain-of-thought reasoning with self-verification, and dynamic few-shot example selection using semantic similarity. The JSON mode examples alone will save you hours of parsing headaches. What I like most is the progressive disclosure approach, starting simple and adding complexity only when needed. It includes concrete patterns for A/B testing prompts, handling malformed responses, and building reusable template systems with proper variable interpolation.