# 06 - Prompt Engineering at Scale: Techniques and Best Practices

Complete guide to Prompt Engineering at Scale: Techniques and Best Practices: architecture, practical implementation and best practices for developers and technical teams.

## What you'll learn

- Chain-of-Thought significantly improves accuracy on complex tasks
- Structured output (Pydantic) eliminates parsing errors and guarantees format
- Prompts must be versioned, tested and deployed like any code
- A/B testing with statistical significance before promoting new versions
- LLM-as-judge scales quality evaluation at reduced cost

*This article is part of the **AI Engineering** series on federicocalo.dev.*

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## Read the full article

The complete article (16 min read) with code examples, diagrams, and practical exercises is available here:

**➡️ [06 - Prompt Engineering at Scale: Techniques and Best Practices](https://federicocalo.dev/en/blog/prompt-engineering-scale-techniques-best-practices)**

`https://federicocalo.dev/en/blog/prompt-engineering-scale-techniques-best-practices`

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*By [Federico Calò](https://federicocalo.dev) — Software Developer & Technical Writer*