# Ultimate Prompt Engineering Playbook

A collection of 114 runnable Jupyter notebooks that each teach one prompt engineering technique, from zero-shot prompting through chain-of-thought reasoning, few-shot learning, and output formatting, across several LLM providers.

Ultimate Prompt Engineering Playbook is a curated set of 114 interactive notebooks, one per prompting technique, meant to be run directly in Google Colab against OpenAI, Anthropic, Google, and other providers. Each notebook pairs a technique with runnable code, real-world style examples rather than toy problems, and, where available, benchmark data and analysis of cases where the technique fails.

The notebooks are grouped into sections covering foundational prompting, reasoning and logic techniques such as chain-of-thought and tree of thoughts, few-shot and in-context learning, role-playing and persona techniques, and output control and formatting such as structured or JSON output. The project is organized as a table of contents linking directly to each notebook.

Website: https://github.com/amerob/ultimate-prompt-engineering-playbook