Prompt Engineering Techniques is a focused companion repository that teaches prompt engineering systematically, from fundamentals to advanced strategies. It contains around twenty-plus hands-on Jupyter notebooks, each dedicated to a specific technique such as basic prompt structures, prompt templates and variables, zero-shot prompting, few-shot prompting, chain-of-thought, self-consistency, constrained generation, role prompting, task decomposition, and more. The tutorials are designed to be practical; you can run them directly, examine the prompts, and see how small changes affect model behavior and quality. The repository is framed as a “techniques library” that complements a more detailed book, which expands on the same topics with deeper explanations and exercises. It is intended for a wide audience, from beginners learning how to structure their first prompts to advanced practitioners optimizing stability, controllability, and reliability in production systems.
Features
- Extensive set of Jupyter notebook tutorials covering key prompt engineering techniques
- Progressive structure from introductory concepts to advanced strategies and implementations
- Concrete examples of patterns like zero-shot, few-shot, chain-of-thought, and self-consistency
- Focus on practical, ready-to-use prompt templates that can be adapted to real projects
- Companion material to a full book with deeper explanations and structured exercises
- Community-driven approach with contribution guidelines and links to related RAG and agent resources