This repository serves as a comprehensive hub for over 25 prompt engineering techniques, designed for practitioners working with Generative AI, Large Language Models (LLMs), Agents, and Retrieval-Augmented Generation (RAG). It offers a structured way to explore and implement various prompting strategies to enhance AI model performance and output quality.

How It Works

The project categorizes prompt engineering techniques into logical groups, including Basic, Advanced (Reasoning, Break Down, Ensemble, Critique, Multilingual, Multi-Step). Each technique is briefly described, and a link is provided for further learning, enabling users to systematically understand and apply different methods for interacting with AI models.

Quick Start & Requirements

The provided README does not include installation instructions, specific prerequisites, or quick-start commands. The repository functions as a curated list of techniques and learning resources rather than a runnable software package.

Highlighted Details

• Catalogues over 25 distinct prompt engineering techniques.
• Covers a broad spectrum from fundamental to advanced strategies, including reasoning, decomposition, ensemble methods, self-critique, multilingual applications, and multi-step processes.
• Each technique is accompanied by a link for deeper exploration and understanding.
• Promotes staying current with Generative AI advancements via a linked newsletter.

Maintenance & Community

The repository promotes a newsletter, AIxFunda, for updates on Generative AI, LLMs, Agents, and RAG. No specific community channels (e.g., Discord, Slack) or details regarding maintainers or contributors are present in the README.

Licensing & Compatibility

The README does not specify a software license. Consequently, its terms for commercial use or integration with closed-source projects remain undetermined.

Limitations & Caveats

This repository is a collection of techniques and pointers to external learning materials, not a deployable library with code implementations. It lacks explicit setup instructions, dependency lists, or usage examples. The absence of a defined license is a significant caveat for potential adoption.