# Awesome-Prompt-Engineering

A curated collection of resources on prompt and context engineering, from basic prompting techniques through agentic patterns, tool use, and production AI system design.

Awesome-Prompt-Engineering is a curated list of resources spanning prompt engineering and the broader discipline of context engineering, which the repository describes as architecting the full information environment around a model, including system prompts, conversation history, retrieved knowledge, tool definitions, and memory.

Its sections progress from an introductory timeline of AI development, through basic prompting techniques such as structure, roles, delimiters, and constraints, to intermediate reasoning techniques such as few-shot prompting and chain-of-thought, and advanced agentic patterns such as ReAct, tool use, and self-reflection. Further sections cover multi-modal prompting, building autonomous agent systems, a guide to tools for building and evaluating AI systems, and deep-learning fundamentals relevant to language models, plus a curated reading list organized by topic.

It is maintained as a GitHub repository and companion site, written primarily in Python and Markdown.

Website: https://natnew.github.io/Awesome-Prompt-Engineering/