# dair-ai/Prompt-Engineering-Guide

> 🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

- GitHub: https://github.com/dair-ai/Prompt-Engineering-Guide
- Website: https://www.promptingguide.ai/
- Category: Learning & Lists (https://ideas.asveas.com/c/learning); also AI Agents, RAG, Search & Data
- Tags: ai-agents, chatgpt, deep-learning, generative-ai, language-model, llm, openai, prompt-engineering, rag, mdx
- Language: MDX · License: MIT
- Stars: 79,987 · Forks: 8,778 · Open issues: 298
- Last push: 2026-03-11 (8 months ago)
- Vibe score: 77/100

## What it is
Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.

## When to use it
Reach for Prompt-Engineering-Guide when you want to learn a topic, find more tools, or borrow battle-tested prompts and examples — it's written in MDX and fits stacks tagged ai-agents, chatgpt, deep-learning, generative-ai.

## Maintenance
dair-ai/Prompt-Engineering-Guide looks maintained, but updates are slowing: the last push was 8 months ago (2026-03-11), with 79,987 stars and 298 open issues.

## Quick start
```bash
git clone https://github.com/dair-ai/Prompt-Engineering-Guide.git
```

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Source: https://ideas.asveas.com/r/dair-ai/Prompt-Engineering-Guide · Catalog: https://ideas.asveas.com/llms.txt