Prompt Engineering Guide
Open-source MIT-licensed guide by DAIR.AI covering prompting techniques, model-specific tips, examples, and resources for building with LLMs.
At a Glance
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Updated Feb 2026
About Prompt Engineering Guide
Prompt Engineering Guide is a free, open-source knowledge base maintained by DAIR.AI that teaches practical prompting methods for large language models. The site organizes core techniques (e.g., zero-shot, few-shot, chain-of-thought, self-consistency, prompt chaining, ReAct, RAG) with concise explanations and copyable examples. It also includes model-specific guidance (ChatGPT, Claude, Gemini, Llama, Mistral and more), an examples hub across tasks, coverage of risks and misuses, and curated links to papers, tools, notebooks, and datasets. The project is MIT-licensed, translated into multiple languages, and welcomes community contributions via GitHub.
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Pricing
Free (Open Source)
Get started with Prompt Engineering Guide at no cost with Full site access and MIT-licensed repository.
- Full site access
- MIT-licensed repository
- Community contributions
Capabilities
Key Features
- Technique library: zero-shot, few-shot, chain-of-thought, self-consistency, prompt chaining, ReAct, RAG
- Model-specific prompting guides (e.g., ChatGPT, Claude, Gemini, Llama, Mistral)
- Prompt Hub with ready-to-use examples across tasks (classification, coding, QA, summarization, evaluation, etc.)
- Agents section covering agent concepts and components
- Guides on optimizing prompts, function calling, context engineering, and code/data generation
- Risk and misuse coverage (adversarial prompting, factuality, bias)
- Curated resources: papers, tools, notebooks, datasets, additional readings
- Community contribution workflow with Edit links to GitHub
- Multilingual site with translations
- MIT-licensed content and source code
Integrations
Demo Video
