Prompt Engineering Guide
Prompt Engineering Guide is a comprehensive open-source repository curated by DAIR.AI that provides guides, research papers, lessons, notebooks, and other resources focused on prompt engineering, context engineering, retrieval-augmented generation (RAG), and AI agents. The project aims to serve as a central hub for practitioners and researchers to learn about and stay updated on the rapidly evolving field of prompting large language models. It includes a curated collection of academic papers, practical tutorials, and code examples that illustrate best practices and advanced techniques. The repository covers a wide range of topics, from basic prompt design to more specialized areas such as chain-of-thought prompting, context engineering, and building autonomous AI agents. It also includes notebooks that allow users to interactively experiment with different prompting strategies and integrate them into their own applications. The content is maintained by DAIR.AI and the open-source community, ensuring that it reflects current developments and practical insights. In addition to textual guides, the guide provides links to relevant research papers, benchmark datasets, and tools that can help users deepen their understanding. It is designed for both beginners who are new to prompt engineering and experienced developers looking to refine their skills. The resource is freely accessible and can be used for self-study, teaching, or as a reference for building production systems.
- Category
- AI Agents
- Pricing
- Open Source
Problem solved
The tool addresses the lack of a centralized, structured, and continuously updated resource for learning prompt engineering and related techniques. It consolidates scattered information, research papers, and practical examples into one accessible location, saving users time and providing a trusted starting point for both learning and application.
Use cases
- Learning the fundamentals and advanced techniques of prompt engineering
- Staying updated with the latest research papers and methods in RAG and AI agents
- Accessing interactive notebooks to practice prompt design and context engineering
- Building and improving AI agent workflows using curated resources
- Teaching prompt engineering in academic or workshop settings
- Finding benchmark datasets and evaluation resources for prompting tasks
Audience
- Developers
- ML Engineers
- Data Scientists
- Researchers
- Hobbyists
Pros
- Comprehensive coverage of prompt engineering and related AI topics
- Free and open source, accessible to everyone
- Regularly updated with new research and practical content
- Includes hands-on notebooks and code examples
- Curated by DAIR.AI, a trusted AI education organization
Cons
- May be overwhelming for complete beginners due to the breadth of content
- No formal certification or guided learning path
- Relies on community contributions, which can vary in quality and timeliness
- Requires self-directed learning; no interactive support or mentorship
Official website: https://github.com/dair-ai/Prompt-Engineering-Guide
Canonical LambdaBase page: https://www.lambdabase.com/tools/prompt-engineering-guide