OpenAI’s API guide covers prompt engineering strategies and tactics for working with large language models.
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8 alternativesPrompt Engineering Guide
The Prompt Engineering Guide teaches prompt engineering and provides learning materials about language models.
About Prompt Engineering Guide
Prompt Engineering Guide is a web resource for learning to develop and optimize prompts for language models. It explains prompting basics, prompt elements, and design tips, along with techniques such as zero-shot, few-shot, and chain-of-thought prompting.
It also provides materials on AI agents, context engineering and function calling, applications such as generating code and data, model-specific notes, and sections on risks, research findings, papers, tools, notebooks, and datasets.
Key features
- Explanations of prompting basics, elements, and design tips
- Tutorials for zero-shot, few-shot, and chain-of-thought prompting
- Guides for AI agents, function calling, and context engineering
- Example prompt collection for coding, classification, and reasoning tasks
- Model-specific notes for ChatGPT, Claude, Gemini, Llama, and others
- Sections on risks including prompt injection, bias, and factuality
Best for: Researchers and developers who want to learn prompting techniques and work with language models.
Good for
- Covers prompting from basics to techniques such as chain-of-thought and ReAct
- Includes example prompts for tasks such as coding, classification, and question answering
- Addresses agents, model-specific notes, risks, papers, tools, and datasets
Prompt Engineering Guide at a glance
- Website
- promptingguide.ai
- Category
- AI & Machine Learning › AI Learning & Guides
- Type
- Website
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Prompt Engineering Guide FAQ
What does the site mean by prompt engineering?
Developing and optimizing prompts to use language models for applications and research topics, including interacting with models and augmenting them with domain knowledge and external tools.
How do researchers and developers use prompt engineering?
Researchers use it to improve LLM capacity on tasks such as question answering and arithmetic reasoning, while developers use it to design prompting techniques that interface with LLMs and other tools.
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