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What is Prompt Engineering Guide?
The Prompt Engineering Guide is a free, continuously updated reference covering prompting techniques, model-specific tips, and links to relevant research, maintained as an open resource rather than a paid course.
Key features
- Covers prompting techniques from basic templates to advanced chain-of-thought and agent patterns
- Model-specific guides for major LLM providers
- Summaries of relevant academic research on prompting
- Practical examples you can adapt directly
- Regularly updated as new techniques and models emerge
How to get started
- Go to promptingguide.ai and browse by technique or topic
- Read the model-specific section for the LLM you're using
- Adapt the provided examples to your own use case
- Check back periodically as new techniques are added
Use cases
- Learning specific prompting techniques like chain-of-thought
- Quick reference while writing prompts for a project
- Understanding the research behind popular prompting methods
- Onboarding a team onto shared prompting best practices
Prompt Engineering Guide vs. alternatives
| Tool | How it compares |
|---|---|
| Prompt Engineering Guide | A living reference for prompting techniques. |
| Learn Prompting | more structured, course-style format |
| DeepLearning.AI | video-based instead of a written reference |
FAQ
Is Prompt Engineering Guide free to use?
Prompt Engineering Guide's plans: Free. Pricing and free-tier limits change over time, so check the official site above for the latest details.
What is Prompt Engineering Guide used for?
A living reference for prompting techniques.
Who is Prompt Engineering Guide best for?
Prompt Engineering Guide is a good fit for learning specific prompting techniques like chain-of-thought, or quick reference while writing prompts for a project.
What are the alternatives to Prompt Engineering Guide?
Commonly compared alternatives include Learn Prompting and DeepLearning.AI, see the comparison above for how they differ.
Related tools
Last reviewed: 2026-08 · Reviewed by AIKetra editors · How we evaluate tools
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