# dair-ai/prompt-engineering-guide

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75,678 stars · 8,223 forks · MDX · MIT

## Links

- GitHub: https://github.com/dair-ai/Prompt-Engineering-Guide
- Homepage: https://www.promptingguide.ai/
- awesome-repositories: https://awesome-repositories.com/repository/dair-ai-prompt-engineering-guide.md

## Topics

`agent` `agents` `ai-agents` `chatgpt` `deep-learning` `generative-ai` `language-model` `llms` `openai` `prompt-engineering` `rag`

## Description

This project is a comprehensive educational resource and technical guide focused on the development, optimization, and application of large language models. It provides a structured curriculum for mastering prompt engineering, ranging from foundational principles of instruction design to advanced techniques for improving model reasoning, accuracy, and reliability.

The guide distinguishes itself by offering deep technical insights into agentic workflows and autonomous system design. It covers the implementation of multi-step reasoning chains, tool integration through function calling, and stateful memory management. Beyond basic prompting, it explores sophisticated frameworks that combine reasoning and acting, as well as methodologies for retrieval-augmented generation and the creation of synthetic datasets to address data scarcity in specialized domains.

The documentation also addresses the broader engineering surface of AI development, including defensive strategies for application security and automated evaluation loops for model verification. These resources are designed to support developers in building complex, task-oriented AI systems that can interact with external APIs and maintain continuity across long-running processes.

## Tags

### Artificial Intelligence & ML

- [Agentic Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-orchestration.md) — Provides methodologies for dynamic task decomposition and autonomous multi-step workflow execution.
- [Agentic Orchestration Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-orchestration-frameworks.md) — A technical reference for implementing multi-step reasoning workflows, tool integration, and stateful memory management in autonomous AI systems.
- [Prompt Engineering](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-engineering.md) — Provides comprehensive guidance on designing and optimizing instructions for language models.
- [Prompt Engineering Fundamentals](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-engineering-fundamentals.md) — Prompt Engineering covers core principles of prompt construction, including standard formatting conventions and the relationship between instruction quality and output reliability.
- [Prompt Engineering Guides](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-engineering-guides.md) — Serves as a comprehensive guide for developing and optimizing prompts for large language models. ([source](https://www.promptingguide.ai/introduction))
- [Agentic Reasoning Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-reasoning-frameworks.md) — Prompt Engineering implements the ReAct framework to combine reasoning and acting, improving model performance on decision-making and knowledge-intensive tasks.
- [Agentic Workflows](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-workflows.md) — Provides frameworks for structuring autonomous reasoning chains and multi-step agentic tasks.
- [Chain-of-Thought Prompting](https://awesome-repositories.com/f/artificial-intelligence-ml/chain-of-thought-prompting.md) — Provides foundational knowledge on chain-of-thought prompting for complex reasoning. ([source](https://www.promptingguide.ai/techniques/cot))
- [Prompt Design Best Practices](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-design-best-practices.md) — Provides foundational tips and best practices for designing effective prompts. ([source](https://www.promptingguide.ai/introduction))
- [Retrieval-Augmented Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/retrieval-augmented-generation.md) — Provides resources for implementing retrieval-augmented generation to build knowledge-aware systems.
- [Tool-Use Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/tool-use-orchestration.md) — Describes approaches for combining reasoning with external tool usage. ([source](https://www.promptingguide.ai/techniques/art))
- [Automated Chain-of-Thought](https://awesome-repositories.com/f/artificial-intelligence-ml/automated-chain-of-thought.md) — Explains methods for automating the generation of reasoning chains. ([source](https://www.promptingguide.ai/techniques/cot))
- [Automatic Prompt Engineering](https://awesome-repositories.com/f/artificial-intelligence-ml/automatic-prompt-engineering.md) — Covers frameworks for automating the generation and selection of prompts. ([source](https://www.promptingguide.ai/techniques/ape))
- [Prompt Chaining Strategies](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-chaining-strategies.md) — Prompt Engineering enables task decomposition by chaining sequential subtasks to improve the reliability and performance of complex document-based question answering systems.
- [Reasoning Workflows](https://awesome-repositories.com/f/artificial-intelligence-ml/reasoning-workflows.md) — Explains architectural patterns and prompting techniques for complex multi-step reasoning. ([source](https://www.promptingguide.ai/introduction/examples))
- [Tool Integration](https://awesome-repositories.com/f/artificial-intelligence-ml/tool-integration.md) — Maps natural language intents to executable external APIs to enable interaction with real-world systems.
- [Active Prompting Techniques](https://awesome-repositories.com/f/artificial-intelligence-ml/active-prompting-techniques.md) — Details active prompting methods for dynamic example selection. ([source](https://www.promptingguide.ai/techniques/activeprompt))
- [Context Engineering](https://awesome-repositories.com/f/artificial-intelligence-ml/context-engineering.md) — Structures input data and instructions to manage agent behavior and maintain domain-specific knowledge.
- [LLM Application Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-application-frameworks.md) — Defines best practices for building task-oriented AI applications using RAG and synthetic data.
- [Prompting Techniques](https://awesome-repositories.com/f/artificial-intelligence-ml/prompting-techniques.md) — Provides guidance on crafting prompts to improve the quality and consistency of model results. ([source](https://www.promptingguide.ai/introduction/basics))
- [Instructional Prompting](https://awesome-repositories.com/f/artificial-intelligence-ml/instructional-prompting.md) — Explains how to use direct commands to achieve specific tasks. ([source](https://www.promptingguide.ai/introduction/tips))
- [Model Configuration Settings](https://awesome-repositories.com/f/artificial-intelligence-ml/model-configuration-settings.md) — Explains how to adjust model settings to influence output behavior. ([source](https://www.promptingguide.ai/introduction))
- [Prompt Specificity Guidelines](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-specificity-guidelines.md) — Emphasizes the importance of specificity in achieving high-quality model results. ([source](https://www.promptingguide.ai/introduction/tips))
- [Reasoning Methodologies](https://awesome-repositories.com/f/artificial-intelligence-ml/reasoning-methodologies.md) — Prompt Engineering supports chain-of-thought techniques to elicit logical reasoning from models through intermediate steps, including manual and automatic approaches.
- [Prompt Formatting](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-formatting.md) — Defines standard prompt structures for question-answering and other common tasks. ([source](https://www.promptingguide.ai/introduction/basics))
- [Prompt Iteration Workflows](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-iteration-workflows.md) — Outlines the iterative process required to optimize prompt performance. ([source](https://www.promptingguide.ai/introduction/tips))
- [Prompt Optimization Tips](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-optimization-tips.md) — Offers practical advice for avoiding impreciseness in prompt design. ([source](https://www.promptingguide.ai/introduction/tips))
- [Prompting Strategies](https://awesome-repositories.com/f/artificial-intelligence-ml/prompting-strategies.md) — Explains advanced prompting techniques like Tree of Thoughts to improve model reasoning on complex tasks. ([source](https://www.promptingguide.ai/techniques/tot))
- [Question Answering](https://awesome-repositories.com/f/artificial-intelligence-ml/question-answering.md) — Details strategies for structuring prompts to improve accuracy in question-answering tasks. ([source](https://www.promptingguide.ai/introduction/examples))
- [Stateful Memory Systems](https://awesome-repositories.com/f/artificial-intelligence-ml/stateful-memory-systems.md) — Tracks task progress and historical context to maintain continuity during long-running agentic processes.
- [Synthetic Data Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/synthetic-data-generation.md) — Uses language models to create high-quality datasets for training and evaluation.
- [Tool Integration Patterns](https://awesome-repositories.com/f/artificial-intelligence-ml/tool-integration-patterns.md) — Prompt Engineering provides function calling capabilities to integrate external APIs with language models for tool usage and agentic workflows. ([source](https://www.promptingguide.ai/))

### Education & Learning Resources

- [Prompt Engineering Guides](https://awesome-repositories.com/f/education-learning-resources/prompt-engineering-guides.md) — Provides structured tutorials on zero-shot chain-of-thought prompting techniques for language models. ([source](https://www.promptingguide.ai/techniques/cot))
- [AI Development Curricula](https://awesome-repositories.com/f/education-learning-resources/ai-development-curricula.md) — A structured learning path that teaches developers how to design, optimize, and evaluate interactions with language models for complex tasks.
- [Prompt Engineering Curricula](https://awesome-repositories.com/f/education-learning-resources/prompt-engineering-curricula.md) — Serves as a foundational resource for learning the discipline of prompt engineering. ([source](https://www.promptingguide.ai/introduction))
- [AI Knowledge Bases](https://awesome-repositories.com/f/education-learning-resources/ai-knowledge-bases.md) — Serves as a comprehensive educational hub for learning about language model development.

### Part of an Awesome List

- [Learning and Prompt Engineering](https://awesome-repositories.com/f/awesome-lists/ai/learning-and-prompt-engineering.md) — Comprehensive collection of resources for effective prompt engineering.
- [LLM Development](https://awesome-repositories.com/f/awesome-lists/ai/llm-development.md) — A comprehensive guide to prompt engineering techniques.
- [Prompt Engineering](https://awesome-repositories.com/f/awesome-lists/ai/prompt-engineering.md) — Comprehensive educational materials for mastering prompt design.
- [Prompt Engineering Frameworks](https://awesome-repositories.com/f/awesome-lists/ai/prompt-engineering-frameworks.md) — Canonical resource for prompt techniques, RAG, and agentic workflows.
- [Prompt Engineering Resources](https://awesome-repositories.com/f/awesome-lists/ai/prompt-engineering-resources.md) — Definitive open-source resource hub for prompt engineering learners.
- [AI Development Resources](https://awesome-repositories.com/f/awesome-lists/devtools/ai-development-resources.md) — Structured guide to prompt engineering techniques and research.
- [Developer Tools and Infrastructure](https://awesome-repositories.com/f/awesome-lists/devtools/developer-tools-and-infrastructure.md) — Comprehensive resources for prompt engineering.
- [Educational Guides](https://awesome-repositories.com/f/awesome-lists/learning/educational-guides.md) — Curated collection of papers, lectures, and learning resources.
- [Learning and Reference](https://awesome-repositories.com/f/awesome-lists/learning/learning-and-reference.md) — Comprehensive guide to prompt engineering and RAG.

### Security & Cryptography

- [AI Security](https://awesome-repositories.com/f/security-cryptography/ai-security.md) — Implements defensive strategies to protect language model interactions from malicious manipulation.

### Testing & Quality Assurance

- [Model Evaluation](https://awesome-repositories.com/f/testing-quality-assurance/model-testing/model-evaluation.md) — Uses automated evaluation loops to validate and refine model outputs against predefined criteria.