Prompt Engineering

OpenAI’s API guide covers prompt engineering strategies and tactics for working with large language models.

"Tips and tricks for working with Large Language Models like OpenAI's GPT-4".

This repository collects templates for CLAUDE.md, Cursor rules, and PRPs used with AI coding assistants.

Langfuse provides open-source tracing and evaluation for language model applications and agents.

This repository teaches 22 prompt engineering techniques through Jupyter Notebook tutorials.

This article discusses DSPy and its role in prompt engineering frameworks such as LangChain and LlamaIndex.

Tensor Trust offers an interactive game about testing AI security and model robustness.

Localforge provides a local coding agent with a web interface that works on project files.

A curated list of generative AI tools, projects, models, and references.

An open-source visual programming environment for battle-testing prompts to LLMs.

This repository curates prompts for Google Gemini image generation, with previews and multiple language versions.

Claude’s prompt engineering documentation explains prompting techniques and interactive tutorials.

Prompt Engineering Guide collects lessons, papers, notebooks, and resources on prompting, retrieval-augmented generation, and AI agents.

A set of principles for building LLM powered software intended for production users.

This guide explains prompt techniques for generating art and copy, with templates and style suggestions.

The Prompt Engineering Guide teaches prompt engineering and provides learning materials about language models.

This repository studies how agentic coding assistants work, including prompt patterns and agent coordination.

OpenPrompt provides a place to create, use, and share prompts for ChatGPT.

Swarms provides an enterprise oriented framework for coordinating multiple AI agents.

This SDK provides AI evaluations, prompt management, and observability for Python and TypeScript workflows.

code2prompt converts a codebase into one language-model prompt with a source tree, templates, and token counts.

LLMFlows provides components for building language model applications with explicit workflows.

This Lil’Log article explains prompt engineering methods for steering autoregressive language models.

Learn Prompting provides a guide to generative AI and prompt engineering, with lessons and examples.