Prompt Engineering

26 Principles of Good Prompts

See also: Prompt engineering for text generation and Guides The 26 principles of good prompts are a set of 26 practical rules for writing prompts to large...

Agentic Context Engineering

Agentic Context Engineering (ACE) is a framework for scalable and efficient context adaptation in large language models (LLMs) that lets an AI system improve...

AI AgentsArtificial Intelligence

Auto-CoT

Auto-CoT (Automatic Chain of Thought) is an automated prompting method that builds few-shot Chain-of-Thought demonstrations for large language models without...

Large Language Models

Chain of Density prompting

Chain of Density (CoD) is a prompting technique for abstractive text summarization with large language models, introduced in the 2023 paper "From Sparse to...

Natural Language Processing

Chain of Verification (CoVe)

Chain of Verification (CoVe) is a prompting technique that reduces factual hallucinations in large language models by having the model fact-check its own draft...

Large Language Models

Chain-of-Thought

Chain-of-thought (CoT) is a sequence of intermediate steps that a language model generates before its final answer. Chain-of-thought prompting is the narrower...

Deep LearningMachine Learning

Context engineering

Context engineering is the practice of designing, building, and optimizing the full set of information that a large language model receives in its context...

AI AgentsArtificial Intelligence

CustomGPT Instructions for Knowledge (Uploaded Files)

"CustomGPT Instructions for Knowledge (Uploaded Files)" is the informal name for a short block of default instructions that OpenAI prepends to a Custom GPT's...

ChatGPTOpenAI

Fine-tune ChatGPT with Perplexity, Burstiness, Professionalism, Randomness and Sentimentality Guide

See also: Guides, ChatGPT Guides and Prompt Engineering Guides The perplexity, burstiness, professionalism, randomness, and sentimentality guide is a prompt...

ChatGPT

Graph of Thoughts

Graph of Thoughts (GoT) is a prompting and reasoning framework that models the intermediate steps of a large language model as an arbitrary directed graph...

Large Language Models

How to Pressure LLMs for Better Output

See also: Prompt engineering, Chain-of-thought prompting, LLM anxiety, and Large language model Pressuring large language models (LLMs) is a family of prompt...

Large Language ModelsNatural Language Processing

Least-to-Most Prompting

Least-to-Most Prompting is a few-shot prompting technique for large language models introduced by researchers at Google Brain in May 2022. The method addresses...

Large Language Models

Meta Prompting

See also: artificial intelligence terms Meta prompting (also spelled meta-prompting) is an advanced prompt engineering technique where large language models...

Artificial IntelligenceMachine Learning

MidJourney Prompt Generator

MidJourney Prompt Generator is a generic category name that refers to the broad class of tools, custom GPTs, and prompt templates that help users compose...

AI Tools & ProductsImage Generation

Prompt

A prompt is the input given to a generative AI model, particularly a large language model (LLM), that elicits a desired response. In the simplest case, a...

Large Language Models

Prompt engineering for image generation

Prompt engineering for image generation is the practice of writing and refining the text prompts that guide text-to-image AI image generation models such as...

Prompt engineering for text generation

See also: Prompt engineering, Prompts and Prompt engineering for image generation Prompt engineering for text generation is the practice of designing the...

ReAct (prompting)

See also: Prompt engineering, Chain-of-thought prompting, Tool use, AI agents, and LangChain ReAct (short for Reasoning and Acting) is a prompting paradigm for...

AI AgentsReasoning Models

Self-Discover prompting

Self-Discover is a prompting framework for large language models in which the model first composes a task-specific reasoning structure from a library of atomic...

Large Language Models

Self-Refine

Self-Refine is an inference-time prompting framework in which a single large language model iteratively improves its own output by alternating between...

Large Language Models

Self-consistency

Self-consistency is a decoding strategy for large language models that samples multiple chain-of-thought reasoning paths for the same question and returns the...

Large Language ModelsReasoning Models

Skeleton-of-Thought

Skeleton-of-Thought (SoT) is a prompting technique for large language models that reduces end-to-end generation latency by first eliciting a short outline of...

AI Inference

Step-Back Prompting

Step-Back Prompting is a two-stage prompting technique introduced by researchers at Google DeepMind in October 2023. It elicits stronger reasoning from large...

Large Language Models

System prompt

See also: Prompt, User prompt, and Prompt engineering A system prompt is a special set of instructions, guidelines, persona definitions, and contextual...

AI SafetyLarge Language Models

Tree of Thoughts

Tree of Thoughts (ToT) is a prompting and inference-time search framework for large language models that lets the model explore multiple intermediate reasoning...

Artificial IntelligenceReasoning Models

Vibe Coding Tips and Tricks

See also: Vibe Coding Vibe coding is the practice of building software by describing what you want in natural language and letting an AI write the code. The...

AI Code GenerationSoftware Development

Zero shot, one shot and few shot learning

See also: Machine learning terms Zero-shot, one-shot, and few-shot learning are three related settings in machine learning and prompt engineering defined by...

Machine Learning