AI Glossary

A comprehensive encyclopedia of artificial intelligence and context management terminology — with definitions, in-depth articles, and authoritative sources.

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Chain-of-Thought

Also known as: CoT, Chain-of-Thought Prompting, Step-by-Step Reasoning

A prompting technique that improves AI reasoning by instructing the model to decompose complex problems into intermediate reasoning steps before arriving at a final answer.

Context Management

Context Compression

Also known as: Prompt Compression, Context Condensation

Techniques for reducing the token count of context provided to language models while preserving the most essential information, enabling more efficient use of limited context windows.

Context Management

Context Window

Also known as: Context Length, Token Limit, Context Size

The maximum amount of text (measured in tokens) that a language model can process in a single interaction, determining how much information the model can consider when generating a response.

Context Management

Few-Shot Learning

Also known as: Few-Shot, In-Context Learning, k-Shot Learning

A machine learning approach where models learn to perform tasks from only a small number of examples, typically provided within the prompt or during a brief adaptation phase.

Context Management

Grounding

Also known as: AI Grounding, Factual Grounding, Knowledge Grounding

The process of connecting AI model responses to verified factual information, source documents, or real-world data to ensure outputs are accurate and substantiated.

Context Management

Model Context Protocol

Also known as: MCP

An open standard developed by Anthropic that standardizes how AI applications connect to external data sources, tools, and context providers through a unified protocol.

Context Management

Prompt Engineering

Also known as: Prompt Design, Prompt Crafting, In-Context Learning

The practice of designing, optimizing, and structuring inputs (prompts) to AI language models to elicit desired outputs, including techniques for instruction formatting, context provision, and output specification.

Context Management

Retrieval-Augmented Generation

Also known as: RAG

A technique that enhances AI model outputs by retrieving relevant information from external knowledge sources and incorporating it into the model's context before generating a response.

Context Management

Semantic Search

Also known as: Vector Search, Neural Search, Meaning-Based Search

A search methodology that understands the contextual meaning and intent behind a query rather than matching exact keywords, using embeddings and vector similarity to find semantically relevant results.

Context Management

9 terms under "Context Management"