41 terms defined

Self-Evolving AI Agent Glossary

Plain-English definitions of AI agent terminology. Every term explains not just what it means, but how it differs from what people confuse it with — plus how self-evolving agents replace rented SaaS.

Core Concepts (14)

Agentic AI

AI that operates autonomously over extended tasks, making decisions without step-by-step human direction.

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AI Agent

An autonomous AI system that takes actions on your behalf to accomplish a goal.

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AI Agent Memory

The mechanisms by which an AI agent retains and recalls information across sessions and tasks.

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AI Copilot

An AI assistant embedded in a product that helps users complete tasks within that product's context.

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AI Guardrails

Constraints and safety mechanisms that limit what an AI agent can do to prevent unintended actions.

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AI Hallucination

When an AI model generates factually incorrect information with apparent confidence.

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AI Orchestration

The coordination and management of multiple AI agents or LLM calls within a system.

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AI Workflow

A predetermined sequence of steps with AI embedded at specific points — as opposed to an autonomous agent.

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Autonomous Agent

An AI agent that operates without human intervention to complete multi-step tasks.

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Generative AI

AI systems that generate new content — text, images, code, audio — rather than only classifying or analyzing input.

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Human-in-the-Loop (HITL)

An AI system design pattern where humans review or approve key agent decisions before they're executed.

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LLM (Large Language Model)

A deep learning model trained on large text corpora that can generate, understand, and reason with language.

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Multi-Agent System

An architecture where multiple specialized AI agents collaborate to complete complex tasks.

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Self-Evolving

An AI system that improves over time based on user feedback, patterns, and performance.

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Technical (22)

Agentic RAG

A RAG system where an AI agent controls the retrieval strategy adaptively, rather than following a fixed pipeline.

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Chain-of-Thought (CoT)

A prompting technique that asks an AI model to reason step-by-step before producing a final answer.

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Composio

An integration platform that provides 900+ OAuth-managed tool connections for AI agents.

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Context Window

The maximum amount of text an LLM can process in a single interaction.

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Embeddings

Numerical vector representations of text that encode semantic meaning.

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Few-Shot Prompting

Including a small number of input-output examples in a prompt to guide an AI model's behavior.

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Fine-Tuning

Additional training of a pre-trained LLM on domain-specific data to specialize its behavior.

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Function Calling

A model capability that allows LLMs to request calls to predefined functions with structured arguments.

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Inference

The process of running a trained AI model to generate output from a given input.

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LangChain

An open-source framework for building LLM-powered applications and AI agents in Python and JavaScript.

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MCP (Model Context Protocol)

Anthropic's open standard for connecting AI models to external tools and data sources.

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MCP Server

A process that exposes tools, resources, and prompts to MCP-compatible AI clients.

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OAuth

An open authorization standard that lets apps access user data from other services without sharing passwords.

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Prompt Engineering

The practice of designing inputs to AI models to reliably produce desired outputs.

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RAG (Retrieval-Augmented Generation)

A technique that grounds AI responses in retrieved documents rather than relying solely on training data.

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Semantic Search

Search that finds results by meaning rather than exact keyword matching.

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System Prompt

Instructions provided to an LLM before the conversation begins, setting its role, behavior, and constraints.

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Tool Call

A specific invocation of an external tool by an AI agent during task execution.

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Tool Use

An AI model's ability to call external functions, APIs, or services during reasoning.

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Vector Database

A database optimized for storing and searching high-dimensional vector embeddings.

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Webhook

A mechanism for one system to notify another system in real time when an event occurs.

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Zero-Shot Prompting

Asking an AI model to complete a task with no examples of the desired output.

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Business & Use Cases (5)

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