Basics

Article

Introduction: Terminology Matters

We’ve all seen articles about “an AI system”, but what does that actually mean? The raw LLM that generates text? The agent that makes decisions? The tools it calls? The infrastructure that makes it all work reliably? Without clear terminology, teams build brittle integrations, set wrong expectations, and misplace trust—expecting intelligence where there’s really just …

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AI System

An AI system is the comprehensive integration of components that collectively deliver artificial intelligence-powered functionality. It combines the generative capabilities of LLM, the reasoning and decision-making processes of agents, the action-enabling capabilities of tools, and the reliability mechanisms of the orchestration layer. Additional infrastructure components, such as integration layers, plugin frameworks, or standardized protocols like …

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AI Agent

An AI agent is a type of AI system that uses a LLM for reasoning and autonomously pursues goals by making decisions, invoking tools, and adapting to feedback. Agents add goal-directed behavior on top of raw model outputs, enabling systems to act in dynamic and flexible ways. Agents can use different mechanisms to access tools, …

Article

AI Tool

An AI tool is a capability beyond an LLM’s native text generation that an AI agent can invoke to access data, perform actions, or integrate with services. Tools can be connected in different ways: through direct API calls, plugin frameworks, or standardized protocols such as the Model Context Protocol (MCP). Key characteristics Also: A tool …

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