Agent Chaining

Agentic AI

AI systems that can autonomously plan, reason, and take actions to achieve goals with minimal human intervention.

AI Agent

An autonomous software entity that perceives its environment, makes decisions, and takes actions to achieve specified objectives.

Autonomous Agent

An AI agent capable of operating independently, making decisions and taking actions without continuous human oversight.

Reactive Agent

An AI agent that responds to environmental stimuli with predefined actions without maintaining an internal model of the world.

Deliberative Agent

An AI agent that maintains an internal model of its world and reasons about actions before executing them.

BDI Architecture

Belief-Desire-Intention — an agent architecture where agents reason about beliefs, desires, and intentions to decide actions.

Agent Planning

The ability of an AI agent to formulate a sequence of actions to achieve a goal from its current state.

Tool Use

The capability of AI agents to interact with external tools, APIs, and services to extend their functionality.

Agent Hierarchy

An organisational structure where agents are arranged in levels, with higher-level agents delegating tasks to lower-level ones.

Supervisor Agent

An agent that oversees and coordinates the work of other agents, making high-level decisions and resolving conflicts.

Agent Sandbox

An isolated environment where AI agents can safely execute actions and experiment without affecting production systems.

Human-on-the-Loop

A system where humans monitor AI operations and can intervene when necessary, but don't approve every action.

A meta-agent that coordinates, monitors, and manages a team of sub-agents, allocating tasks and synthesising results to fulfil complex multi-domain objectives.

An AI agent specialised in writing, debugging, refactoring, and testing software code, capable of operating across multiple files and understanding project-level context.

The transfer of a task or conversation from one specialised AI agent to another based on skill requirements, escalation rules, or domain boundaries.

An advanced retrieval-augmented generation pattern where an agent dynamically decides what information to retrieve, from which sources, and how to refine queries iteratively.

A multi-agent scenario where agents pursue conflicting objectives, leading to adversarial or game-theoretic interactions.

An AI agent that selects actions to maximise a utility function representing the desirability of different outcomes.

An AI agent that autonomously navigates web pages, fills forms, extracts information, and completes online tasks by controlling a browser through programmatic or visual interfaces.

Standardised evaluation of AI agent capabilities across tasks like tool use, planning, reasoning, and task completion.