Agent Lifecycle Management

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 mechanism allowing language models to invoke external functions or APIs based on natural language instructions.

Standardised protocols and languages used for inter-agent communication in multi-agent systems.

A multi-step business process executed entirely by AI agents with minimal human intervention, spanning planning, execution, monitoring, and error recovery phases.

A catalogue of available tools and APIs that agents can discover and invoke, with descriptions, schemas, and authentication details enabling dynamic capability acquisition.

The complete set of possible actions available to an AI agent in a given environment, defining the boundaries of what the agent can do to accomplish its objectives.

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

A system composed of multiple interacting AI agents that collaborate, negotiate, or compete to solve complex problems.

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

Monitoring

The continuous observation of system performance, availability, and health using automated tools and dashboards.