15 technical terms defined for the 2026 agentic era.
The ability of an AI agent to independently decompose goals, plan steps, and adapt its approach without human guidance.
The core execution cycle of an autonomous agent: observe, reason, act, evaluate—repeated until the goal is achieved or a stopping condition is met.
Human-in-the-Loop — a design pattern where autonomous systems pause for human confirmation before executing consequential actions.
An attack vector where malicious instructions embedded in external content attempt to hijack an AI agent's behavior.
The mechanism by which LLMs invoke external functions, APIs, or services to perform actions beyond text generation.
Retrieval-Augmented Generation — enhancing LLM outputs by retrieving relevant documents or data at inference time.
A prompting technique that improves LLM reasoning by instructing the model to show its intermediate reasoning steps before arriving at an answer.
Routing agent tasks to the appropriate specialized agent or tool based on semantic understanding of the request, rather than keyword or category matching.
Coordinating AI agents that process and generate multiple modalities—text, images, audio, video, and structured data—within a single workflow.
An orchestration framework for building stateful, cyclical multi-agent workflows as directed graphs with native HITL support.
A multi-agent orchestration framework that organizes autonomous agents into teams with defined roles and collaboration patterns.