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AI & Agents

Agentic AI

Agentic AI is the general term for AI systems that plan and act autonomously toward a goal rather than responding to one prompt at a time. It describes the capability class; an "AI agent" is a specific deployed instance of it. The defining property is autonomy over a sequence of steps, including tool use.

Vendors use "agentic AI" and "AI agent" interchangeably, which makes the term unreliable as a purchasing signal. The useful question when evaluating any product described this way is concrete: can the system call our systems and change state, or can it only generate text about them? Everything else is positioning.

The shift agentic AI describes is from single-turn assistance to multi-step execution. Instead of a person prompting, reading, deciding and prompting again, the system holds the goal and runs the loop itself. That is genuinely valuable where the loop is long and the steps are checkable, and it is mostly overhead where a single well-formed answer would have sufficed.

Codazz builds this in production — AI Agent Development.

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Agentic AI
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Common questions about agentic ai.

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Effectively yes, at different levels of abstraction. Agentic AI names the capability — systems that plan and act autonomously. An AI agent is a particular system built with that capability. Because vendors use both loosely, the reliable way to compare products is to ask whether the system can act on your systems, not which label it carries.

The capability is real and deployed in production; the labelling is inflated. Many products marketed as agentic are retrieval assistants that return text, which is useful but is not autonomy. The distinction is testable in a demo: ask the vendor to show the system changing a record in a live system and then show you the trace of how it decided to.

Related terms

AI Agent

An AI agent is a software system that pursues a goal by taking actions, not just producing text.

Multi-Agent System

A multi-agent system is an architecture where several specialised AI agents work on one goal, typically coordinated by a supervisor agent that decomposes the task, routes each part to the right specialist, and checks results before accepting them.

Agent Orchestration

Agent orchestration is the layer that decides which AI agent handles which part of a task, in what order, and what happens when one fails.

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