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Agentic AI

A system that acts instead of only answering.

The term is currently stuck onto anything with an AI interface. This page draws the line and says where the difference begins in practice.

Romana Hieß holding a small robot in her palm, Florian Hieß holding its remote control

Definition

Where the line runs.

Agentic AI means systems that take a goal, plan several steps for it on their own, call tools and check the result before they answer. The difference from a chatbot lies not in language ability but in the ability to act.

A language model on its own predicts text. An agentic system is allowed to do something in between: start a search, fetch a page, run a calculation, write a record. And it is allowed to decide how often it repeats that.

The second difference is the feedback loop. When an intermediate result is no good, an agentic system starts again. That loop is what makes it useful and hard to predict at the same time.

Stages

Four degrees of independence.

Stages ascending
  • Answer model answers from training knowledge, no access outward
  • Retrieval model fetches sources and answers from them, one step
  • Sequence model plans several steps and calls tools
  • Action model carries out operations with consequences, such as a booking

For visibility the second stage is the decisive one. From there your website becomes a source instead of a memory.

Relevance

Why this counts for your website.

As long as a system answers only from training, your website is a memory from the day before yesterday. Once it retrieves, your website is a source from today. That is the difference between a number you cannot influence and one you can work on.

From the third stage a second requirement arrives. A system planning several steps discards poor sources along the way. So it decides not only whether it finds you but whether it keeps using you.

The fourth stage changes the demands on data. If a system is to buy or book, price, availability and terms have to be machine readable and correct. More under agentic commerce.

Common questions

About agentic systems.

Is every chatbot an agent?
No. A chatbot answers. An agent plans, calls tools and checks afterwards. Most offerings with the word agent in the name are chatbots with a connection.
What does autonomous mean here?
That the intermediate steps are not prescribed. The human sets the goal, the system picks the route. Full autonomy without oversight is rare and rarely sensible.
How does this relate to agentic search?
Agentic search is one application of it: a system that researches a question on its own. The overview sits under agentic search.
Is agentic AI the same as AGI?
No, and the terms get mixed up readily. Agentic AI describes an arrangement of model, tools and loop, not a level of intelligence.
What risks come with the action stage?
Mistakes with consequences. A wrong text can be corrected, a wrong order costs money. That is why approval steps are standard for anything touching money or contracts.
Does a small company need this?
As a provider rarely. As an affected party very much so: your customers use such systems whether or not you deploy any yourself.
How do I tell whether a system retrieves or answers from training?
From the citations and from currency. Ask about information newer than the model and you see immediately whether it fetches.
What is a tool call?
A function the model is allowed to trigger: search, retrieval, calculation, database access. The standard for it is called MCP.
Can several agents work together?
Yes, that is a common arrangement: a planning agent distributes subtasks to specialised ones. It raises capability and the number of failure points in equal measure.
How fast does this field move?
Fast in the tooling, slowly in the fundamentals. The requirement that information be retrievable, unambiguous and correct held from day one and will stay.

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