An ordinary search is a question and a set of results. Agentic search goes much further: the system thinks about the question itself, splits it into sub-questions, consults several sources and independently composes a complete answer. It is searching that reasons.
What is agentic search?
Agentic search is a form of search in which an AI works like a kind of researcher. Instead of running one query, it breaks a complex question into steps, performs multiple searches, assesses the findings and combines everything into a well-founded answer.
How does this differ from ordinary search?
With ordinary search, you do the thinking: you formulate sub-questions, click through, compare and conclude yourself. With agentic search, the AI takes over that thinking. It decides which sub-questions are needed, which sources it consults and how it combines the pieces.
An example
Someone asks: I want to renovate, find a contractor and know which permits I need. An agentic system splits this up: first look up the permits, then find suitable contractors, then combine it all. At each sub-step it consults sources. Your content can be one of those sources at each step, provided it is relevant and findable.
What does this mean for you?
Agentic search rewards content that answers sub-questions clearly. The better your pages cover separate, concrete questions, the more often you surface as a source in such a multi-step search. It strengthens the importance of in-depth, well-structured content around a topic.
