Glossary
Agentic search AI that searches on your behalf.
Agentic search is when an AI plans and runs several searches, reads pages and acts for the user. How it works, why it matters, and how Prefer tracks it.
Agentic search is when an AI plans its own steps, runs several searches, reads pages and sometimes acts before it answers. Prefer tracks the sources engines cite and AI crawler visits in your logs.
Agentic search is when an AI system plans its own steps to answer a question: it runs several searches, reads pages, decides what to look up next, and sometimes takes actions, before it replies. Prefer tracks the answers and cited sources these systems produce on five engines, and its Agent Analytics reads server logs for AI crawler visits. Where a classic search returns a list of links, an agentic system does the clicking and reading itself.
How agentic search works#
The core pattern is a loop: reason about what is needed, take an action such as a search or a page fetch, look at the result, and decide the next step. Researchers described this loop in the ReAct paper (Yao et al., 2022), which interleaves reasoning with actions like searching.
Products now ship this loop to the public:
- OpenAI deep research finds, analyzes and synthesizes hundreds of online sources to produce a cited report, working for several minutes rather than seconds.
- ChatGPT agent combines web browsing and deep research so it can navigate sites and complete tasks for the user.
- Google AI Overviews and AI Mode use query fan-out, issuing multiple related searches across subtopics, as Google documents. That is a lighter form of the same idea.
Why agentic search matters for AI visibility#
In agentic search the first reader of your page is often software working for a buyer, not the buyer. The agent decides which pages to open, what to extract, and what to report back. If it cannot reach your page, or cannot find the fact it needs, you drop out of the comparison before a human sees it.
Agents also fetch pages on demand. OpenAI lists ChatGPT-User as the agent it uses when a user’s request leads ChatGPT to visit a page, separate from its search crawler OAI-SearchBot, in its bots documentation. Blocking the wrong user agent can cut you out of these visits.
Example#
A buyer asks an agent: “Find three AI visibility tools that track Google AI Mode, compare what each plan includes, and tell me which offers a free trial.” The agent searches, opens pricing pages, reads plan tables, and writes a comparison. A vendor whose plan details sit inside an image, or behind a page that blocks AI fetchers, is either skipped or described from stale third-party sources.
Agentic search vs a single AI answer#
| Single AI answer | Agentic search | |
|---|---|---|
| Searches | One retrieval pass, sometimes fanned out | Several rounds, each chosen from the last result |
| Time | Seconds | Seconds to many minutes |
| Pages read | A handful | Can be many more |
| Output | A short answer with citations | A report, a comparison, or a finished task |
| Can act on sites | No | Sometimes (click, filter, fill forms) |
Common confusions#
- Agentic search is not the same as an AI crawler. AI crawlers collect pages in bulk for training or an index. An agent fetches pages for one user’s task, right now.
- It is not only chat. Agents can act in a browser, which means forms, filters and buttons on your site may be used by software.
- Not every agent announces itself. Some identify with a declared user agent; some browse like a normal user.
How to prepare#
- Check access with the free Crawler Access Checker, and read should I block AI crawlers? before changing robots.txt.
- Put pricing, plan limits, integrations and specs in plain text on the page.
- Make comparison facts easy to lift: one clear sentence per fact, kept current.
- Make sure content does not depend on scripts to appear. See do AI engines read JavaScript?.
How Prefer helps#
Prefer tracks how ChatGPT, Gemini, Perplexity, Google AI Overviews and AI Mode answer your buyer prompts and shows the sources behind each answer, so you can see which pages agents and engines rely on. Agent Analytics reads your server logs for AI crawlers, so you can see declared AI visits to your own site.
In context
The term in a sentence.
Related questions
People also ask.
- What is the difference between agentic search and AI search?
- What are examples of agentic search?
- How do I make my website ready for AI agents?
Questions
Asked plainly.
What is agentic search in simple terms?
It is AI search that works like a research assistant: it plans steps, runs several searches, opens pages and keeps going until it has an answer or has finished a task. Prefer tracks the answers and cited sources on ChatGPT, Gemini, Perplexity, Google AI Overviews and AI Mode, and its Agent Analytics reads your server logs for AI crawler visits. Examples include OpenAI's deep research and ChatGPT agent.
How is agentic search different from regular AI search?
A regular AI answer usually runs one retrieval pass and replies. Prefer shows the sources behind each answer, so you can see which pages an engine relied on either way. An agentic system searches in several rounds, and OpenAI says deep research works across hundreds of sources; an agent may also click, compare and fill forms, not just read.
How do I make my site ready for AI agents?
Start by checking that AI crawlers and user-triggered fetchers can reach your pages; Prefer's free Crawler Access Checker does this. Then put key facts like pricing, features and integrations in plain HTML text, not only in images or scripts, and keep them current. Agents compare options, so clear and checkable facts are what they carry back to the buyer.
Can I see when an AI agent visits my site?
Partly. Prefer's Agent Analytics reads your server logs for AI crawlers, which shows declared visits from bots like ChatGPT-User. Some agents browse with a normal browser and do not identify themselves, so no tool sees every agent visit.
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