AI Agent
An AI system that plans and executes multi-step tasks autonomously — researching, calling tools, and acting toward a goal rather than just answering.
An AI agent is much more than a system that simply answers a single prompt. It is a system that can plan and carry out complex, multi-step tasks on its own. Instead of just responding, an agent acts. It breaks a large goal into smaller sub-tasks, runs searches, analyzes the results, identifies any missing information, and refines its approach until the job is done.
Take a question like, "What services does a specific company offer?" A research agent won't just run one search. It uses a process called query fan-out to generate multiple, targeted queries. It enters a loop of planning, searching, assessing, and refining until it has a complete answer.
This shift changes the game for search engine optimization. AI agents are now finding information by issuing dozens of derived queries and consuming web content through structured interfaces. This is why new standards like WebMCP, and AI assistants like Amazon's Rufus, are becoming so critical. They define how websites must structure their information so these autonomous agents can easily find, understand, and use it.
An AI agent is a system that plans and carries out multi-step tasks on its own — breaking a goal into sub-tasks, running searches or tools, reading results, and iterating — rather than simply answering a single prompt. It's the difference between a system that responds and one that acts.
Our multi-step research agent, built on Google's query fan-out inside an agentic framework, shows the pattern: given "what services does DEJAN AI offer?", it generates several targeted queries, runs a research loop, identifies knowledge gaps, and issues follow-up searches until it can answer. That loop of plan → search → assess → refine is the core of agentic behaviour.
For AI SEO, agents change the game because they issue many derived queries via query fan-out and consume content through structured interfaces. This is exactly why standards like WebMCP and assistants like Amazon's Rufus matter for how sites expose themselves to agents.