An AI agent is a software system that uses artificial intelligence — usually a large language model — to understand a situation, decide what to do, and take action toward a goal with little or no step-by-step human direction, often calling external tools and APIs along the way.
Most agents share four moving pieces: a reasoning model that plans; memory that carries context between steps; a set of tools — search, code execution, databases, APIs — it can invoke; and a goal that tells it when the job is done. What separates an agent from a plain chatbot is the loop: it acts, observes the result, and decides the next step instead of answering once and stopping.
Agents already sit behind features like agentic search, where the system runs its own chain of queries before answering. Picture a technical-SEO agent pointed at a domain: it crawls the sitemap, flags pages returning 5xx errors, checks Core Web Vitals, notices three templates missing structured data, and hands back a prioritised fix list — work that used to mean an afternoon across five tools.
To reach outside data and services safely, agents increasingly rely on the Model Context Protocol, a shared standard for tool access.
No. A chatbot responds to messages; an agent pursues a goal, taking multiple actions and course-correcting on its own until it reaches it.
They handle repetitive checks and data gathering well, but strategy, judgement, and brand nuance still need people. Our AI SEO services pair the two.