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AI for the Web

AI Agents

What AI agents are, how agentic workflows work, and practical agent use cases for SEO, marketing, content and websites.

What is an AI agent?

An AI agent is a system where a language model is given a goal, a set of tools (search, a browser, a code runner, an API) and the ability to decide which tool to use next. Instead of answering once, it loops: plan → act → observe the result → decide the next step, until the goal is met or it needs a human.

AI agents vs chatbots

A chatbot answers the message in front of it. An agent takes actions across multiple steps and systems. The practical difference: a chatbot can draft a meta description; an agent can crawl your site, find pages missing meta descriptions, draft them and open a review task — if you give it those tools and permissions.

Agentic workflows

Most reliable business automations are 'agentic workflows': a fixed pipeline you design (trigger → steps → approval → output) where AI handles specific judgment steps. They are easier to test, cheaper and safer than fully autonomous agents. Start there, and add autonomy only where the error cost is low.

Agents for SEO, marketing, content and websites

Good starter use cases are narrow and reviewable: auditing pages for missing metadata, clustering keywords, drafting content briefs, summarising analytics weekly, triaging support emails, or monitoring broken links. Keep a human approval step before anything is published, sent or spent.

Guardrails that matter

Give agents the minimum permissions they need, log every action, cap spend and rate, require approval for irreversible actions, and never let an agent publish unreviewed content. Treat anything an agent reads from the web as untrusted input.

Guides

AI Agents guides

Directory

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