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SEO Automation: what to hand to an agent and what never to
Agents are good at the mechanical layer of search work. Strategy, tone and what you will not publish stay with a person. This course draws that line.
Routine search work is data: crawls, status codes, clusters, link lists. Agents can do that. Agents can propose priorities and draft copy, but a responsible person must review brand fit, evidence and the risk of changing a page that already converts. Define that decision boundary before automating publication.
Ten modules in the player. Practice on the site: SEO and growth.
For whom
- Practising SEO and in-house marketers who already run a crawl and a keyword set
- Operators who want engineering patterns, not a promise that a model will rank the site
- Too early if you still need a first lesson on snippets and title tags
Modules
- SEO as an agent task
- The agent stack for SEO
- Technical site audit
- Keyword Intelligence
- The content agent
- SERP monitoring and links
- Pipeline orchestration
- Evaluation and iteration
- AI search and GEO
- Frontier models in SEO
After the course
- Split a search workflow into agent-sized steps
- Assemble a stack: data sources, model, output
- Build a technical-audit agent that ranks issues by harm
- Automate keyword clustering and intent mapping
- Run a multi-stage content pipeline instead of one giant prompt
- Watch SERP and backlink movement with an agent, not a weekly screenshot
- Orchestrate the pipeline with a human still on the gate
- Measure whether the automation is saving hours, not just calling APIs
- Adapt the strategy when generative answers sit above the blue links