The hands-on, prompt-driven side of AI keyword research — how to actually run expansion, intent labelling, and clustering in an LLM. The strategy lives in the canonical Research guide; this is the execution.

Using AI to analyze, refresh, and optimize existing pages and raw drafts — semantic gap analysis, SERP-feature alignment, and readability — with the human review that adds real experience and protects E-E-A-T.

How to run coordinated, multi-channel content campaigns with AI — aligning tools to goals and funnel stages, filling gaps with analytics, governing the work through a calendar, and measuring impact — without letting automation flatten the brand.

How SEO practitioners with little coding background can build custom tools with an AI coding assistant — treating AI as a copilot, growing a project from script to app, and prompting well enough to ship something reliable.

A copy-and-adapt library of task-oriented prompts for common SEO work — keyword research, on-page and content, technical SEO, and link building — designed to produce reliable output from Claude, ChatGPT, or Gemini.