The complete AI SEO playbook, built by Trace Cohen at Value Add VC.com, delivers a proven system that grew a site from 604K to 4.6M monthly impressions in three months, grounded in real‑world testing and avoiding generic prompts.

It combines AI agent orchestration using multi‑model pipelines (Opus/Fable for planning, Sonnet for writing, Haiku for grunt work) with a 5‑format content rotation, voice training, and anti‑AI fingerprint detection, running up to three concurrent agents for efficiency. A weekly GSC feedback loop automates title rewrite candidates, cannibalization checks, query gap mining, and striking‑distance optimization, feeding diagnostic scripts that surface issues for AI‑driven fixes.

The playbook includes 14 diagnostic scripts and 9 battle‑tested configs covering safety guards, agent orchestration, quality gates, and anti‑AI detection, plus structured data schemas and CI automation. Scripts such as rewrite‑candidates, template‑detector, cannibalization‑detector, and weekly‑report generate actionable insights, while configuration files define format rotation, publish gates, keyword anticipation rules, and enforce repo locks and build cost control.

Continuous integration pipelines run weekly reports, triage findings, and apply rewrites, merges, refreshes, or deletions, creating a self‑healing loop where improved rankings generate better GSC data, making the system smarter each week, and isolates content writers from git while keeping deployment expenses low.