llms.txt explained: the one-hour setup that gets you cited by AI
llms.txt is a plain-text index that tells AI engines which pages are canonical and what each covers. It takes an hour and costs nothing. How to build one.
End-to-end operator-grade playbooks: the actual marketing systems we run on our own brands and our clients', documented step by step so you can copy them.
73 essays tagged playbook
llms.txt is a plain-text index that tells AI engines which pages are canonical and what each covers. It takes an hour and costs nothing. How to build one.
Digital PR is the only link-building tactic that survived Google’s spam updates — and it now earns AI citations too. Formats, pitching, and measurement.
The AI content engine we actually run: a human-gated pipeline of research, drafting, and editing agents that makes work good enough to rank and get cited.
Local search has three surfaces to win: the Map Pack, classic organic, and AI answers. The 2026 playbook — fundamentals that still rank, plus the AI layer.
AI Overviews pushed paid results down the page and changed which queries are worth bidding on. Where paid search still wins, and where it bleeds money.
One long-form piece should yield 10–15 distribution-ready fragments. The extraction playbook, plus the GEO layer that turns each fragment into a citation.
Testimonials and security badges still matter, but the AI-spam era added requirements. Specific dates, named operators, and dated original work now win.
Every brand voice sounds the same because everyone uses the same AI to write it. Specific points of view and named operators stand out more than ever.
Not a nostalgia tour. Eight campaigns from 2024–2026 that moved real numbers, what made them work, and what is portable to a smaller operator’s budget.