§ 00 — Guides
AI Visibility Guides
Working notes on how AI systems retrieve, resolve, and select sources — written for people implementing the work rather than describing it. Each guide links back to the underlying frameworks.
§ 01 — Foundations
What AI visibility is, how AI search works, and the vocabulary the field uses.
What Is AI Visibility?
AI visibility is whether AI systems retrieve, resolve, and select your content when composing answers. The three conditions, how it differs from SEO, and how to measure it.
definitional · 8 min ·
RAG Explained in Plain English
What Retrieval-Augmented Generation actually is, how the four-stage pipeline works, and why RAG is foundational for AI visibility and authority systems.
definitional · 10 min ·
§ 02 — Getting Cited
Practical work for being retrieved, named, and linked inside generated answers.
How to Rank in ChatGPT
You do not rank in ChatGPT, you get retrieved and selected. Crawler access, self-contained passages, entity resolution, and how to measure the result.
how-to · 9 min ·
§ 04 — Implementation
Files, markup, and identity work that makes a site machine-readable.
llms.txt: What It Is and Whether It Does Anything
llms.txt is a proposed markdown index for AI systems. What the format is, what is actually verified about adoption, and whether to publish one.
definitional · 7 min ·
§ 06 — Strategy
Market formation, capital stacks, and the infrastructure economics upstream of AI visibility.
AI for SMBs in 2026: Build Workflows, Not Tool Stacks
A practical operating guide for turning AI experimentation into measurable business leverage. Start with workflows, not tool stacks.
how-to · 18 min ·
Compute Capital
AI compute is becoming an input commodity, infrastructure asset, collateral base, and eventually a financial market. A strategic guide to the capital stack, compute treasury, and the benchmark problem.
definitional · 11 min ·
§ 07 — Agents
Memory, MCP connectors, and the practical tooling that lets agents work across applications.
5 Questions About AI Memory & Agents — Answered
A practical reference on Claude auto-memory, token costs, vector search vs. grep, Cowork success rates, and MCP connectors — sourced from 2026 research and official docs.
diagnostic · 9 min ·
§ 08 — Essays
Founder psychology, decision-making, and long-form notes from the operator layer.
Do Not Confuse Relief with Truth
A philosophical essay on why relief is not a verdict, why withdrawal is underrated, and how founders can build the habit of separating comforting narratives from accurate conclusions.
definitional · 7 min ·
Coming soon — 21 in progress
- Generative Engine Optimization (GEO), Explained
- How AI Search Actually Works: Retrieval, Ranking, and Selection
- Is SEO Dead in 2026?
- AI Search and Visibility Glossary
- How to Get Cited by ChatGPT
- How to Show Up in Google AI Overviews
- How to Get Recommended by Perplexity
- How to Get Cited by Claude
- How to Format Content So AI Systems Cite It
- GEO vs SEO: What Actually Changed
- AEO vs GEO vs SEO
- ChatGPT vs Google for Discovery
- AI Visibility Tools Compared
- Schema Markup for AI Search
- Entity SEO: Building a Machine-Readable Identity
- Should You Block AI Crawlers in robots.txt?
- Structured Data Checklist for AI Visibility
- Why Your Traffic Dropped After AI Overviews
- How to Track ChatGPT Referral Traffic
- How to Measure AI Visibility
- Zero-Click Search: What It Means for Publishers
8 published / 29 planned