field guide
Learn how search and AI visibility connect in practice.
These practical guides explain the foundations, evidence, publishing, and measurement that improve visibility in Google, ChatGPT and Gemini.
What is AI SEO? A practical definition for modern search
Understand how traditional SEO, AI-assisted SEO, GEO, and answer-engine optimization fit together—and where the work actually changes.
Read the guideGenerative engine optimization: what GEO is and how it works
A grounded guide to GEO, AEO, AI visibility, and the work required to become a useful source for generative answers.
Read the guideHow to show up in Google AI Overviews without abandoning SEO
Build the technical, editorial, and evidence foundations that make a page useful in Google’s generated answers.
Read the guideHow to get cited by ChatGPT: build sources worth retrieving
Learn how to create accessible, specific, well-supported sources that ChatGPT can retrieve, understand, and cite.
Read the guideShopify SEO checklist: from catalog truth to collection authority
A mechanism-level checklist for Shopify stores: catalog fit, canonical and duplicate-content handling on filtered and paginated collections, how sitemap.xml actually works, app-script weight, theme structured data, collection architecture, and controlled publishing.
Read the guideSEO for startups: build a search asset before a content treadmill
A constrained decision framework for startup SEO: when search is actually ready to invest in, how technical debt compounds pre-product-market-fit, how to sequence content against one wedge, when paid beats organic, and how a small engineering team runs it through GitHub.
Read the guideAI visibility tools: what they measure and how to choose one
A reproducible eight-criterion method for evaluating any AI visibility tool, monitoring platform, or LLM optimization service — and how to tell whether you need observation or execution.
Read the guideHow to measure AI search visibility without an opaque score
Build a reproducible prompt panel, preserve cited sources, account for variance, and connect observations to published initiatives.
Read the guideEvidence-rich content: the difference between pages and sources
Turn internal expertise into pages that are specific, reviewable, useful to buyers, and easier for search and AI systems to understand.
Read the guideWhat is AEO? Answer engine optimization, defined
AEO stands for answer engine optimization: the work of getting an AI assistant to name your site when it answers a buyer's question. What it means, how it differs from SEO and GEO, and how to measure it.
Read the guideSEO vs GEO vs AEO: one operating map, not three strategies
SEO, GEO, and AEO are layers on the same site, not three vendors to hire. A practical map for when to spend on ranking, extractable answers, or retrieval and corroboration — and why monitoring is not a fourth line item.
Read the guideWhat is Managed AI Search?
A category definition for the work between an SEO agency, an AI visibility tracker, and a governed publishing platform.
Read the guideTechnical SEO checklist before you scale content
What has to be true of a site — robots and sitemap, canonicals, redirects, rendering, internal links, metadata, structured data, and indexation versus discovery — before adding content volume is worth the effort.
Read the guideNext.js SEO on Vercel and Cloudflare Pages
How to do SEO on a Next.js site deployed to Vercel or Cloudflare Pages with Git as the source of truth: the Metadata API, sitemap.ts and robots.ts, redirects, JSON-LD, rendering strategy, and preview-deployment review.
Read the guideSEO automation: what to automate, and what to never automate
A practical split of SEO work into what automates safely, what needs a human, and what should never run unattended — plus how to judge an automation tool before you trust it with your site.
Read the guideApproval-gated SEO: why the exact diff matters
Why an AI SEO tool has to show the precise before-and-after change before it publishes anything, what should never be pre-authorized, and how versioned approval, stale-change detection, staged rollout, verification, and rollback fit together.
Read the guideHow to read your free Foliora site snapshot
What a bounded public scan can establish deterministically, what remains a sample of the strategy shape, and what connected Foliora research adds next.
Read the guidepreview
Move from the guide to a bounded public snapshot.
See the connected service on AI search optimization.