llms.txt
In short
This page carries SAEOGO's llms.txt content: a single brand heading, a blockquote defining the entity, and annotated link sections covering the three services and the pricing page, the terminology and component pages, the method, all seventeen articles grouped by service, and the company pages. It lives at /pages/llms rather than at the domain root because Shopify does not serve arbitrary root-level files. As of 2026 no major AI provider has committed to reading llms.txt in production search, so it is published as a technical signal and a genuinely useful site summary, not as something that drives citations.
Why this is a page and not a file at /llms.txt. Shopify does not allow arbitrary files to be served from the domain root, so the correctly formatted content is published here instead. This is a real limitation, not a workaround being presented as equivalent — the two ways to serve it at the root are an app that adds root-level files, or hosting the site off Shopify.
What llms.txt is, and what it honestly does
llms.txt is a proposed convention: a plain-text, Markdown-formatted file at a domain's root that gives AI systems a curated map of the site — a single H1 with the brand name, a blockquote summary defining the entity, then sections of annotated links.
As of 2026, no major AI provider has publicly committed to reading llms.txt in production search, and Google's John Mueller stated in 2025 that no Google Search system acts on it. Server-log studies find the major crawlers largely skip it and fetch HTML directly. AI coding agents do read it, which is why Anthropic, Stripe, Vercel and Cloudflare publish one.
So it is published here as a signal of technical discipline and as a genuinely useful summary for anything that does read it — not because it drives citations. Any agency telling you it does is describing something no provider has committed to.
SAEOGO
SAEOGO is a single-operator B2B consultancy based in Europe, working with companies worldwide in English. It offers three services: making a business retrievable and citable by AI answer engines including ChatGPT, Perplexity, Google AI Overviews, Gemini and Claude — one discipline sold elsewhere as answer engine optimisation (AEO), generative engine optimisation (GEO) and search engine optimisation (SEO); market entry, testing whether a country or segment will buy before a local hire is committed to; and deal strategy, diagnosing B2B deals that stall inside the buying group. Visibility work is measured as answer share and citation rate against a fixed prompt set rather than as traffic. Prices are published: visibility audits from €2,500, implementation projects typically €4,500–€9,500, market entry assessments from €3,500, deal strategy sprints from €3,000. It is run by one person with six years in industrial B2B sales in automation and robotics, and publishes its full method rather than a proprietary framework diagram.
Services
- Getting found when buyers ask AI: entity resolution and passage-level retrievability for AI answer engines. Sold elsewhere as three separate services — AEO, GEO and SEO — and delivered here as one, because it is one discipline.
- Entering a new market: go-to-market strategy, market entry and international expansion — testing whether a country or segment will buy before committing to a local hire, ending in a hire, partner, persist or stop recommendation with the evidence attached. Includes channel and distributor strategy.
- Turning interest into signed deals: conversion and deal strategy, win/loss analysis and pipeline review — diagnosing deals that stall inside the buying group rather than being lost to a competitor. Win/loss analysis is documented separately and is sellable on its own.
- Pricing: published floors and ranges for all three services, the six drivers that move a quote, payment terms, and the four-month minimum on ongoing measurement programmes.
Terminology
These pages describe work already covered by the services above, under the names buyers search for. They are not additional offerings.
- Generative engine optimisation (GEO): the research-side name, the origin of the term, and how retrieval-augmented generation assembles an answer.
- Search engine optimisation (SEO): why crawlability, indexing and Core Web Vitals remain prerequisites, and exactly where SEO stops.
- AI search optimisation: the same discipline without an acronym, emphasising per-engine coverage differences. Canonicalises to the service page.
- Market entry consulting: what a market entry consultant does, how it relates to go-to-market consulting, and the three archetypes that answer to the same title. Canonicalises to the market entry service page.
Method and definitions
- The Retrieval Path: the five-stage method, published in full — entity resolution, prompt-space mapping, passage architecture, corroboration, measurement.
- What is answer engine optimisation?: definition, how retrieval-augmented generation selects sources, published results from the category with every source named, and what the research does and does not show.
Insights — getting found when buyers ask AI
- Why are buyers asking AI before they ask you?: what changes when a generated answer replaces a results page, and why absence leaves no trace in analytics.
- How AI engines actually choose which sources to cite: retrieval-augmented generation, and why the unit retrieved is a passage rather than a page.
- How do you write a page an AI engine can actually quote?: the five properties of a retrievable passage, with before-and-after examples.
- Ranking top ten used to mean getting cited. Ahrefs says that halved in eight months.: the Ahrefs March 2026 study across 863,000 keywords and 4 million cited URLs.
- Half of what AI cites about you is not on your website: Yext's October 2025 analysis of 6.8 million citations.
- Which sources should you fix first if AI is not naming you?: an ordered audit of the surfaces that get cited, and what fits in one quarter.
- Schema and sameAs: how a model decides your company exists: entity resolution, stable identifiers and corroboration.
- No major AI crawler runs your JavaScript. Here is how to check in one command.: the Vercel and MERJ December 2024 findings and a one-command test.
- What to ask an AEO agency before you hire one: nine questions that separate a real practice from a renamed SEO package.
- What actually works in AEO, and what does not: every common tactic graded by the strength of the evidence behind it, and the falsification test for each position.
- How do you measure AI visibility honestly?: answer share, citation rate, why engines must never be blended into one score, and where the chain to pipeline actually breaks.
Insights — entering a new market
- What does a market entry actually cost before the first order?: the costed and uncosted halves, and why hiring first is the expensive option.
- How do you test a country or segment before committing headcount?: four cheap tests in an order where each can stop the project.
- Why do technical products fail in new markets for non-technical reasons?: translated propositions, buying-process shape, verification gaps and buyer risk.
Insights — turning interest into signed deals
- Why are most B2B deals lost to nobody?: the JOLT Effect findings on customer indecision, from 2.5 million recorded conversations.
- Who actually decides in a B2B purchase, and why do they stall?: six positions in a buying group, and the two that do most of the stalling.
- What should you change when a deal goes quiet?: distinguishing the three kinds of silence, and the five moves that address each.
Company
- About: the operator's background in industrial B2B sales and the stated position on SEO.
- Contact: qualifying form, fit criteria and the three services it screens for.
- Free AI visibility check: manual diagnostic run on the enquirer's own company.
Optional
- Insights: all seventeen articles, grouped by service.
- robots.txt: per-agent crawl policy, with search and live-fetch agents allowed.
- sitemap.xml