GEO: Be Visible When the AI Answers

01 — Approach

How language models cite brands

ChatGPT, Perplexity, Gemini and Claude answer questions by retrieving sources, weighing them and summarizing. What gets cited is what is clearly worded, well supported and easy for a machine to understand. Vague marketing prose falls through that grid, while precise statements with numbers, definitions and clean structure stick. That is exactly what we work on: we make your content the most convenient source a model can find on your topic.

We do not fiddle with prompts on a hunch. We take what we have learned about search systems since 2006 and carry it over to the new generation of answer engines. The mechanics are different, the craft behind them surprisingly familiar.

02 — Current

What is changing in AI search right now

In 2026 GEO is visibly professionalizing. llms.txt, a kind of robots.txt for language models, is establishing itself as a curated index of a domain's most important content in machine-friendly Markdown. At the same time it is becoming clear that AI engines weight freshness heavily: a guide from 2024 without updates loses to a well-maintained 2026 article on the same topic.

The bigger shift is still ahead: a growing share of search queries will soon not be typed by humans at all, but executed by AI agents that research, compare and shop on someone's behalf. These agents read websites programmatically and lean on llms.txt, structured data and clean content. Whoever builds for them today is tomorrow's source.

03 — Discipline

Quotable content structure

We rebuild content so it can be cited: one clear statement per paragraph, questions as headings, definitions and numbers where a model expects them, FAQ schema as a structured complement. Part of this is describing your brand consistently, on your own site as well as in the directories and industry articles from which models assemble their picture of you.

If you want to know how AI systems describe your brand today: we check that across the relevant engines in the free first call, just write to us.

04 — Discipline

llms.txt and the technical base

On the technical side we make sure AI crawlers can reach your content at all and classify it correctly: llms.txt with a curated table of contents, deliberate permissions for GPTBot, PerplexityBot and friends in robots.txt, structured data for organization, products and FAQs, clean heading hierarchies instead of pure design markup. None of this is rocket science, but it has to be maintained consistently across the whole site.

05 — Measurement

Monitoring your AI mentions

Without measurement, GEO stays a belief system. We regularly test with defined question sets whether and how ChatGPT, Perplexity, Gemini and Claude mention your brand, which sources they cite while doing so and whether the statements are accurate. Add referral traffic from AI answers and the crawler hits in your server logs. Together that produces a trend line that lets you prove progress instead of claiming it.

06 — Context

GEO does not replace SEO, it builds on it

The sources cited in AI answers come largely from the classic top rankings. If you are invisible organically, language models will rarely find you either. That is why we never run GEO in isolation but on the foundation of our SEO work, embedded in the channel mix of the performance overview, where paid channels like Google Ads pay into the same goals. We publish deeper articles on GEO, llms.txt and AI search on an ongoing basis in the blog.