Episode Description
Your pricing page is not what the model is reading. Malte Landwehr of Peec AI wrote his bachelor thesis on PageRank, ran in-house SEO at Europe’s largest price comparison site, and now measures brand visibility inside answer engines for a living. His argument: LLMs resolve to consensus, so five stale Reddit threads and an old G2 profile will happily overrule the price you changed last week.
Key takeaways
- One canonical page cannot create consensus. The same fact has to be findable in enough places that agreeing with you is the cheapest option.
- He is against a separate .md URL and for serving markdown by user agent. Same URL, different response. He also calls it cloaking, out loud, and says he would not do it to Google.
- Fan-out queries are a placement map, not a keyword list. Target the cited pages that already name several of your competitors.
- Watch the words the model adds that you never prompted. The pattern rotates; the method is to keep watching, not to memorise this month’s word.
- Two live manipulation surfaces, both already measurable. Hallucinated domains inside fan-outs, and paid advertorials being treated as grounding sources.
- Why consensus beats your canonical page
- Against a second URL, for serving by user agent
- Fan-outs as a placement map
- Manipulation surfaces and AI-content guardrails
- Chapters and timestamps
- People, ideas and sources mentioned
- Questions this episode answers
- Go deeper
If you only talk about your pricing on your pricing website and then you change your pricing and then there are five Reddit threads and two reviews on random blogs that still talk about your old pricing, ChatGPT will answer with your old pricing if a user asks about it.
— Malte Landwehr
The remedy is distribution of a single fact rather than optimisation of a single page. G2, Yelp, your own footer, social profiles, press release boilerplate, the help centre, the product docs. The goal is to make agreeing with you cheap to verify.
Against a second URL, for serving by user agentLLMs are looking for fresh content. So refreshing content, updating it, and then also making sure there’s a machine readable last updated date.
— Malte Landwehr
I would not do that. As an SEO, I don’t want the same content on two different URLs. It wastes crawl resources. If humans land on the .md version, there are no links to click. There’s nothing for them to do. It’s a horrible experience. What can make sense is that my server makes a decision. When a human comes, I serve them the HTML version. And when a LLM crawler comes, I serve them the markdown file under the same URL.
— Malte Landwehr
He does not pretend this is clean. He names it as a form of cloaking and says he would run it for LLM crawlers and not for Google. He also supplies the fix for the two-URL version if you insist on it: set the canonical in the HTTP header, because a text file has no HTML head to put one in.
Fan-outs as a placement mapThey also inject ads specifically for the LLM. And that is again going very much in direction of cloaking.
— Malte Landwehr
I would look at the sources both on the URL and on the domain level and see for these existing URLs, can I get my brand mentioned there if I’m not mentioned yet? And the trick is often to look for the ones that have multiple of your competitors already mentioned because then it’s often reasonable to contact and say, hey, can I also be added?
— Malte Landwehr
The corollary saves you a quarter of wasted outreach: a page that is an interview with a competitor’s chief executive is unwinnable, so do not spend anything on it. Sort the cited sources by how many rivals they already list, and work down.
The terms you did not prompt
Especially terms that the LLMs are adding that were not part of the prompt... A few days ago, ChatGPT started adding the term official to a lot of fan out queries. So right now I recommend everybody to put the word official in the footer of their website.
— Malte Landwehr
Cheap, testable, and explicitly time-bound. He is clear these patterns rotate, which is the actual instruction: watch the added terms, do not enshrine one of them.
Manipulation surfaces and AI-content guardrailsThere are some prompts I’m tracking where it’s in the range of 2 or 3 % of the prompts have a hallucinated domain. In these cases, the domain is just parked. But if I was an evil person, I would now register this domain or buy it and put up some completely negative content about the brand that supposedly owns it.
— Malte Landwehr
He raises a second surface alongside it: in an insurance prompt set he monitors, roughly 2% of the sources an LLM leans on are paid advertorials. Humans skip advertorials. Models quote them.
When AI content is worth publishing
If you can create it with a prompt, why would ChatGPT or OpenAI or Google crawl index and rank it and use it? They could just use that prompt on their own.
— Malte Landwehr
His acceptable cases are all data-backed: summarising real reviews on a product page, or writing up structured data nobody else holds. And if you want to know whether your own output is detectable, he names the four measures to run over it.
Perplexity... compression rate... jacquard and the other is cosine [similarity]. And if you use these four measures you will often find that there are many, many very easy to detect footprints in AI written content.
— Malte Landwehr
Benchmark all four on a corpus of your human-written text, run them again on the AI-written batch, and compare. He notes you can have Claude write the Python and that you do not need the maths to read the result.
Chapters| Time | What happens |
|---|---|
| 00:00 | Twenty years of SEO, and a PageRank thesis |
| 01:48 | Is PageRank still running inside Google? |
| 03:37 | Bot crawling is not the reasonable surfer |
| 05:57 | Serving markdown to LLM crawlers, and why a parallel .md URL is not the way |
| 08:57 | Time magazine, and ads only the model sees |
| 12:55 | Hallucinated domains in ChatGPT fan-outs |
| 14:23 | Advertorials used as grounding sources |
| 16:55 | Consensus: stale threads beat your pricing page |
| 19:43 | The five-step query fan-out method |
| 24:21 | Cannibalisation loosens up |
| 29:34 | Perplexity, compression rate, Jaccard and cosine |
| 38:02 | MCP turns systems of record into databases |
| Entity | What it is |
|---|---|
| Peec AI | Software for measuring and improving visibility inside LLM answer engines |
| Malte Landwehr | Twenty-plus years in SEO. Agency co-founder, product lead at Searchmetrics, five years in-house at Europe's largest price comparison site |
| Query fan-out | The expansion of one prompt into many underlying searches, including terms the user never typed |
| Time Magazine | Cited as serving markdown site-wide and injecting ads into the model-facing version |
| Perplexity, compression rate, Jaccard, cosine similarity | The four measures he recommends for finding AI-content footprints in your own writing |
| Hallucinated domains | Parked domains appearing inside fan-out site: queries, and an open manipulation surface |
- Should I publish a .md version of every page for LLMs?
- How do I set a canonical on a markdown file that has no HTML head?
- Why does ChatGPT give an outdated fact about my company?
- What do I actually do with a list of query fan-outs?
- How can I tell whether my AI-written content is detectable?
- Are advertorials being used as grounding sources by LLMs?
- Is cannibalisation still a problem in the era of AI search?
Every link above goes somewhere different. These are the ones not already mentioned above.
- the markdown argument he is answering here, made by an operator who publishes the second URL on purpose and reports his crawl telemetry for it.
- a sceptic on the same question, arguing from enterprise scale, where the cost is not authoring the file but owning it across a million pages.
- a text-only copy of this episode built for pasting into a model, with each claim tied to the speaker who made it.
peec.ai, and he is most responsive on LinkedIn.
Cite this episodeLandwehr, Malte. Interviewed by Jeremy Rivera. “Consensus, Query Fan-Outs and AI Content Guardrails.” The Unscripted SEO Podcast, 10 August 2026. https://unscriptedseo.com/episode-recap-malte-landwehr-of-peec-ai-on-consensus-query-fan-outs-and-ai-content-guardrails/