▶  AI Search · S6E133 · 53:27 · August 24, 2026

What Fan-Out Queries Reveal About AI Search with Malte Landwehr

Guest: Malte Landwehr, CMO/Chief Product Officer at Peec AI | Ex-Idealo
Hosts: Jon Clark & Joe DeVita

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about this episode

Malte Landwehr is CPO and CMO at Peec AI, and he spent two decades in search before this — VP Product at Searchmetrics, then VP SEO at idealo, running enterprise SEO across roughly 130 million pages. His core argument: LLMs reward consensus. If your website, your founder’s LinkedIn, your press release footer, and your G2 profile describe you three different ways, the model has nothing consistent to trust. Describing yourself identically everywhere you have control is the highest-leverage AI visibility work most brands still haven’t done. He also gets specific about what doesn’t hold up. Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) have picked up tactics that don’t survive testing — schema markup can’t carry facts your body copy leaves out, duplicate .md versions of pages went uncited across hundreds of thousands of chats, and llms.txt is guidance for AI agents rather than a visibility lever. What works is duller: declarative sentences, concrete numbers, and content that answers what the fan-outs are already asking about you.

In This Episode

  • Why LLMs look for consensus — and what happens when your site, LinkedIn, and G2 profile don’t match
  • How should you do keyword research when fan-out queries add terms you never wrote?
  • What ChatGPT’s site: fan-outs reveal about whether OpenAI has its own link graph
  • Does schema markup still influence AI citations? What the testing actually shows
  • Markdown copies, .md URLs, and llms.txt — where each one belongs
  • Product feeds, Yelp/Resy/OpenTable, and how local visibility works inside ChatGPT
  • Why the biggest lever is usually the wrong first project

A practitioner’s map of what to change, what to measure, and what to ignore in AI search right now.

Connect with Malte Landwehr

Peec AI
Malte’s Website
Malte on LinkedIn
Malte on X

 

Chapters

  • 0:00

    Intro

  • 1:44

    Welcome and Malte’s background

  • 4:35

    Has AI changed shopping behavior?

  • 6:39

    Markdown for AI crawlers on comparison sites

  • 9:40

    Describing your brand consistently for LLMs

  • 13:26

    Can LLM reasoning ever be explainable?

  • 16:16

    Do links still matter in AI retrieval?

  • 18:02

    Fan-out site: searches and expired domains

  • 20:38

    Brand mentions or clean data first?

  • 24:31

    Could anything replace PageRank?

  • 28:01

    Keyword research in the age of fan-outs

  • 32:07

    Does formatting affect retrieval?

  • 34:28

    llms.txt: agents versus AI search

  • 37:12

    What schema markup can and can’t do

  • 40:12

    Schema conflicts and JavaScript rendering

  • 42:40

    Product feeds and local visibility in ChatGPT

  • 46:48

    Risks of chasing platform partnerships

  • 49:30

    An ads.txt for brand facts?

  • 50:43

    Rapid fire