- 2026
- 19 Jul 2026 Why visibility in one AI engine says little about the next: one month of retrieval-to-citation data from eight B2B projects
I spent a month measuring how often ChatGPT, Perplexity and Google AI Overview actually cite a source they retrieved. Across eight B2B projects the pattern holds: three engines, three near-separate source pools. AI visibility is three targets, not one.
- 5 Jul 2026 The prompt as a Lego figure: why AI visibility runs on entities, not keywords
AI systems break every prompt into several sub-queries and search for answers in parallel. Whoever optimizes only for the starting term is absent from the majority of these runs. Why entity mapping replaces the foundation that keyword thinking once was.
- 3 Jul 2026 llms.txt: what the file does, what Google says about it — and when you should create one
The complete guide to llms.txt: origin, structure, Google's official position, what the data shows about its use and who the file really pays off for — with my own analysis of 2,041 source domains, an example and practical steps.
- 29 Jun 2026 How ChatGPT chooses its sources — and the GEO levers that follow
A look at the traffic beneath the answer shows how ChatGPT gathers, selects and cites sources. What of it is actually evidenced, and where to act for your AI visibility.
- 25 Jun 2026 Retrieved but not cited: the most valuable gap in your AI visibility
When an AI model retrieves your page but does not cite it, that is your biggest opportunity. How to measure the gap, prioritize it, and track it over time.
- 2025
- 21 Mar 2025 The relevance of LLM visibility for online shops
Buying decisions are shifting into AI answers. Why LLM visibility becomes a channel of its own for online shops and how to occupy it.