the blog.

what we find when we measure AI answers. it starts with the 100-audit report and its chapters — cases are on their way.

researchfeatured n = 100
87%
known to AI · never recommended
100 GEO audits: why AI knows your brand but never recommends it

the five mistakes repeating in 87–100% of audits, the myths the market still pays for, and the state of AI visibility by niche.

researchchapter 02 n = 100
~100%
audits with no entity anchor
100 audits, 5 mistakes on repeat

the five failures found in 50–100% of audits: no entity anchor, no schema, anonymous content, no llms.txt, nothing worth quoting.

researchchapter 03 n = 100
0/5
market beliefs left standing
5 beliefs. 100 audits. 0 survivors.

no correlation between organic traffic and entering an LLM answer — and four more things the market still pays for.

researchchapter 04 n = 100
37
average score in web3 & crypto · out of 100
one disease. three faces.

the state of LLM visibility across web3 & crypto, iGaming and B2B services — same illness, three different symptoms.

guidechapter 05
"read. verify.
quote."
the whole game, in three words
read. verify. quote.

the three layers that decide whether AI names you — readability, entity, citability — and why the order can't be swapped.