AI Visibility Scorecard
Kevin Lacker's blog
lacker.io · Media & Entertainment
Somewhat visible. AI bots can read Kevin Lacker's blog, but it is missing the structured signals that push citation rate above competitors.
AI engines read this profile 5 times
Claude · Apple Intelligence · Meta AI
#222,408 of 1,966,627 in Media & Entertainment for AI visibility
6
AEO Visibility
iBorderline · 5.7/10
0
Muse Index Score
iAI agent readiness
Not agent-ready · 0/100
4
AI Adoption
iBasic · 4/100
About Kevin Lacker's blog
from our crawl and measurement
Kevin Lacker's blog is one of the businesses we track in the Media & Entertainment space. Its AI visibility score is 5.7 out of 10: the engines can find it, but they do not have much to hold on to.
Our crawl found a readable heading structure. It is missing structured data describing the business, an llms.txt file and a sitemap.
AI crawlers have visited once in our tracking, including ClaudeBot (Anthropic).
The 6 signals AI reads
Strong · Good · Fair · Weak
Structured Data
Weak
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
Good
Clear headings and answer-style content.
Entity Clarity
Fair
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
Weak
Experience, Expertise, Authority, Trust markers.
Technical AEO
Good
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
Good
Sitemaps and entity links AI can follow.
Off-page authority
How the web signals your brand to AI
Backlinks
Strong
Inbound links from other sites.
Domain Authority
Weak
Little domain authority yet.
Reference Presence
Weak
Not in AI knowledge graphs yet.
News & Press
Weak
No press coverage found yet.
Community
Strong
Forum and community discussion.
Social Mentions
Weak
No social discussion found yet.
What this score means
Your AEO score measures whether AI search engines - ChatGPT, Claude, Perplexity, Gemini - can actually read your site and cite it in answers. Roughly two-thirds of sites are invisible to them. At 5.7/10, Kevin Lacker's blog has a working base to build on - fixable, and the signals above are where to start.
Frequently Asked Questions
Why is rewrite search important?
I think most “normal person mathematics” can be thought of as a series of rewrites. Consider a question like “what are the factors of 27?” (I found this by googling “math question” and taking the first one that looked like a pure math question.) The normal way to solve this is roughly, first you consider that 27 = 3^3. Then you perhaps know that for a prime p, the factors of p^n are p^k for k in [0, n].
What can we do about it?
I worked on the Lean rewrite_search tactic for a while. It didn’t end up as useful as I had hoped. The main problem is that there are so many possible ways to rewrite a formula, you can’t use a plain breadth-first search and get very far. We need to be using AI heuristics. In Lean we were hoping to get mathematicians to tag theorems based on how good they were for rewriting, but this was just too much of a hurdle.
Is this your brand?
The exact fixes for Kevin Lacker's blog
Which AI engines already crawl you
Free AI bot monitoring: see every AI crawler that visits you
How to Get Your Brand Cited by ChatGPT, Gemini, and Claude: The Complete AEO Guide
The search landscape has fundamentally shifted. While Google still dominates, millions of users now ask questions to ChatGPT, Gemini, and Claude instead of typing into a search bar.
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Source & Attribution
Scored by Engagemii on August 2, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/lacker-io
Cite this score: Engagemii (2026). "AEO Score for Kevin Lacker's blog." Retrieved from https://engagemii.com/aeo/brands/lacker-io
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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