SUPER EXCITED TO PRESENT!
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https://t.co/JfIjzSSyGL
#SEO#Schema
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Has the dust settled now that Google took away FAQ schema? The (possibly) most abused schema out there.
Now you think about other schemas because all of a sudden (not really) it's relevant to GEO?
π₯±
Check my tweets from 2022/23 you're late to the game.
"Ensures AI engines can parse and connect your content."
That's the SaaS pitch for 'Technical GEO.' Schema. Structured data. Clean architecture.
Ensures.
LLMs were built to read unstructured language. There's nothing to ensure.
Read on The Inference: https://t.co/1SoLxa1hn0
Just FYI, if you still happen to link to one of my websites/projects, delete the link, I no longer own any of my domains and the websites should be down.
Google did it, so I did too.
My own android AI model chat app. 100% local, download the model and chat.
It was compiled by my vibe coding built android app builder that I host on my homelab.
It can either build apps by JSON script instructions or by Qwen coder model
@Hostinger published their full AI SEO playbook. Free. No lead-gen form. Here it is and how to leverage it for your brand π
π€ TL;DR:
A practical and transparent AI search case study: 100 articles re-engineered leading to a 52% AI citation share growth in 3 months - their 6-step framework and how to apply it to your brand:
1οΈβ£ Semantic SEO structure
Answer-first intros. Every H2 as a direct question. First sentence under each heading must answer it.
π‘ Audit your top 10 articles. Can the intro answer the query in one sentence? Can every H2 become a question?
2οΈβ£ Topical authority - start with comparisons
Build topic clusters but prioritise comparison content first. AI prefers pros/cons, features, pricing, quantifiable data over vague descriptions.
π‘ Source comparison topics via Google Autocomplete, Reddit, and your SEO tool.
3οΈβ£ Make your authority legible to AI (EEAT)
Detailed author bios with real credentials, linked to their profiles. Give AI a reason to trust the source, not just the content.
π‘ Check your bylines. If they don't show expertise, fix them first.
4οΈβ£ Make commercial pages citable
Informational summaries, HTML tables (features/specs/pricing), and FAQ sections. AI prefers Q&A for direct citation.
π‘ Pick your top 3 commercial pages and add one table and one FAQ each.
5οΈβ£ Remove crawler friction
Schema markup, fix 404s, and "create an llms.txt file giving AI platforms explicit crawl permission"
π‘ Removing crawler friction - yes, llms.txt - nah. I specifically tested this and no search engine (not AI nor traditional) specifically fetched it once according to log files.
6οΈβ£ Optimise for AI agents
AI agents leave slow, unstructured pages. PageSpeed is no longer just a ranking signal, and no longer just for Google.
π‘ Run your top pages through PageSpeed Insights. Under 70 on mobile needs fixing.
How they tracked the success of their AI SEO Framework - KPIs:
π Visibility - track 5-10 customer questions monthly across AI tools. Monitor movement in 6-8 weeks.
π Citation share - test 10-15 questions in Perplexity and ChatGPT etc. Competitor appearing where you should? Content gap. Allow 2-3 months.
π¬ Brand sentiment - ask AI: "What are common complaints about [Brand]?" Narrative off? Publish corrective content. Track quarterly.
πͺ My 2-pence
π‘ This is one of the most openly shared AI SEO frameworks I've seen from a brand doing this at scale - and it holds up.
π‘ But it's not plug-and-play. It requires structured experimentation to isolate what works for YOUR brand - customer research for real intent, competitor analysis to find gaps you can credibly win. The playbook gives you the method. The work is in testing and iterating.
π‘ Timelines matter. 6-8 weeks for visibility, 2-3 months for citation movement. Anyone promising faster is trying to sell you something.
π‘ Genuinely one of the rare times I'd say: read the source, not just the summary.
Links (looks like there might be more in this series, worth following): https://t.co/H861zplBRg
https://t.co/91mYbdkswJ
#ai #seo #hostinger #aiseo #llms
π₯±.
And with that said, there's always more to test and learn, even if it's not on Google, or other AI-centered search engines. But the cost is purely educational (at this point) and cannot be justified otherwise, and nobody really want (trust me I tried) put money into research.
Pinnacle and the "point of no return" for the human race.
By then, sure demand and population will grow, but that level of efficiency means running multiple instances together as one to correct and check each other in an untethered form will be the peak point.
2/2.
Been a while so here is my prediction (echoing?) of AI.
(Might as well since I don't do SEO anymore)
My gut say that the race is now for efficiency rather then "better" or "smarter".
The day a smartphone or a raspberry pi can run locally todays top Claude model will be the
1/2
I am seeing the /blog/ sections for various large companies dropping in the last week or two.
The blogs seem to be full of tons of explainer content for basic concepts within their niche, like "what is ____" or "how to use ____"
Yup that's the future, I knew it would come to it as soon as the "AI" boom started. The next stage is figuring out how to make it affordable and available to the average person and how to remove the goggles/headsets we are currently constrained and move into direct injection.