Fazlay RabbyFazlay RabbyAI Search Optimization
Search is splitting in two: the result list, and the single answer an assistant gives instead. AI Overviews, ChatGPT and Perplexity now answer before anyone clicks. I structure your site so those systems can read it, understand it, and name your business when a buyer asks.
Why Now
A growing share of buying questions never reach a result page. The model answers, the buyer acts, and nothing appears in your rankings report — because nothing ranked and nothing was clicked. This is the work that decides whether you are quotable.
Why It Matters
AI Overviews sit above the first organic result, and assistants answer in a paragraph with no click at all. Ranking well is still necessary — it is just no longer sufficient. The model has to be able to lift your answer out of the page.
No amount of persuasive writing gets a model to quote you. It cites what it can parse: clear entities, consistent naming, valid schema, and plain statements of fact sitting on pages it is allowed to crawl.
I build the chatbots and automations these engines sit beside, and I've run Claude, ChatGPT and agentic tooling in daily production since 2022. That's the difference between advising on AI search and working inside it every day.
This site runs the playbook: schema on every page, a machine-readable llms.txt, clean semantic HTML, and a trained assistant answering service questions. You get the version I have already tested on my own traffic.
My Process
First I find out what the assistants already say about you. Which buyer questions you are absent from, which competitors get named instead, which sources they cite, and how much of your content is even parseable in the first place.
Then the foundation: clear entities, consistent naming across the site, and schema stating what you do, where you do it and who for — so a model has facts to work with rather than marketing to interpret.
An llms.txt, well-formed HTML, a clean heading hierarchy, and answer-shaped content placed where extraction actually happens. Everything an engine needs, in the form it prefers to read.
Prompts get tracked over time, so you can see the moment you start appearing in answers and which pages did the work. Like rankings, this is measured rather than assumed.
What's Included
A baseline of what the major assistants currently say about you and your named competitors, across the questions your buyers actually ask.
Consistent entities, organization and service markup, and structured data implemented and validated — the machine-readable version of who you are.
A curated file that tells an assistant which pages matter and what they contain, alongside clean robots and sitemap configuration that lets the right things through.
Service and FAQ content written to be extracted: direct answers, unambiguous facts, and the specifics models look for instead of adjectives.
Crawlability, rendering, indexation and Core Web Vitals handled first, because an engine that cannot fetch the page will never quote it.
A tracked prompt set re-run over time, with what changed and which pages moved the needle — reported in plain English next to your existing SEO data.
Working Together
American search is where most of my work lives, and answer engines are being adopted at different speeds by market. Here is how I handle that rather than pretending one playbook fits everywhere.
Most of my clients sell to American buyers, and AI Overviews are already reshaping how those buyers research local and commercial services. The examples, the entity naming and the content structure are all built for US search behavior first.
I work across the UK and European Union too. Where a brand serves several markets, entities and schema are built to stay unambiguous across languages and locales instead of fragmenting into near-duplicate pages.
Consent tooling that blocks rendering is one of the most common reasons a European site is invisible to crawlers and assistants alike. I keep analytics, tag management and markup inside consent boundaries without hiding your content from the machines reading it.
I'm a full stack developer, so the schema, the llms.txt, the markup and the content changes get shipped by the person who diagnosed them. You don't receive a strategy deck and a list of tickets for a developer to deprioritize.
Who This Is For
Companies where a single extra qualified call pays for the engagement, and where buyers now ask an assistant for a recommendation before they ever see a result page.
Editorial operations with large archives — like the Canadian news publication whose technical SEO I run — where being citable by answer engines depends on taxonomies, canonicals and structure holding together at scale.
Teams whose buyers compare tools by asking a model. Clear product entities, documentation structure, and schema make the difference between being shortlisted in an answer and being left out of it.
FAQ
They share a foundation but aim at different outcomes. SEO gets your page into the result list; AI search optimization gets your business into the answer itself. That means entity clarity, schema all the way through, facts stated plainly on crawlable pages, and machine-readable files like llms.txt — because a model quotes what it can parse, not what is persuasive.
I track a fixed set of buyer questions against the major assistants and record whether you appear in the answer, which competitors are named instead, and which sources get cited. Those prompts are re-run over time so progress is a trend line rather than a feeling. It sits alongside your normal Search Console and ranking data, not instead of it.
No, and anyone promising that is guessing. Nobody controls what these models generate. What I can control is how legible your business is to them: correct entities, valid schema, clean crawlable HTML, and content written so a model can extract a clear fact. That is the input side, and it is where the work gets done.
No, it extends it. If the site is not crawlable and indexable, nothing else in the chain matters — that is why the audit starts with the classic technical ground: rendering, indexation, Core Web Vitals and internal structure. AI search optimization is layered on top of a site that already works.
It is usually ongoing rather than a one-off, because these engines change often. SEO retainers start at $895/month and AI automation work starts at $1,495, and the strategy call decides which shape fits. You get a fixed written quote within 48 hours and no lock-in on monthly work. Full details are on the pricing page.
Yes. The US is my primary market and I also work across the UK, the EU and Canada. European projects get consent-aware analytics and GDPR-conscious data handling from the start, pricing is quoted in USD with no regional markup, and I reply within 2 hours wherever you are.
Book a free strategy call — I'll run your buyer questions against the major assistants first and show you what comes back. Or email hello@fazlayrabby.com and I'll reply within 2 hours.
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