About Semantic Vector

From old-school SEO to AI-era visibility systems

Most “About” pages try to impress you with a highlight reel.

This one has a simpler job: show you why the person behind Semantic Vector actually understands what’s happening to search – and what to do about it.

My name is Sergey Lucktinov, and for the last 15+ years I’ve been doing one thing – helping websites get found.

The difference is that I started in the old world of SEO – and stayed long enough to help build the new one.

15 years in the keyword era (and what it taught me)

I didn’t begin with entities, retrieval models, or AI overlays.

I began where most agency owners and SEOs did:

• Keyword research spreadsheets
• Link-building campaigns
• On-page tweaks and technical audits
• Month-over-month traffic graphs

I ran campaigns, grew affiliate projects, built and led teams, and worked across industries where rankings were the main scoreboard.

Those years taught me a few things that never stopped being true:

• Most businesses don’t need “more content” – they need coherent content.
• Most SEO problems are structural, not tactical.
• Most agencies are set up to sell activity, not outcomes.

For a long time, that was enough.

If you understood crawlability, relevance, and authority better than your competitors, you won.

Then the ground moved.

When search stopped being about pages

As Google rolled out updates like Hummingbird, RankBrain, BERT, MUM, and finally AI Overviews, something subtle but decisive changed.

Search stopped being about matching words and started being about understanding meaning.

You could feel it in the results:

• Pages with decent links and good content would still get sidelined.
• Entire sites would rise or drop not because a page changed, but because the context around them changed.
• “Doing everything right” didn’t guarantee stability anymore.

I went looking for answers in the only place that still felt honest – how the systems actually work.

That path led me into Semantic SEO – and into the research and patent literature around how Google and other AI systems interpret and retrieve information.

The pivot: from SEO tactics to Semantic SEO

The turning point was realizing that Google doesn’t really “rank pages” in the way most of the industry still talks about it.

It ranks:

• Entities (people, brands, products, concepts)
• Relationships between those entities
• Patterns of behavior and trust over time

Once you see that, traditional SEO stops being “wrong” – it just becomes incomplete.

That’s where Semantic SEO enters:

• You stop optimizing for keywords and start modeling meaning.
• You stop thinking in “articles” and start thinking in Semantic Content Networks (SCNs).
• You stop asking, “How do we rank this page?” and start asking,
  “How do we design this entity so Google can’t misunderstand it?”

I rebuilt my entire approach around that logic – from how I structure a single paragraph to how I architect entire site trees.

And then AI arrived in full force.

Beyond Semantic SEO: SRO and AI infrastructure

When LLMs and AI overlays started to sit on top of classic search, something clicked:

Semantic SEO explained how to become understandable.

But it didn’t fully explain how to become retrievable once AI models sat between the user and the index.

That’s where I started developing SRO – Semantic Retrieval Optimization.

SRO is built on a simple reality:

AI systems don’t just list results.
They retrieve, weigh, and assemble answers.

That means visibility becomes probabilistic:

• Is your content likely to be retrieved as a candidate?
• Is it likely to be trusted once retrieved?
• Is it likely to be chosen when similar passages exist?

I went deep into:

• Query fan-out behavior
• Passage-level scoring
• Trust calibration and corroboration
• Retrieval cost and crawl economy
• How AI assistants like Gemini, ChatGPT, and Perplexity treat content differently than classic Google

Those explorations turned into two filed patents focused on AI infrastructure and retrieval behavior – how systems can interpret, score, and surface content based on semantic clarity and trust, not just keyword overlap.

SemanticVector sits on top of that stack:

• 15+ years of SEO
• A complete pivot into Semantic SEO
• The creation of SRO and AI infrastructure models that look at search from the system’s point of view, not the marketer’s

What this actually means for you

All of that is interesting background.

But if you’re here as an agency owner, SEO lead, or brand-side decision-maker, you care about something more practical:

“What does this change for my business?”

Here’s what working with Semantic Vector is designed to give you:

• Stability in an unstable search environment
  Your site stops behaving like a fragile ranking machine and starts behaving like a coherent information system that AI models can safely rely on.
• Clarity in a noisy industry
  You get explanations grounded in how retrieval, ranking, and AI summarization actually work – not whatever this week’s SEO thread is panicking about.
• Upgraded client or stakeholder conversations
  Instead of “we’ll publish more content,” your pitch becomes
  “we’re redesigning how your brand is represented inside search and AI systems.”
• A roadmap for the AI era
  Not “AI SEO hacks,” but a structured way to:
  • model entities and relationships,
  • build semantic networks,
  • calibrate trust,
  • and reduce retrieval friction.

What Semantic Vector is (and isn’t)

Semantic Vector is:

• A consultancy that operates at the intersection of SEO, semantics, and AI retrieval.
• A partner for agencies and brands that want to upgrade their strategy, not just “fix pages”.
• A place where we translate research, patents, and system behavior into concrete actions your team can execute.

Semantic Vector is not:

• A content factory.
• A “we’ll do everything” agency.
• A place to buy quick fixes or ranking hacks.

If you want volume, there are plenty of vendors.

If you want to understand — and shape — how AI systems see your brand, that’s where we come in.

Who I work best with

Over the years, I’ve learned that results aren’t just about tactics; they’re about fit.

SemanticVector is a good fit if you are:

• An agency that wants to move from deliverables to strategic leadership in AI-era search.
• A brand or in-house team managing a complex site that can’t afford to guess why visibility is rising or falling.
• A founder, CMO, or head of SEO who’s tired of surface-level explanations and wants a system-level understanding.

If your goals are:

• “We need 30 blog posts per month.”
• “We just want more traffic quickly.”

…we’re probably not a match.

If your goals are:

• “We want to become the most understandable and trusted result in our space – to users and AI systems alike,”

then we’re speaking the same language.

How I think about your site

When I look at a website, I’m not asking:

• “What’s the target keyword?”

I’m asking:

• What entities does this brand own – and which ones should it own?
• What does this site look like as a semantic graph, not a sitemap?
• Where is trust flowing – and where is it leaking?
• How expensive is it for Google or an AI model to retrieve a correct, confident answer from this site?

Then we rebuild:

• The structure (SCN and internal linking)
• The signals (schema, entities, authors, corroboration)
• The experience (rendering, layouts, clarity for humans and machines)

So that your brand isn’t just ranking – it’s safe to choose for any system trying to answer a question in your domain.

Why this matters now

Search is moving from:

• Pages → Entities
• Rankings → Retrieval & reasoning
• Traffic → Trust, inclusion, and choice

You can feel that shift in:

• AI Overviews summarizing answers above organic results
• Chat-based assistants citing a handful of domains
• Users getting answers without ever “visiting ten blue links”

You can fight that change, or you can design for it.

SemanticVector exists for the second option.

If you’re ready to operate at the next level

If you:

• Know that traditional SEO alone is no longer enough,
• See AI overlays and retrieval as both a threat and an opportunity,
• Want your brand or your agency to be the one that leads, not reacts —

then we should talk.

This isn’t about adding another service line.

It’s about upgrading how you think about visibility — and building systems that AI can’t ignore.

Sergey Lucktinov
Founder, Semantic Vector
Author of Semantic SEO, SRO & AI: Get Found, Trusted, and Chosen in the AI Era
Inventor of AI infrastructure and retrieval optimization methods (2 filed patents)