by Maria Dykstra
Maria Dykstra is an AI Visibility Architect who has diagnosed algorithmic authority failures for 50+ B2B companies. Former Microsoft leader ($2B ad systems, 36 markets). Creator of the Algorithmic Authority Stack and author of The Invisible Audience.
If you’re a founder, expert, or thought leader, you’ve probably felt it.
That uneasy gap between what you know and what the market sees.
You publish content. You post on LinkedIn. You try to “show up.”
And somehow… the louder, less qualified people outrank you.
It’s not because they’re smarter.
It’s because they’re easier for AI to understand.
Visibility today isn’t about keywords.
It’s about meaning.
Search engines and large language models (Google Search, Google’s Knowledge Graph, Perplexity, ChatGPT, Gemini) don’t match words.
They map entities — the people, concepts, frameworks, and terms that define expertise.
And here’s the part most founders miss:
AI is already mapping you. Whether you like the map or not.
The question is not “Does AI understand me?”
The real question is:
Did you give AI anything worth understanding?
That’s where the Entity Stack Map comes in — the structured blueprint of your expertise that turns your thought leadership into something AI can actually recognize, rank, and amplify.
This isn’t theory.
This is how modern search works.
And if you learn to control it, you stop competing with louder voices and start becoming the reference point in your category.
Let’s break this down.
Why Entities Matter More Than Keywords (and Always Will)
Keywords were built for early search engines.
Entities were built for everything we use now.
Google announced this shift over a decade ago when it launched the Knowledge Graph — a massive database of people, places, concepts, and relationships.
Its purpose was simple:
Stop reading pages. Start understanding meaning.
That shift has only accelerated with LLMs.
AI models don’t “read” your content.
They reverse-engineer your ideas into a semantic structure.
They identify the entities.
They map how those entities connect.
They decide whether you’re a source… or background noise.
IBM explains this directly in their Semantic Search technical overview:
Semantic search = entity understanding + entity relationships.
If your ideas aren’t structured?
AI fills in the gaps — usually incorrectly.
If your frameworks aren’t named?
AI attributes them to someone else.
If your POV is scattered across random posts?
AI treats each post like a one-off, instead of part of a system.
This is why strong founders lose visibility to weaker competitors.
It’s not a strategy problem.
It’s a semantic problem.
So What Exactly Is an Entity?
Simple version:
An entity is a “thing” with meaning.
Something AI recognizes as its own concept.
Examples:
- A person (Maria Dykstra, Jensen Huang, Bill Gates)
- A company (TreDigital, Exactly AI)
- A concept (Authority, GTM Strategy, Semantic Search)
- A framework (Founder Visibility Engine™, Language Ledger)
- A product (AI Visibility Engine, 50-Asset Founder System)
- A service (Fractional CMO, Advisory, GTM Buildout)
If it’s real, defined, and meaningful → it’s an entity.
If it’s vague, unstructured, or one-off → it’s a keyword.
Keywords don’t build authority.
Entities do.
Where Founders Go Wrong (The Cost of Unstructured Expertise)
Most founders publish content like they’re dropping sticky notes into the void.
One post about leadership.
One about AI.
One personal story.
One tactical tip.
One CTA.
That’s fine for engagement.
It’s terrible for authority.
Here’s what AI sees:
- Random ideas
- No hierarchy
- No frameworks
- No unifying signals
- No consistent terminology
- No identifiable expertise map
It cannot rank you for anything meaningful because nothing ties together.
Meanwhile your competitors — even the mediocre ones — may have:
- One clear framework
- One repeatable message
- One defined set of terms
- One consistent hierarchy of entities
AI sees a pattern.
And patterns win.
This is exactly why, inside the Founder Visibility Engine™, the first thing we do is extract the founder’s POV, frameworks, and terminology and organize them into a structured system (as outlined on page 5 of your program overview).
That system becomes the Entity Stack.
But the map is what makes it usable.
Enter: The Entity Stack Map
Here’s the simplest way to understand it:
The Entity Stack is what you know.
The Entity Stack Map is how you organize it so AI understands you.
It is the hierarchy of:
- Your identity
- Your frameworks
- Your execution components
- Your proof
This hierarchy becomes the blueprint AI uses to decide:
- Who you are
- What you’re known for
- What your core expertise is
- What differentiates your work
- Whether your ideas reinforce each other
- Whether you deserve visibility in your category
And when this blueprint is clean?
Every post reinforces your authority.
Every article strengthens your signal.
Every interview expands your semantic footprint.
Every answer engine starts citing your frameworks.
Every LLM begins to “understand” your voice and POV.
You stop building content.
You start building meaning.
The 4-Layer Structure of a High-Authority Entity Stack Map
There are dozens of variations, but the one I use — and the one we deploy inside our Visibility Engine work — uses four layers.
This is the version optimized for AI search, LLM retrieval, and cross-platform authority.
Layer 1: Core Identity Entities
These define the founder.
- Your name
- Your company
- Your role
- Your category
For example:
Maria Dykstra | TreDigital | Authority Strategist | AI GTM Expert
This tells AI who is speaking.
You’d be shocked how many founders skip this.
Layer 2: Framework Entities
These are your proprietary systems — the backbone of your expertise.
Examples from your own materials (PDF):
- Founder Visibility Engine™
- AI Visibility Engine
- Language Ledger
- Context File System
- Proof-First Content Model
This is where founders build the most authority — because frameworks create category language.
Layer 3: Execution Entities
These are the tactical components inside your bigger systems.
From your process:
- Interview extraction
- POV development
- Content mapping
- Short-form scripts
- Carousels
- 50-asset content system
These show AI the depth of your expertise.
Layer 4: Proof Entities
This is your credibility layer.
The Founder Visibility Engine PDF references several examples:
- GTM client work
- Fortune 500 work
- Multi-channel programs
- Case studies
- Reddit pilot
- AI-powered program
These are not “nice to mention.”
They are semantic anchors.
When you cite proof, you strengthen your entity relationships.
A Real Example: What My Own Entity Stack Map Looks Like
This will give you a concrete sense of how to do it for yourself.
Core Identity
Maria Dykstra
TreDigital
AI GTM Strategist
Fractional CMO
Framework Entities
Founder Visibility Engine™
AI Visibility Engine
Context File System
Language Ledger
Proof-First Content Model
50-Asset Content Engine
(These appear in your own materials — and are referenced consistently.)
Execution Entities
Content calendar system
Interview extraction
Founder POV development
Viral hook library
Distribution loops
Strategic pillars
Lead magnet engine
Short-form scripts
Proof Entities
Fortune 500 experience
Microsoft tenure
AI Readiness Framework
Exactly AI GTM
FreeWill Reddit pilot
AI-powered content system
Multi-channel GTM programs
This is one stack — but the map is what makes it functional.
Let’s talk about the map.
How an Entity Stack Map Actually Works Behind the Scenes
Here’s the part most founders never realize:
AI does not see content as content.
AI sees content as signals.
Each signal reinforces or weakens:
- Your category
- Your expertise
- Your frameworks
- Your identity
Over time, AI models build a graph — a map — of who you are.
This is literally how Google’s Knowledge Graph works:
https://developers.google.com/knowledge-graph
This is how Bing Entity Understanding works:
https://learn.microsoft.com/en-us/bing/search-apis/bing-entity-search/overview
This is how semantic search models work (IBM reference again here):
https://www.ibm.com/topics/semantic-search
This is how LLMs structure internal embeddings (OpenAI explains entity extraction and embedding similarity here):
https://platform.openai.com/docs/guides/embeddings/what-are-embeddings
If you do not give AI a structure, it creates one for you — and it’s never the one you want.
The Entity Stack Map fixes the chaos.
It shifts you from:
Unstructured expert → Recognized authority.
Because once AI sees the hierarchy, it starts ranking and citing you as the source.
The Practical Side: How to Build Your Entity Stack Map
Let’s make this tangible.
Here’s the exact 7-step process I use with founders inside the Visibility Engine work.
This is the practical version — the one you can implement today.
Step 1: List Your Identity Entities
Write down:
Your name
Your company name(s)
Your category
Your core expertise
This becomes your semantic foundation.
Step 2: Extract Your Frameworks
List every repeatable system you use with clients.
If it happens the same way twice → it’s a framework.
If it has a name → it’s an entity.
If it solves a specific problem → it’s a high-value entity.
Step 3: Break Your Frameworks Into Components
List the building blocks.
These become your Execution Entities.
Step 4: Gather Your Proof Entities
Case studies
Client results
Notable companies
Project names
Industries
Programs
You need these to anchor credibility.
Step 5: Group Everything Into the 4 Layers
Identity
Framework
Execution
Proof
The moment you see this hierarchy, your entire content strategy shifts.
Step 6: Rewrite Your Profiles Using These Entities
Your LinkedIn, X, website, podcast bio — all should reinforce your Entity Stack.
Step 7: Build Content That Repeats These Entities Intentionally
You don’t need new ideas.
You need consistent entities.
This is how you turn content into a signal.
What Happens When You Use an Entity Stack Map Consistently
You don’t need to post more.
You need to post strategically.
Here’s what starts happening once your entity system is recognized:
- AI begins surfacing your frameworks in search
- Your name appears alongside your system
- Answer engines begin referencing your terminology
- Content platforms rank you for authority, not recency
- Your posts build compounding semantic weight
- You become top-of-mind in your category
- Your brand becomes “machine-readable”
This is exactly why the Founder Visibility Engine™ centers around extracting your POV, structuring your concepts, and delivering 50+ content assets from your own words — because structured entities outperform random content every time.
This is how you build visibility without the grind.
Final Take: Your Expertise Deserves Structure
The Entity Stack Map is not optional anymore.
Not for founders.
Not for experts.
Not for anyone who wants to build authority in an AI-driven world.
AI models decide who gets visibility based on meaning.
Your meaning needs a blueprint.
When you structure your entities:
You become easier to understand.
Your frameworks become memorable.
Your content becomes intentional.
Your authority compounds.
Your brand stops drifting and starts scaling.
And AI stops guessing — and starts amplifying you.
If you want to build your Entity Stack Map the right way, send me a message.
It’s the first step we build inside the Founder Visibility Engine — and the reason our clients go from invisible to undeniable in months, not years.
