Sorilbran Stone | Visibility Engineer
Expertise → Authority. Visibility → Demand.
For more than 15 years, I’ve worked across search, content, AI, and demand generation, testing what makes expertise easier to find, trust, and buy from. The goal? Revenue. It is always revenue.
Latest
How the Validation Era Will Reshape AI Visibility
Attention now requires proof. What changes when humans and AI systems both start asking whether expertise can be verified?
Read the article →What I write about
The work behind modern discovery.
How company knowledge gets turned into something buyers and machines can actually find, understand, trust, and use.
Owned Media
Building a company site that earns attention, authority, and demand over time.
Search & Discovery
How buyers find companies through search, recommendations, and increasingly fragmented discovery paths.
AI Retrieval & Recommendation
What AI systems retrieve, what they infer, and what makes a company usable in an answer.
Knowledge & Proof
Turning expertise, evidence, and institutional knowledge into clear source material.
Revenue Infrastructure
Connecting publishing, organic discovery, AI referrals, and conversion back to pipeline.
Owned media maturity
When does a company blog become revenue infrastructure?
A company blog publishes. Revenue infrastructure compounds. Each new piece should add something reusable: an answer, evidence, authority, search demand, a citation, or buyer trust.
Most growth-stage companies are sitting on expertise-hub knowledge and publishing like they only have a company blog.
The market relies on you to understand the space.
You help buyers understand the problem and evaluate solutions.
You answer the questions buyers have about the problems you solve.
You publish about the company and what it sells.
Frameworks + mental models
Ways I make the problem easier to see.
These are working tools I use to diagnose why a company is easy—or hard—for search engines, AI systems, and buyers to understand.
Minimum Viable Knowledge Graph
The smallest useful set of connected information a machine needs to understand who a person or company is, what it does, who it serves, what it knows, and what proves the claim.
- Identity
- Specialization
- Audience + context
- Expertise
- Proof
- Connections
Legibility. Eligibility. Extractability.
A company has to be identifiable, credible enough to include, and structured clearly enough for a machine to use. Those conditions shape whether AI systems can safely surface, cite, and recommend what you publish.
Read the LEE model →Recall. Retrieval. Inference.
Sometimes the model answers from what it already knows. Sometimes it retrieves. Sometimes it decides it knows enough and constructs the answer anyway. Each behavior creates a different visibility problem.
Open the mental model →Blue Puddles
Small, defensible pockets of expertise where a company has unusually strong proof and real demand. The goal is not to own the ocean. It is to find the water you can actually own.
Read the origin story →Proof Compounds
Evidence becomes more valuable when buyers, journalists, sales teams, search engines, and AI systems can all reuse it. Documented proof is not just validation. It is infrastructure.
See the proof →Proof
The work behind the ideas.
These numbers come from systems I directly built, owned, or managed. Sales Operations—not Marketing—qualified the opportunities and assigned deal value.
Tools
Useful things you can take with you.
Books, diagnostics, references, and machine-readable material built from the same work documented across this site.
Signal Builder
Map the entity structure, expertise, proof, and connections behind your brand.
Minimum Viable Knowledge Graph
A repeatable way to document the information machines need to understand an entity.
LLM Behavior Optimization
Recall, retrieval, inference—and the visibility problems each behavior creates.
AI Visibility Glossary
Plain-English definitions for the language behind AI search, retrieval, entities, and recommendation.
AI Brief
A canonical onboarding page built for founders, their AI systems, and machine-mediated consulting.
Receipts
People who saw the work up close.
Flip any card to see the original.
By 2019, Sorilbran had assembled a full-blown content-marketing machine with us… She just chipped away and got it done.
The receipt · Lauren Jung
Sorilbran Othello is the master of AI Visibility. I’ve personally seen her work drive millions of dollars in opportunities from blue chip clients searching AI for “best [x] to work with” and landing on her clients by name. No cold outreach. Just AI doing the work.
The receipt · Kevin McClain
Sorilbran is super smart and can distill complex concepts into easy-to-understand formats.
The receipt · Tarun Gehani
One of the absolute best people I’ve ever had the honour of working with. Sorilbran has a magical way of weaving together seemingly disparate concepts to make sense of what is happening in the SEO/AEO/GEO world — second to none.
The receipt · Anthony Nestel
About
Sorilbran Stone
I’m a Detroit-based Visibility Engineer, strategist, and founder. I help founder-led companies turn what their teams know into content and evidence that buyers can find, trust, and act on.
I founded Five-Talent Strategy House and lead the Detroit Media + Innovation Lab. I’ve spent 15 years in search and content, including years building publishing and acquisition systems tied directly to qualified pipeline.
Field notes
New work when there’s something worth saying.
New articles, frameworks, useful tools, and the occasional “wait, look at this” from the field. No daily nonsense.