Chapter 13: The AI-First Future
In January 2026, I added a file to my website that no human will ever read.
It's called llms.txt. It sits at the root of kenny-kane.com, and its sole purpose is to tell AI systems how to understand my site. Which pages are canonical. Which content represents the real me. How to cite my work properly. What to prioritize and what to skip.
I wrote a blog post about it at the time, and the framing I used still feels right: the goal isn't to control AI. That ship sailed. The goal is to make it easier for AI systems to be accurate.
That's a sentence I couldn't have written five years ago. Not because the technology didn't exist, but because the idea that you'd need to communicate directly with machines about your professional identity --- bypassing human readers entirely --- would have sounded absurd.
It doesn't sound absurd anymore.
It sounds like the future. And in many ways, it's already the present.
• • •
The Shift That's Already Happened
Throughout this book, I've described a journey from human-readable web presence to machine-readable digital identity. From building a website for people to visit, to building structured data for machines to parse. From writing blog posts for human readers, to positioning content for AI citation. From hoping Google would figure out who I am, to explicitly telling every AI system exactly who I am.
That shift isn't coming. It's happened.
In 2025, I watched AI move from a tool I used in my workflow to a partner that reshaped how my organizations think, operate, and scale. The same capabilities that helped a cancer survivor receive better follow-up at TCF also helped a Firmspace member get faster service. The common thread wasn't the technology. It was the intentional design of systems that amplified human work rather than replaced it.
And that phrase --- amplified human work rather than replaced it --- is the key to everything that comes next.
• • •
What Changes
I'm not going to pretend I can predict the specific technologies that will matter in five years. Anyone who tells you they know exactly what AI search will look like in 2030 is selling something.
But I can identify the trajectories that are already clear.
AI becomes the primary discovery layer.
People are already shifting from "Google it" to "ask ChatGPT." The ten blue links are giving way to single, synthesized answers. Knowledge Panels are becoming the default presentation of professional identity. AI Overviews are replacing traditional search results for an increasing number of queries.
This trend doesn't reverse. The next generation of professionals won't think of search as scrolling through links. They'll think of it as asking a question and getting an answer. And that answer will be assembled from whatever structured, authoritative, citable content exists about you online.
If you've built the system described in this book --- structured data, Wikidata, authoritative blog content, cross-linked ecosystem --- you're already positioned for that future. If you haven't, you're increasingly invisible.
New standards will emerge for communicating with AI.
The llms.txt file I added to my site is early infrastructure. It's a proposed standard, not a universally adopted one. There's active debate about whether it works, whether AI systems actually read it, and whether it's worth the effort.
I added it anyway. Because the pattern is clear even if the specific implementation evolves. We went from robots.txt (telling crawlers what to index) to schema markup (telling search engines what content means) to llms.txt (telling AI systems how to understand and cite your work). Each layer adds more specificity, more control, more intentional communication between humans and machines.
Whatever comes after llms.txt will follow the same pattern. More structured ways to help machines understand who you are and what you've done. The formats will change. The principle won't.
AI systems will get better at cross-referencing claims.
Right now, if you publish something on your blog, AI systems generally take it at face value --- especially if it's consistent with what other sources say. That won't last forever. AI systems will get better at evaluating the reliability of sources, cross-referencing claims across platforms, and identifying inconsistencies.
This is good news for people who've built their digital identity honestly. If your schema markup, your Wikidata entry, your LinkedIn, your published work, and your blog all tell the same true story, cross-referencing only strengthens your position.
It's bad news for people who've exaggerated credentials, fabricated roles, or tried to game the system with misleading content. The window for that kind of manipulation is closing.
The disambiguation problem gets harder before it gets easier.
More people are creating digital content. More people are building personal websites. More people are discovering structured data and Wikidata. As awareness grows --- which is the whole point of this book --- more professionals with common names will be competing for AI attention.
The people who move first have an advantage. The infrastructure I built in late 2025 established my entity in knowledge graphs before the space got crowded. Early movers in any system benefit from less competition and more time for their signals to compound.
If you're reading this and you haven't started yet, you're not too late. But you'll be later tomorrow than you are today.
• • •
What Stays the Same
Here's what I'm more confident about than any specific technology prediction: the principles that make this system work are permanent.
Clarity beats cleverness.
Whether you're writing for Google's algorithm in 2015, ChatGPT in 2025, or whatever AI system dominates in 2035, clear and explicit communication of who you are and what you do will always outperform vague, clever, or hedged language. Machines are literal readers. They reward precision.
Owning your narrative matters more than ever.
The Stupid Cancer story from Chapter 8 isn't going to become less relevant as AI evolves. The principle that your history can be simplified, edited, or erased by platforms you don't control only becomes more important as AI systems become the primary way people learn about you. Own your domain. Publish your story. Control the canonical source.
Consistency across platforms is a trust signal.
When every platform tells the same story about you --- same name, same titles, same organizations, same description --- machines trust the information more. That's true today and it will be true in any future system that needs to verify identity claims across multiple sources.
Systems compound over time.
A blog post you write today will still be indexed, cited, and discoverable in five years. A Wikidata entry you create today will still be referenced by knowledge graphs in a decade. The infrastructure is durable in ways that social media posts and algorithm-dependent content are not.
Real experience is the only defensible content.
AI can generate generic content about any topic. What it can't generate is your specific experience doing specific work. "How I rebuilt a nonprofit website in 72 hours" is defensible. "10 Tips for Website Design" is not. As AI-generated content floods the internet, first-person, experience-based documentation becomes more valuable, not less.
• • •
The Biggest Variable: Human in the Loop
If there's one principle that ties this entire book together, it's this: the human has to stay in the loop.
Every strategy I've described depends on a human making intentional decisions. What to write. What to claim. What structured data to implement. What story to tell. How to connect the pieces. When to update. What's true and what's not.
AI is the partner, not the author.
I didn't let AI write my books. I used it as a writing partner that asked questions until the books emerged from what I already knew. I didn't let AI decide my professional identity. I told it who I am through structured data and authoritative content. I didn't let ChatGPT erase me from Stupid Cancer's story. I wrote myself back into the record.
Every chapter of this book is a human-in-the-loop story. The technology changes. The tools evolve. The platforms shift. But the human --- the person who lived the experience, built the career, made the decisions --- is always the one guiding the system.
That's the variable that never changes, no matter how sophisticated AI becomes.
The people who will thrive in an AI-first future aren't the ones who learn to game the latest algorithm or exploit the newest platform. They're the ones who understand that AI amplifies what's already there. If what's there is honest, structured, authoritative, and human --- the system works.
If what's there is thin, inconsistent, or fabricated --- no amount of optimization will save you.
• • •
Building for Humans and Machines
When I wrote the llms.txt blog post, I ended with three statements that captured my thinking:
"I care how my work is understood."
"I care about attribution."
"I'm building for humans and machines."
That's the mindset for the AI-first future. Not choosing between human readers and machine readers. Building for both. Understanding that in 2026 and beyond, your professional identity needs to be legible to people who visit your website and to AI systems that will never see your homepage but will describe you to millions.
The structured data speaks to machines. The blog speaks to humans and machines. The books speak to humans and feed the machines. The Wikidata entry speaks to knowledge graphs. The llms.txt file speaks directly to AI.
Each layer serves a different reader. Together, they form a complete picture of who you are.
That's not a technical project. It's an identity project. And it's one that every professional will need to undertake --- whether they share their name with a comedian and a rapper, or whether they're the only person in the world with their name.
Because in the AI-first future, the question isn't whether machines will describe you to the world.
It's whether you'll have any say in what they tell people.
• • •
CONCLUSION: Disambiguation Is Never Done
The comedian still owns KennyKane.com.
I checked before writing this. He does. Same domain I registered for $15 as a broke teenager in 2003. Same domain I let expire in 2004 because I couldn't justify the renewal. Same domain that's been occupied by someone else for over twenty years.
I'm not going to buy it. I'm not going to try to negotiate for it. He got there first, and he stayed. That's his, and I've made my peace with it.
Because here's what I know now that I didn't know then: the domain was never the point.
• • •
When I started this journey, I thought the problem was that I didn't own my name online. That if I could just get KennyKane.com back, everything would fall into place. I'd be discoverable. I'd be the first result. I'd own my digital identity.
That was wrong.
The problem was never the domain. The problem was that I didn't understand how discovery actually works. I didn't know that machines need structured data to understand who you are. I didn't know that a Wikidata entry could establish you in the knowledge graph without Wikipedia's permission. I didn't know that a blog post on your own site could change what ChatGPT tells the world about you.
I didn't know any of this because, until recently, almost nobody did. The awareness gap was the real barrier --- not the $15 I couldn't afford in 2004.
• • •
This book exists because I believe that gap is closing.
Everything I've described --- structured data, Wikidata, schema markup, GEO, AI citation, the validation loop, the digital ecosystem --- was gatekept knowledge five years ago. It required specialists, agencies, and budgets that most professionals didn't have.
Now it requires curiosity and a willingness to learn in public.
I built my entire digital identity system in a matter of months, in spare hours between running three organizations, using AI as my partner. Not because I'm technical. Because the tools have finally caught up to the problem.
If you've read this far, you have everything you need to do the same thing. Not my specific story --- that's mine. But the system. The framework. The step-by-step process for making search engines and AI know exactly who you are.
• • •
My dad doesn't need any of this.
His legacy is the thousands of patients he helped through surgery on Long Island. The families he comforted. The people he made laugh in the most terrifying moments of their lives. That legacy doesn't live in a knowledge graph or a schema markup property. It lives in the memories of real people who were in the room.
My legacy is different. It lives online. In search results and AI answers and knowledge graphs and blog posts and books. In systems that describe me to people I'll never meet.
Both legacies are real. Both matter. They just require different infrastructure.
• • •
I'm still not the only Kenny Kane.
The comedian is still performing in California. The rapper is still making music in Memphis. There are still other professionals on LinkedIn with the same name. There's still a fictional character in a novel I've never read.
Google knows which one I am now. So does ChatGPT. So does Claude. So does Wikidata. So does the Knowledge Graph.
Not because I beat the other Kenny Kanes. Not because I drowned them out with content or gamed an algorithm or bought my way to the top of search results.
Because I learned how to speak the language that machines understand. And I told them, clearly and consistently, exactly who I am.
That's all disambiguation is, in the end. Not competition. Clarity.
• • •
Mrs. Meagher was right. I do have a great name.
It took me twenty years, a lost domain, two decades of being confused with other people, a nonprofit that simplified my story, and an AI system that didn't know I existed to figure out how not to waste it.
But I figured it out.
And in a world where you can be anything, at a minimum, be yourself --- according to AI.
• • •
ACKNOWLEDGMENTS
Mrs. Meagher, you told a fifteen-year-old kid he had a great name and shouldn't waste it. It took me twenty years, but I finally figured out what you meant. Thank you for planting a seed you probably forgot about the moment the bell rang.
Dad --- the original Kenny Kane. You never needed a Knowledge Panel or a Wikidata entry. You built your legacy one patient at a time, one joke before anesthesia at a time, one handshake at a time. Everything I know about showing up for people started with watching you do it every day. This book exists because your name was worth fighting for.
Matthew Zachary --- my friend, my CEO, my competitor in a gentleman's race neither of us ever officially won. You built something extraordinary with Stupid Cancer, and I'm proud of the years I spent helping build it alongside you. The fact that I had to write myself back into the story doesn't diminish what we built together. It just proves that documentation matters.
Mallett and Michelle --- a friendship that started on Bourbon Street during St. Patrick's Day and turned into a podcast, a blog post, and a permanent piece of my professional infrastructure. That's networking done right. Thanks for the conversation and for letting me grab life by the balls on your show.
To my colleagues at Firmspace, the Testicular Cancer Foundation, and Gryt Health --- thank you for being a constant spark for my AI curiosity. Every system we built together, every problem we solved, every conversation about how to work smarter became raw material for this book. You made me better at what I do, and you gave me something worth writing about.
And to the comedian in California who still owns KennyKane.com --- no hard feelings. You got there first. You held on when I let go. This book wouldn't exist without that $15 lesson.
APPENDIX A: Tools & Resources
This is a reference list of every tool, platform, and resource mentioned in this book. URLs and details are current as of early 2026. Tools change, platforms evolve, and pricing shifts --- verify before committing to anything.
• • •
Website & Hosting
Squarespace --- https://www.squarespace.com
Website builder and hosting platform. What I use for kenny-kane.com. Supports custom code injection for schema markup, clean blog functionality, and built-in analytics. Not the most flexible platform, but fast to publish and easy to maintain.
• • •
Analytics & Measurement
Squarespace Analytics --- Built into Squarespace
Basic traffic and page view data. My quick pulse check for blog post performance. Shows entries, visitors, views, and traffic sources per page.
Fathom Analytics --- https://usefathom.com
Privacy-focused website analytics. No cookie banners required. Clean, simple dashboard. I use this alongside Squarespace's built-in analytics for a fuller picture without the complexity of Google Analytics.
Google Search Console --- https://search.google.com/search-console
Free tool from Google that shows what search queries drive traffic to your site, which pages are indexed, and how your site performs in search results. Essential for understanding how people find you through Google.
Semrush --- https://www.semrush.com
Comprehensive SEO and digital marketing platform. I use it primarily for monthly big-picture reviews --- keyword rankings, site health, and the AI Visibility dashboard that measures how often your content appears in AI-generated answers. Paid tool with various tiers.
Google Lighthouse --- Built into Chrome DevTools
Website performance, accessibility, and SEO auditing tool. Gives scores out of 100. Useful for catching real problems, but don't chase perfect scores --- they don't correlate with discoverability.
• • •
Structured Data & Schema
Schema.org --- https://schema.org
The collaborative project that defines structured data types used by Google, Microsoft, Yahoo, and Yandex. The authority on what properties and types are available for schema markup. Start with the Person type: https://schema.org/Person
Google Rich Results Test --- https://search.google.com/test/rich-results
Tests whether your structured data is valid and eligible for rich results in Google Search. Paste your URL and it shows what Google can read from your markup. Use this to validate after any schema changes.
Schema.org Validator --- https://validator.schema.org
Validates your structured data against the Schema.org specification. More detailed than Google's tool --- shows warnings and suggestions beyond just pass/fail.
JSON-LD --- https://json-ld.org
The format for implementing structured data recommended by Google. JSON-LD (JavaScript Object Notation for Linked Data) lets you embed machine-readable data in your website's code without changing the visible content.
• • •
Knowledge Graph & Wikidata
Wikidata --- https://www.wikidata.org
Free, open knowledge base that feeds Google's Knowledge Graph, Wikipedia, and AI systems. Anyone can create an entry. Lower notability requirements than Wikipedia. My entry: https://www.wikidata.org/wiki/Q137101943
Google Knowledge Graph --- No public interface for editing
Google's database of entities (people, organizations, places, things) and their relationships. Feeds Knowledge Panels in search results. You can't edit it directly --- it pulls from Wikidata, your website's structured data, and other authoritative sources.
Google Knowledge Panel --- Appears in Google search results
The information box that appears on the right side of Google search results for recognized entities. Built from Knowledge Graph data. You can claim your panel through Google's verification process once it appears.
• • •
Publishing & Books
Amazon Kindle Direct Publishing (KDP) --- https://kdp.amazon.com
Self-publishing platform for ebooks and paperbacks. Where I published The Accidental Nonprofiteer and Mission-Driven Ecommerce. Free to publish; Amazon takes a percentage of sales.
Amazon Author Page --- https://author.amazon.com
Author profile on Amazon linked to your published books. Part of the authority infrastructure --- creates a verified connection between your name and your published work.
Goodreads --- https://www.goodreads.com
Book discovery and review platform owned by Amazon. Claim your author profile to connect your books to your digital identity. My profile: https://www.goodreads.com/author/show/37817067.Kenny_Kane
BookBub --- https://www.bookbub.com
Book promotion and discovery platform. Another spoke in the publishing ecosystem that reinforces author identity.
Google Play Books --- https://play.google.com/books
Google's ebook marketplace. Another distribution channel that creates a verified book listing connected to your name.
Apple Books --- https://books.apple.com
Apple's ebook marketplace. Same principle --- wider distribution creates more verification signals.
• • •
AI Tools
Claude (Anthropic) --- https://claude.ai
AI assistant. My primary writing partner for books and blog content. The tool I use for the conversation-to-content workflow described in Chapters 6 and 7.
ChatGPT (OpenAI) --- https://chat.openai.com
AI assistant. Used for generating meta titles and descriptions, testing AI citation (asking it about yourself), and general workflow assistance.
Manus --- https://manus.im
AI agent platform. Another tool I use for extracting blog posts from project work.
Perplexity --- https://www.perplexity.ai
AI-powered search engine. Useful for testing how AI systems describe you and your work, since it shows sources alongside its answers.
• • •
Professional Profiles & Platforms
LinkedIn --- https://www.linkedin.com
Professional networking platform. Maintain a consistent profile that matches your website and structured data. A verification spoke, not the hub.
Crunchbase --- https://www.crunchbase.com
Business and professional database. Useful for establishing organizational connections. My profile: https://www.crunchbase.com/person/kenny-kane
MuckRack --- https://muckrack.com
Media and journalism platform. Useful if you've been quoted or featured in press coverage.
Forbes Councils --- https://councils.forbes.com
Invitation-based professional communities with publishing privileges on Forbes.com.
• • •
Content & SEO Standards
llms.txt --- Proposed standard
A file placed at your website's root that provides instructions to AI systems about how to understand, cite, and prioritize your content. Early infrastructure for communicating directly with AI. Still a proposed standard with debated effectiveness, but signals intent.
robots.txt --- Web standard
File that tells search engine crawlers which pages to index and which to skip. Different purpose than llms.txt --- controls crawling, not comprehension.
Sitemap (XML) --- Web standard
File that lists all pages on your site for search engines to discover. Usually at yourdomain.com/sitemap.xml. Most website platforms generate this automatically.
• • •
APPENDIX B: The Disambiguation Checklist
This checklist breaks the work described in this book into three phases. You don't need to do everything at once. Start with the first 30 days, build momentum, and expand from there.
• • •
Phase 1: Foundation (Days 1-30)
The goal of Phase 1 is to establish your hub and your basic machine-readable identity.
Week 1: Claim Your Hub
Register a domain with your name (or a variation like firstname-lastname.com)
Set up a simple website with at minimum: About page, Contact page, Blog section
Write a clear, specific bio that states your name, titles, organizations, and location
Add a professional headshot
Week 2: Implement Basic Structured Data
Add Person schema markup to your website (JSON-LD format)
Include: name, jobTitle, worksFor, address (at least city and state)
Add a disambiguatingDescription property that differentiates you from others with your name
Validate with Google's Rich Results Test
Validate with Schema.org Validator
Week 3: Connect Your Existing Profiles
Audit your existing profiles (LinkedIn, social media, professional directories)
Make sure every profile uses consistent name, title, and description language
Add sameAs properties to your schema markup pointing to each profile
Link each external profile back to your website where possible
Week 4: Publish Your First Blog Post
Write about something you've actually done --- a project, a decision, a problem you solved
Add Article or BlogPosting schema markup identifying you as the author
Generate a meta title and description
Share on one platform (LinkedIn or wherever your audience is)
Phase 1 Checkpoint: You should now have a website with structured data, consistent profiles across platforms, and at least one published blog post. Run Google's Rich Results Test on your homepage to confirm your schema is valid.
• • •
Phase 2: Authority Building (Days 31-90)
The goal of Phase 2 is to establish your entity in knowledge graphs and build a body of citable content.
Wikidata Entry (Allow 1-2 Days)
Research citation sources --- you need verifiable references for every claim
Create a Wikidata account
Build your entry with core properties: Instance of (Human), name, occupation(s), employer(s), education, work location
Add online identifiers: website, LinkedIn, social media handles
Add at minimum 10-15 citations from reliable sources
Connect to organization entities (create them if they don't exist)
Add your Wikidata ID to your website's schema markup (sameAs property)
Add a visible link to your Wikidata entry on your website (footer or about page)
Content Foundation (Ongoing Through Phase 2)
Publish 2-4 more blog posts documenting real work
Add internal links between blog posts
Create a links page consolidating all your online presences in one place
Create a disambiguation page if others share your name (optional but valuable)
Ensure every blog post has proper Article schema markup
Publishing (If Applicable)
If you have expertise worth sharing, consider writing a short book or guide
Self-publish through Amazon KDP
Claim your Amazon Author Page
Create a Goodreads author profile
Add Book schema markup to your website
Add book listings as citations on your Wikidata entry
Phase 2 Checkpoint: You should now have a Wikidata entry, a growing blog, cross-linked platforms, and the validation loop in place (website ↔ Wikidata ↔ Google Knowledge Graph). Ask ChatGPT or Claude about yourself and see what they say. Note the baseline --- you'll compare against this later.
• • •
Phase 3: Growth & Optimization (Days 91-365)
The goal of Phase 3 is to expand your citable content, monitor your AI presence, and let the system compound.
AI Citation & GEO
Test what AI systems say about you quarterly (ChatGPT, Claude, Perplexity)
Identify prompts and questions where you should be cited but aren't
Write blog posts that directly answer those questions with specific, first-person experience
Consider adding an llms.txt file to your website with citation preferences and canonical URLs
Measurement Setup
Set up Google Search Console for your domain
Choose an analytics tool (Fathom, Squarespace Analytics, or similar)
Check Semrush or similar tool monthly for AI Visibility trends
Track which blog posts perform best and note surprises
Ecosystem Expansion
Look for podcast, guest post, or speaking opportunities
Document each appearance on your blog with proper links
Add new appearances to your Wikidata entry's sameAs properties
Ensure any new publications or major projects get added to your structured data
Knowledge Panel
If your Knowledge Panel appears, claim it through Google's verification process
If it hasn't appeared, review the validation loop --- is your website connected to Wikidata? Is your Wikidata entry connected to your Knowledge Graph ID?
Add your Knowledge Graph ID to your schema markup once available
Ongoing Maintenance
Update structured data when roles, titles, or organizations change
Check Wikidata revision history quarterly for unauthorized edits
Keep blogging about real work at whatever cadence is sustainable
Re-test AI citation quarterly and note improvements
Phase 3 Checkpoint: By the end of year one, you should have a functioning digital ecosystem --- hub website with structured data, Wikidata entry, growing blog, cross-linked platforms, and measurable AI visibility. The system compounds from here. Each new post, each new citation, each new connection strengthens the whole.
• • •
The Quick-Start Version
If the full checklist feels overwhelming, here's the absolute minimum to start making a difference:
1. Get a website with your name on it
2. Add Person schema markup with your name, title, employer, and location
3. Add a disambiguatingDescription
4. Write one blog post about real work you've done
5. Make sure your LinkedIn matches your website
That's five steps. You can do them in a weekend. Everything else builds from there.
• • •
APPENDIX C: Glossary
Terms are listed alphabetically. Definitions are written for the non-technical reader.
• • •
AI Overview --- Google's AI-generated summary that appears at the top of some search results, replacing or supplementing traditional blue links. Draws from multiple sources to provide a synthesized answer.
Algorithm --- The set of rules a search engine or AI system uses to decide what content to show you. Google's algorithm determines search rankings. Social media algorithms determine what appears in your feed.
Article Schema --- A specific schema markup type (Article or BlogPosting) used to identify blog posts and articles on your website. Tells search engines who wrote the content, when it was published, and what it's about.
Canonical URL --- The "official" version of a web page. When the same content exists at multiple URLs, the canonical URL tells search engines which one to treat as the authoritative source.
Citation (AI) --- When an AI system references your content in its generated answer. The AI-era equivalent of being quoted or linked to. Being cited by AI is the goal of Generative Engine Optimization.
Cross-linking --- The practice of connecting your various online platforms to each other. Your website links to your LinkedIn, your LinkedIn links to your website, your schema markup references your Wikidata entry, and so on.
Disambiguation --- The process of clarifying which entity (person, place, thing) is being referred to when multiple entities share the same name. In this book, it refers specifically to making search engines and AI systems distinguish you from other people with your name.
disambiguatingDescription --- A specific property in Schema.org's Person type that provides a short text description to help differentiate you from other people with the same name. Example: "American business executive, CEO of Firmspace and Testicular Cancer Foundation, author of The Accidental Nonprofiteer."
Digital Ecosystem --- The interconnected network of platforms, profiles, content, and structured data that together form your complete online identity. The hub (your website) connected to spokes (LinkedIn, Wikidata, Amazon, social profiles, etc.).
Entity --- In the context of knowledge graphs, an entity is a distinct, identifiable thing --- a person, an organization, a place, a book. Google's Knowledge Graph stores information about entities and the relationships between them.
Fathom Analytics --- A privacy-focused website analytics tool that provides traffic data without requiring cookie consent banners.
GEO (Generative Engine Optimization) --- The practice of positioning your content to appear in AI-generated answers. The successor to traditional SEO, focused on being cited by AI systems rather than ranking in search results.
Google Knowledge Graph --- Google's database of entities and their relationships. Powers Knowledge Panels and feeds information to Google's AI systems. You can't edit it directly --- it pulls from Wikidata, structured data, Wikipedia, and other authoritative sources.
Google Knowledge Panel --- The information box that appears on the right side of Google search results for recognized entities. Shows a summary of who you are, what you do, and links to your profiles. Built from Knowledge Graph data.
Hub --- In the hub-and-spoke model, your primary website --- the platform you control completely. All other platforms (spokes) connect back to the hub.
JSON-LD (JavaScript Object Notation for Linked Data) --- The recommended format for implementing structured data on websites. Embedded in your site's code as a script tag, invisible to human visitors but readable by machines.
Knowledge Graph ID --- A unique identifier assigned by Google to entities in its Knowledge Graph. Format: /g/[alphanumeric string]. Example: /g/11gbhmd9kg. Including this in your schema markup strengthens the connection between your website and your Knowledge Graph entity.
Lighthouse --- Google's open-source tool for auditing website performance, accessibility, and SEO best practices. Gives scores out of 100. Accessible through Chrome DevTools.
llms.txt --- A proposed standard for a file placed at a website's root directory that provides instructions to AI systems about how to understand, cite, and prioritize the site's content. Similar in concept to robots.txt but designed for AI comprehension rather than crawling.
LLM (Large Language Model) --- The type of AI system that powers tools like ChatGPT, Claude, and Perplexity. Trained on vast amounts of text data and capable of generating human-like responses to questions.
Meta Description --- A short text summary of a web page that appears in search results below the page title. Doesn't directly affect rankings but influences whether people click through to your page.
Person Schema --- The Schema.org type used to describe a person in structured data. Includes properties like name, jobTitle, worksFor, address, sameAs, and disambiguatingDescription.
Platform Independence --- The principle of never depending on a single platform for your digital identity. If any one platform changes, disappears, or removes your content, your core identity remains intact on your own domain.
Rich Results Test --- Google's tool for validating whether your structured data is correctly implemented and eligible for enhanced search result features.
robots.txt --- A standard file placed at a website's root directory that tells search engine crawlers which pages to index and which to skip. Controls crawling behavior, not comprehension.
sameAs --- A Schema.org property that links your structured data to your profiles on other platforms. Tells machines that your Wikidata entry, LinkedIn profile, Amazon author page, and other profiles all belong to the same person.
Schema Markup --- Code added to your website that tells search engines what your content means, not just what it says. Uses vocabulary from Schema.org to provide structured, machine-readable information about people, organizations, articles, books, and other entities.
Schema.org --- The collaborative project founded in 2011 by Google, Microsoft, Yahoo, and Yandex that defines the vocabulary for structured data. Provides standardized types and properties that search engines universally understand.
Search Console --- Google's free tool for monitoring your website's presence in Google Search results. Shows which search queries lead to your site, how your pages are indexed, and any technical issues.
SEO (Search Engine Optimization) --- The practice of improving your website's visibility in search engine results. Traditional SEO focuses on ranking in Google's blue links. Increasingly being supplemented or replaced by GEO.
Sitemap (XML) --- A file that lists all pages on your website for search engines to discover and index. Usually generated automatically by your website platform.
Spoke --- In the hub-and-spoke model, any platform or profile that connects back to your hub (website). LinkedIn, Wikidata, Amazon, social media profiles, and Goodreads are all spokes.
Structured Data --- Information organized in a standardized format that machines can read and understand. On websites, this typically means schema markup in JSON-LD format embedded in your site's code.
Validation Loop --- The circular reinforcement between your website, Wikidata, and Google's Knowledge Graph. Your website references your Wikidata entry. Wikidata references your website. Google reads both and builds your Knowledge Graph entity. All three pointing to each other creates a trust signal.
Vanity Metrics --- Measurements that feel important but don't correlate with meaningful outcomes. Examples: follower counts, Klout scores, PageSpeed scores, social media likes.
Wikidata --- A free, open knowledge base operated by the Wikimedia Foundation. Anyone can create and edit entries. Feeds Google's Knowledge Graph, AI systems, and other platforms. Lower notability requirements than Wikipedia.
Wikidata QID --- The unique identifier for any entity in Wikidata. Format: Q[number]. Example: Q137101943. Used to reference specific entities across platforms and in structured data.
• • •
APPENDIX D: Full Schema Markup Example
This is the actual structured data implemented on kenny-kane.com as of early 2026. It's provided as a reference --- not a template to copy verbatim, but a real-world example of what a complete implementation looks like for a professional with multiple roles, published books, and connections to several organizations.
This code is embedded in the site's header using Squarespace's code injection feature. It's invisible to human visitors but readable by every search engine and AI system that crawls the page.
• • •
{ "@context": "https://schema.org", "@graph": [ { "@type": "WebSite", "@id": "https://kenny-kane.com/#website", "url": "https://kenny-kane.com/", "name": "Kenny Kane", "inLanguage": "en", "about": { "@id": "https://kenny-kane.com/#person" }, "publisher": { "@id": "https://kenny-kane.com/#person" }, "potentialAction": { "@type": "SearchAction", "target": "https://kenny-kane.com/?s={search_term_string}", "query-input": "required name=search_term_string" } }, { "@type": "WebPage", "@id": "https://kenny-kane.com/#webpage", "url": "https://kenny-kane.com/", "name": "Kenny Kane --- Official Site", "isPartOf": { "@id": "https://kenny-kane.com/#website" }, "about": { "@id": "https://kenny-kane.com/#person" }, "primaryImageOfPage": { "@type": "ImageObject", "url": "https://images.squarespace-cdn.com/content/v1/5e2e43f8ab72a14d5b9b1898/225e7eb4-2c89-405a-b945-f61c77cd0e4c/KK+SQ+2025.jpg?format=2500w" }, "breadcrumb": { "@id": "https://kenny-kane.com/#breadcrumb" }, "inLanguage": "en", "mainEntity": { "@id": "https://kenny-kane.com/#person" } }, { "@type": "BreadcrumbList", "@id": "https://kenny-kane.com/#breadcrumb", "itemListElement": [ { "@type": "ListItem", "position": 1, "item": { "@type": "WebPage", "@id": "https://kenny-kane.com/", "name": "Home" } } ] }, { "@type": "Person", "@id": "https://kenny-kane.com/#person", "name": "Kenny Kane", "givenName": "Kenny", "familyName": "Kane", "url": "https://kenny-kane.com/about-kenny-kane", "image": { "@type": "ImageObject", "url": "https://images.squarespace-cdn.com/content/v1/5e2e43f8ab72a14d5b9b1898/225e7eb4-2c89-405a-b945-f61c77cd0e4c/KK+SQ+2025.jpg?format=2500w" }, "description": "Entrepreneur and executive; CEO at Firmspace and Testicular Cancer Foundation; CTO & Co-Founder at Gryt Health; author of Mission-Driven Ecommerce and The Accidental Nonprofiteer.", "disambiguatingDescription": "American business executive, CEO, and author based in Austin, Texas. Not to be confused with Kenny Kane the comedian or Kenny Kane the rapper.", "address": { "@type": "PostalAddress", "addressLocality": "Austin", "addressRegion": "TX", "addressCountry": "US" }, "homeLocation": { "@type": "Place", "name": "Austin, Texas" }, "identifier": { "@type": "PropertyValue", "propertyID": "google_kgmid", "value": "/g/11gbhmd9kg" }, "alumniOf": { "@type": "CollegeOrUniversity", "name": "Louisiana State University Shreveport", "description": "MBA" }, "knowsLanguage": "en", "knowsAbout": [ "Real Estate", "HealthTech", "Nonprofit Leadership", "Structured Data", "Schema Markup", "AI Writing Tools", "Ecommerce", "Digital Strategy", "Personal Branding" ], "hasOccupation": [ { "@type": "Occupation", "name": "Chief Executive Officer" }, { "@type": "Occupation", "name": "Chief Technology Officer" }, { "@type": "Occupation", "name": "Author" } ], "jobTitle": [ "Chief Executive Officer", "Chief Technology Officer", "Author" ], "worksFor": [ { "@id": "https://firmspace.com/#org" }, { "@id": "https://testicularcancer.org/#org" }, { "@id": "https://grythealth.com/#org" } ], "sameAs": [ "https://www.wikidata.org/wiki/Q137101943", "https://www.linkedin.com/in/kenny-kane", "https://x.com/kennykane", "https://www.instagram.com/kennykane", "https://www.bookbub.com/authors/kenny-kane", "https://www.forbes.com/councils/forbesbusinesscouncil/people/kennykane/", "https://medium.com/@KennyKane", "https://theorg.com/org/gryt-health/org-chart/kenny-kane", "https://theorg.com/org/firmspace/org-chart/kenny-kane", "https://propmodo.com/author/kennykane/", "https://www.huffpost.com/author/kenny-kane", "https://www.crunchbase.com/person/kenny-kane", "https://muckrack.com/kenny-kane", "https://www.amazon.com/author/kennykane", "https://www.practicalecommerce.com/book-excerpt-mission-driven-ecommerce", "https://www.goodreads.com/author/show/37817067.Kenny_Kane", "https://www.mallettandmichelleonds.com/ep206-grab-life-by-the-balls-kenny-kane-of-testicular-cancer-foundation-and-firmspace/", "https://www.forbes.com/councils/forbesbusinesscouncil/2026/01/22/the-2026-operator-mindset-why-high-reliability-offices-could-win-the-market/" ], "subjectOf": [ { "@id": "https://kenny-kane.com/#book-accidental-nonprofiteer" }, { "@id": "https://kenny-kane.com/#book-mission-driven-ecommerce" } ] }, { "@type": "Organization", "@id": "https://firmspace.com/#org", "name": "Firmspace", "url": "https://firmspace.com/", "logo": { "@type": "ImageObject", "url": "https://images.squarespace-cdn.com/content/v1/5eced2fbf685b34b038c4c6f/1596847578386-8SFIL4ZSB5V3W120SV00/FS+-+Firmspace+LOGO+BLK+HRZ+2.png?format=750w" }, "sameAs": [ "https://www.linkedin.com/company/firmspace/", "https://x.com/firmspace" ] }, { "@type": "Organization", "@id": "https://testicularcancer.org/#org", "name": "Testicular Cancer Foundation", "url": "https://testicularcancer.org/", "logo": { "@type": "ImageObject", "url": "https://testicularcancer.org/wp-content/uploads/2024/05/TCFWITHTYPE-1.webp" }, "sameAs": [ "https://www.linkedin.com/company/testicular-cancer-foundation/", "https://x.com/TesticularCancr" ] }, { "@type": "Organization", "@id": "https://grythealth.com/#org", "name": "Gryt Health", "url": "https://grythealth.com/", "logo": { "@type": "ImageObject", "url": "https://images.squarespace-cdn.com/content/v1/6862a5bb9a2ad81569589743/b691ed9d-f32d-4e1a-a2eb-11ddfd93227e/grytlogo-ellipse-1.png?format=1500w" }, "sameAs": [ "https://www.linkedin.com/company/grythealth/", "https://x.com/grythealth" ] }, { "@type": "Book", "@id": "https://kenny-kane.com/#book-accidental-nonprofiteer", "name": "The Accidental Nonprofiteer", "alternateName": "The Accidental Nonprofiteer: Building Systems That Serve Your Mission (Not the Other Way Around)", "author": { "@id": "https://kenny-kane.com/#person" }, "bookFormat": "https://schema.org/EBook", "url": "https://kenny-kane.com/books/the-accidental-nonprofiteer", "datePublished": "2024-08-12", "inLanguage": "en", "description": "From a teenager learning customer service at a small-town pharmacy to building systems that serve thousands of cancer survivors, Kenny Kane's journey reveals the unexpected path many nonprofit leaders actually take.", "genre": ["Business", "Nonprofit Management", "Leadership"], "sameAs": [ "https://www.amazon.com/dp/B0FLXM8QF4", "https://books.apple.com/us/book/the-accidental-nonprofiteer-building-systems-that/id6754780697", "https://play.google.com/store/books/details/Kenny_Kane_The_Accidental_Nonprofiteer_Building_Sy?id=4_WKEQAAQBAJ", "https://www.goodreads.com/book/show/240005474-the-accidental-nonprofiteer" ] }, { "@type": "Book", "@id": "https://kenny-kane.com/#book-mission-driven-ecommerce", "name": "Mission-Driven Ecommerce", "alternateName": "Mission-Driven Ecommerce: What Building a Store Taught Me About Systems, Community, and Becoming an Operator", "author": { "@id": "https://kenny-kane.com/#person" }, "bookFormat": "https://schema.org/EBook", "url": "https://kenny-kane.com/mission-driven-ecommerce-book", "datePublished": "2025-10-16", "inLanguage": "en", "description": "At twenty-five, Kenny Kane turned a single $20 t-shirt into a six-figure ecommerce operation that funded programs, sparked conversations across the country, and redefined what a nonprofit could build.", "genre": ["Business", "Ecommerce", "Entrepreneurship"], "sameAs": [ "https://www.amazon.com/dp/B0FWMFSFRC", "https://books.apple.com/us/book/mission-driven-ecommerce-what-building-a-store/id6754781229", "https://play.google.com/store/books/details?id=G1uQEQAAQBAJ", "https://www.goodreads.com/book/show/242875785-mission-driven-ecommerce" ] } ] }
• • •
What to Notice
The @graph structure. This isn't a single entity declaration --- it's a connected graph of entities. The Person, three Organizations, and two Books all reference each other through @id links. This tells machines not just who I am, but how I'm connected to other entities.
The disambiguatingDescription. "Not to be confused with Kenny Kane the comedian or Kenny Kane the rapper." One line that solves the core problem this book describes.
The sameAs array. Seventeen external URLs connecting my website to every authoritative platform where I have a verified presence. Each link is a trust signal.
The identifier property. My Google Knowledge Graph ID (/g/11gbhmd9kg) is explicitly declared, connecting my website directly to Google's entity database.
The Organization entities. Firmspace, TCF, and Gryt Health each have their own @id, logo, URL, and sameAs properties. They're not just mentioned --- they're declared as separate, connected entities.
The Book entities. Each book has its own @id, publication date, descriptions, and sameAs links to Amazon, Apple Books, Google Play, and Goodreads. They create a web of verification that strengthens the author claim.
This is a living document. When roles change, books are published, or new platforms become relevant, this markup gets updated. But the structure remains the same.
• • •
APPENDIX E: Google Search Console Performance Data
This is the actual Google Search Console performance data for kenny-kane.com from October 2024 through early February 2026. It represents the full timeline of the digital disambiguation project described in this book.
• • •
Monthly Summary
-------------- -------------- ----------------- -------------- -------------- Month Clicks Impressions Avg. CTR Position
Oct 2024 7 680 16.0 1.0%
Nov 2024 9 408 20.9 2.2%
Dec 2024 8 668 21.6 1.2%
Jan 2025 7 1,496 34.9 0.5%
Feb 2025 9 837 23.9 1.1%
Mar 2025 9 941 24.9 1.0%
Apr 2025 7 841 25.7 0.8%
May 2025 14 1,412 25.6 1.0%
Jun 2025 14 2,462 35.4 0.6%
Jul 2025 26 2,961 32.2 0.9%
Aug 2025 52 3,154 21.5 1.6%
Sep 2025 91 3,358 9.6 2.7%
Oct 2025 157 5,800 6.6 2.7%
Nov 2025 206 11,109 7.5 1.9%
Dec 2025 336 19,665 7.3 1.7%
Jan 2026 720 120,878 5.3 0.6%
Feb 2026* 156 38,452 4.5 0.4% -------------- -------------- ----------------- -------------- --------------
*February 2026 is partial (first 5 days only).
• • •
Key Metrics
Click growth (Oct 2024 → Jan 2026): 7 → 720 (103x increase)
Impression growth (Oct 2024 → Jan 2026): 680 → 120,878 (178x increase)
Average position improvement: 16.0 → 5.3 (page two → top five on page one)
February 2026 pace: 156 clicks in 5 days, projecting to exceed January's total.
• • •
Timeline Correlation
The data shows a clear inflection point beginning in September 2025, which correlates directly with the implementation timeline described in this book:
July 2025: First AI citation discovery (Chapter 8). Blog post about positioning organic content for AI discovery published. Clicks begin trending upward.
August 2025: Clicks double from July (26 → 52). Average position improves significantly (32.2 → 21.5).
September 2025: Clicks nearly double again (52 → 91). Average position jumps to 9.6 --- first time consistently on page one. Structured data optimization begins.
October 2025: "Why I'm Investing in Structured Data" blog post published. Clicks reach 157. Position holds at 6.6.
November 2025: Wikidata entry created. Knowledge Panel project completed (Chapter 5). Clicks reach 206. Impressions break 10,000 for first time.
December 2025: System compounds. "My Year in AI" blog post published. Clicks reach 336. Impressions nearly double to 19,665.
January 2026: Breakout month. GEO sourdough starter post and llms.txt post published. Clicks reach 720. Impressions explode to 120,878. Position improves to 5.3.
• • •
What This Data Shows
The growth pattern is not linear --- it's exponential. The system described in this book produces compounding returns. Each piece of infrastructure (structured data, Wikidata, blog content, cross-linking) reinforces the others, and the combined effect accelerates over time.
The first eight months (October 2024 through May 2025) were essentially flat: single-digit clicks, minimal impressions, poor search position. The work during that period --- building the website, writing blog posts, establishing basic presence --- was necessary but insufficient on its own.
The inflection came when the machine-readable infrastructure was added: structured data, Wikidata, the validation loop. The human-readable content and the machine-readable infrastructure together produced results that neither could achieve alone.
That's the thesis of this book, expressed in data.