Should AI Get a Cover Credit?

Here's a question I've been wrestling with: if I use Claude to help me write a book, should that go on the cover?

Not buried in the acknowledgments between my coffee maker and my dog. On the cover. Like those black-and-white Parental Advisory stickers that started appearing on albums in the 90s — a warning label signaling that something inside might be... different.

It sounds absurd when I put it that way. But the conversation around AI and writing has gotten so charged that I think we've lost the plot on what "assistance" actually means.

Where exactly is the line?

I used Grammarly for years. It catches typos, suggests restructuring sentences, occasionally flags that I've used "actually" four times in one paragraph. Nobody has ever suggested Grammarly deserves a co-author credit.

When I wrote for BigCommerce and Practical Ecommerce, my editors did far more invasive work on blog posts — restructuring arguments, cutting sections that weren't landing, pushing me to rethink how I was framing things. The published piece was better because of them. Sometimes significantly better. But the byline was still just my name. That's how editing works.

And then there's the ghostwriting industry, which has quietly existed for decades. Business books, celebrity memoirs, thought leadership from executives who definitely didn't write their own 200 pages. The ghostwriter's name rarely appears anywhere. We've collectively decided that's fine.

So when I use Claude to talk through ideas, to unstick myself when I'm staring at a blank page, to ask "what's the emotional core of this chapter?" — is that fundamentally different? Or are we just spooked because the assistant isn't human?

What AI actually does (at least for me)

I should be specific about how I work with Claude, because I think the discourse has gotten murky. I don't type "write me a book about nonprofit leadership" and paste whatever comes back.

What I do is closer to having a thinking partner. I explain my ideas out loud. Claude asks questions. I realize I haven't thought something through. I talk it out. I write. I get stuck. I describe what I'm trying to say. Claude helps me find the thread.

The ideas are mine. The stories are mine. The perspective comes from fifteen years of building things and screwing things up and learning from both. Claude didn't live that. I did.

But Claude helped me get it onto the page. And I'm genuinely unsure whether that requires a disclaimer.

The warning label problem

Here's what bothers me about the "slap a label on it" approach: it frames AI assistance as something to warn people about. Like explicit lyrics. Like something potentially harmful that consumers need to be protected from.

But those Parental Advisory stickers tell an interesting story. They were meant as warnings, but artists started wearing them as badges. The sticker signaled edge, authenticity, an unwillingness to sanitize. Tipper Gore wanted to protect kids; instead she created a marketing tool.

Would an "AI-Assisted" label work the same way? Would it become a signal that the author is forward-thinking, working at the edge of what's possible? Or would it tank sales because readers assume the book isn't "real"?

I don't know. But I do know that the framing matters enormously.

The question underneath the question

I think the real anxiety isn't about disclosure. It's about authenticity. It's the worry that if AI helped, the work isn't really yours.

But I've never written anything alone. I've had conversations that shaped my thinking. Read books that gave me frameworks. Had editors push back on weak arguments. Collaborated with co-founders who sharpened my ideas through friction.

Writing has always been collaborative, even when only one name goes on the cover. The collaboration just used to be invisible.

Maybe AI makes the assistance more visible, and that visibility is what's uncomfortable. We've been pretending the lone genius author exists. AI pulls back the curtain on a process that was never as solitary as we told ourselves.

Where I've landed (for now)

I don't think AI assistance requires a warning label. I don't think it requires a co-author credit. I think it requires honesty — with yourself about what you actually contributed, and with readers if they ask.

If someone asks me whether I used AI to help write my book, I'll tell them yes. I'll tell them it was like having a really good editor and thinking partner available at 2am when I couldn't sleep and needed to work through a chapter. I'll tell them the ideas and experiences are mine, and Claude helped me articulate them.

But I'm not putting a sticker on the cover.

At least not a warning. Maybe a thank you.

Claude AI for Writing: The Complete Guide for Authors and Content Creators

Introduction

The rise of AI writing tools has changed how we think about authorship. For most creators, the challenge isn’t whether AI can write—it’s how to make it work with your process, not against it.

After years of building organizations and publishing books, I’ve found that Claude AI (especially the 3.5 Sonnet model) is the first system that feels less like a generator and more like a collaborator. It doesn’t try to be the author—it helps you become a better one.

This guide distills how I use Claude to write and edit long-form projects like The Accidental Nonprofiteer and Mission-Driven Ecommerce. Whether you’re a novelist, nonfiction writer, or content creator, you’ll see how to integrate AI into your workflow without losing your voice or authenticity.

What Claude AI Is — and Isn’t

Claude AI, built by Anthropic, is designed for reasoning, writing, and understanding context across long documents. Unlike other AI tools that focus on output volume, Claude emphasizes precision and tone.

I primarily use Claude 3.5 Sonnet (also called Sonnet 4.5)—a balanced model built for speed, depth, and continuity. It’s strong enough to handle book-length manuscripts and responsive enough for quick editing sessions.

But here’s the truth: Claude AI doesn’t write books for you. It helps you write books faster, cleaner, and with better focus. I use it not to generate drafts from scratch but to refine structure, diagnose weak spots, and clarify language. The human remains the author. Claude is the editor you can always reach at 2 a.m.

My Writing Workflow with Claude 3.5 Sonnet

Step 1: Diagnose Before You Generate

When starting a project, I load my early material into Claude and ask it to analyze first. I treat it like a developmental editor. My favorite opening prompt is:

“Before editing anything, tell me what this manuscript is really about and where it loses energy or focus.”

Claude responds with structural and emotional notes that often reveal blind spots. It identifies sections that drift from the thesis or repeat ideas—a level of pattern recognition that’s easy to miss as the author.

The key lesson: don’t ask Claude to write first. Ask it to diagnose.

Step 2: Restructure by Principle, Not Paragraph

Once the big ideas are mapped, I ask Claude to help restructure chapters around principles, not chronology. This is especially powerful for nonfiction, where lessons or frameworks matter more than timeline.

In Mission-Driven Ecommerce, for example, Claude helped reorder sections around themes like community, sustainability, and automation instead of “year one,” “year two,” and so on. The result was tighter and more readable.

Prompt example:

“Reorganize this table of contents around recurring themes rather than chronological events. Prioritize clarity and flow over completeness.”

Step 3: Edit for Tone and Readability

After structure comes tone. Claude is exceptional at mirroring your style once it’s seen enough examples. I’ll often paste two or three paragraphs that capture my voice and say:

“Match this tone—direct, conversational, confident—and apply it across this section.”

Claude will smooth the phrasing without sterilizing it. It’s more like a thoughtful copy editor than an auto-correct engine.

Step 4: Refine and Compress

Claude excels at compression—turning long sections into crisp, readable passages. For blog posts, I’ll feed it a 2,000-word essay and ask:

“Cut this to 1,200 words while preserving flow, rhythm, and human voice.”

The results are surprisingly natural. Sonnet 4.5 balances brevity with empathy, so the rewrite feels human, not mechanical.

Step 5: Final Pass and Contextual Links

For final polishing, I use Claude to surface internal and external link ideas. It naturally suggests where to connect related articles, books, or case studies, improving SEO and reader retention.

Prompt example:

“Suggest relevant internal and external links for this article to improve SEO and reader experience.”

Prompt Techniques that Actually Work

Over time, I’ve found that Claude rewards clarity and collaboration. Here are the principles that matter most:

1. Use Context Windows

Paste entire sections of your work so Claude understands your flow. It performs best when it can see a full scene, chapter, or argument.

2. Give Direction, Not Commands

Claude responds better to framing than instruction. Instead of “Write a better intro,” say:

“Rewrite this introduction to create curiosity and establish credibility within three sentences.”

3. Iterate in Threads

Each draft builds on the last. Keep the conversation alive in a single chat thread so it retains continuity and style memory.

4. Review Together

When you disagree with its suggestion, explain why. Claude refines faster when it understands your editorial reasoning.

How Authors and Creators Can Use Claude

For Nonfiction Books

• Diagnose manuscript structure and chapter order.

• Refine tone and transitions.

• Generate titles, summaries, and keyword phrases for SEO.

• Turn book sections into blog or newsletter content.

For Fiction and Storytelling

• Develop believable dialogue and pacing.

• Create alternate endings or character motivations for review.

• Identify inconsistencies across long drafts.

For Content Creators

• Repackage essays for social media or newsletters.

• Maintain a consistent tone across platforms.

• Generate outlines, meta descriptions, and tag suggestions.

Where Claude Falls Short

Claude isn’t perfect. It doesn’t understand emotional nuance the way a human does. It occasionally over-edits, sanding off voice and rhythm in pursuit of clarity.

You have to guide it—remind it what “human” feels like. I often add prompts such as:

“Keep the imperfections that make this sound human. Avoid over-smoothing or generic phrasing.”

Also, Claude doesn’t replace a real editor. It accelerates your process, but final judgment should always rest with you.

The Ethics of AI-Assisted Writing

AI authorship raises questions about originality and ownership. My position is simple: tools like Claude belong in the process, not the credit.

I wrote my books with AI’s help, not by AI. Claude made the process faster and more organized, but it didn’t replace the thinking, the research, or the experience behind the words.

Transparency matters. If you use AI to help you create, say so. It doesn’t diminish your authorship—it modernizes it.

Integrating Claude Into Your Publishing Workflow

• Draft in Google Docs and move chapters into Claude for review.

• Use Claude for Amazon descriptions and meta data—it’s excellent at writing short, persuasive copy.

• Refine tone for author bios, press kits, and email campaigns.

• Connect posts internally: link this guide to related pieces like How I Used Claude AI to Write My Book (And Why It Wasn't What You Think) and Generative Engine Optimization for Nonprofits: Why It Matters Now.

Claude becomes more useful the longer you use it. Its rhythm starts matching yours.

The Future of Writing With Claude

In 2025, the conversation around AI and creativity isn’t about replacement—it’s about augmentation. Tools like Claude 3.5 Sonnet are making it possible for solo creators to work at the scale of teams without losing quality.

Claude doesn’t compete with your creativity. It protects it—by taking care of the friction that keeps writers from finishing. Outlines, rewrites, titles, tone—it can manage all of it while you stay focused on the story you want to tell.

FAQs

Can Claude AI write a full book?

Not by itself. It can help you structure, edit, and expand content, but your input is essential for voice, story, and direction.

Which Claude AI model is best for writing?

Claude 3.5 Sonnet (4.5) offers the best balance of creativity, speed, and long-context memory. Opus is more advanced but slower; Haiku is lighter and better for quick tasks.

Is it ethical to use AI for writing?

Yes—when used transparently as a collaborator, not a ghostwriter. AI enhances process efficiency, not ownership.

How do I keep my writing voice when using Claude?

Feed Claude multiple samples of your tone before editing. Ask it to match rhythm and diction, not just grammar.

Conclusion

Writing with Claude isn’t about outsourcing creativity—it’s about reclaiming it. It’s a way to collaborate with technology that respects your instincts while eliminating the busywork.

If you treat Claude like a thoughtful editor instead of a content machine, it will help you produce your best work yet. The future of writing isn’t AI or human—it’s the partnership between them.

Why I'm Investing in Structured Data (And Why You Should Care About Schema Markup)

This week, I took a hard look at the structured data on my website. Not because I'm chasing some technical SEO checklist, but because I realized something important: if I don't tell search engines who I am, they'll figure it out on their own. And when there are two other people with my exact name competing for the same search results, I can't afford to leave that interpretation up to chance.

Structured data, specifically schema markup, is how you give search engines the context they need to understand your identity. It's not about gaming the system. It's about clarity. When someone searches for Kenny Kane, I want Google to know exactly which one I am. The CEO and author in Austin, not the comedian in Los Angeles or the rapper in Memphis.

The Problem with Ambiguity

Search engines are good at making educated guesses, but they're not perfect. When you share a name with other public figures, those guesses can go sideways fast. Without structured data, Google has to infer who you are based on scattered signals across the web. Sometimes it gets it right. Sometimes it mixes you up with someone else. And sometimes it just shrugs and shows a little bit of everyone.

That's what was happening to me. My site had basic schema markup, which is better than nothing, but it wasn't doing enough to differentiate me. It listed my roles and my books, but it didn't emphasize the things that make me distinct. My location. My career timeline. My specific affiliations with organizations that have their own authority and recognition.

The more I thought about it, the more I realized that structured data isn't just a technical nicety. It's a strategic asset. It's how you control the narrative before someone even clicks on your site.

What Structured Data Actually Does

Schema markup is a language that search engines understand natively. It's a way of saying, "Here's who I am, here's what I do, here's where I'm based, and here's how I'm connected to these other entities you already recognize." When you implement it properly, you're not just optimizing for search. You're building a knowledge graph that connects you to the rest of the web in a structured, verifiable way.

For me, that means connecting my name to Firmspace, the Testicular Cancer Foundation, and Gryt Health. It means linking my author profile to my books on Amazon and Goodreads. It means specifying that I'm based in Austin, Texas, which immediately sets me apart from the other Kenny Kanes. And eventually, when I have a Wikipedia page, it means linking that page directly into my schema so Google knows it's the authoritative source.

This isn't about vanity. It's about precision. When someone searches for me, I want the results to reflect the work I've actually done, not a blended average of three different people.

Why Location Matters More Than You Think

One of the simplest but most powerful additions I'm making to my schema is geographic information. Adding Austin, Texas as my home location seems almost too obvious, but it's one of the strongest differentiators I have. The comedian is in Los Angeles. The musician is in Memphis. I'm in Austin. That single data point cuts through a lot of confusion.

Location isn't just a detail. It's context. It tells search engines where I operate, what markets I'm connected to, and what communities I'm part of. It also helps with local search, which matters more than people realize. When someone searches for "Kenny Kane Austin" or "Austin CEO," I want to show up. And I want to show up as the definitive result, not as one of several possibilities.

Geographic data also supports other parts of my digital strategy. If I'm speaking at an event in Austin, writing about the Austin tech scene, or getting covered by local media, that location context reinforces the connection. It's one more signal that tells search engines, "This is the Kenny Kane who's based here, who works in these industries, and who's connected to these organizations."

The Role of Disambiguation

There's a specific schema property called "disambiguating description" that I'm adding to my markup. It's exactly what it sounds like: a short statement that clarifies who you are when your name might be confused with someone else's. For me, that description is simple. "American business executive, CEO of Firmspace and Testicular Cancer Foundation, author of The Accidental Nonprofiteer."

That one sentence does a lot of work. It immediately distinguishes me from the comedian and the musician. It highlights my primary roles and my most recognizable credential. And it gives search engines a clear, structured way to categorize me when they're building knowledge panels or answering queries.

Disambiguation isn't just for people with common names. It's for anyone whose identity might overlap with someone else's in search results. If you're in a crowded field, or if your work spans multiple industries, disambiguation helps search engines understand which version of you to show in which context.

Connecting to Authority

One of the most valuable things structured data does is connect you to entities that already have authority in Google's knowledge graph. For me, that means linking to Firmspace, which has its own Wikipedia page. It means linking to the Testicular Cancer Foundation and Gryt Health, both of which have established digital footprints. And it means linking to my books on Amazon, my articles on Forbes, and my profiles on LinkedIn and Crunchbase.

Each of those connections is a signal. It tells search engines that I'm not just claiming to be a CEO or an author. I'm verifiably connected to organizations and platforms that validate those claims. The more of those connections you can establish in your schema, the stronger your knowledge graph becomes.

This is also why pursuing a Wikipedia page is so important. Wikipedia is one of the most authoritative sources in Google's ecosystem. When you have a Wikipedia page, and when that page is linked into your schema, it becomes the anchor for your entire digital identity. It's the single source of truth that everything else connects back to.

Why This Matters for AI Search

There's another reason I'm prioritizing structured data right now, and it has to do with the future of search. AI-powered search engines like ChatGPT, Claude, and Perplexity are becoming more prominent, and they rely heavily on structured data to generate answers. When someone asks an AI, "Who is Kenny Kane?" I want the response to be clear and accurate. Not a guess. Not a blend of multiple people. Just me.

Structured data is how you ensure that AI systems have the right information to work with. It's how you make sure that when these tools pull information about you, they're pulling from authoritative, verified sources rather than making inferences based on incomplete data.

The Long Game

Implementing structured data isn't a one-time project. It's an ongoing process. As my career evolves, as I take on new roles or publish new work, my schema needs to be updated to reflect that. It's part of maintaining your digital presence, just like updating your LinkedIn profile or refreshing your website copy.

But the payoff is worth it. Structured data is one of the few things in SEO that you can control directly. You can't control how other sites link to you, and you can't control how search engines rank your content. But you can control the information you provide about yourself. You can make sure that when search engines are trying to figure out who you are, they have all the context they need to get it right.

For me, that means being deliberate about the details. Adding my location. Clarifying my roles. Connecting my work to the organizations I lead. Linking to authoritative sources that validate my credentials. And eventually, once I have a Wikipedia page, making sure that page is woven into my schema so it becomes the definitive reference point.

If you're in a similar situation, whether it's name confusion or just a lack of clarity in how you show up in search results, structured data is one of the most effective tools you have. It's not flashy, and it's not something most people will ever see directly. But it's foundational. It's how you take control of your digital identity and make sure that when people search for you, they find the right version of your story.

And in a world where your online presence is often the first impression you make, that clarity matters more than ever.

I Asked Lindy AI to Write My Wikipedia Page

This week I asked Lindy AI to generate a Wikipedia page about me. Not to publish on Wikipedia itself, just to see what it could create from my public footprint.

The result looked surprisingly real. It built a full article with an infobox, clean sections, and a references list that linked to my site, Forbes articles, and even my books. It read like something that could actually live on Wikipedia.

Initially, it wasn’t perfect. A few dates were wrong and some sources were thin, but that was the value. It showed me what the internet already says about me, how consistent my story is, and where I could improve the trail of verified information behind it.

I used it as a checklist to tighten my own online narrative. If an AI can build a convincing profile in seconds, it’s a good reminder that your digital presence is always being written, whether you’re involved or not.

AI isn’t just a writing tool anymore. It’s a mirror that reflects your public story back to you. The best thing you can do is make sure it’s reflecting the version you actually want people to see.

Kenny Kane

Kenny Kane

Born

Islip, New York, U.S.

Education

Farmingdale State University (Communications)
LSU Shreveport (MBA)

Occupation

Business executive, entrepreneur, nonprofit leader, author

Known for

CEO of Testicular Cancer Foundation
CEO of Firmspace
Co-Founder of Gryt Health
Author of "The Accidental Nonprofiteer"

Website

kenny-kane.com

Kenny Kane is an American business executive, entrepreneur, author, and nonprofit leader known for his work in healthcare advocacy, technology, and commercial real estate. He currently serves as Chief Executive Officer of both the Testicular Cancer Foundation and Firmspace, and is Co-Founder and Chief Technology Officer of Gryt Health.

Early Life and Education

Kane graduated from Islip High School in June 2005.^[1] He attended Suffolk County Community College (2005-2007) and Binghamton University (2006) before completing his undergraduate studies in Professional Communications at Farmingdale State University of New York (2007-2010).^[1] In 2023, Kane earned his Master of Business Administration (MBA) from LSU Shreveport while continuing his full-time executive roles.^[1][2]

Kane began his career at age 15 as a Pharmacy Technician at Islip Pharmacy & Surgical in Islip, New York, where he worked from 2002 to 2007. He continued in pharmacy roles at CVS Health (2007-2008) and Northwell Health (2007-2010).^[1]

Career

Nonprofit Leadership

Stupid Cancer (2010-2016)

Kane's entry into nonprofit work was inspired by his father's diagnosis with stage 2b testicular cancer.^[3][4] In 2010, while attending a guest lecture at his university, Kane emailed the founder of "I'm Too Young For This! Cancer Foundation" during the presentation and secured an internship.^[5] He joined the organization full-time later that year.

The organization rebranded as Stupid Cancer in 2011, and Kane held progressively senior roles, ultimately serving as Co-Founder and Chief Operating Officer (November 2014 - May 2016).^[1][6][7] During his tenure, Kane helped scale Stupid Cancer into a nationally recognized voice for young adults affected by cancer, launching e-commerce operations, producing national conferences, and leading multi-city awareness campaigns.^[8]

Testicular Cancer Foundation (2016-Present)

In May 2016, the Testicular Cancer Foundation announced the hiring of Kenny Kane as its new Executive Director (later CEO).^[9][10] Kane relocated from New York City to Austin, Texas, to assume the role on June 1, 2016.^[9][10]

Under his leadership, TCF has:

• Expanded digital infrastructure and online reach^[11]
• Modernized fundraising operations^[12]
• Grown the annual TCF Summit into a major resource hub^[13]
• Introduced innovative programs including the world's first AI-powered testicular self-examination tool (2025)^[14]

Kane's role encompasses overall strategy, fundraising, digital transformation, and program execution, with a focus on delivering resources to young men and their families.^[11]

YNPN-NYC

Kane served on the board of Young Nonprofit Professionals Network of New York City (YNPN-NYC), holding positions as Partnerships Chair (August 2014 - December 2015) and Board Chair (January 2016 - June 2016).^[1]

Technology and Healthcare

Gryt Health (2016-Present)

Kane is Co-Founder, Chief Technology Officer, and Board Member of Gryt Health, a survivor-led healthtech company.^[1][15] In this role, he advises on technology strategy, governance, and scaling patient-centered digital health solutions. Gryt Health connects cancer patients globally to community support, clinical trials, and real-time resources.^[15]

Commercial Real Estate

Firmspace (2017-Present)

Kane joined Firmspace, a premium flexible workspace provider, as a Technology and Operations Consultant in May 2017.^[1] He has held multiple leadership positions:

• Technology and Operations Consultant (May 2017 - December 2017)
• Director of Operations (January 2018 - August 2019)
• Vice President of Operations (September 2019 - June 2020)
• Chief Operating Officer (July 2020 - September 2022)
• Chief Executive Officer (October 2022 - Present)^[1][16]

As CEO, Kane oversees all aspects of national operations including finance, HR, IT, AV, security, and facilities for Firmspace's network of premium workspaces across the United States.^[1][16][17]

Writing and Thought Leadership

Kane has been a prolific writer on business operations, digital strategy, and nonprofit management:

Forbes Councils

• Forbes Nonprofit Council Member (March 2017 - February 2018)^[1][18]
• Forbes Business Council Member (July 2020 - June 2022)^[1][19]

Publications

• Practical Ecommerce - Columnist (May 2015 - March 2016)^[1][20]
• BigCommerce - Columnist (October 2014 - November 2015)^[1]

Kane has authored articles on topics including donor cultivation, digital transformation, e-commerce for nonprofits, and operational efficiency.^[18][20][21] His work has been featured in Forbes, Practical Ecommerce, BigCommerce, and other business publications.

Notable articles include:

• "How You Can Get Past Barriers That Keep Potential Donors From Giving" (Forbes, May 2017)^[18]
• "Five Morale-Boosting Tips To Use In A Fundraising Slump" (Forbes, May 2017)^[22]
• "Book Excerpt: Mission-Driven Ecommerce" (Practical Ecommerce, October 2025)^[20]

Books

The Accidental Nonprofiteer (2025)

Kane's first book, "The Accidental Nonprofiteer: Building Systems That Serve Your Mission (Not the Other Way Around)", was published on August 10, 2025.^[23] The book draws from Kane's experience building nonprofit infrastructure from the ground up, beginning with his internship at I'm Too Young For This! Cancer Foundation in 2010.

The book addresses leaders who "never planned to run a nonprofit" but found themselves building organizations to solve problems they encountered personally. Kane shares practical insights on building systems, empowering volunteers, and maintaining mission focus while scaling operations.^[23] The book is available on Amazon and Google Play.

Mission-Driven Ecommerce (2025)

Kane's second book, "Mission-Driven Ecommerce", was announced in October 2025.^[24] The book focuses on e-commerce strategies specifically designed for mission-driven organizations and nonprofits.

Awards and Recognition

• Forbes Business Council Member (2020-2022)^[1][19]
• Forbes Nonprofit Council Member (2017-2018)^[1][18]
• Featured in "Band of Ballers" series by A Ballsy Sense of Tumor (2019)^[4]

Personal Life

Kane is based in Austin, Texas.^[1][10] His career has been significantly influenced by his father's testicular cancer diagnosis, which motivated his dedication to cancer advocacy and patient support.^[3][4]

Philosophy and Leadership Style

Kane describes his approach as "building with purpose, leading with systems, and staying focused on the people we serve."^[1] He is known for his ability to apply cross-industry experience to create innovation, combining tech startup savviness with corporate operational expertise.^[25]

In "The Accidental Nonprofiteer," Kane emphasizes building technology and systems that serve people rather than processes, drawing from lessons learned in customer service, email marketing, and organizational infrastructure.^[23]

External Links

• Personal Website
• LinkedIn Profile
• Amazon Author Page
• Goodreads Author Page
• Testicular Cancer Foundation
• Firmspace
• Gryt Health

References

1. Kane, Kenny. "About Kenny Kane". kenny-kane.com. Retrieved October 23, 2025.
2. Kane, Kenny. "How I Earned My MBA Without Pressing Pause on Life". kenny-kane.com. Retrieved October 23, 2025.
3. "Kenny Kane – CEO of Testicular Cancer Foundation". A Ballsy Sense of Tumor. September 6, 2019. Retrieved October 23, 2025.
4. "Band of Ballers: Kenny Kane – CEO of Testicular Cancer Foundation". aballsysenseoftumor.com. Retrieved October 23, 2025.
5. Kane, Kenny. "From Intern to CEO, and Still Fighting Cancer Like Hell". LinkedIn. Retrieved October 23, 2025.
6. "Kenny Kane - Crunchbase Person Profile". Crunchbase. Retrieved October 23, 2025.
7. "Kenny Kane's Biography". Muck Rack. Retrieved October 23, 2025.
8. "Ecommerce and Building a Thriving Community with Kenny Kane of Stupid Cancer". INspired INsider. Retrieved October 23, 2025.
9. "Non-Profit Expert and Advocate Kenny Kane Tapped as The Testicular Cancer Foundation Executive Director". PRWeb. May 9, 2016. Retrieved October 23, 2025.
10. "Non-Profit Expert and Advocate Kenny Kane Tapped as The Testicular Cancer Foundation Executive Director". Testicular Cancer Foundation. May 9, 2016. Retrieved October 23, 2025.
11. "Testicular Cancer Foundation Donor Cultivation". CauseVox. Retrieved October 23, 2025.
12. Kane, Kenny. "How You Can Get Past Barriers That Keep Potential Donors From Giving". Forbes. May 15, 2017. Retrieved October 23, 2025.
13. "TCF Summit 2025: A Transformative Weekend". Testicular Cancer Foundation. April 28, 2025. Retrieved October 23, 2025.
14. "Introducing: The World's First AI Testicular Self Exam". Testicular Cancer Foundation. August 21, 2025. Retrieved October 23, 2025.
15. "Kenny Kane - Gryt Health". The Org. Retrieved October 23, 2025.
16. "Kenny Kane - Firmspace". The Org. Retrieved October 23, 2025.
17. Kane, Kenny. "What Commercial Real Estate Leaders Need To Know About the Hybrid Work Era". Forbes. July 19, 2021. Retrieved October 23, 2025.
18. Kane, Kenny. "How You Can Get Past Barriers That Keep Potential Donors From Giving". Forbes Nonprofit Council. May 15, 2017. Retrieved October 23, 2025.
19. "Kenny Kane's Profile". Muck Rack. Retrieved October 23, 2025.
20. Kane, Kenny. "Book Excerpt: Mission-Driven Ecommerce". Practical Ecommerce. October 23, 2025. Retrieved October 23, 2025.
21. "Kenny Kane's Articles". Muck Rack. Retrieved October 23, 2025.
22. "Five Morale-Boosting Tips To Use In A Fundraising Slump". Forbes Nonprofit Council. May 18, 2017. Retrieved October 23, 2025.
23. Kane, Kenny. "The Accidental Nonprofiteer: Building Systems That Serve Your Mission (Not the Other Way Around)". kenny-kane.com. August 10, 2025. Retrieved October 23, 2025.
24. Kane, Kenny. "Announcing My Second Book: Mission-Driven Ecommerce". kenny-kane.com. October 18, 2025. Retrieved October 23, 2025.
25. "Testimonials". kenny-kane.com. Retrieved October 23, 2025.

See Also

• Testicular Cancer Foundation
• Stupid Cancer
• Young adult cancer advocacy
• Healthcare technology
• Flexible workspace industry
• Nonprofit management

Beyond the Platform: What GoFundMe Taught Us About Nonprofit Tech Ownership

This week, headlines broke that GoFundMe quietly created fundraising pages for 1.4 million nonprofits across the U.S. Most of those organizations had no idea the pages even existed. It’s a perfect, if uncomfortable, illustration of where nonprofits stand today in the digital landscape. Tech platforms are moving faster than most organizations can keep up with, and if you don’t actively manage your digital presence, someone else will.

That’s not a dig at GoFundMe. Their intent was to make it easier for donors to find and give to nonprofits. But it highlights a bigger truth: digital transformation isn’t optional anymore. It’s not just about adopting tools; it’s about owning your identity, your data, and your narrative in an increasingly automated world.

When platforms create something on your behalf without asking, it’s a sign that your digital footprint isn’t fully under your control. For many nonprofits, that’s the wake-up call. If you’re running a nonprofit today, you have to ask yourself who controls your donor data, where your stories live, and what happens if a platform changes the rules or shuts down tomorrow. For years, we’ve relied on “free” or convenient tech to manage fundraising, communications, and volunteers. But convenience can come with a cost: loss of visibility, fragmented data, or misaligned branding that confuses your supporters. The GoFundMe situation reminds us that digital transformation starts with digital ownership. Before you chase new technology, make sure you truly own the assets that represent your mission online.

Let’s be clear: digital transformation isn’t about buying software. It’s about restructuring how your organization operates around technology that works for you, not the other way around. It means automating what’s repeatable so staff can focus on mission-critical work, connecting systems so fundraising, communications, and program data actually talk to each other, and making decisions based on insight, not instinct. Most importantly, it’s about protecting donor trust by managing data responsibly.

When I started my nonprofit career, we used to duct-tape systems together—email lists in one place, event registrations in another, donor CRM halfway updated somewhere else. It worked, sort of, but it wasn’t transformation. It was survival. True digital transformation is when technology becomes your infrastructure, not your headache. It’s when your organization operates seamlessly, with staff empowered by tools that make their work more meaningful instead of more complicated.

At the heart of any modern nonprofit technology strategy are five ideas: ownership, automation, security, scalability, and literacy. Data ownership means not relying solely on third-party platforms as your donor database and making sure your records are secure, accessible, and exportable. Automation means freeing your team from repetitive administrative tasks so they can focus on building relationships and delivering programs. Security means treating donor information with the highest level of care and transparency, ensuring your supporters know their trust is earned and maintained. Scalability means choosing cloud-based systems that can grow with you rather than hold you back. And digital literacy means making sure your team (not just one tech-savvy person) feels confident navigating and adopting new systems.

If all of this feels overwhelming, start small. Begin with a technology audit to understand where your data lives and who controls it. Then, take back ownership of your digital profiles, including any GoFundMe pages that might have been created without your knowledge. Clean up your logins and security, and identify one process to modernize: maybe automating thank-you messages, consolidating donor records, or streamlining communications between departments. Transformation doesn’t happen overnight. It happens one workflow at a time.

The nonprofits that thrive over the next decade will be those that move as fast as their cause deserves. They’ll understand that “digital” isn’t a department or a project; it’s part of how we lead. If GoFundMe can spin up a million nonprofit pages overnight, imagine what your organization could do with that same energy, but with intention, alignment, and full ownership.

Don’t wait for platforms to define your presence. Define it yourself. Digital transformation isn’t about keeping up with technology; it’s about taking back control of your mission’s digital future.

The Rise and Flux of the Chief Automation Officer

When I first wrote about the Chief Automation Officer a couple years ago, it felt like a defining role for the next decade. Someone had to connect the dots between all the apps, processes, and platforms that were supposed to make work smarter. And for a moment, that was true — automation was the next big thing.

But in tech, “the next big thing” doesn’t stay still for long.

From Big Thing to Background Process

The Chief Automation Officer was meant to be the bridge between operations and technology — a translator of efficiency. Yet, as AI raced onto the scene, automation became less of a job title and more of a feature. What was once a dedicated role is now baked into every SaaS platform, marketing suite, and CRM. Everyone’s an automator now, whether they realize it or not.

That’s not failure — it’s evolution. When a technology matures enough to become invisible, it’s usually a sign it succeeded.

The Flash Analogy

If you ever learned Adobe Flash, you know the feeling.
It was the future once — interactive websites, animations, multimedia experiences. Then browsers changed, standards shifted, and a whole generation of Flash developers had to reinvent themselves almost overnight.

The lesson? Specialization has a shelf life. The web kept evolving, and those who thrived were the ones who understood why things worked, not just how.

Automation is having its Flash moment. The tools are still there, but the world has moved on. What used to be a skill is now an expectation.

Generalists Win the Long Game

This is where being a generalist matters.
If you understand systems, logic, data flow, and human behavior — you can adapt. If you only know one platform or one way of doing things, you’re in trouble.

The best operators today don’t just build Zaps or workflows. They ask better questions:

• What problem am I really solving?

• What happens when this tool disappears?

• How can I design for resilience, not just convenience?

AI didn’t kill automation. It absorbed it.
And that’s the same wave that will roll through dozens of other job titles in the coming years.

Watch for the Signs

You can always tell when a role is about to shift. Suddenly the conferences get quiet. The LinkedIn titles start changing. The tools you used to evangelize start using AI to replace the very thing you were doing manually.

That’s when you know it’s time to evolve again.

Automation isn’t over — it’s just automated. The people who saw that coming are already working on the next layer: intelligence, integration, and insight. The rest are still learning Flash.

Announcing My Second Book: Mission-Driven Ecommerce

Turning a Store Into a System for Good

I’m excited to officially announce the release of my second book, Mission-Driven Ecommerce — now available on Amazon Kindle.

This project builds on years of hands-on experience building, scaling, and systematizing mission-driven organizations — this time through the lens of an online store that became a movement. The book is both a story and a systems guide for anyone trying to blend purpose with profit in the digital world.

About the Book

When I started the Stupid Cancer Store, I didn’t know I was writing a playbook for sustainable impact. I just wanted to create something useful — a way to turn community passion into tangible results.

What began as a handful of T-shirts and hoodies evolved into a $215,000 ecommerce engine supporting thousands of young adults affected by cancer. Mission-Driven Ecommerce captures those lessons and expands them into a repeatable framework for founders, operators, and nonprofit leaders alike.

Inside, I share:

• The full behind-the-scenes story of how the store grew into a national mission platform.

• How to design ecommerce systems that work for you, not against you.

• How automation can serve your values instead of eroding them.

• What it means to scale without losing authenticity.

It’s not a book about viral hacks — it’s about building infrastructure that lasts.

Why I Wrote It

Too often, mission-driven founders feel forced to choose between integrity and growth. This book is my reminder — and hopefully yours — that you can build systems that scale without selling out.

It’s also about reclaiming the operator mindset: being intentional, measuring what matters, and designing your work around impact instead of ego.

If The Accidental Nonprofiteer was about discovering leadership through circumstance, Mission-Driven Ecommerce is about applying those lessons to the digital economy — where every click, system, and sale can reinforce your mission.

Publication Details

• ASIN: B0FWMFSFRC

• Publication Date: October 16, 2025

• Language: English

• Print Length: 112 pages

• File Size: 444 KB

• Simultaneous Device Usage: Unlimited

• Screen Reader & Word Wise: Supported

• Enhanced Typesetting & Page Flip: Enabled

So What Do You Do? Here's My Real Answer

What Do You Actually Do?

It's a question I've been asked countless times at parties, networking events, and even by family members who nod politely while clearly having no idea what I'm talking about. For years, I'd fumble through some variation of my job title or rattle off a list of technologies I work with, watching eyes glaze over in real-time.

But recently, after fifteen years in tech, something clicked. The answer was there all along, hiding in plain sight across every role, every team, every project I've touched.

I enable productivity.

That's it. That's what I do.

The Pattern I Didn't See

Looking back, I can see it everywhere. At Stupid Cancer, I wasn't just managing systems—I was making it possible for a small team to punch way above their weight class. In commercial real estate tech, I wasn't just implementing solutions—I was translating complex systems into tools people could actually use. In every role, the through-line was the same: take something complicated and make it work for real people doing real work.

It turns out my strongest value add isn't any single technical skill. It's technological intuition—that ability to look at a complex system and understand not just how it works, but how to make it work for people. To see the gap between what technology can do and what end users need it to do, and then bridge that gap.

I've always been the person teams come to when something isn't clicking. When a new tool isn't being adopted. When processes feel harder than they should be. When there's a sense that "there has to be a better way to do this."

The AI Moment

Which brings me to where we are right now.

We're standing at the edge of the biggest productivity shift in a generation. AI isn't coming—it's here. But here's what I'm seeing: most teams are either paralyzed by uncertainty or rushing in without the right safeguards. They're stuck between "we need to do something with AI" and "we have no idea where to start" or worse, "we can't risk the security implications."

And this is exactly where fifteen years of making complex systems accessible becomes incredibly relevant.

I know how to help teams adopt transformative technology in a smart, secure way. I understand both the possibilities and the pitfalls. I can translate between the technical and the practical. I can help teams move from anxiety to execution, from complexity to clarity.

This is the next chapter of what I've been doing all along—just with stakes that are higher and possibilities that are bigger than ever before.

What This Actually Looks Like

In practice, this means I'm the person who:

• Sees the bottleneck in a workflow that everyone else has accepted as "just how it is"

• Knows when to implement a sophisticated solution and when a simple one will do

• Can explain technical decisions in ways that make sense to non-technical stakeholders

• Understands that the best technology is the one people will actually use

• Stays ahead of what's coming so teams don't fall behind what's already here

It means I'm not just building or implementing—I'm enabling. Every past and present team I've been part of has been more productive because I was there. Not because I'm the smartest person in the room, but because I have this particular intuition for making technology serve people instead of the other way around.

Why This Work Matters to Me

Here's what makes this deeply satisfying: I've done this across wildly different sectors—nonprofit cancer advocacy, commercial real estate, e-commerce, startups—and the mission never mattered less because of it. In fact, it mattered more.

When I was at Stupid Cancer, making systems more efficient meant our small team could reach more young adults facing cancer. In commercial real estate, simplifying complex workflows meant professionals could focus on serving their clients instead of fighting their tools. Every time I've made technology more accessible, I've amplified someone's ability to do meaningful work.

That's what drives me. Not the technology itself, but what it enables people to accomplish.

Whether it's mission-driven work saving lives or mission-critical work driving business results, the satisfaction comes from the same place: watching teams go from frustrated to empowered, from bottlenecked to flowing, from "we can't" to "we did."

After fifteen years, I've realized this skill set—the combination of deep technical understanding, people-focused thinking, and the intuition to bridge the two—is exactly what organizations need but rarely find. And I'm lucky enough to find fulfillment in work that spans any industry, any mission, any team that needs to do more with what they have.

The Next Chapter

So when someone asks me what I do now, I have clarity: I enable productivity through technological intuition and by making complex systems accessible to the people who need to use them.

We're living through one of the most exciting moments in the history of work. AI is rewriting the rules of what's possible, and watching teams figure out how to harness that potential—thoughtfully, securely, effectively—is genuinely thrilling. The barriers that have slowed us down for years are starting to come down, and the possibilities for what teams can accomplish are expanding faster than ever.

After fifteen years of doing this work in different forms, I'm more energized than ever about what comes next. Not just for me, but for everyone who's willing to embrace the change and do the work to get it right.

Podcast Feature: The Flex Uncensored Podcast — Clarity in Flex with Kenny Kane

Recorded August 30, 2023

I joined hosts Jamie Russo and Giovanni Palavacini on The Flex Uncensored Podcast to talk about Firmspace’s growth, our focus on serving established professionals, and my own path from operations to CEO.

The conversation covered:

• Ideal customers: why Firmspace was built for attorneys, financial services, consultants, and other professionals who value privacy and security.

• My leadership style: servant leadership, staying close to operations, and “extreme ownership.”

• Design + infrastructure: lessons from using demountable walls, acoustic strategies, and how we balance flexibility with confidentiality.

• Brand positioning: why Firmspace is “aspirational but attainable,” offering an alternative between mass-market coworking and long-term direct leases.

We also swapped a few stories—from building spaces over Zoom during COVID, to managing giant rooftop signage projects, to parenting a toddler.

Looking Back at My Binghamton 1.0

Almost ten years ago, I wrote about one of the most formative experiences of my life: earning a 1.0 GPA during my one semester at Binghamton University. At the time, I called it “educational bankruptcy.” I described the noisy dorms, my car being towed on day two, the registration system crashing, and how a bad semester sent me back home to regroup.

Re-reading that post now, I realize how much of my current life is still tethered to the lessons of that time.

• Environment matters. I learned quickly that I couldn’t thrive in a noisy suite or a lecture hall with 300 students. Today, as CEO of Firmspace, I obsess over creating environments where high-caliber professionals can thrive. That thread connects directly back to Binghamton.

• Timing matters. I transferred at the last minute and paid the price in stress and missed opportunities. These days, I preach planning, preparation, and process. Business strategy, like school, punishes you for winging it.

• Systems matter. Watching a university’s registration portal collapse taught me that bad systems create bad experiences. That frustration shaped my love for operational excellence and my belief that details matter.

Back then, I closed the post with a reflection that “failure” sometimes becomes the best thing that ever happens to you. Today, with almost twenty years more perspective, I believe that even more strongly.

My 1.0 didn’t define me, but it did direct me. It pushed me into communications, into nonprofits, into Stupid Cancer, and eventually into leading organizations in health, technology, and commercial real estate.

When I look back now, I see a straight line between the kid who couldn’t sleep through the noise in College-in-the-Woods and the leader who builds quiet, intentional workspaces for others. The setbacks were signals.

So if you’ve ever had a “1.0 moment” — whether in school, work, or life — don’t bury it. Revisit it. Sometimes those moments aren’t the end of the story. They’re the beginning.

Generative Engine Optimization for Nonprofits: Why It Matters Now

For years, nonprofits have invested in search engine optimization (SEO) to ensure that when someone types a question into Google, their mission, programs, and resources are discoverable. But search is changing. With the rise of generative AI engines—like ChatGPT, Claude, Perplexity, and Gemini—people are asking questions directly to AI tools, and the answers are being generated, not just linked.

This shift introduces a new frontier: Generative Engine Optimization (GEO).

What is Generative Engine Optimization?

GEO is the practice of making your nonprofit’s content discoverable, credible, and retrievable by AI-driven search engines. Instead of optimizing for algorithms that rank links, you’re optimizing for large language models (LLMs) that summarize, synthesize, and recommend.

When someone asks, “What organizations support young adult cancer survivors?” you want your nonprofit’s name, story, and resources to appear in the AI-generated answer—not buried in a footnote.

Why Nonprofits Should Care

1. Visibility drives trust and donations
   If generative engines don’t recognize your organization, potential donors, volunteers, or beneficiaries may never know you exist.

2. Mission-critical accuracy
   Many nonprofits work in health, education, or advocacy—fields where misinformation spreads fast. If AI engines generate incomplete or outdated responses, communities lose out.

3. Leveling the playing field
   GEO allows smaller nonprofits to compete with large institutions. AI models don’t just rely on backlinks and budgets—they lean on high-quality, structured, and consistent content.

How to Get Started with GEO

Here are practical steps nonprofits can take to prepare for the generative future of search:

1. Own Your Story with a Blog or Knowledge Hub

AI models rely heavily on first-party sources. Your nonprofit’s blog, resource library, or knowledge hub becomes the raw material for answers. Publish explainers, FAQs, and thought leadership tied directly to your mission.

2. Structure Content for Machines and Humans

Use clear headings, question-based titles, and concise answers. Example: instead of “Our Services,” use “What services does [Nonprofit Name] provide?”. This mirrors the way users ask generative engines for help.

3. Keep Information Fresh

AI tools pull from the most up-to-date information they can access. Outdated pages (old board lists, expired programs) hurt credibility. Regular updates signal trustworthiness to both humans and machines.

4. Build Digital Authority

Mentions on credible partner sites, press coverage, and cross-linking strengthen your nonprofit’s authority. When AI engines triangulate information, they prioritize content that shows up consistently across multiple reputable sources.

5. Experiment with Direct AI Queries

Search for your nonprofit in ChatGPT, Perplexity, or Gemini. See what comes up. Are you mentioned? Is the information correct? If not, you know where to start shaping your content footprint.

GEO as a Mission Strategy

Generative Engine Optimization isn’t just a marketing tactic—it’s a mission-critical strategy. The communities you serve increasingly turn to AI for guidance, resources, and recommendations. Ensuring your nonprofit shows up in those conversations means more people can access your help, join your cause, and trust your expertise.

The shift from SEO to GEO isn’t about abandoning what works—it’s about extending your reach into where the future of search is already happening. Nonprofits that embrace GEO today will be the ones most visible, trusted, and impactful tomorrow.

Why I’m Glad I Never Learned Flash—and How That Shapes What I Choose to Learn About AI

Back in the early 2000s, everyone told me I should learn Flash. It was the thing—the language of slick websites, cool animations, and interactive experiences. I thought about it, but something held me back. Eventually, Flash disappeared, swept away by HTML5, mobile devices, and changing tech standards. And I’ve never regretted not sinking hours (or years) into mastering it.

That lesson has stuck with me: not every technology is worth learning. The tricky part is figuring out which ones are.

Fast-forward to today, and the same question hovers over artificial intelligence. AI feels massive, like the internet did in the ‘90s—too big to ignore. But it’s also moving so fast that it’s easy to wonder: am I learning something that will still matter in two years? Or am I about to sink time into the next Flash?

How I Decide What to Learn in AI

Here’s the framework I’ve been using:

1. Focus on Foundations, Not Tools
   Tools come and go. Flash went. So did Vine. Even ChatGPT will evolve into something else. But the foundation of AI—how models are trained, how prompts shape outputs, how to evaluate trust and bias—those skills translate across platforms. I’d rather learn the concepts than the “hot” app of the moment.

2. Solve Problems I Already Have
   I don’t chase AI for AI’s sake. I ask: what’s something I’m already doing that feels repetitive, time-consuming, or expensive? That’s where I test AI first. If it helps, it sticks. If it doesn’t, I move on.

3. Look for Skills That Compound
   Some learning creates leverage across everything else I do. For me, that means prompt design, data literacy, and understanding how to evaluate outputs. These compound like learning Excel once did—you can apply them everywhere.

4. Keep the Experimental Mindset
   I don’t need to “bet everything” on a single tool. Instead, I run experiments: small, low-stakes tests that show me what’s useful. I treat AI learning less like a college degree and more like a running lab notebook.

The Big Difference from Flash

The difference between Flash and AI is scale. Flash was niche—powerful, but limited. AI isn’t going away. The question isn’t if you should learn it, but how you’ll decide what to learn first.

For me, the lesson is clear: don’t obsess over the shiny tools that might vanish. Invest in understanding the principles, and use them to solve real problems today. That way, even if a tool disappears tomorrow, the time I spent learning won’t.

Your Next Nonprofit Board Member Needs to Be in AI—And You Need to Find Them Now

Nonprofits are facing a moment of reckoning. For decades, boards were built around three things: fundraising, governance, and community representation. Those things still matter—but there’s a new seat at the table that’s no longer optional: artificial intelligence.

Why AI Belongs in the Boardroom

AI isn’t just about ChatGPT spitting out grant applications faster. It’s fundamentally reshaping how organizations manage data, personalize outreach, automate repetitive tasks, and scale impact. For nonprofits that are often understaffed and resource-strapped, these capabilities aren’t “nice-to-have”—they’re lifelines.

If your board doesn’t have someone who understands AI, you’re operating with a blind spot as big as not having anyone with financial expertise. Would you run a nonprofit without a treasurer? Of course not. The same logic now applies to AI.

The Strategic Imperative

Boards are supposed to look around corners. AI is that corner. A board member with AI expertise can:

• Guide responsible adoption so your organization doesn’t get swept up in hype or unintentionally misuse technology.

• Spot opportunities for efficiency—automating back-office work, donor engagement, or even program delivery.

• Ask better questions about vendors, consultants, and data ethics.

• Future-proof your mission by ensuring your organization isn’t left behind as AI becomes embedded in every sector.

Without this perspective, you risk making decisions today that age about as well as putting your entire donor database in a spreadsheet without backups.

Where to Find Them

The good news: AI expertise doesn’t always mean hiring the Chief Scientist of OpenAI. The right board member might be:

• A product manager at a mid-sized tech company building AI-driven tools.

• A data scientist with nonprofit experience who wants to give back.

• An entrepreneur experimenting with AI to solve real-world problems.

They don’t need to have “AI” in their title—they need to have applied AI in a way that aligns with your values.

Why Now

AI isn’t a “someday” issue. It’s here, shaping fundraising strategies, program delivery, and organizational infrastructure right now. The nonprofits that move quickly will set the standard. The ones that wait will spend the next decade playing catch-up.

Adding an AI leader to your board isn’t about trend-chasing. It’s about ensuring your mission remains relevant, efficient, and impactful in a world that’s being rebuilt around algorithms.

Your next board recruitment cycle isn’t complete until you’ve asked: “Who’s bringing AI expertise into this room?”

How I Used Claude AI to Write My Book (And Why It Wasn't What You Think)

Let me be clear from the start: Claude AI didn't write my book. I did.

But without Claude as my writing partner, "The Accidental Nonprofiteer" would still be sitting in a Google Doc as 5,000 words of unfinished potential, just like it had been for the past eight years.

When I tell people I used AI to help finish my book, I usually get one of two reactions: either "That's cheating!" or "Wow, so AI can just write books now?" Both responses miss what actually happened. The reality is more nuanced—and more interesting.

The Problem I Couldn't Solve Alone

By 2016, I had written what I thought was a halfway decent manuscript about nonprofit tech leadership. I had compelling stories from my decade helping build Stupid Cancer, frameworks that I knew worked in practice, and insights that could genuinely help other "accidental nonprofiteers" who found themselves building organizations without formal training.

But I was stuck. What I had read like a collection of really good blog posts, not a coherent book. I couldn't figure out how to create narrative flow between chapters, how to structure the content for maximum impact, or even whether I was writing a memoir or a manual.

Every time I opened the document, I felt overwhelmed. I'd make small edits, rearrange sections, and then close it again, no closer to having something publishable.

Sound familiar? If you've ever started a creative project and gotten lost in the middle, you know exactly what I'm talking about.

What AI Actually Did (And Didn't Do)

When I finally decided to try working with Claude AI, here's what I discovered:

What Claude Did:

• Diagnosed structural problems I couldn't see after staring at the same content for years

• Identified gaps in logic and flow between chapters

• Suggested organizational frameworks that served the content better

• Provided immediate feedback on drafts and revisions

• Helped me see patterns across 5,000 words that I missed when reading linearly

• Asked clarifying questions that forced me to articulate my actual message

• Caught inconsistencies in tone and terminology across chapters

What Claude Didn't Do:

• Write any original content for the book

• Generate the stories, insights, or frameworks

• Create the voice or perspective

• Make editorial decisions about what to include or cut

• Handle the emotional labor of actually finishing a long-term project

Think of it less like "AI wrote my book" and more like "AI helped me become a better editor of my own work."

The Collaboration Process

The actual process looked nothing like asking ChatGPT to "write a book about nonprofits." Instead, it was an iterative partnership that evolved over our collaborative sessions:

Phase 1: The Brutal Diagnosis

I uploaded my entire manuscript and asked Claude to identify what was missing. The response was both validating and devastating: I had good material, but I was trying to write two different books at the same time. I needed to choose between memoir and manual, then restructure everything to serve that choice.

This was feedback I couldn't get from reading my own work. When you're too close to a project, you can't see the forest for the trees.

Phase 2: Structural Surgery

With Claude's help, I reorganized the entire book around a simple principle: use personal stories to illustrate universal principles. Each chapter would start with a specific experience from my early career and building Stupid Cancer, then extract broader lessons that any organization could apply.

Claude was particularly good at saying things like: "This story about volunteer management in Chapter 8 would be more powerful if readers understood the email crisis from Chapter 3 first." Connections I couldn't see became obvious.

Phase 3: Voice and Flow

I'd write new sections or heavily revise existing ones, then share them with Claude for feedback on clarity, tone, and readability. Claude caught when I slipped into nonprofit jargon, when examples needed more context, or when transitions between ideas felt abrupt.

It was like having an editor who could read 5,000 words in seconds and immediately spot what was working and what wasn't.

Phase 4: The Publishing Push

When it came time to actually publish, Claude helped with everything from Kindle formatting to marketing copy to SEO optimization. Having a partner who could seamlessly shift from developmental editing to technical publishing guidance made the whole process less overwhelming.

What This Taught Me About AI and Creativity

AI doesn't replace human creativity—it amplifies it. The stories, insights, and frameworks in my book all came from my actual experience. But Claude helped me see how to organize and present that experience in ways that would serve readers better.

The quality of collaboration depends on the quality of input. Claude could only work with what I gave it. The better I got at asking specific questions and sharing focused excerpts, the more useful the feedback became.

AI is excellent at pattern recognition, good at structure, but you still need to bring the soul. Claude could spot inconsistencies across 11 chapters that I would never catch reading sequentially. But the voice, perspective, and emotional core of the book had to come from me.

Having an always-available writing partner changes everything. No scheduling conflicts, no guilt about "bothering" someone with half-formed ideas, no waiting for feedback. I could work on the book whenever inspiration struck.

The Ethics Question

Some writers worry that using AI diminishes the authenticity of their work. I understand the concern, but I think it misunderstands what's actually happening.

I didn't use AI to generate ideas or write content. I used it to become better at organizing my own ideas and presenting my own content. It's not fundamentally different from using a grammar checker, a developmental editor, or a writing coach—except that it's faster, cheaper, and available 24/7.

The book that resulted is more authentically "mine" than what I had before, not less. Claude helped me figure out what I was actually trying to say and say it more clearly.

For Other Writers Considering AI Partnership

If you're thinking about using AI in your writing process, here's what I learned:

Start with diagnosis, not generation. Don't ask AI to write for you. Ask it to help you understand what's not working in what you've already written.

Be specific about what you need. "Make this better" gets generic responses. "Does this transition work?" or "Is this example clear?" gets useful feedback.

Iterate rapidly. The real value comes from the back-and-forth. Share drafts early and often, use the feedback to guide your next revision, then share again.

Remember you're the author. AI can help you refine your ideas and improve your structure, but the insights and voice have to come from your actual experience and perspective.

Use it for what it's good at. AI excels at spotting patterns, identifying gaps, and suggesting organizational structures. It's less good at understanding nuance, emotional resonance, or what you're really trying to accomplish.

The Bottom Line

Eight years after I wrote the first draft, "The Accidental Nonprofiteer" is finally available on Kindle. It's a better book than what I had in 2016—clearer, more organized, and more useful to the people who need it.

AI didn't write my book. But it helped me write my book better.

And for a perfectionist who had been stuck in revision hell for nearly a decade, that made all the difference.

The technology served the creativity, not the other way around. Which, coincidentally, is exactly the principle I write about throughout the book when it comes to choosing tools that grow with your mission rather than distract from it.

Sometimes the best way to practice what you preach is to get out of your own way and ask for help—even if that help comes from an algorithm.

When You Feel Like You Don’t Belong at the Table You Built

When I co-founded a nonprofit, I thought the hardest part would be fundraising, or managing volunteers, or learning how to read a budget without breaking into hives. I didn’t expect one of the biggest challenges to be… me.

More specifically, the voice in my head that kept whispering:
“You’re not qualified to be here.”
“They’re going to figure out you don’t know what you’re doing.”
“Any day now, someone will ask you to hand in your keys.”

That voice had a name: imposter syndrome.

And it hit me in moments I didn’t expect—sitting in a meeting with hospital executives, walking into a conference where everyone seemed to have degrees I didn’t, even accepting awards for the work I’d done.

Where it comes from

For accidental founders, imposter syndrome often comes from the gap between how you started and where you are now. I didn’t go to school for nonprofit management. I learned systems by breaking them, fundraising by asking awkwardly, and leadership by getting it wrong before I got it right.

When you build something from scratch, you spend so much time figuring it out on the fly that it can feel like everyone else must have a secret playbook you missed.

What I’ve learned

1. Credentials aren’t the only currency. Your lived experience, resilience, and ability to rally people around a cause are just as valuable as formal training.

2. Most people are winging it, too. The folks you’re intimidated by? They’re probably Googling answers under the table.

3. Your mission matters more than your resume. If you’re showing up for the people you serve, you already belong in the room.

4. Preparation quiets the voice. The more you document your work, track your impact, and understand your numbers, the less room there is for self-doubt to creep in.

5. Find your truth-tellers. Surround yourself with people who will remind you of your wins when you can’t see them.

A quiet shift

The turning point for me was realizing that the “real” nonprofit leaders I was comparing myself to… were often comparing themselves to someone else. Everyone feels underqualified when they’re stretching into something bigger.

Now, when I hear that voice, I remind myself: I don’t have to be the most credentialed person in the room. I just have to be the one who cares enough to keep showing up.

If you’ve ever felt like an imposter in your own work, know this: your mission wouldn’t be where it is without you. And if you built the table, you have every right to sit at it.

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If this resonates with you, I go deeper into overcoming imposter syndrome—and other challenges accidental founders face—in my book, The Accidental Nonprofiteer. It’s part field guide, part survival manual, and all hard-earned lessons from my years co-founding and growing a national nonprofit.

Your Tech Stack Shouldn’t Require a Decoder Ring

Between 2010 and 2016, when I was building the nonprofit I co-founded, I treated our tech stack like a puzzle only I could solve. If there was a tool with advanced features, hidden settings, and a learning curve steep enough to scare off the average user, I was all in.

Zapier with multi-step filters? Love it.
Custom-coded WordPress plugins? Yes, please.
Google Sheets with so many formulas it looked like mission control? Absolutely.

And here’s the problem: it worked… as long as I was the one running it.

The moment I went on vacation, got sick, or handed something off to a volunteer, the whole system ground to a halt. Not because the mission was complicated—but because I’d made the tools unnecessarily complex.

Over time, I realized this wasn’t just inconvenient—it was risky. If something happened to me, a lot of the organization’s institutional knowledge and access would disappear overnight. That’s not leadership; that’s gambling with the mission.

Here’s what I learned the hard way:

1. Share passwords like the organization depends on it—because it does.

Stop keeping logins in your head or on scraps of paper. Use a shared password manager like 1Password so anyone with the right permissions can access what they need without emailing passwords around. I’ve seen weeks wasted because a critical account was locked and the only person who knew the password was unreachable.

2. Create internal reference documents while you work.

Every time you run a process—publishing a blog post, sending a Mailchimp email, updating the website—write it down in plain language in a shared document. Not polished manuals. Just clear, step-by-step notes. Over time, you’ll build an internal library that makes onboarding easier and keeps operations from grinding to a halt when someone leaves.

3. Favor adoption over optimization.

Squarespace, Mailchimp, Google Drive—these aren’t “basic,” they’re accessible. Your mission isn’t to impress other tech nerds; it’s to keep your systems usable by the widest number of people. The best tool is the one your team can actually use, even if it’s missing a few features you love.

4. Avoid single points of failure.

If you’re the only one who can update the website, send an email blast, or pull a report, you’re not building a sustainable organization—you’re building a bottleneck. The goal is that someone else could run the core operations tomorrow without calling you for help.

5. Think of operations as a risk management tool.

Your tech stack isn’t just about efficiency—it’s about derisking the mission. Staff turnover, illness, vacations, and even emergencies shouldn’t take the organization offline. If your systems are simple, documented, and accessible, the work can continue seamlessly no matter who’s in the chair.

The fancy tools might make you feel like you’re operating on another level. But the real test of your tech stack isn’t how impressive it looks—it’s whether the mission keeps moving when you’re not at the keyboard.

What Working as a Pharmacy Technician at 15 Taught Me About Life

Most teenagers spend their after-school hours playing video games or hanging out with friends. I spent mine counting pills, managing prescriptions, and learning hard truths about responsibility that would shape who I am today. At 15, I was among the youngest pharmacy technicians, and the experience taught me lessons about accountability, personal brand, and responsibility that no classroom ever could.

The Weight of Real Responsibility

When you're handling medications that people depend on to live, there's no room for teenage carelessness. Every prescription I filled, every pill I counted, every label I printed carried real consequences. A mistake wasn't just a bad grade—it could mean someone didn't get their heart medication on time, or worse.

This wasn't the artificial responsibility of school projects or chores. This was the real deal. Patients trusted me with their health, their insurance information, and their most personal medical details. At an age when most of my peers were learning to be responsible for their homework, I was learning what it meant when other people's wellbeing depended on my accuracy and attention to detail.

The owner of the pharmacy didn't care that I was 15. The medications needed to be right, the insurance claims had to be processed correctly, and the patients deserved the same level of service whether I was having a good day or a terrible one. That taught me that true responsibility isn't about how you feel—it's about showing up and performing regardless of your circumstances.

Building a Personal Brand Before I Knew What One Was

I didn't realize it at the time, but working in a customer-facing role at such a young age was essentially a masterclass in personal branding. Every interaction I had with patients, every phone call with insurance companies, and every conversation with the pharmacist was building my reputation.

Patients would specifically ask for "the young one" when they called in refills, not because of my age, but because I had developed a reputation for being thorough and patient with their questions. I learned that your personal brand isn't what you say about yourself—it's what others consistently experience when they interact with you.

I saw how quickly word spread when someone was unreliable or dismissive. In a small community, your reputation follows you everywhere. This taught me that competence without character is worthless, and that how you make people feel is often more important than what you know.

I quickly learned that the real goal wasn't to be impressive for my age—it was to be genuinely valuable, period. That shift in mindset changed everything about how I approached not just work, but all my commitments.

Accountability in High-Stakes Situations

Nothing teaches accountability faster than making a mistake that affects someone else's health. Early in my time at the pharmacy, I mislabeled a prescription—caught by the pharmacist before it went out, but a stark reminder of what was at stake.

Instead of making excuses about being new or young, I had to own the error completely. I had to understand not just what went wrong, but why it went wrong, and what systems I needed to put in place to prevent it from happening again. The pharmacist didn't coddle me or lower the standards because of my age. The expectation was simple: figure out how to be better.

This experience taught me the difference between taking the blame and taking responsibility. Taking the blame is passive—it's about absorbing consequences. Taking responsibility is active—it's about understanding your role, learning from it, and making changes to prevent future problems.

I learned to speak up immediately when I made mistakes, to ask questions when I wasn't sure about something, and to double-check everything because "I thought I did it right" wasn't an acceptable explanation when someone's medication was involved. This accountability mindset became second nature and served me well in every job and relationship since.

Lessons That Last a Lifetime

Working as a pharmacy technician at 15 gave me a career foundation that extended far beyond healthcare. The precision required taught me attention to detail. The patient interactions taught me empathy and communication. The insurance battles taught me persistence and problem-solving.

But more than the technical skills, it taught me what it means to be someone others can count on. In a world where many people struggle with follow-through and reliability, having learned these lessons early became one of my greatest professional assets.

The experience also taught me the value of competence over credentials. While my peers were focused on getting good grades to get into good colleges to get good jobs, I was already proving my worth in the workplace. I learned that capability speaks louder than potential, and that earning trust through consistent performance opens doors that degrees alone cannot.

The Unexpected Gift of Early Professional Experience

Looking back, starting my career so young wasn't just about earning money or looking impressive on college applications. It was about learning who I could become under pressure, how I responded to real responsibility, and what kind of professional I wanted to be.

Those early lessons about responsibility, personal brand, and accountability became the foundation for everything that followed. They taught me that age is often just a number—what matters is your willingness to learn, your commitment to excellence, and your ability to put others' needs ahead of your own ego.

For any young person considering entering the workforce early, my advice is simple: find a role where the work matters, where mistakes have consequences, and where you'll be held to adult standards. The lessons you learn there will serve you for the rest of your life.

The pharmacy may have been where I learned to count pills, but it's really where I learned to count on myself.

How I Wrote My Own Answer into ChatGPT: Positioning Organic Content for AI Discovery

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Recently, I asked ChatGPT a simple question: Who are the founders of Stupid Cancer?

The first answer I got?
The founder of Stupid Cancer is Matthew Zachary…

Technically not wrong—Matthew was the original founder. But it left something out: me.

I was the co-founder. And for years, my name hadn’t shown up in that answer. But then, something changed. A few weeks after publishing a blog post on my personal site about my journey co-founding Stupid Cancer, I asked again.

This time, ChatGPT responded:
The primary founder of Stupid Cancer is Matthew Zachary… Additionally, Kenny Kane is recognized as an honorary co-founder…”

There it was. My own words, now reflected back at me by the world’s most widely used AI.

And the best part? The source wasn’t Wikipedia. It wasn’t a press release. It was my own blog—the one I control.

That’s when it hit me: in the era of AI, the most valuable SEO isn’t just for human eyes—it’s for the models too.

Writing for the Next Reader: AI

Most of us learned to write for people—your readers, your audience, your customers. But now there’s a new kind of reader: large language models. These systems scour the internet, absorb the information, and distill it into answers for billions of queries.

If you want to be part of the answer, you need to feed them the right story.

Blog Posts as Training Data

The blog post I wrote wasn’t optimized for clicks or keywords. It was personal. I shared my experience co-founding Stupid Cancer, the road trips we ran across the country, and the emotional and operational grit it took to build a movement.

But I also made sure it was:

• Clear: I explicitly used the term co-founder alongside my name

• Credible: It lived on my personal website with other consistent, related content

• Structured: It had headings, timelines, and logical flow

That’s exactly the kind of content that LLMs like ChatGPT look for and train on.

Organic AI Positioning: The New SEO

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What I accidentally did was something every founder, thought leader, and builder should be doing intentionally:
Positioning your content to show up in AI-generated answers.

Here’s what I’ve learned works:

1. Say It Clearly.
   If you were a co-founder, say “I was the co-founder.” Not “I helped start” or “was part of the early team.” AI—and readers—favor clarity.

2. Own the Source.
   Publishing on your own site, under your own name, gives the content authority. It becomes harder to ignore.

3. Match How People Ask Questions.
   Think in prompts. What would someone type into ChatGPT or Google? Write content that answers that exact query.

4. Be Redundant Across Channels.
   If your site, your LinkedIn, and your bios all reinforce the same story, it helps machines (and humans) triangulate what’s true.

5. Structure for Scanning.
   Use headers, bullet points, dates, and facts. Help the model extract meaning easily. You’re not just telling a story—you’re building a data model with words.

From Ghost to Co-Founder

When I first searched, I wasn’t there. The public narrative around Stupid Cancer was incomplete, at least from the AI’s perspective.

But instead of editing Wikipedia or chasing press, I just told my story on my own terms. And now, when someone asks ChatGPT who started Stupid Cancer, it tells them the truth: Matthew and Kenny.

That’s a quiet kind of win. And it might be the future of digital reputation.

From Game Boys to GPTs: Riding the Greatest Tech Wave Ever

Growing up in the ‘80s and ‘90s felt like living on the edge of a digital frontier. I remember the first time I held a Game Boy in my hands—like holding a book, grey, and gloriously pixelated. Tetris never looked so good. Then came the Super Nintendo with its magical purple buttons, delivering Donkey Kong Country and Zelda in vibrant color. PlayStation blew our minds with discs instead of cartridges and the first truly cinematic games. Xbox followed with Halo and LAN parties that redefined "multiplayer."

We weren’t just playing games—we were watching the world shift beneath our feet.

We went from flip phones with snake to the first iPhone, a glass slab that somehow packed the internet, our music libraries, and a camera all into one device. Our generation didn’t read about revolutions in textbooks—we lived through them in real time.

Now, fast forward to today. I’m working in AI and emerging technologies, and the feeling is familiar. That same energy. That same sense of, “Wait... we can do that?” Watching tools like ChatGPT and Lovable go from novelties to industry-changing powerhouses feels a lot like the moment Mario first jumped in 3D or when YouTube suddenly made us all broadcasters. It’s not just a new tool—it’s a whole new way of being.

The shift we’re living through now is arguably bigger than anything before. AI isn't just about efficiency or automation—it’s becoming a partner in how we think, create, and solve problems. It’s helping entrepreneurs move faster, artists dream bigger, and researchers push further. Every day, something drops that makes you rethink what’s possible.

Sometimes I wonder if younger generations will realize how wild it was to go from blowing into NES cartridges to talking with an AI that can write essays, code apps, or compose music. We rode the whole wave. We didn’t just adapt—we evolved with it.

There’s something uniquely lucky about being born at a time when floppy disks, CDs, USB drives, and the cloud all had their moment. We got to experience dial-up and fiber. AOL Instant Messenger and iMessage. We were there for the beep-boop of dial-up, and now we’re watching AI draft legal contracts in milliseconds.

Being part of the generation that played 8-bit games after school and now experiments with machine learning models before dinner? That’s a privilege. And it’s not over.

If the past few decades taught us anything, it’s that the best stuff is always just around the corner. I’m here for it. And if you are too—buckle up. We’ve still got plenty of wave left to ride.

Who Has Your Back?

It's a simple question. But in leadership, life, and the low points in between, it's one of the most important ones you can ask.

We spend a lot of time talking about strategy. Growth plans. Market opportunities. Metrics and margins. But none of that matters if you don’t have people around you who can pick you up when you’re exhausted, call you out when you’re off course, or stand by you when things get messy.

I’ve had the privilege of building teams, leading organizations, and navigating both the nonprofit and for-profit worlds. And here’s something I’ve learned the hard way: It’s not about how many people report to you, or how many people follow you. It’s about who shows up—especially when they don’t have to.

• The colleague who jumps in unasked because they see you drowning in details.

• The mentor who reminds you of your worth when you’ve just failed hard.

• The friend who doesn't need the full backstory to tell you, “You’ve got this.”

I can trace every major inflection point in my life to someone who had my back. A professor who saw something in me before I saw it in myself. A founder who took a chance on me when I was still figuring it out. A board member who reminded me that impact is rarely convenient—and worth it every time.

We all want to believe we’re self-made. But the truth is, nobody does this alone. The higher you climb, the more crucial it is to have people who’ll give you the honest feedback, the hard truths, and the steady encouragement. Not just the ones who applaud your wins—but the ones who sit with you in the losses.

So ask yourself:
Who has your back?
And just as importantly—whose back do you have?

Because in the end, it's not just about what you build.
It's about who you build it with.

“Everyone is a gangster until it’s time to do gangster shit.”

— Tony Soprano