He Killed His Own Product After 6 Months, Then Raised $7M

He Killed His Own Product After 6 Months, Then Raised $7M

Football clubs spend billions on players, and a shocking number of those decisions still come down to an agent's text and a gut feeling.  Jake Schuster is building the AI that changes who makes that call. In this episode of the Gen ZEO Playbook, Rayyan Ali sits down with Jake Schuster, founder of Gemini Sports, the AI co-pilot for sporting directors. Jake has raised around $7 million, his investors own 27 sports organizations around the world, and his customers have ranged from the Indianapolis Colts in the NFL to European football clubs like Parma and Monaco. The twist: he's not a career technologist. He's a former sports scientist who worked with elite programs in the run-up to the 2016 Olympics and got tired of fighting MATLAB, SQL, and Python just to answer basic questions about his players. We get into why football's biggest transfers still happen over WhatsApp, why he killed his first product six months too late, and why "being clever is commoditized" in sports tech. What you'll learn: -What an AI co-pilot for sporting directors actually does on a chaotic transfer deadline day Why clubs don't lack information — they lack information at their fingertips How Jake accidentally built a "faster horse" and what made him kill his first product Why Gemini sells workflows and automation, not algorithms — and why models are table stakes The three ways sports tech competitors are missing the point (and the fake "head of AI" problem) Why billion-dollar clubs are run like overgrown family offices, decades behind Fortune 500s Who's accountable when a £40M signing recommended by data flops How to sell into a skeptical, relationship-driven industry with no existing budget line Why shipping real product updates every three weeks is "breaking people's brains" Why pain tolerance, not intelligence, is the only quality a founder actually needs Chapters: 00:00 Intro 02:04 Jake joins the show 02:15 Deadline day: what Gemini actually does when three deals are moving at once 04:33 From sports scientist to founder: the moment behind the company 06:03 Building a product for nobody — and killing it six months too late 08:19 Real edge or just selling certainty? Pushing back on the pitch 12:10 What competitors get wrong: algorithms, scouts, and vaporware 14:17 Why billion-dollar clubs are overgrown family offices 17:11 The future: squad management becomes asset trading 18:33 The £40M flop question: who takes the blame — the director or the algorithm? 22:40 Useful co-pilot or expensive blame machine? 24:26 Selling a category that doesn't exist yet 28:00 Winning over skeptical, slow-moving buyers 30:42 How Gemini ships so fast (hint: don't be cheap with engineers) 31:17 Advice to his younger self + the one trait every founder needs 34:12 Rayyan's three takeaways and your homework About Jake Schuster: Jake is the founder of Gemini Sports, an AI co-pilot that unifies recruitment, finance, and analysis for sporting directors — on their phone, where the football industry actually lives. A former sports scientist who worked with elite Olympic and rugby programs, he's raised ~$7M from investors who own 27 sports organizations worldwide. Connect with Jake: https://www.linkedin.com/in/jake-george-schuster/ About the show: The GenZEO Playbook is a podcast on founders, building, and the shifts that decide who wins next. New episodes on YouTube and wherever you listen.

Three Kids From a Debate Team Built a $10B Company. Here's the Playbook.

How did three college dropouts build a $10 Billion company in less than two years, becoming self-made billionaires at an age younger than Mark Zuckerberg?   In this episode of the GenZEO Playbook Podcast, host Rayan Ali breaks down the incredible rise of Mercor, a startup founded in 2023 that hit a $10B valuation by October 2025. While everyone else was racing to build flashy chatbots, these founders won by owning the single most unglamorous, boring layer of the AI revolution: grading AI homework for giants like OpenAI and Anthropic.   Steal their exact 3-part growth playbook to build your own leverage in the tech space: - Judgment Arbitrage: How to get rich by finding and supplying the human expert bottlenecks that AI labs desperately need. - The Reverse Raise: The exact strategy they used to raise millions from a position of total power, allowing them to dictate terms to elite investors like Peter Thiel. - Replacement Pain: How to bulletproof your startup so your biggest customers don't wake up and decide to build your product in-house.  Stop believing the myth of the genius dropout. Mercor’s success wasn't magic, it was positioning.   TIMESTAMPS 00:00 - Younger Than Zuckerberg: The 3 Dropouts Who Built a $10B Empire 01:10 - The Secret Layer Underneath OpenAI & Anthropic   02:15 - Framework 1: How Judgment Arbitrage Works   04:10 - Framework 2: The "Reverse Raise" (Fundraising With Total Leverage)   06:00 - Framework 3: Preventing OpenAI From Eating Your Company   08:30 - The Dark Side of $10B: The Myth of Non-Stop Burnout   Subscribe to the Gen ZEO Playbook YouTube channel: https://www.youtube.com/@genzeoplaybook [https://www.youtube.com/@genzeoplaybook]

SEO Is Dead. Here's How to Get Your Business Found Inside ChatGPT

SEO isn't dead, it's evolving into something bigger and more lucrative. In this episode of the GenZEO Playbook, Jason Patel breaks down why the next gold rush isn't building AI, it's getting found inside of it. Jason is a two time founder who built and sold an EdTech company called Transition, and his new company, Open Forge AI, helps businesses rank higher and more often inside AI search engines like ChatGPT, Gemini, and Claude. The twist: he doesn't have a computer science degree. He studied political communication, and he argues the team that tells you the truth beats the team that codes the fastest. We get into what answer engine optimization (AEO) actually means, how a non-technical founder built an AI company, and why distribution, not the product, is the new moat. What you'll learn: - What answer engine optimization (AEO) is and how it differs from traditional SEO - Why customers from AI search convert better even when total traffic drops 20 to 30% - How to get cited inside ChatGPT, Gemini, and Claude answers - Why a non-technical founder can win the AI gold rush with communication over code - How Open Forge tracks black-box citation changes across AI engines in real time - Why LinkedIn pulse articles and posts are getting picked up by AI search - How to build a team with the psychological safety to tell you the truth before it costs you a year - Why adapting and changing course is evolving, not giving up Chapters: 00:00 Intro 00:55 Who is Jason Patel 02:31 What Open Forge does and what AEO means 12:45 Why customers buy more even as traffic drops 16:06 Selling visibility inside a black box you can't control 16:40 Staying on top of citation changes in real time 19:13 Building a team that tells you the truth 21:29 Does a supportive workplace breed the bare minimum 23:16 Catapult or crutch: what you're really selling 24:26 Advice to his $80K-in-debt younger self 26:05 Host's three takeaways and your homework About Jason Patel: Jason Patel [https://www.linkedin.com/in/pateljason/] is a two time founder who built and sold the EdTech company Transition. His new venture, Open Forge AI, helps businesses get cited and discovered inside AI search engines. He studied political communication and believes communication, not just engineering, is the edge in the AI era. About the show: The Gen ZEO Playbook [https://www.youtube.com/@genzeoplaybook] is a podcast on founders, building, and the shifts that decide who wins next. New episodes on YouTube and wherever you listen.

PewDiePie's Odyssey: Why 16-Year-Old Founders Should Be Worried

PewDiePie just shipped a free, self-hosted AI tool, called it his "trillion dollar project," and opened with one line: the war on Big Tech has just begun. It pulled 62,000 GitHub stars in under 7 days, a number most VC-backed startups never hit in a full year. But strip the branding and you find the same script we already watched four months ago. In this episode I break down what actually shipped, why it looks identical to the last hype cycle right before reality showed up, and the one 10-minute test you should run on this product (and on your own startup idea) this week. What you'll learn: - Why 62,000 GitHub stars tells you everything about reach and nothing about retention - The difference between a borrowed engine (the model) and a real moat (distribution, trust, data ownership) - Why "free and open source" is a strategy, not a personality, and why it kills your pricing power - The security catch nobody is putting in their thumbnails: an agent running with no sandbox on your machine - The "borrowed engine" problem that will hit every AI idea you build on top of someone else's model - The 3-question wrapper test: find the engine, name the moat, run the lab catch test - How to tell in one sentence whether you have a company or just a great feature Chapters: 00:00 The one-line take: hype is faster than the moat 00:46 The setup: what we're breaking down and 3 things to cover 01:15 What actually happened (the 60-second version) 01:32 Inside the product: self-hosted, open source, autonomous agents 02:15 The numbers: 62K GitHub stars in 7 days 02:38 The privacy-first pitch: "yours and yours forever" 02:59 The part headlines skip: we ran this experiment 4 months ago 04:06 Borrowed engine vs. what's actually his 04:14 The security catch: no sandbox, admin-level access 04:35 Why this matters for Gen Z founders 05:05 Distribution can fake a moat 05:26 "Free" is a strategy, not a personality 06:04 The borrowed-engine problem hits your idea too 06:23 The wrapper test: 3 questions to run this week 07:20 Where this lands: not a scam, not a revolution About the show: The GenZEO Playbook breaks down the products, hype cycles, and founder lessons that actually matter, from the POV of a 16-year-old building his own stack. Subscribe here: https://www.youtube.com/@genzeoplaybook [https://www.youtube.com/@genzeoplaybook]

FIFA Spent $500M on Scouting. A Startup Is About to Make That Worthless

In 2007, Stephan Maric [https://www.linkedin.com/in/stephanmaric/] built one of the first social networks for sports fans, before "sports tech" was even a phrase. It didn't become the giant he imagined. Almost 20 years later, he's betting on the exact same obsession again, this time with AI. In this episode of the GenZEO Playbook, Stephan walks through building Defans, the AI sports assistant he calls "ChatGPT, but for sports," and what his 2026 self knows that his 2007 self got wrong. We get into being early without being right, why timing beats ideas, and how a small startup survives when Google and ESPN are circling the same field. Stephan breaks down why a product anyone can copy in a weekend is just a feature, not a moat, and why for an AI product, trust is the real product: get one live score wrong and you lose that fan forever. He also shares how Defans is built with tools like Lovable, Google Cloud, Codex, and vibe coding, how the team grew to millions of organic views on TikTok, Instagram, and Facebook with zero ad spend, and the revenue model rolling out this summer (a $3.90/month subscription, in-app ads, and ticket links). If you're a founder, builder, or 16-year-old obsessed with sports who secretly wants to build something, this one is for you. Chapters 00:00 Intro 02:34 What Defans actually does 03:48 Why they added voice to text 05:08 What everyone missed about sports tech in 2007 06:35 What his 2026 self knows that his 2007 self got wrong 08:16 Dreaming of a worldwide sports brand 09:35 What stops a competitor from copying you in a weekend 12:18 Keeping an AI honest when data changes every 10 seconds 13:36 How Defans plans to make money 15:14 The five years away, and why he came back 16:48 Getting your first real users with zero audience 18:01 One thing to start doing this week 19:36 Three takeaways: early vs right, moats, and trust Subscribe to the Gen ZEO Playbook for more founder breakdowns. Drop a comment with the one founder you want broken down next. https://www.youtube.com/@genzeoplaybook [https://www.youtube.com/@genzeoplaybook]  #sportstech #AIstartup #founderstory #startup #entrepreneurship