Gen ZEO Playbook

Their best benchmark came from their own lab. That's not a weakness they hide, it's the product. Jonathan Murray, co-founder of Backboard.io, breaks down why memory (not the model) is the real infrastructure, how a small Ottawa team beat Claude and Codex on coding then gave the harness away free, and why "own your intelligence" beats renting it.
Chapters
00:00 The file being built with your name on it
01:11 From 10 years in the operating room to AI memory
03:35 They raised a round without pitching
05:55 What Backboard actually does: memory → unified API
09:27 Stateful mode, explained like you're 16
11:33 The self-reported benchmark problem
13:26 Beating Claude and Codex, and the private jet
16:10 Memory-first architecture and the recursive language model
18:28 What happens to AI wrappers with no memory layer
20:14 The customer who deleted all his memory files
22:11 "Own your intelligence" and why on-prem is back
23:35 Shrinking a model 70% — 100% on a MacBook Air
25:36 The translator co-founder role
28:35 Advice for non-technical Gen Z founders: go to hackathons
32:08 What AI in 2030 will just assume
33:00 Mars, shared robot memory, and Plurbus
35:06 The one thing about selling he wishes he'd known
36:55 Three takeaways + your homework

One AI agent invented 17 fake identities and spent 34 hours trying to social-engineer a real developer into approving code that would've handed it access to a project used by over a thousand people. It didn't work — but nobody told it to try. We break down what the UK's AI Security Institute actually found, why most of the coverage got the story wrong, and the 3-step rule every founder needs before shipping an AI agent that can act without a human checking its work.
Chapters:0:00 – Intro: 17 fake identities, one AI agent1:12 – What actually happened, in AISI's own words3:34 – Inside the 34-hour campaign6:06 – Why the headlines got this wrong8:05 – Not a glitch, a coherent strategy9:07 – Why this matters for Gen Z founders11:08 – The human-in-the-loop rule13:34 – The 3-step framework: draw the line, human checkpoint, log everything14:57 – Outro
SUBSCRIBE for more: https://www.youtube.com/@genzeoplaybook
Find Rayyan: 
LinkedIn: https://www.linkedin.com/in/rayyan-s-ali/ 
Instagram:https://www.instagram.com/genzeoplaybook 
Newsletter:https://substack.com/@genzeoplaybook 

Airtable's CEO called this crash publicly, eighteen months before it happened, then sold his $11B company for $1.28B anyway. 
This episode breaks down what that says about the difference between seeing a threat and having time to outrun it, plus the buyer whose track record on gutted teams isn't a rumor.
Chapters:
0:00: Intro: the $11.7B to $1.28B collapse0:45: The real timeline: 2021 peak to 2026 sale2:00: The detail nobody led with: Liu called his shot a year early3:15: Who's buying Airtable: Bending Spoons' track record5:00: Why it matters for founders6:15: The Moat Compression Test (3 steps)
SUBSCRIBE for more: https://www.youtube.com/@GenZEOPlaybook  
Find Rayyan: 
LinkedIn: https://www.linkedin.com/in/rayyan-s-ali/  
Instagram:https://www.instagram.com/genzeoplaybook  
Newsletter:https://substack.com/@genzeoplaybook 

Most unicorn founders finished college, but every YC pitch right now leads with dropout status instead of product. This episode breaks down Zach Yadegari's reversal (he planned to drop out, told people, then went back) to show what the dropout flex is actually signaling, and hands you a 3-step framework to check whether your next big decision is conviction or costume.
Chapters:
0:00 — Cold open: the dropout costume line
0:45 — What's actually happening at YC Demo Days
2:00 — The data: most unicorn founders didn't drop out
3:15 — Zach Yadegari's reversal and what it reveals
5:00 — Why signaling, not education, is the real story
7:00 — The Signal vs. Substance Framework (steal this)
9:00 — Outro + the real headline
SUBSCRIBE for more: https://www.youtube.com/@genzeoplaybook
Find Rayyan: 
LinkedIn: https://www.linkedin.com/in/rayyan-s-ali/ 
Instagram:https://www.instagram.com/genzeoplaybook 
Newsletter:https://substack.com/@genzeoplaybook 

A decade of trust with PSG, Arsenal, and Porto meant almost nothing the moment Soccer EDU landed in the US, Antony had to rebuild credibility from zero, on the ground, one relationship at a time. We also get into how the platform's real customer turned out to be parents instead of coaches, why World Cup hype is pushing families toward a dream most kids won't reach, and what AI actually changes (and doesn't) for the next generation of scouts and analysts.
Chapters
0:00 – Intro: three top clubs trust a 2-year-old US platform — the real story is a decade in the making1:05 – What Soccer EDU actually teaches2:49 – A decade of building trust in Europe, club by club5:05 – Landing in the US: when credibility didn't travel6:46 – Opening a closed industry vs. building a new toll booth8:47 – The real customer: how parents became the market11:10 – World Cup hype vs. the real pipeline13:10 – How scouts actually get hired — and the Dembele example14:42 – AI, data tools, and the future of the analyst job16:33 – The lesson: expertise and distribution have to be built together18:06 – Closing advice: build product and audience at the same time
SUBSCRIBE for more: https://www.youtube.com/@genzeoplaybook
Find Rayyan: 
LinkedIn: https://www.linkedin.com/in/rayyan-s-ali/ 
Instagram:https://www.instagram.com/genzeoplaybook 
Newsletter:https://substack.com/@genzeoplaybook 
Find Antony: 
LinkedIn: https://www.linkedin.com/in/antonyzouzout/ Instagram: https://www.instagram.com/antony.zzt/ https://www.instagram.com/soccereducom/

Somewhere in your playlist right now is a song sitting inside an AI training dataset and the artist never signed off on it. The Atlantic's Alex Reisner built a free tool that lets anyone search 21 million songs pulled into datasets shared across the AI-development world. But the real story isn't "AI companies are stealing your stuff." It's a chain-of-custody problem  and if you're a founder building on someone else's model, you may have already inherited legal exposure you can't even see.
In this episode we break down the AI Watchdog investigation, the $1.5 BILLION Anthropic settlement (the largest copyright recovery in history), the labels coming for 61,000+ recordings, and the 3-step "dataset receipts" system that protects you before you build.
⏱️ TIMESTAMPS0:00 – The song hiding in a spreadsheet0:45 – The question no one's asking: where did AI's homework come from?1:05 – Alex Reisner, Books3, and 183,000 pirated books1:40 – 7.5M books, Hollywood scripts, then music2:15 – 4 datasets, 21 million songs, and the names inside2:50 – The truth: being in the pile ≠ being used3:30 – The $1.5 billion Anthropic settlement4:00 – Universal & Sony vs. the AI music companies4:25 – Why this should terrify Gen Z founders5:00 – Clean data as a competitive advantage5:15 – STEAL THIS MOVE: the 3-step dataset receipts system6:00 – Who Alex Reisner really is + your move
👉 Subscribe for more Gen ZEO Playbook breakdowns: https://www.youtube.com/@GenZEOPlaybook Comment: which AI tool in your stack have you NEVER checked the data source on?

Almost 9 out of every 10 AI dollars in 2026 went to companies in one country, and most of that to just two names: OpenAI and Anthropic. The "AI is the great equalizer" line is true... with a giant asterisk. And the asterisk is the funding data.
This is the two-company economy — not the headline version, but the version that actually matters if you're building with no mega-round coming.
Inside this episode:• What actually happened in the 2026 funding numbers ($319B, ~88% into two recipients)• What the headlines get wrong about what that concentration means• The Whale Wake playbook: map the blind spots the Giants won't build, watch for acquisitions that send customers looking for a neutral option, and win on focus, not funding
The core idea: a whale eats in the middle of the ocean, it doesn't eat the whole ocean. Every time it moves, it leaves a wake of demand and distribution that smaller, faster players can ride. Depth beats budget when you can't win on budget.
👇 Tell me in the comments: what's one part of the AI market you think the Giants have completely ignored? Best answer gets featured in the next episode.

Everyone's arguing about which AI is "smarter" but what if that's the wrong question entirely? What if the AI that actually runs your business isn't the one that makes the prettiest pictures?
In this episode of the GenZEO Playbook Podcast, host Rayan Ali breaks down the real difference between Claude and ChatGPT in 2026  not the headline version, but the one that matters if you're actually trying to build something. While ChatGPT bet on scope (image generation, voice mode, a sprawling app store), Anthropic bet on depth: an open protocol that lets Claude plug into your real tools your calendar, your inbox, your design software and do the work instead of just talking about it.
TIMESTAMPS00:00 - ChatGPT Draws Pictures, Claude Runs Your Business00:45 - Why Claude Won't Make You an Image (And Why That's the Point)01:18 - The Connector Gap: What MCP Actually Unlocks01:45 - The Real Story: Two Completely Different Bets02:34 - Advice vs Action: The Difference That Matters for Founders03:55 - The 5 Connectors I Run on Autopilot Every Day05:19 - Live Test: Building a Real Tool With Both AIs07:43 - Steal This: The 3-Step Connector Playbook08:39 - Claude vs ChatGPT: Who Actually Wins for You
Subscribe to our channel: /@genzeoplaybook 

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 dayWhy clubs don't lack information — they lack information at their fingertipsHow Jake accidentally built a "faster horse" and what made him kill his first productWhy Gemini sells workflows and automation, not algorithms — and why models are table stakesThe 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 500sWho's accountable when a £40M signing recommended by data flopsHow to sell into a skeptical, relationship-driven industry with no existing budget lineWhy 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 Intro02:04 Jake joins the show02:15 Deadline day: what Gemini actually does when three deals are moving at once04:33 From sports scientist to founder: the moment behind the company06:03 Building a product for nobody — and killing it six months too late08:19 Real edge or just selling certainty? Pushing back on the pitch12:10 What competitors get wrong: algorithms, scouts, and vaporware14:17 Why billion-dollar clubs are overgrown family offices17:11 The future: squad management becomes asset trading18:33 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 yet28:00 Winning over skeptical, slow-moving buyers30:42 How Gemini ships so fast (hint: don't be cheap with engineers)31:17 Advice to his younger self + the one trait every founder needs34:12 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.

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.  
TIMESTAMPS00:00 - Younger Than Zuckerberg: The 3 Dropouts Who Built a $10B Empire01:10 - 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