EPISODE 78

Claire Stapleton spent twelve years at Google and YouTube writing the company's story, from ghostwriting for Larry Page to running YouTube's social media, before she co-organized the 2018 Google Walkout, when 20,000 employees walked out over how the company handled sexual harassment. Kevin and Jason, who started at Google a year before Claire, talk with her about her new memoir, Don't Be Evil. They cover what happens when a company that sells meaning as a perk discovers that meaning is expensive, how Google+ got tied to everyone's bonus, why YouTube's marketing org ended up marketing to its own executives, and why tech workers who once petitioned and walked out have gone quiet. Claire also shares a story that didn't make the book, describes the subway ride home after leaving, explains what it was like to read talking points written about herself, and tells us why she still calls Google a "low key greatest company."

CHAPTERS

00:00 – Cold open

00:41 – Is culture load-bearing or just marketing?

04:07 – Selling meaning as a perk

05:42 – Ghostwriting Larry Page and the cure-death era

08:35 – Google+ and the corporate bonus

10:29 – When the story cracked: Creative Lab

13:18 – YouTube and the brand vulnerability briefing

15:54 – Was advertising the real mission all along?

18:10 – Marketing to executives instead of the public

21:31 – Maven, the walkout, and why workers went quiet

25:21 – Would she organize the walkout again?

28:08 – The subway ride home

32:06 – Where to find Claire and Don't Be Evil

33:13 – The Founder Mode Five

LINKS

Connect with Claire Stapleton

Don't Be Evil • Tech Support • LinkedIn • X/Twitter • Instagram

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EPISODE 76

JJ Zhuang, co-founder and CEO of Pretty Good AI, returns to Founder Mode to answer for the predictions he made on the show over a year ago. Kevin and Jason had Claude grade all ten, and JJ defends his record on hiring generalists over specialists, how much code AI is really writing, why taste is the one thing you can't train into a model, and why slide decks are dead when you can just build the thing. He finishes 6.5 for 10, which beats the weatherman, and points to the release of Opus 4.6 as the moment things that used to not work suddenly started working. In the second half, JJ looks ahead: why Pretty Good AI is skipping the "sell the same widget a thousand times" playbook to become the AI team for healthcare practices, how to build guardrails around AI that's confidently wrong, why the human work that's left will be 100% hard work, how the team keeps protected patient data away from AI agents, and how a lean team can win a crowded healthcare AI market.

CHAPTERS

00:00 – Cold Open: Why Not Just Solve All Your Problems?

00:31 – JJ Returns: Grading 10 Predictions One Year Later

01:58 – Generalists vs. Specialists: Who Should You Hire?

04:39 – Is AI Really Writing Half of All Code?

07:28 – Taste, Comprehension, and the Human Edge

09:58 – Instant Prototypes, Fast Software, and the Death of Slide Decks

12:39 – Directing AI and the Most Overhyped Buzzword

14:32 – Overhyped or Underestimated? The Opus 4.6 Moment

17:09 – The Scorecard: 6.5 for 10

18:00 – Pretty Good AI's Big Bet: Solve Every Problem

20:02 – What Success Looks Like: Becoming Your Customers' AI Team

20:39 – Designing Around AI That's Confidently Wrong

22:20 – Where the Line Between AI and Humans Moves Next

24:09 – Building on Models That Change Every Few Months

25:58 – Compliance When Your Team Is Agents

28:23 – What Patients Notice First

30:17 – How a Lean Team Wins a Crowded Market

LINKS

Connect with JJ Zhuang

Pretty Good AI • LinkedIn • X/Twitter

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EPISODE 75

Kevin and Jason go solo on the week AI stopped asking permission. Jason opens with a Claude Code session that sent a Slack message to a client's CEO instead of drafting it, complete with a "sent from Claude" tag at the bottom, then offered to file a bug report about itself. That kicks off a run through what founders are actually paying for now: Jason's $800-a-month HubSpot bill and his plan to swap it for Dharmesh Shah's $1-a-month USpot, levels.io running a multi-million-dollar business on hand-coded PHP and a single server, and why the "SaaSpocalypse" is more nuanced than Twitter thinks. Kevin traces the freemium playbook back to Zimbra, where 98% of users never paid and the top 2% funded the company, and asks the question that hangs over the whole episode: how do you build trust in a market where everything can be free? They also get into Jason's agentic agency experiment, why succession is really about handing off jobs rather than titles, why nobody has built a marketing agent with taste yet, and the biological age scores every app is suddenly handing out, each one conveniently favoring its own algorithm.

CHAPTERS

00:00 – The Slack message Claude sent by itself

00:39 – A dozen AI tools in a single day

03:46 – $800 a month for a CRM

04:26 – Dharmesh's $1 CRM and the SaaSpocalypse

08:03 – Freemium after vibe coding: the Zimbra lesson

10:32 – Building an agentic agency

13:20 – Succession: hand off jobs, not titles

16:33 – What AI still can't do in marketing

19:18 – Biological age scores and walled-garden health data

22:22 – Founder Mode top five

LINKS

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EPISODE 74

Kiko Zang spent more than half her life pretending to be someone else — born in China, sent alone to boarding school in New Zealand at 12, then to USC at 17, then back to China as the Chinese-looking person who couldn't hold an adult conversation in Chinese. Pretending, as she puts it, was a survival instinct that became one of her strongest skills. In this episode she traces that pattern from the classroom in China where she refused to rehearse a fake PTA lesson, through the years of self-censoring at work, to the full head-to-toe mascot costume she wore around crypto conferences — where, strangely, the expectations placed on a female founder vanished and she got to be more herself than she was without it. Now CEO of Chomp, she's building an app around the gap between what people say in public and what they actually believe in private, and she brings the receipts: 50,000 users, two million answers, and a question about saying "I love you" in the first month of dating that came back 93% green flag when nobody was watching — while every single player assumed it would be a coin flip. Kevin and Jason play a live pack on air, and the conversation moves into why honest human opinion may be the most valuable data set of the AI era, why there's no durable moat in consumer, and what Kiko learned after a co-founder breakup when her own team had to tell her she'd been muting herself in meetings. Her conclusion: the fear felt true not because it was real, but because she believed it was.

CHAPTERS

00:00 – More herself inside the suit

00:40 – Know your audience or know yourself

04:07 – Half a life spent pretending

06:14 – The PTA rehearsal that got her sent abroad

08:34 – The reluctant founder

11:44 – The fursuit and who gets assumed to be the founder

14:05 – Anonymity, honesty, and shared reality

16:12 – Playing Chomp live

19:24 – 93% green flag and the perception gap

22:20 – Pluralistic ignorance and why consumer has no moat

24:31 – Honest opinion as the data of the AI era

27:50 – The co-founder breakup and fears that aren't real

30:06 – Where to find Chomp

LINKS

Connect with Kiko Zang

chomp.fyi • LinkedIn • X/Twitter

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EPISODE 73

Mohammad Moahid has operated multiple companies across e-commerce, consumer electronics distribution, and real estate, and competed for Team Canada as an equestrian. He argues the gap between companies talking about AI and companies actually running on it comes down to ops, not technology. In this episode he explains why leaders are structurally cut off from on-ground reality, why a 5,000-person firm is still managing a hundred active projects out of email threads while million-dollar invoices get written by hand, and where the MIT Nanda study's 95% failure rate really comes from (hint: it's the people layer, not the software). He walks through the "chief agent officer" model, an AI chief of staff coordinating specialist agents across zoning, leasing, acquisitions, and legal. He covers the four pillars he uses to diagnose any business, and the pricing thesis behind what his team calls outcome as a service: you don't pay an accountant for software, you pay so you never think about your books again. Plus what happens to agencies and professional services firms when outcomes get cheaper, and the one thing Mo says humans have to keep owning completely.

CHAPTERS

00:35 – AI as the operating system, not another tool

04:37 – What competing for Team Canada taught Mo about execution

05:23 – Why leaders are always removed from on-ground reality

07:26 – Million-dollar invoices, still written by hand

08:33 – Being his own first customer

09:49 – Why 95% of AI implementations fail

10:45 – The command brief and the four pillars

12:49 – The chief agent officer and the 80/20 rule

14:57 – Outcome as a service: accountant vs. QuickBooks

19:05 – Employee fear, and why agencies should be worried

21:17 – What humans still have to own completely

22:41 – Building your own harness

LINKS

Connect with Mohammad Moahid

zerotoagent.com • LinkedIn • Instagram

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EPISODE 72

No guest and no notes on Jason's side, so Kevin runs the board for once. The two dig into the question underneath every pricing decision: what unit of value are you actually selling? Jason retraces underpricing his agency in the early days and the shift from billing hours to building productized services with near-zero marginal cost, while Kevin walks through losing a deal to a competitor selling raw phone minutes, where the buyer admitted the product was worse and bought it anyway. From there they get into using AI to reconcile invoices against vendor spend down to the penny, a sweep that turned up 23 fraudulent charges and an education in BIN enumeration. They cover the strange state of the market, where a public company doing $275M gets taken private at 2x forward revenue while venture-backed startups raise at 100x. And they close on the AI back office: Kevin's 76 scheduled agents, the 13 supervisor agents he built to watch them, and the eight days of automations that reported success, success, success while quietly writing results to a directory that didn't exist.

CHAPTERS

00:32 – No guest, no notes: a solo episode

00:51 – What unit of value are you actually selling?

02:24 – "I did what most people do and I underpriced"

04:26 – Losing a deal to phone minutes

08:50 – Letting AI reconcile your invoices and vendor spend

12:41 – 23 fraud charges and BIN enumeration

15:02 – Weave goes private: 2x revenue vs. 100x rounds

17:09 – The private and public markets dance

19:21 – 76 agents, 13 supervisors, and "successfully failing"

21:57 – Most people are bad managers

25:34 – DHH's Linux distro and talking to your OS

26:50 – Founder Mode top five

LINKS

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EPISODE 71

Jess Chan built Longplay from an email and SMS agency into a strategic growth partner that has helped more than a hundred e-commerce brands generate hundreds of millions in revenue, and then she handed over the CEO title. In this episode she explains why, and makes the case that the hardest decisions in business are the ones nobody claps for. She talks about letting lucrative client relationships drift on purpose, taking pay cuts, and flatlining revenue for two years to fix the foundations, because a hockey stick for one year often means out of business in three. She breaks down her diagnostic approach to lifecycle marketing and why most people are solving the wrong problem extremely fast and extremely well, describes what she learned building a seven figure agency during the least profitable stretch of her business, and shares the moment she realized a company is like a kid who eventually has to stand on its own. Kevin and Jason open with Kevin's first startup, an embroidery business run out of a one bedroom apartment near UCLA, and the navel gazing loop every early founder falls into. Jess also gets into why she thinks she is better off than Elon Musk, why hurt people hurt people applies to founders more than anyone, the real trade-offs between agency and SaaS after building both, and how she uses AI to buy back space instead of running yesterday's playbook faster.

CHAPTERS

00:00 – Cold open: the founders whose companies become their jobs

01:05 – Henriksen Embroidery, LLC and the navel gazing trap

04:46 – What playing the long game actually means

06:26 – Turning down money on purpose

07:54 – Handing over the CEO title

10:52 – Why email was never the real problem

12:55 – Most people are solving the wrong problem

14:34 – The seven figure agency that wasn't profitable

17:04 – Success, balance, and why Elon sounds miserable

18:35 – Hurt people, hurt people, and that includes founders

20:15 – Agency vs SaaS: choose your hard

23:03 – What AI is great at and what still needs humans

25:37 – Using AI to buy back space

27:46 – The Founder Mode Top Five

LINKS

Connect with Jess Chan

Longplay • LinkedIn • X/Twitter

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