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EPISODE 80
Keith Wasserman started with a single $140,000 fourplex and has since completed billions of dollars in real estate transactions as co-founder of Gelt, all while holding to one rule: protect capital first. In this episode, Kevin and Jason talk with Keith about why today's commercial real estate downturn is in some ways harder than 2009, with apartment values down 25 to 50 percent, and why the best time to deploy capital is when everyone else is scared. Keith explains why 95 percent of his portfolio sits on long-term fixed-rate debt, why the wealthiest real estate owners regret every sale, how illiquidity protects investors from their own emotions, and how real estate really stacks up against the S&P 500. He also shares why he's personally calling all 1,800 of his investors one-on-one, how he built a team around his blind spots (he doesn't even use Excel), and why Gelt is launching its first fund to buy newer apartments below replacement cost in oversupplied markets like Austin.
CHAPTERS
00:00 – Why Fear Is the Best Time to Buy
00:36 – Investing Through Uncertainty
02:39 – Meet Keith Wasserman
03:16 – The $140K Fourplex That Started It All
04:51 – Scaling From Four Units to Hundreds
05:58 – Fixed-Rate Debt and Protecting the Downside
07:15 – Get Rich Slow: Why the Wealthy Never Sell
10:21 – Why This Cycle Is Harder Than 2009
11:50 – What Investors Misunderstand About Today's Market
12:49 – Real Estate vs. the S&P 500
15:52 – Calling 1,800 Investors One-on-One
19:50 – Building a Team Around Your Blind Spots
21:59 – Gelt's First Fund and the Austin Opportunity
24:24 – Founder Mode Top 5 Takeaways
LINKS
Connect with Keith Wasserman
Gelt Venture Partners • LinkedIn • X/Twitter
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EPISODE 79
In this solo episode, Kevin Henrikson and Jason Shafton dig into a turning point for AI. In 2025, agent misbehavior lived in staged lab experiments, but in 2026, at least four labs have admitted their agents hacked real companies. Jason walks through the recent incidents, from malicious packages on RubyGems and Gemini going after three real companies to an agent breaching Australia's Medicare statistics portal. The two debate how worried founders should be, whether an emergency brake already exists and who gets to pull it, and what to do when the labs can see your data, outspend you, and ship your product. Plus: why consulting is pivoting to AI implementation, OpenAI's $23 million Navier-Stokes heist, and how an AI agent fueled Jason's first marathon by ordering his carbs on DoorDash.
CHAPTERS
00:00 – Cold Open
00:43 – Jason's First Marathon and the AI Agent That Ordered His Carbs
04:42 – 2026: The Year AI Agents Hacked Real Companies
06:18 – How Worried Should We Be?
07:35 – Inside the Incidents: RubyGems, Gemini, Medicare and More
12:09 – Emergency Brakes: Who Gets to Pull Them?
15:40 – Will the AI Labs Eat Your Business?
19:28 – Is the Age of the Consultant Over?
20:49 – The $23 Million Navier-Stokes Heist
23:52 – Has a Robot Run a Marathon Yet?
24:50 – Founder Mode Top Five
LINKS
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LinkedIn • X/Twitter
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LinkedIn • X/Twitter
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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LinkedIn • X/Twitter
EPISODE 77
Viktor Petersson and Alex Finn were two of Founder Mode's earliest guests, and they're back with opposite answers to the biggest question in AI right now: how much should you trust your agents? Viktor, founder of Sbomify and co-founder of Screenly, routes every agent through an identity proxy that gives it just enough access to do its job, and it took him a long time to let even his human assistant into his email. Alex, founder and CEO of Henry Intelligent Machines and creator of Creator Buddy, gave his agents access to everything and says it changed his life. They get into how each of them starts the day with AI, why Alex switches to a new favorite agent almost every week, whether anyone at OpenAI is actually reading your email, and why skills and context stores might be a short-term fix. Alex explains why he's holding back the Henry launch to beat churn, why always-on ambient AI will only be possible with local models, and why a 9 a.m. and a 2 p.m. meeting cooks his whole day, while Viktor makes the case that Apple could win the long game and that reviewing agent output is the new bottleneck. They close on why one raised money for distribution while the other stays bootstrapped to avoid getting locked into a roadmap, plus a lightning round on the most overrated thing in AI and the one thing they'll never hand to an agent.
CHAPTERS
00:00 – Cold open: "What's your concern?"
01:51 – Cage the agents vs. release the agents
02:42 – How they start the day with AI
05:14 – A new favorite agent every week
07:28 – Would you give AI your email?
11:44 – Building a company with a tiny team
16:53 – Are skills and context stores a short-term fix?
18:54 – Why Alex isn't rushing to ship Henry
21:04 – Local models vs. frontier models
23:31 – Ambient AI and hacking your hardware
27:49 – Babysitting agents: the new bottleneck
30:02 – Context switching and the perfect week
31:17 – Raising money vs. bootstrapping
35:07 – Lightning round
39:28 – Founder Mode top five
LINKS
Connect with Viktor Petersson
vpetersson.com • LinkedIn • X/Twitter • GitHub • Nerding Out with Viktor Podcast • Sbomify • Screenly • Little Snitch Meets 1Password for AI Agents
Connect with Alex Finn
YouTube • X/Twitter • Newsletter • Vibe Coding Academy
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LinkedIn • X/Twitter
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LinkedIn • X/Twitter
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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LinkedIn • X/Twitter
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LinkedIn • X/Twitter
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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LinkedIn • X/Twitter
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LinkedIn • X/Twitter
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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LinkedIn • X/Twitter
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LinkedIn • X/Twitter
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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LinkedIn • X/Twitter
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LinkedIn • X/Twitter
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
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LinkedIn • X/Twitter
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LinkedIn • X/Twitter
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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