Founder Mode

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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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

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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EPISODE 70
Kevin and Jason go guest-free for a wide-ranging conversation about what happens when AI starts sounding like you, posting for you, and filling up your inbox. They open by admitting they ran this very episode through an AI video podcast generator and got back a 31-minute clip where neither of them blinked once, then dig into the dead internet theory and why Kevin's real objection isn't that the internet is dead but that it was never trustworthy to begin with — including the moment he discovered more than half of what Perplexity was feeding his research agent came from scraper sites. From there they get practical: why founder thought leadership almost always fails on time rather than talent, the four ways to run it without writing every post yourself, why going viral off a Sam Altman hook produces friends texting you instead of pipeline, and the uncomfortable truth that your actual buyer may be a physician standing at a hot desk logged in under somebody else's name. The back half turns to the mess AI leaves behind — the rise of the "agent inbox," an agent that apologized for taking the weekend off, and why both of them default to the most expensive model available and treat the bill as tuition rather than overhead.

CHAPTERS
00:00 – The $200 brain
00:40 – We made an AI version of this podcast
02:39 – The dead internet theory
04:39 – When Perplexity poisons your own research
05:49 – Watermarks, fingerprints, and who owns your writing
06:55 – Founder thought leadership: worth the time?
09:26 – Four ways to do it without doing it all yourself
12:00 – The rise of the course boi
14:31 – Fish where the fish are
17:11 – The agent inbox
20:49 – Token maxing
25:01 – Founder Mode top five

LINKS
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LinkedIn • X/Twitter
EPISODE 70
Kevin and Jason go guest-free for a wide-ranging conversation about what happens when AI starts sounding like you, posting for you, and filling up your inbox. They open by admitting they ran this very episode through an AI video podcast generator and got back a 31-minute clip where neither of them blinked once, then dig into the dead internet theory and why Kevin's real objection isn't that the internet is dead but that it was never trustworthy to begin with — including the moment he discovered more than half of what Perplexity was feeding his research agent came from scraper sites. From there they get practical: why founder thought leadership almost always fails on time rather than talent, the four ways to run it without writing every post yourself, why going viral off a Sam Altman hook produces friends texting you instead of pipeline, and the uncomfortable truth that your actual buyer may be a physician standing at a hot desk logged in under somebody else's name. The back half turns to the mess AI leaves behind — the rise of the "agent inbox," an agent that apologized for taking the weekend off, and why both of them default to the most expensive model available and treat the bill as tuition rather than overhead.

CHAPTERS
00:00 – The $200 brain
00:40 – We made an AI version of this podcast
02:39 – The dead internet theory
04:39 – When Perplexity poisons your own research
05:49 – Watermarks, fingerprints, and who owns your writing
06:55 – Founder thought leadership: worth the time?
09:26 – Four ways to do it without doing it all yourself
12:00 – The rise of the course boi
14:31 – Fish where the fish are
17:11 – The agent inbox
20:49 – Token maxing
25:01 – Founder Mode top five

LINKS
Stay Connected with Founder Mode
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Connect with Kevin
LinkedIn • X/Twitter

Connect with Jason
LinkedIn • X/Twitter