EPISODE 54

Kevin and Jason break down why Anthropic is out of compute, why that's actually a strategy, and what it means for everyone using Claude right now. They dig into the Mythos model as the best marketing moment in AI, why artificial scarcity works, and why $200/month for Claude Max is the cheapest hire you'll ever make. Then they shift to AI in the enterprise — why one "AI Week" won't rewire your company, why Anthropic's one-person growth marketing team is the new bar, and the playbook for founders selling into big companies: pick a hard enough wedge, stop selling the product, and sell transformation instead.

CHAPTERS

00:00 – Cold Open: The Mythos Model Is Too Good To Release

00:35 – Welcome to Founder Mode

00:59 – Why Anthropic Is Out of Compute

02:28 – Good Customer, Bad Customer: Who's to Blame?

04:00 – $200/Month Is the Cheapest Hire You'll Ever Get

05:31 – Token Maxing and the New Scarcity

07:01 – How to Fire Bad Customers (And Why Anthropic Is Doing It Wrong)

10:50 – The Mythos Model: The Best Marketing Moment in AI

13:19 – AI in the Enterprise: Why One AI Week Isn't Enough

18:25 – The "One More Prompt" Flow State

19:57 – Selling Into Enterprise: Pick a Hard Wedge, Sell Transformation

22:48 – Closing Takeaways and Top Five

LINKS

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EPISODE 53

In this episode, Kevin and Jason sit down with Shain Noor, co-founder of Silvia, an AI-powered personal CFO built to help people reason through financial decisions, not just track them. Shain explains why the entire history of personal finance apps has focused on clicking and aggregating data rather than helping users actually decide what to do, and how Silvia uses Anthropic-powered agents with a verification layer to deliver trustworthy, personalized financial guidance. The conversation covers the co-pilot vs. autopilot distinction, the surprising discovery that users ask Silvia things they'd never tell their human financial advisor, how proactive alerts like the daily summary email drove retention, and why building the reasoning layer first, before adding any execution or action capabilities, is the right foundation for trust.

CHAPTERS

00:00 - The judgment-free financial advisor

02:38 - Introducing Shain Noor and Silvia

03:51 - Why finance apps have always missed the reasoning layer

05:51 - Co-pilot vs. autopilot: trust, transparency, and guardrails

08:29 - What surprised Shain: users sharing what they hide from their advisors

12:42 - Measuring retention and the proactive alerts breakthrough

17:02 - Team size, the ProCap merger, and competing with legacy finance

19:41 - The future: everyone becomes a manager of AI agents

LINKS

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Silvia • LinkedIn • X/Twitter

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EPISODE 52

Jason Shafton and Kevin Henrikson unpack where AI is genuinely useful and where it starts to create more noise than leverage, using examples from AI email triage, long chat memory drift, and agentic workflows. Kevin explains how memory can become polluted when models start treating their own prior inferences as fact, including a prompt he used to compare what an AI thought was “ground truth” against what he had actually told it. From there, the conversation shifts into a practical framework for building AI systems and human teams the same way: define the job, provide the right tools and access, layer in review and guardrails, and judge success by whether time spent together compounds into more output. They close by connecting startup hiring, high-agency operators, and founder-led culture back to the same core test they use for AI: does this person or tool create leverage, or does it create drag?

CHAPTERS

00:00 – AI memory drift and false “ground truth”

01:24 – Testing AI email triage and the risks of over-filtering

03:13 – Good AI versus bad AI in real workflows

05:31 – Why controlled memory leads to more consistent AI outputs

08:29 – How to apply AI to workflows that currently rely on humans

11:12 – Building multi-agent content systems with clear roles and QA

13:40 – Hiring high-agency people for early-stage teams

16:01 – The “pick up the shovel” standard for startup operators

22:36 – The real test for both employees and AI: leverage or drag

26:16 – Founder Mode Top 5 Takeaways

LINKS

Connect with Kevin Henrikson

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