Podbit · All-In with Chamath, Jason, Sacks & Friedberg
Nikesh Arora of Palo Alto Networks told Jason Calacanis that testing a frontier AI model against their own systems was devastating — it found critical bugs in hours that their own team had missed. They halted everything for six weeks of emergency patching. That's the case for government red teaming in a single anecdote.
Where this was said
At 25:20 · chapter starts 16:28
Feldman takes the conversation into longer time horizons. The fundamental constraint on human knowledge is that paradigms shift at the speed of generations: Thomas Kuhn showed us that Freud, Skinner, and their disciples maintained intellectual dominance not because their ideas were right, but because they held positions of leadership until they died. New ideas have to wait for the old guard to exit. AI breaks this constraint. Feldman reaches for the geneticist's tool: fruit flies produce two generations per day, allowing researchers to observe thousands of generations of evolution in a single career. AI is now doing the equivalent for knowledge — compressing what previously took centuries of human intellectual turnover into near-instantaneous iterative cycles. He closes with the Palace of Versailles as metaphor: the builders who worked on century-long projects across multiple family generations were doing recursive, compounding learning. AI is that, but at the speed of compute.
The open source AI landscape has quietly become a geopolitical flashpoint. Outside of OpenAI's OSS model, most available open source options are Chinese. Regulated industries in finance and healthcare that need on-premise, sovereignty-friendly AI have almost nowhere to turn for domestic alternatives.
Nikesh Arora of Palo Alto Networks told Jason Calacanis that when tested with a frontier AI model, it found unknown critical bugs — forcing the company to halt operations and patch for six weeks.
By any definition anyone would have offered 10, 20, or 50 years ago — including the Turing test — we have already hit AGI. The goalposts moved because the reality arrived faster than our imagination could keep up.
Feldman argues that by any definition of AGI used 10, 20, or 50 years ago — including the Turing test — AI has already blown past it.
The fastest path to Twitter growth isn't volume — it's forming sharp opinions about how the platform works and sharing them immediately. People cluster around those who understand the rules and say so out loud.
Sam had no coding knowledge, so he used ChatGPT voice mode to generate his entire codebase and copy-pasted it into Notepad. A friend later introduced him to Cursor, and he never looked back.
Copy days of Discord chat history, paste it into ChatGPT, and ask it to list recurring pain points. The ones that come up most often are your best product bets.
Sam's top advice: when prompting Cursor, tell it to architect code for 100,000 users from day one. The AI changes its approach, building scalable frameworks instead of brittle one-user code.
With AI coding tools like Cursor, Bhanu replicates an existing free tool for a new keyword in under 5 minutes. What used to be a multi-day build is now a lunch-break task.
Ahrefs, SiteGPT, Cal.com, PostHog, Datafast, Sibyl AI, Bento, Feather, Featurepace, Mintlify, Cloud Code, ChartMogul — Bhanu runs his entire business solo with these 12 tools.
PropGPT runs on React Native with TypeScript and Python for ML, Neon for the database, RevenueCat and Superwall for monetization. LLM costs are $20/month, data APIs $100/month, and after $10K in monthly marketing spend, margins sit at roughly 50%.
Game apps keep users engaged long enough for ads to pay off. Tool apps don't — so if you're building a utility, ads are almost always the wrong call and subscriptions are your only real lever.
Inside SEO Bot, a single button labelled 'Boost My Domain Rating' routes users directly to Listing Bot. That one interaction converts a user of one tool into a user of two — without any marketing cost.
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