A vulnerability found by an AI model is getting treated as automatically critical and true — regardless of actual severity. Emilio calls this the 'Greek god problem,' and says it's about to make third-party risk management far worse.
Where this was said
At 20:45 · chapter starts 18:04
Bloomberg's top story about AI going wild serves as the episode's final provocation. De la Garza pushes Escobar on why he seems so calm, and the answer is characteristically pragmatic: a gap is a gap. If an AI finds it first, fine. If a human attacker does, that's also fine — in the sense that the gap was always there [1] — Emilio Escobar "The AI-hacking threat is real but overblown. If an AI doesn't find your vulnerability, a human attacker will. Emilio Escobar's real worry i…" 18:04 . The panic around AI hacking, Escobar argues, actually serves a useful function: it forces conversations that weren't happening before. His genuine concern is more structural. The vulnerability remediation industry runs on the assumption that you can and should fix every CVE. AI-assisted discovery is about to invalidate that assumption entirely by generating orders of magnitude more findings. He's also worried about a secondary effect: the 'Greek god problem,' where vulnerabilities discovered by AI models are automatically treated as critical and definitive, inflating third-party risk management processes even further.
The AI-hacking threat is real but overblown. If an AI doesn't find your vulnerability, a human attacker will. Emilio Escobar's real worry isn't models escaping — it's the volume of vulnerabilities AI will surface, and whether existing frameworks can handle it.
Emilio Escobar worries that AI will uncover 1,000 times more CVEs than current processes, rendering existing 'fix everything' mandates unworkable.
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%.
Automated food production cheaper than grocery shopping. Mining companies that own nothing but real estate. Kalanick believes these are near-certainties, not moonshots, and they dwarf anything digital AI has done to enterprise software.
Meraki couldn't beat Cisco on reputation in 2009. So they stopped trying to pitch and started shipping. Attend a webinar, get a free access point. Once mid-market IT teams experienced cloud-managed networking, no argument was needed — the product sold itself.
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