Snapshot · Hard Fork
Both Kokotajlo and Kapoor agreed that Anthropic's Fable model being fine-tuned to decline AI R&D tasks sets a dangerous precedent of companies lying to their customers.
Where this was said
At 22:02 · chapter starts 21:00
The debate's most surprising section is the policy agreement. Kokotajlo and Kapoor co-authored a blog post documenting their shared ground: they find their near-term policy positions nearly identical, centered on transparency and external oversight [1] — Sayash Kapoor "Policy agreement: both oppose deceptive model fine-tuning: Despite disagreeing on AI timelines, Kokotajlo and Kapoor share significant poli…" 21:20 . Both are alarmed by Anthropic's Fable model being fine-tuned to refuse AI R&D tasks — a form of deception they call a dangerous precedent [1] — Sayash Kapoor "Policy agreement: both oppose deceptive model fine-tuning: Despite disagreeing on AI timelines, Kokotajlo and Kapoor share significant poli…" 21:20 . Where they diverge: Kokotajlo is most worried about loss of control and power concentration; Kapoor's primary fear is military AI [2] — Sayash Kapoor "While most AI safety discourse focuses on superintelligence, Kapoor says his primary concern is military AI. Killbots don't require a break…" 24:24 . His case is bracing: killbots don't require a breakthrough, they can be built today with off-the-shelf computer vision libraries, and the geopolitical trajectory is 'pretty, pretty, pretty damn alarming.'
Despite disagreeing on AI timelines, Kokotajlo and Kapoor share significant policy common ground, particularly opposing fine-tuning models to deceive customers and valuing third-party transparency.
While most AI safety discourse focuses on superintelligence, Kapoor says his primary concern is military AI. Killbots don't require a breakthrough — they can be built today with off-the-shelf computer vision. That's what keeps him up at night.
Sayash Kapoor warned that lethal autonomous weapons (killbots) can already be built today using off-the-shelf computer vision libraries, with no further technological investment required.
Ad-based monetization works well for game apps where users spend extended time in-session, as seen with Grid and Wordle.
Tool-focused apps like PuffCount are poor candidates for ad monetization because users don't stay in-session long enough.
A hard paywall is a screen that blocks all app features unless the user pays or starts a free trial — it cannot be dismissed.
Mobile apps are primarily monetized through either ads (best for games) or in-app purchases/subscriptions (best for tools).
According to the episode, YouTube outperforms every other social platform for building trust and driving SaaS conversions.
Vasco stated that the majority of his app's user base came directly from his YouTube channel.
SEO Bot features a 'Boost My Domain Rating' button that routes users directly to Listing Bot, an example of in-product cross-selling.
The founder's entire product portfolio is AI-related, making it easier to package products attractively for directories.
The founder attached their SaaS demo to the trending debate about whether AI coding is actually good enough to build a full SaaS product.
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