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Dylan Field described 'vibemath-ing' — using AI to explore mathematical problems — as a way to test verifiable AI capabilities in contrast to the subjective nature of design evaluation.
Where this was said
At 6:22 · chapter starts 6:08
Asked whether he has 'AI psychosis,' Field laughs and says it's better to front-run it than let it sneak up on you. His current obsession is what he calls 'vibemath-ing' — using AI to explore mathematical problems, not to prove theorems, but to study how AI attacks verifiable problems. [1] — Dylan Field "Dylan Field is using AI to tackle math problems — what he calls 'vibemath-ing' — because math is one of the few domains where AI correctnes…" 06:22 He contrasts this with design evaluation, where two people can look at the same thing and reach opposite conclusions; in math, the answer is right or it isn't. This love of exploration has a longer backstory: Field says he was into crypto collectibles (now NFTs) early on, and before that, WebGL, the browser graphics technology that eventually became the technical foundation for Figma. The pattern, he argues, is consistent — go deep on something before you know where it leads, and it pays off in ways you can't anticipate.
Dylan Field is using AI to tackle math problems — what he calls 'vibemath-ing' — because math is one of the few domains where AI correctness is black and white. It's the polar opposite of design evaluation, and he thinks exploring the edges of what models can do pays off in unexpected ways.
Dylan Field said his early exploration of WebGL was a key technology that eventually led to the founding of Figma.
Kevin Roose's theory: CEOs are obsessed with vibe coding because it reminds them of when their jobs were fun. Dylan Field's take: people love making things, and AI is democratizing that for everyone — not just executives building weekend projects.
Dylan Field pushes back on the 'design is dead' narrative. When AI generates the average, having genuine creative voice and pushing beyond the first output is exactly how you stand out. The App Store has more apps than ever — but the same number are actually being used.
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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