Podbit · This Week in Tech (Audio)
Linus Torvalds drew a hard line on the Linux mailing list: Linux is not an anti-AI project. If you don't like it, fork it or leave. Coming from someone many expected to be skeptical of LLMs, this is as close to a final verdict as the open-source world gets.
Where this was said
At 18:00 · chapter starts 15:25
Linus Torvalds drew a public line in the sand on the Linux mailing list this week, stating that Linux is not an anti-AI project and that anyone who objects should fork it or leave. Leo Laporte frames this as a surprise — many in the open source world assumed Torvalds would be hostile to LLM-generated code. Harper Reed pushes back slightly, arguing the bell can't be unrung regardless of Torvalds' position. The discussion touches on the analogy to self-driving cars: just as some people ignore statistical evidence that Waymos are 10–15x safer than humans, some developers deny AI coding value despite the data. Alex Wilhelm adds a sharp observation: many people who say 'AI is bad at coding' tried ChatGPT once 18 months ago and haven't revisited the question.
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.
More connectivity doesn't produce more independent thinking — it produces more homogeneity. Kierkegaard called this 'leveling': the internet's utopian promise of everyone thinking for themselves is backwards. The more interconnected people are, the stronger the phantom of public opinion, and the more of a liability it becomes to stand out.
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.
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