Podbit · Hard Fork
AI is surprisingly bad at using computers despite it being a verifiable domain. Patel explains why: you can't run millions of parallel training rollouts on the real Amazon or Slack — so labs have to build clones of every website, which is enormously labor-intensive.
Where this was said
At 43:55 · chapter starts 41:40
Kevin Roose asks Patel about his attempts to automate podcast production. Patel notes that most tokens he processes daily are AI-generated — it's clearly making him more productive — but pushes back on the narrative that full job automation is imminent. Casey Newton gives a concrete example: AI can now produce a 4-minute pre-interview briefing document that would have required a full hire previously. Kevin admits he got access to Claude Fable the day before but felt too 'dumb to use it' because he couldn't identify prompts that would stump the previous model. The consensus: AI is genuinely useful, but the full range of human work is consistently underestimated by those predicting imminent automation.
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.
Directory listings are a powerful but underrated growth channel — but only if your product is genuinely interesting enough to earn the click. AI products have a natural advantage here because they're easy to package in a compelling, clickable way.
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.
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