Podbit · On Purpose with Jay Shetty
A great engineer given AI tools becomes a 100x engineer. An entry-level engineer given the same tools just generates more technical debt. AI is an amplifier, not a leveler, and companies that hand it to everyone equally will pay a steep price.
Where this was said
At 48:05 · chapter starts 45:48
Jay asks what three human skills will survive the AI wave. Lucy's answers are precise and unconventional: first, emotional intelligence and the capacity for human connection — AI can draft a contract but cannot close a deal with warmth; second, taste — the ability to select the best output from a hundred AI-generated options; third, and most urgently, the ability to scale your own time using AI before the rest of the market catches up [1] — Lucy Guo "AI can negotiate contracts and write code, but it cannot close a deal with emotional warmth, and it cannot pick the best design from 100 ge…" 44:40 . She then pivots to hiring, revealing that every role in her current companies — including non-technical account executives — now involves a weekend take-home where candidates must use tools like Cursor, Replit, or Claude Code to build a functional bot from scratch. She is not testing output; she is measuring learning velocity, because a fast learner who did not know these tools on Friday can be a 10x employee by Monday, and that potential outweighs years of static experience.
Lucy Guo tests every new hire — including non-technical sales roles — on their ability to build an AI-powered tool over a weekend. She is not just testing output; she is measuring learning trajectory. A fast learner who did not know Cursor on Friday can become a 10x employee by Monday, and that matters more than years of experience.
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.
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.
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