Once Theo and Ben spent time with GPT-5.6, returning to 5.5 wasn't just annoying — it was actively painful. Their mental bar for what an AI should do had been reset by the new model, so 5.5's tendency to stop mid-task and ask for permission felt far worse than it ever had before.
Where this was said
At 7:30 · chapter starts 7:00
Theo and Ben dig into their actual day-to-day experience with 5.6, and the clearest signal emerges not from the model itself but from the regression to 5.5. Theo describes the single most noticeable change: 5.6 doesn't stop after the first part of a task and ask for permission to continue [1] — Theo "5.5→5.6 regression: 1/5th completion: When forced back to GPT-5.5 during testing, tasks that 5.6 happily ran to completion got only about a…" 08:10 . That habit was one of his biggest frustrations with 5.5, and with 5.6, it simply vanished. When forced back to 5.5 during testing windows, similar tasks got only about a fifth of the way through before stopping — a stark regression. Ben adds a philosophical point: the best AI is the one you don't notice [2] — Ben "I notice Phi-5 more than I notice the new model, which is huge. Like, that's what you want AI to do. If you notice it, it's bad." 09:20 . He'd previously thought 5.5 was so good that future model improvements would be imperceptible — he was entirely wrong. The hosts also flag the deeper cognitive dynamic: spending time with a better model raises your expectations, which then makes the older model feel far worse than it ever did before.
When forced back to GPT-5.5 during testing, tasks that 5.6 happily ran to completion got only about a fifth of the way through before stopping.
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.
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.
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