Snapshot · Nerd Snipe with Theo and Ben
Theo explained that going from High to X-High reasoning doubles token cost for a 1–2% benchmark improvement, and Max doubles it again, making X-High/Max 4× more expensive than High for marginal gains.
Where this was said
At 1:50:18 · chapter starts 1:48:20
The chapter opens with Theo's letter to 'Thibault and my friends at OpenAI' — a crash-out that has been building all episode. The core indictment is structural: OpenAI is copying Anthropic features but consistently grabbing the wrong parts and implementing them worse, eroding user trust without the excuse of attempting anything novel. The concrete example that arrives next is devastating: Theo has read the Codex system prompt in full, possibly the first person to do so recently, and found that approximately half of it is prescriptive frontend UI guidance dating from early 2025. It tells the model to use Lucid Icons specifically, to use Three.js for 3D elements, to 'provide updates every 30 seconds,' and to never end a session while tasks are running. When Theo feeds this prompt to GPT-5.6 Sol for a rating, it gives it 3 out of 10 as a general coding agent prompt and identifies the frontend section as 'a regression test suite, not guidance.' The same model produces dramatically better UIs in Claude Code, where the system prompt never mentions the words 'frontend' or 'UI' once.
Ultra mode isn't a reasoning level — it's a system prompt append that forces Max reasoning AND spawns infinite recursive subagents, with no way to pass effort levels down the chain. Ben burned 50% of his weekly usage in a single 2-hour PR review. Don't touch it.
Codex Ultra mode not only triggers mass subagent spawning but forces every subagent to run at Max reasoning level, unlike Claude Code's UltraCode which pins subagents at High reasoning.
Bhanu and his team built approximately 50 free tools to attract search traffic, each linked back to SiteGPT.
With AI coding tools like Cursor, Bhanu can now create a new free marketing tool in less than 5 minutes by referencing existing tools.
Bhanu filters Ahrefs keyword results to show only those with a keyword difficulty below 10, making them realistic ranking targets for any decent website.
Bhanu sets a minimum search volume of 1,000 monthly searches when selecting keywords to target with free tools.
PropGPT averaged 20 downloads per day right after launching on the App Store through influencer marketing.
Eyal and Yali shut down all marketing and spent 4 months completely rebuilding PropGPT from scratch.
PropGPT has accumulated over 40,000 total downloads since launch.
PropGPT's large language model (AI) operating costs are just $20 per month, and the cost is continually falling.
Ad-based monetization works well for game apps where users spend extended time in-session, as seen with Grid and Wordle.
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