Snapshot · Dwarkesh Podcast
Despite massive improvements in compute technology and supply, H100 GPU rental prices are higher than 3 years ago because smarter AI models raise the opportunity cost of compute.
Where this was said
At 15:22 · chapter starts 0:00
Dwarkesh introduces Alex Imas and Phil Trammell. They explore labor share stability, the relational sector, the Mongolian economist thought experiment, and whether human intrinsic goods can survive automation. [1] — Alex Imas "Scarcity after AGI will concentrate in goods where human involvement is intrinsically part of the value — not just because humans are capab…" 00:44
Scarcity after AGI will concentrate in goods where human involvement is intrinsically part of the value — not just because humans are capable, but because consumers actively prefer the human to be in the loop. The hypothesis only holds if willingness-to-pay survives replacement, and we currently lack the data to know.
Ricardo correctly predicted that industrial-era jobs would be automated. He completely failed to predict that new jobs would replace them, and that prime-age employment in 2026 would be near an all-time high. The lump-of-labor fallacy has fooled experts for two centuries — and may be fooling them again.
Despite all historical automation, prime-age employment in 2026 is the second highest ever recorded, surpassed only by the 2000 peak — a fact David Ricardo would have found shocking.
The main U.S. database tracking job tasks has rarely been updated and is of very low quality, making it nearly impossible to track which jobs are being created or destroyed by automation.
Despite every wave of automation since the Industrial Revolution, labor's share of GDP has remained above 60%, which economists call a Kaldor fact — almost suspiciously stable.
A Mongolian economist in 1400 predicting scarcity would have assumed people satiate in horses and yogurt and concentrate spending on singers. They would have been wrong — because wealth expansion always generates new varieties. The same failure awaits anyone predicting AGI scarcity by holding varieties fixed.
Sam's initial MVP was coded in approximately one week using ChatGPT voice mode and copy-pasting code, with no prior technical experience.
Sam argues Discord is 10x better than email for building relationships with younger users who rarely check their inbox.
Sam's monthly operating costs include Cursor ($200), AI image generation ($100), AI video generation ($200), hosting ($100), email marketing ($80), and AI compute ($300–$500).
Sam recommends copying days of Discord chat history into ChatGPT and prompting it to list recurring pain points as a fast, free market research technique.
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.
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