Alex Imas and Phil Trammell – What remains scarce after AGI?

Economics of AGI episode w Alex Imas and Phil Trammell.

There’s a bunch of important questions about how we deal with AI that only economics can answer.

What is the optimal way to tax and redistribute the wealth that will be generated? How should countries not in the AI supply chain index into the gains? Is there any world where inequality doesn’t explode?

It might seem like these questions have obvious answers, but the first thing economics teaches you is that your intuitions can often be entirely wrong.

It was very helpful to chat through these things with Alex and Phil.

Watch on YouTube; read the transcript.

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Google’s Gemini Omni has incredible video editing capabilities -- you can upload a video and have Omni change the background, adjust lighting, or add specific elements. But Omni is also a preview of how future frontier models will be trained -- fully multimodal on both input and output. You can try it yourself in the Gemini app at gemini.google or in Flow at flow.google

Cursor used targeted RL with textual feedback to help train their Composer 2.5 model. One of their researchers, Sasha Rush, gave me an impromptu blackboard lecture to explain how this form of on-policy self-distillation works -- I posted the full thing on X. If you want to try Composer 2.5, go to cursor.com/dwarkesh

Timestamps

(00:00:00) – Will capital share increase?

(00:19:36) – Messy Middle scenario

(00:25:57) – How to tax and redistribute AI wealth

(00:30:02) – Why demand collapse is unlikely

(00:39:26) – Human employees would be hard to integrate into the machine economy

(00:43:08) – What if some humans (or AIs) value wealth accumulation intrinsically?

(01:01:28) – What should developing countries do?

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