@levie: The best way you’re going to continue to get large scale agentic adoption is by continuing to bring down the cost of in…
Summary
Levie argues that lowering the cost of AI intelligence (tokens) is key to large-scale agentic adoption, and predicts most information work will involve agents in the future, citing innovation in both open and closed models.
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Cached at: 07/13/26, 04:02 PM
The best way you’re going to continue to get large scale agentic adoption is by continuing to bring down the cost of intelligence. More use-cases open up for AI every time you can have lower cost tokens (for the same or better level of capability).
Almost all information work in the future will involve an agent somewhere in the workflow creating, processing, reviewing, or classifying data in some way. This will happen sooner or later depending on the cost of tokens of frontier models.
Whether this happens from closed or open models is somewhat incidental, but the key is just that it happens. It’s great to see so much innovation and different approaches in AI right now as there are so many more use cases to power.
Gavin Baker (@GavinSBaker): The mega bull case for AI infrastructure would be if market share shifted away from certain frontier labs with 90%+ inference margins toward cheaper models, whether open-source or closed.
It would increase the ROI on AI spend for end customers by increasing intelligence per
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