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It’s been weeks since GPT-5 launched—which is basically a decade in AI time. The hype fog has finally lifted, and that’s the perfect moment to ask: what really changed, what actually matters, what were the actual product strategy decision?
In this episode, Brian Balfour and Fareed Mosavat dig into why OpenAI went all-in on a “one model to rule them all” consumer strategy, the quiet product moves aimed at the next billion users, and the weird tension between how they marketed GPT-5 and what the product strategy actually says.
We also go straight to the money: the “gym-membership” economics of AI, why flat pricing turns into a house of cards, and how usage-based, hybrid, and outcome-based models actually shake out when cost to serve is variable and compute doesn’t magically 10× cheaper.
If you want clear takeaways on strategy, distribution, and monetization, keep listening as we are about to dive in.
By Brian Balfour & Fareed Mosavat4.7
4444 ratings
It’s been weeks since GPT-5 launched—which is basically a decade in AI time. The hype fog has finally lifted, and that’s the perfect moment to ask: what really changed, what actually matters, what were the actual product strategy decision?
In this episode, Brian Balfour and Fareed Mosavat dig into why OpenAI went all-in on a “one model to rule them all” consumer strategy, the quiet product moves aimed at the next billion users, and the weird tension between how they marketed GPT-5 and what the product strategy actually says.
We also go straight to the money: the “gym-membership” economics of AI, why flat pricing turns into a house of cards, and how usage-based, hybrid, and outcome-based models actually shake out when cost to serve is variable and compute doesn’t magically 10× cheaper.
If you want clear takeaways on strategy, distribution, and monetization, keep listening as we are about to dive in.

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