Gamma · AI presentation maker
Use cheaper, faster AI models where the output is good enough
Profitable 6 months after launch; faster product and lower compute costs
Workedfeature-development
What they did
In early versions of AI presentations, Gamma picked long-tail models (not always frontier OpenAI/Anthropic ones) where quality was good enough, gaining speed and much lower compute cost. Phil's rule: frontier models for bleeding-edge prosumer use where cost is no object; cheaper models for price-sensitive consumers, factoring in fast-falling model prices over 6-12 months.
What happened
Faster product and lower compute cost; profitable six months after the March 2023 launch (one of several reasons).
In their words
Sub Club by RevenueCat · 12 AI Growth Lessons for Subscription Apps – Phil Carter, Elemental Growth“in some cases what they found was using some of these longer tail models, not only was the performance good enough in terms of the quality of the output that they were delivering to their users, but also the speed of the product was significantly faster and the cost to the business of the compute power needed to serve these AI powered features was significantly lower”
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