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The case for capability over efficiency in AI apps

A post argues that lasting AI app winners will build what wasn't possible in the SaaS cycle.

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2 Sources, 5h ago, first seen 5h ago

TLDR

A post says many VCs focus on efficiency in AI applications, citing tiny teams reaching $100 million in annual recurring revenue within months as the goal. The author argues that long-term winners will instead build things that weren't possible in the SaaS cycle, putting capability ahead of efficiency.

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2.4K

2 Sources, first seen 5h ago

25 likes2 comments7 saves6 reposts
Featured Source

Combined views

2.4K

2 Sources, first seen 5h ago

25 likes2 comments7 saves6 reposts

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2 Sources

@paulbzMany VCs think the AI application layer is about efficiency: tiny teams hitting $100M ARR in months. But that misses the point. The long-term winners will build what simply wasn't possible in the SaaS cycle... capability > efficiency. From our talk @bitsandpretzels5h
@Katie_RoofRT @paulbz: Many VCs think the AI application layer is about efficiency: tiny teams hitting $100M ARR in months. But that misses the point…4h
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    2 Sources

    @paulbzMany VCs think the AI application layer is about efficiency: tiny teams hitting $100M ARR in months. But that misses the point. The long-term winners will build what simply wasn't possible in the SaaS cycle... capability > efficiency. From our talk @bitsandpretzels5h
    @Katie_RoofRT @paulbz: Many VCs think the AI application layer is about efficiency: tiny teams hitting $100M ARR in months. But that misses the point…4h
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