AI startups require new strategies: This time it's actually different

Sobriety source #2: AI as the next platform shift. Every wave of new companies that transforms their respective industries is fueled by a major platform or technology shift. The advent of the web did this. The smartphone and mobile applications did this. And there is no doubt that AI is our next wave. But does every new wave always necessarily favo... See more

Many of the largest scale uses of AI to date have been at consumer-centric companies that have large data sets to train on (Google, Facebook, Uber, etc). Perhaps incumbents won due to a data advantage that is now going away as companies use the broader internet as an initial training set + are switching to models that work more robustly against sma... See more

However, a key risk with several of these startups is the potential lack of a long-term moat. It is difficult to read too much into it given the stage of these startups and the limited public information available but it’s not difficult to poke holes at their long term defensibility. For example:

• If a startup is built on the premise of taking base L

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The moats are in the customers, not the data. We predicted that the best generative AI companies could generate a sustainable competitive advantage through a data flywheel: more usage → more data → better model → more usage. While this is still somewhat true, especially in domains with very specialized and hard-to-get data, the “data moats” are on

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Earlier this year we met with our Limited Partners. Their top question was “will the AI transition destroy your existing cloud companies?”

We began with a strong default of “no.” The classic battle between startups and incumbents is a horse race between startups building distribution and incumbents building product. Can the young companies with coo... See more