“Three categories of AI startups. This actually is a framework that came in the mobile revolution for us at Spark, and then reapplied. So this is an old lens, reapplied, which is adaptation, evolution, and revolution. And there are versions of this that have existed as people have talked about AI generally. But for us, can I use a mobile analogy to kind of get you there? Yeah. Adaptation is the obvious, like, I’m going to take the thing, and I’m going to make a copy of the thing for AI. And so in the mobile revolution, this was the New York Times makes NewYorkTimes.com on mobile. And that’s the product, right? And that’s obviously a world where 2023 was kind of the big adaptation push. And that was when Adobe Firefly launches. It’s when Spotify DJ launches. It’s when Canva Create, I think it’s called. It’s when, like, you know, the big boys came to town with their AI products. And everybody had, like, a year to go think about what they were going to do after the GPT era. And, like, ship their incumbent advantage stuff. Like, that’s all adaptation. Evolution, I think the easiest way to kind of separate it is it’s when there’s a new workflow. It’s when the behavior has changed slightly. And so the good example of this is in the mobile era is Instagram, where you’re suddenly doing a different behavior than you used to when you think about Flickr or prior photo websites. It’s a new behavior that is native to that medium. Today, you think about things like this can be done by incumbents and by startups, by the way. Like, sometimes a really fast-moving startup will do it. Sometimes it’s an incumbent. Granola is a good example of this, right? They are an evolved product. You are treating, I don’t know if you want to call that an AI meeting note software. I don’t know if you want to call it transcription software. I don’t want to call it just Apple Notes with AI in it. But it’s a different behavior. It’s a different way of using the product. I think Replit agents, the way that they’ve rebuilt, have a really good example of evolving the medium in a way. Descript is another example. Like, you cannot take the incumbent UI and just slap Descript on. It is a rethinking of how you would do audio and video editing from scratch with AI in mind, right? So that’s evolution. And then the last one, revolution, like this is the canonical, like I’m sure this gets talked about every week on your podcast, but this is Uber, right? This is like it’s an entirely new platform that would only exist because this technology exists. Where do we have the most and where do we have the least? You mean today in the market? Today in the market? Oh. I mean, we are in the industrialization of startups playbook land where everybody is trying to churn out some piece of ridiculous arbitrage every week in order to get to the end of your incubator and raise their seed round. So we mostly have evolved products that are not good enough or we have adapted products with a coat of paint on top that says AI. What do you find most interesting? When we invest, most of our largest exits at Spark over time and most of my most satisfying work over time has been on the revolution and sometimes the evolution category. So we have no desire to invest in anything that’s an adaptation. We’re trying to lean towards the more disruptive, the higher risk, knowing that that won’t always work out, but at least it’s a journey worth traveling.
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– Nabeel Hyatt, GP @ Spark Capital: To Win in AI, Investors Need to Change Their Approach.