Jason M. Lemkin explains why AI-generated code erodes feature-based competitive advantages. He demonstrates building an AI VP of Marketing using historical data and the Lovable platform, arguing that proprietary data, network effects, and hardware remain the real moats for sustained growth.
Feature differentiation is really hard to maintain as a moat. You might be ahead for a month, two, six months, but then everybody will catch up because AI is writing so much of our code. In AI-native organizations, 80%+ of the code is written by AI nowadays. So, imagine how many more engineers that you would need in a traditional organization to do that. So, yes, you can still have feature moat. It's just gonna be very short-lived, and you cannot rely on it as an ongoing, predictable way to grow. The moats that are still working are still the same ones, which is hardware, because it's so hard to actually create hardware. Network effects, uh, network effects has always been really hard to create, but once you have it, oh boy, this is a gift that is gonna keep on giving. Data and security and compliance, uh, those are still very well worth investing into because those will be more long-lasting.
100%. Yeah, you mentioned data. So one of the things I did here, just to walk you guys through what I did, if you wanna replicate it too, so Yesterday we did the session where I live built an AI VP of marketing. So if you go to sasreannual.com/resources, you can grab the two things I already pre-vibed for you guys so that you have it handy. But it's a testament to the data. So I packaged up some sample data so that people could just duplicate it, but I gave it a spec. I gave it some sample historical data and I popped it into Lovable and I said, hey, here's my spec for an AI VP of marketing. I— this is what I wanted to achieve. And it's this whole long spec. Build your own AI VP of marketing. Start as a dashboard. Here are all the goals that it's supposed to do. Here's the data, right? Obviously, this is fake data, but when you use your own data, you'll get better results. And I think that's such a true— I'm glad you called that out because so many folks have been asking us, right?
