Alessio Fanelli: belief

Transcript context

…still kicking. They announced some stuff recently. But I think that's another one. It's the fastest growing project in the history of GitHub. But I think, you know, when you maybe like run the numbers on like the value of the stars and like the value of the hype. I think in AI you see this a lot, which is like a lot of stars, a lot of interest at a rate that you didn't really see in the past in open source, where nobody's running to start. Uh, you know, a NoSQL database. It's kind of like just to be able to actually use it. Yeah. I think one thing that's interesting here, one obviously is that in AI, you kind of get paid to promise things and then you, to deliver them, you know, people have a lot of patience. I think that patience has come down over time. One example here is Devin, right this year, where a lot of promise in March and then, and then it took nine months to get to GA. Uh, but I think people are still coming around now and Devin, Devin's [00:55:00] product has improved a little bit, hasn't he? Even you're going to be a paying customer. So I think something Devon like will work. I don't know if it's Devon itself. The Auto GPT has an interesting second layer in terms of what I think is the dynamics going on here, which is a very AI specific layer. Over promising under delivering applies to any startup, but for AI specifically, there's this promise of generality that I can do anything, right? So Auto GPT's initial problem was making money, like increase my net worth. And I think. That means that there's a lot of broad interest from a lot of different people who are trying to do all different things on this one project. So that's why this concentrates a lot of stars. And then obviously, because it does too much, maybe, or it's not focused enough, then it fails to deploy. So that would be my explanation for why the interest to usage ratio is so low. And the second one is obviously pure execution, like the team needs to have a vision and execute, like half the core team left right after AI Engineer Summit last year. [00:56:00] That will be my explanation as to why, like this promise of generality works basically only for ChatGPT and maybe for this year's Notebook LM. Like, sticking anything in there, it'll mostly be direct. And then for basically everyone else, it's like, you know, we will help you complete code, we will help you with your PR reviews. Like, small things.…

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