Nick Turley: belief

Transcript context

…That's a good question. And first off, I don't run the developer stuff anymore. We found someone way more competent to do that and he's amazing. So, I still look after the various forms of chat, but luckily you don't have to make that trade-off OpenAI does. And I can get into that too, but it keeps me a little bit more sane. I will say that you kind of have to practice in two different ways when you're building on this AI stuff. One is sort of working backwards from the model capabilities and that is much more art than science, where I think you really need to look at what tech do we have available and what is the most awesome way to productize it? And if you applied to some sort of PM framework to that, I think you would do something horrible wrong. Because if you have tech that's, for example, GPT-5 is really, really good at front-end coding now, I think that means you've got to reprioritize it. You got to actually bring that capability to life. Maybe that's making ChatGPT better at vibe coding and rendering applications. Maybe that's more like leveraging the taste of the model to make the UI more expressive. There's a number of things we could do, but you kind of have to replan and reprioritize and that is more important than any particular audience segmentation. It's really just looking at what is the magic thing we have and how do you make it shine. Voice is a similar thing. It wasn't like our customers need voice, they're begging for it or something like that. It was like, "Wow, we figured out a way how to make these things anything in, anything out." What is a creative awesome way to productize that and then we can see what people do. So, I think that's one chunk of it. But then the other chunk of it really is more like classic product management where you need to listen to customers and then when your customers are really different, that can be confusing because ChatGPT is a very general purpose product. We see when you look at end users, there's actually an immense amount of overlap in terms of what they want. Primitives like projects or history search or sharing and collaboration, all those kinds of things. They are actually very, very present. Whether or not you're talking to people at work or you're talking to people at home, at school, there's slightly different mechanics sometimes, but they're largely similar investments that I think we can get a lot of mileage out of. And then there's Enterprise-specific work that we just have to do. You've got to do HIPAA, you got to do SOC 2, you've got to do all those things if you want to be a serious player. And those are just non-negotiable. So, it's complex as you correctly identified, but it's kind of the curse of working on a very open-ended and powerful technology. if you want to be a serious player. And those are just non-negotiable. So, it's complex as you correctly identified, but it's kind of the curse of working on a very open-ended and powerful technology. One analogy that someone at OpenAI who I really respect, he's like, "We're kind of like Disney, where Disney has this one kind of creative IP, which is their content, and they have cruises and they have theme parks and they have comics and they have all these different things." And I think we have amazing models, but there's all these different ways that you can productize them and we kind of just have to maximize the impact in all these different ways. As you were talking, I was thinking about how usually horizontal platforms that are just so general and can do so much take a long time to take off because people don't know what to do with them. They're not amazing at anything. And this is an amazing counter example where it took off immediately and everyone figured it out and then over time they figured it out more and more.…

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