Lenny Rachitsky: commitment

Transcript context

…ders, sitting in finance and content and advertising, can do that as well. And then bring back an initial hypothesis where they want to work more deeply with the data scientist and engineer and so on. So, there's something there about the hypothesis generation, prototyping, thinking deeply about problems, that feels like it's accelerating and that functions are able to do that in a more fluid way. But I still see comparative strengths. So, data scientists are still going to be experts at, can we trust this data? Are we interpreting it the right way? What's the data versus judgment that we should be applying here? A product manager is still going to be exceptional at saying, have we really framed the what of this, the problem we're solving in the right way? An engineer still has a craft around the how. How does this scale? What does high quality look like? What problems is this going to create for us based on how we build and deploy something? So, I still see the nuggets of that comparative advantage. It's just that we're able to move more fluidly in a lot of steps that normally we would have blockers on. There's so much interesting stuff here. One is this last point you made, something I've been thinking about. If we all become builders, will we still need separate functions? There's this member of technical staff trend that is happening across AI, where it's like, all right, we don't have a title. You could be anything. You don't have to be in a bucket. What you're saying here is you believe we will continue to have specialties, product person, engineer, data science, designer. While they do more of other functions, there's still a lot of value, and tell me if I'm hearing you correct, in having this specific discipline and skill and background. I still see a craft excellence that's really important in the disciplines that I don't think is going away anytime soon, even if there's fluidity or blurring of the work across the functional lines. It goes back to what I mentioned earlier of you still have humans who have to make sure that what we're doing makes sense. We're solving the right problems in a way that is best for Netflix members or business stakeholders. And that if I talk to an engineer, a data scientist, a designer, yes, they speak more languages now than they used to because they have the benefit of these AI tools, but there's still something that is not replaceable when I think about the craft and how they think about what good looks like. And that feels true across all levels. And I still find great engineering to be scarce, great data science to be scarce, great creativity to be scarce. So, yes, some things are easier, but that hasn't dissolved in my mind.…

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