Lenny's Podcast: Product | Career | Growth
00:20:51 · Elizabeth Stone, Lenny Rachitsky
[00:20:51] S1: I have mixed feelings about that, because we do want to enable with infrastructure and systems thinking, more people to do great work with strong design as part of it. Why not take that opportunity that the new tech provides? But for our most important priorities, design is critical to solve things in the right way. So, we do still make time for important design work. It can move faster. The designers themselves have more tools in their toolkit, so they can do incredible work at a faster velocity, show more options, learn, iterate, test more quickly. But I think it would be a mistake to say design and deep design expertise and thinking gets squeezed out, just because we can write code faster, we can do data analysis faster. At least for a large scale consumer product like Netflix, I feel like we would lose one of the things that makes Netflix great, which is the product technology and design makes a lot of complexity invisible and makes for a seamless customer experience. That's a design mindset that has to be core to it. So, the work itself might look different, but I don't think we lose the mindset. [00:22:06] S0: That's an awesome counterpoint. So, what I'm hearing is trending up skills, attributes you look for, systems thinking. And this mindset of being comfortable, and excited about change, and what's coming, and not being stuck in your own ways. What are you finding is trending down? What are you less looking for that you used to value more highly?
00:22:28 · Elizabeth Stone
[00:22:28] S1: The days of very narrow, deep specialization feel more limited to me. I can come up with examples where we still need it, because there's an industry or technology expertise where there's only a few people in the world who really know how things work. We have examples of that on the team for encoding or how our playback systems work, and things that have been incredibly innovative and novel for Netflix. I still believe we need specialized practitioners in those spaces. But as a general rule, compared to five or 10 years ago, I would believe we have fewer specialists and more people who are generalists or adaptable in multiple directions. And that could be adaptable across functional expertise. It could be adaptable across flavors of engineering. So, can I navigate both backend and front end systems? Can I hook into infrastructure with a lot of expertise? I think the mindset now needs to be I can learn that quickly. And that goes back to the systems thinking. So, I think specialists can learn to have a broader array of tools more easily than was true in the past. So, we need fewer of them perhaps, because talent's able to grow in that direction. And there's something about sticking to a narrow specialty that maybe triggers for me a concern about, what about the mindset of growing in different directions and exploring? And I don't want to be too narrow even in my own assessment of that, but it's important that people who are specialists still have that sense of, I want to try a new way of solving these problems versus the way we have in the past.
00:24:13 · Lenny Rachitsky, Elizabeth Stone
[00:24:13] S0: And when you say specialists, are you thinking front end, I'm a front end engineer versus a backend or are there other versions of that? [00:24:18] S1: Yeah. Or it could be a domain set of knowledge of I'm a deep- [00:24:22] S0: Like a payments expert? [00:24:23] S1: I'm a payments expert. I'm an ads marketplace design expert. I'm an expert in this very specific tooling that studio productions use. So, their specialist and subject matter expertise is an advantage, provided that person is willing to grow and extend into, is this really still the right tool or the right way to think about the problem? So, I think it's the layers of the stack from an engineering perspective that there's less specialty. And then tools that are unlikely to be static or to have a lot of inertia around them. I would think we would want people who are able to innovate and imagine what's the future version of this. And so, we want more talent like that. [00:25:09] S0: Awesome. So, coming back to the systems thinking piece, people hearing this are like, "Okay, I got to work on my systems thinking skillset." How do people develop the skill? Is it just do it for a long time, work at a lot of complex projects? I think of this book that everyone always references with the slinky on the front, Thinking in Systems. Yeah. How do people learn this?
00:25:31 · Elizabeth Stone
[00:25:31] S1: Small trick. Each problem you're trying to solve, step out one click to the like, what am I assuming is true about the broader space in solving this problem? So, I was given a task to build some new feature for the Netflix member experience. Let me take one beat and think about, what is the bigger consumer problem we're trying to solve here? What's the type of content that this feature is going to be able to support? Do I think that the way I was planning to build this is going to make sense in a way that scales across multiple content types? Or it could be something that's a capability that then is contributed to a platform set of offerings from multiple areas. Is the consumer problem that I'm solving with this feature going to be one of the most important consumer problems that Netflix is going to need to solve, as we have an expanding world of entertainment and we want to make it more personalized and immersive? Those are all questions that you don't have to boil the whole ocean. You don't have to solve for Netflix's overall strategy and who are we relative to competition. But you take the thing you're responsible for and you just do one zoom out of the problem you're solving and question that. I wouldn't spend too long in the questioning state, because then you're stuck, then you're not making forward progress. But I think that helps people to think in terms of systems, and question that, are we solving the right problem in the right way that matters for the end consumer?
00:27:07 · Lenny Rachitsky, Elizabeth Stone
[00:27:07] S0: As you describe it, another way I'm thinking about it is think... if you were your manager, what's their broader perspective across not just your one team and problem and KPI, but the larger picture? [00:27:18] S1: I've got advice over years that is similar to that, which is are there ways that I can do my job that helps my manager do their job? And so, if I thought about all the things I'm directly responsible for, but I though about it from the perspective of my manager, so not just product and tech, but finance and content and other parts of the business. I would naturally zoom out and think about how all these component pieces need to come together, and how the whole could be greater than the sum of the parts. I think that's useful thinking. And for engineers to think about, how do I leave a better version of these systems? How do I think about the thing that's going to be high quality and scale for others? There's both a, how do I help my manager? And there's, how do I help my colleagues? Which is a core part of some of our engineering principles of do the thing that is right for the broader organization, instead of just what's right for you locally. That's systems thinking as well. So, it's not just seniority, but it's breadth of the way I solve this problem and I build this, is it going to be useful to my colleagues? And am I going to leave a stronger version of things for the future set of innovations that we want to make? [00:28:24] S0: That is awesome tactical advice. Making your manager's life easier is always a good tactic career-wise.
00:28:24 · Lenny Rachitsky, Elizabeth Stone
[00:28:24] S0: That is awesome tactical advice. Making your manager's life easier is always a good tactic career-wise. [00:28:31] S1: Several reasons. Yeah. [00:28:34] S0: Following the thread a little bit, I know you all added career ladders and levels. Recently, it was a new thing. You used to not have these things. So, on that thread, what have you added to the career ladders within this AI world, if anything, that you find you want people to lean into more, you're looking to more or not? Did you not change your career ladders and performance criteria?