Lenny's Podcast: Product | Career | Growth
00:35:39 · Boris Cherny, Lenny Rachitsky
[00:35:39] S0: Yeah. Exactly. Exactly. I was talking to an engineer earlier today. They're like, "They're writing some service [inaudible 00:35:44], and it's been a month already, and they built up the service. It's working quite well." And then I was like, "Okay. So, how do you feel writing it?" And he was like, "I still don't really know Go." And I think we're going to start to see more and more of this. It's, like, if you know that it works correctly and efficiently, then you don't actually have to know all the details. [00:36:02] S1: Clearly, the life of a software engineer has changed dramatically. It's a whole new job now as of the past year or two. What do you think is the next role that will be most impacted by AI? Either within tech, like, product managers, designers, or even outside tech, just what do you think? Where do you think AI is going next?
00:36:23 · Boris Cherny
[00:36:23] S0: I think it's going to be a lot of the roles that are adjacent to engineering. So, yeah. It could be product managers, it could be design, it could be data science. It is going to expand to pretty much any kind of work that you can do on a computer, because the model is just going to get better and better at this. And the Cowork product is the first way to get at this, but it's just the first one. And it's the thing that I think brings Agentic AI to people that haven't really used it before, and people are starting just to get a sense of it for the first time. When I think about the engineering a year ago, no one really knew what an agent was, no one really used it, but nowadays it's just the way that we do our work. And then when I look at non-technical work today, so, like ... Or maybe semi-technical, like, product work, and data science, and things like this, when you look at the concept of AI that people are using, it's always these conversational AI. It's, like, a chatbot or whatever. But no one really has used an agent before, and this word agent just gets thrown around all the time, and it's just so misused. It's lost all meaning. But agent actually has a very specific technical meaning, which is it's an AI, it's an LLM that's able to use tools. So, it doesn't just talk. It can actually act, and it can interact with your system. And this means it can use your Google Docs, and it can send email, it can run commands on your computer, and do all this kind of stuff. So, I think any kind of job where you do use computer tools in this way, I think this is going to be next. This is something we have to figure out as a society, this is something we have to figure out as an industry. And I think, for me, also this is one of the reasons, it feels very important and urgent to do this work at Anthropic, because I think we take this very, very seriously. And so, now we have economists, we have policy folks, we have social impact folks. This is something we just want to talk about a lot, so, as a society we can figure out what to do, because it shouldn't be up to us.
00:38:19 · Lenny Rachitsky
[00:38:19] S1: So, the big question, which you're alluding to is jobs and job loss, and things like that. There's this concept of Jevons paradox of just as we can do more, we hire more, and it's not actually as scary as it looks. What have you experienced so far I guess with AI becoming a big part of the engineering job? Are you hiring more than if you didn't have AI? And just thoughts on jobs.
00:38:41 · Boris Cherny
[00:38:41] S0: Yeah. For our team we're hiring. So, Claude Code team is hiring. If you're interested just check out the jobs page on Anthropic. Personally, it's all this stuff has just made me enjoy my work more. I have never enjoyed coding as much as I do today, because I don't have to deal with all the minutia. So, for me, personally, it's been quite exciting. This is something that we hear from a lot of customers where they love the tool, they love Claude Code, because it just makes coding delightful again, and that's just so fun for them. But it's hard to know where this thing is going to go. And, again, I have to reach for these historical analogs. And I think the printing press is just such a good one, because what happened is this technology that was locked away to a small set of people, like, knowing how to read and write became accessible to everyone. It was just inherently democratizing. Everyone started to be able to do this. And if that wasn't the case then something like the Renaissance just could never have happened, because a lot if the Renaissance, it was about knowledge spreading. It was about written records that people use to communicate. Because there were no phones or anything like this. There was no internet at the time. So, it's about what does this enable next? And I think that's the very optimistic version of it for me, and that's the part that I'm really excited about. It's just unimaginable. We couldn't be talking today, if the printing press hadn't been invented. Like, our microphones wouldn't exist. None of the things around us would exist. It just wouldn't be possible to coordinate such a large group of people if that wasn't the case. And so, I imagine a world a few years in the future where everyone is able to program, and what does that unlock? Anyone can just build software any time. And I have no idea. It's just the same way that in the 1400s, no one could have predicted this. I think it's the same way. But I do think in the meantime, it's going to be very disruptive, and it's going to be painful for a lot of people. And, again, as a society, this is a conversation that we have to have, and this is a thing that we have to figure out together.
00:40:42 · Lenny Rachitsky
[00:40:42] S1: So, for folks hearing this that want to succeed and make it in this crazy turmoil we're entering, any advice? Is it play with AI tools? Get really proficient at the latest stuff? Is there anything else that you recommend to help people stay ahead?
00:40:58 · Boris Cherny
[00:40:58] S0: Yeah. I think that's pretty much it. Experiment with the tools, get to know them, don't be scared of them. Just dive in, try them, be on the bleeding edge, be on the frontier. And maybe the second piece of advice is try to be a generalist more than you have in the past. For example, in school, a lot of people that study CS, they learn to code, and they don't really learn much else. Maybe they learn a little bit of systems architecture or something like this. But some of the most effective engineers that I work with every day, and some of the most effective product managers and so on, they cross over disciplines. So, on the Claude Code team everyone codes. Our product manager codes, our engineering manager codes, our designer codes, our finance guy codes, our data scientist codes. Everyone on the team codes. And then if I look at particular engineers, people often cross different disciplines. So, some of the strongest engineers are hybrid, product, and infrastructure engineers, or product engineers with really great design sense, and they're able to do design also. Or an engineer that has a really good sense of the business, and can use that to figure out what to do next, or an engineer that also loves talking to users and can just really channel what users want to figure out what's next. So, I think a lot of the people that will be rewarded the most over the next few years they won't just be AI native, and they don't just know how to use these tools really well, but also they're curious and they're generalists, and they cross over multiple disciplines and can think about the broader problem they're solving rather than just the engineering part of it.