Lenny's Podcast: Product | Career | Growth
00:35:18 · Molly Graham
[00:35:18] S1: Okay, so I have a lot of feelings about this and it goes to this super intelligence thing that we were talking about where it's like what we're saying. AI is the smartest employee you've ever hired in the entire world and it's better than you at everything. And I think it causes people to approach it that way when actually most of our experience with AI, I think a lot of people have had the experience with AI where it's like, "That's wrong. I just asked you to do that. This isn't good." I always think AI needs the same coaching and training that a human does, right? It needs context. It needs onboarding. It needs all of these things. And it's kind of much more like an intern, a bad intern often. I call it a lazy intern. And what happens, to your point about AI slop, is that folks are approaching it as if it's great, the best employee they've ever hired, so they just copy, paste, send. Right? And I'm like you would never do that if you though about it as an intern. You would never take the presentation that an intern handed you and just straight forward it to your boss. That is a little bit insane, right? You would iterate on it. You would edit it. You would ask, make sure that it had all the context from the 57 conversations that you've had with the summer intern before you ship that prezo to your boss. AI is the same. And I think part of what's going on with all the slop in the world is people have shipped accountability. It's like, "Oh. AI said this was good enough so I'm just going to copy, paste, send," and that is never been how good work happens. You know what I mean? So I feel like we need a change from this super intelligent being that's better than all of us at our jobs to, "No, it's just a fucking intern, man." And it needs the coaching and context and all of that and many iterations that most interns do. And I think the other thing, to your point, if you don't take accountability for the quality of your work, that shifts to someone else, right? The person that receives it has to deal with it and that is just a drain on organizations. And I literally see CEOs, we talk about this all the time in Glue Club, shipping a strategy memo that was clearly written by AI. That is you role-modeling for your organization that it's fine to outsource your thinking and it's fine to outsource your strategy.
00:37:47 · Molly Graham, Lenny Rachitsky
It's you role-modeling that you don't need accountability for the work that you send. And I feel like it goes down to this thing of this last six months, we've really been overvaluing productivity, which is just you hear all these stories about companies counting tokens and having token leaderboards. It brings me back to the days when people were counting cars in a parking lot and Slack bubbles and lines of code, which we all know is a really bad way to manage people. And we've been focused on, "How do you run as fast as you can on the treadmill?" but not, "Am I going anywhere?" which is to me the difference between productivity and efficiency. Productivity is can you generate more, which at this point I think we've proven we can all generate a bunch of shit that other people then have to wade through, to the point of your tweet. But is that efficient? Does that actually move the conversation forward? And the answer lately has been, "Why, no. It does not." [00:38:49] S0: Yeah. In that report, I have this iceberg image of just we're doing better on top of all the other stuff, but the output is worse, thinking judgment is coming down. So there's a lot of things we're watching. The good news is everyone's aware of this. They're like, "Yeah, maybe this isn't the way we should be working."
00:38:49 · Lenny Rachitsky, Molly Graham
[00:38:49] S0: Yeah. In that report, I have this iceberg image of just we're doing better on top of all the other stuff, but the output is worse, thinking judgment is coming down. So there's a lot of things we're watching. The good news is everyone's aware of this. They're like, "Yeah, maybe this isn't the way we should be working." [00:39:05] S1: No. I thought there was this really interesting engineering report that said for engineering, it has genuinely made people more productive, but the amount of lines of code that have had to be rewritten has gone up 8X. So it's like this very clear symbol of productivity. Obviously, also the security incidents have gone up, et cetera, et cetera. So it's like there's just this difference between productivity and efficiency and I think part of your burnout data is people are just getting swamped. And that's exhausting if what you're doing all day is wading through, "Did the person on the other side of this actually think about it? Did they actually care?" That's tiring. That doesn't feel like a good use of your time. It just feels a little bit infuriating. [00:39:54] S0: Yeah. It comes back to the grief of, "Oh, man. I missed what it used to be. Look at this weird new job I'm doing." [00:40:00] S1: Yeah, totally.
00:40:00 · Molly Graham, Lenny Rachitsky
[00:40:00] S1: Yeah, totally. [00:40:01] S0: Okay, so let's come back to your advice. We kind of went on a really important tangent, but let's summarize what's still true about giving away your Legos and then we'll talk about what's no longer true. So I'll summarize briefly. I took some notes as you were talking. So still true: Change is scary. That's normal. Understand that. It's part of human nature. We don't like change. Learning over knowing, still a very important thing to focus on. It's okay if you don't know, but if you're focused on learning, you'll be probably okay. This idea of standing still at successful companies is actually you're falling behind. Your company's growing. If you're not growing and taking on your challenges and giving away stuff, you're going to fall behind. Is there anything else core to kind of what's still ... [00:40:45] S1: Yeah, I think I would just add one, which is change is scary and hard and the best thing you can do is lean into it. Right? It is not what your instincts tell you to do, but it is actually the best thing you can do in the face of change. And that was the message of Legos. Basically you need to lean into this comfort of change in order to grow. And I think it is still true today, even if it is maybe even scarier than it's ever been.
00:40:45 · Molly Graham, Lenny Rachitsky
[00:40:45] S1: Yeah, I think I would just add one, which is change is scary and hard and the best thing you can do is lean into it. Right? It is not what your instincts tell you to do, but it is actually the best thing you can do in the face of change. And that was the message of Legos. Basically you need to lean into this comfort of change in order to grow. And I think it is still true today, even if it is maybe even scarier than it's ever been. [00:41:12] S0: This season's supporting sponsor is DX. Now that everybody at your company is finally using AI, the question that engineering leaders face is no longer, "Are we using AI?" but, "Is it paying off?" With DX, you can measure and benchmark the impact of AI adoption across your full product life cycle. DX shows you where AI is helping developers and where it's creating new bottlenecks. You can also use it to evaluate AI vendors, monitor costs and licenses, and see exactly what's limiting your agents. That's why hundreds of enterprises, including Snowflake, Sony, and BNY use the DX platform to measure AI's impact on developer productivity. Visit getdx.com/lenny to get a demo of DX. That's getdx. com/lenny. Okay. So now what is different? The advice broadly is, "Okay, make yourself redundant. It's going to be okay."
00:42:11 · Molly Graham
[00:42:11] S1: I know. That's the one that's hard to talk about today. Yeah, make yourself irrelevant, everybody. It's going to go great. Yeah, it's funny. When AI first really took off, it took me a while to really understand what was going on. In total honesty, I was a skeptic for a while where I was like, "We've been automating things for a while. What is this?" But eventually, I got on board and all of a sudden I was like, "Oh." You know that thing I used to do before I went to give a speech at someone's company where I was like, "How fast is your headcount growing?" For me, that was the only symbol I had of, "Are there people to give Legos to?" If I'm going to get up on stage and be like, "Give away your Legos," a lot of times people are like, "Wait a minute. We're not hiring anyone." Who do I give it to? But now, I was like, "Oh, okay. This message is even more relevant because everyone can try to automate parts of their job and everyone can give Legos away." And I will tell you, it has been an interesting journey realizing how different it is to give things away to robots than it is to give them to a human. And principally, the point of Legos was you take this thing you've been working on and you fully hand it to someone else. One of my favorite questions that I get asked at companies when I do the Legos talk is, "What is the best way to give Legos away to someone else?" And I love it because I think basically people expect me to be like, "So you should incredibly, carefully hand this Lego to this person and explain to them exactly why you put it in the position you put it in. Perfectly describe your tower. Make sure they have an instruction manual that they won't fuck up." And my answer is actually, "No. The best way to give Legos away is to chuck them at their face and run in the other direction," because our tendency, again, is towards control. Our tendency is to be like, "You will build this tower exactly how I built it and you will not mess it up." But actually the point is, "No, you're giving it away. You need to fully separate your mind. You need to just hand it to them and trust that the future of whatever that tower is belongs to them." There is both obviously a lot of fear and a whole bunch of stuff that comes with that, but there's a huge amount of freedom. You take this brain space and you ship it to them.