Lenny's Podcast: Product | Career | Growth
01:09:19 · Lenny Rachitsky, Cat Wu
[01:09:19] S1: Something core to what you just shared, which I fully agree with is find problems to solve with AI. There's all this potential what all these tools can do. For a lot of people, the hardest part is just like, "What should I actually do?" And what you're saying here is just pay attention to things that you are doing constantly you can automate, pay attention to just ideas that have been floating around that you haven't had time to do. It's basically it's like solve a problem for yourself is kind of the core advice there. [01:09:46] S0: Exactly. I would also push listeners towards focusing on bringing your automations from, okay, this is a cool concept to like, hey, this actually works 100% of the time. Sometimes I see users trying to automate something, getting it to 90, 95% accuracy and then giving up on it, and if an automation doesn't work 100% of the time, it's not really an automation, and that last five to 10% does take more time. Also, building the automation is often a lot slower than you doing it yourself. I would encourage listeners to put in that time to scope some automation that you really want to get to 100%, put in the elbow grease to teach Claude your preferences, to give it feedback so that it can improve its skill so that it can get to that 100%, and then really then you'll be able to rely on it. There's just not much value in a 95% there automation. [01:10:48] S1: I am super guilty of that. This is really good advice for me.
01:10:48 · Lenny Rachitsky, Cat Wu
[01:10:48] S1: I am super guilty of that. This is really good advice for me. [01:10:49] S0: I am guilty of this too. I've been teaching Cowork to try to get me to inbox zero for Gmail, and it has been very time-consuming and it is definitely not there as you probably realize. [01:11:02] S1: Yeah. Funny enough, that's exactly where my mind goes. I have this workflow I set up where every email I get, it looks for things that are spammy, which is just all these like, "Hey, can I come on your podcast?" Or, "What about this?" All these things, I'm just like, "I don't have time for these sorts of things," and I have it categorized it into a folder called Spammy and it's just like, it's 95% great, but then there's like, oh, wow, I missed an email because it went in there. So this is a good push for me to like, I'm going to work on this. I'm going to get it to perfect. [01:11:28] S0: Yeah. We also are working on making the flow for customizing these commands a lot easier because right now I think you have to know too many concepts. You have to know to define a skill, you have to know to use this skill and give it feedback, and then you have to know to tell Cowork to update the skill based on all the feedback that you gave, and then you also have to know where to read the skill to make sure that the feedback was incorporated the way that you want. It's also our job to make this flow really seamless so that it doesn't feel painful to do.
01:11:28 · Cat Wu, Lenny Rachitsky
[01:11:28] S0: Yeah. We also are working on making the flow for customizing these commands a lot easier because right now I think you have to know too many concepts. You have to know to define a skill, you have to know to use this skill and give it feedback, and then you have to know to tell Cowork to update the skill based on all the feedback that you gave, and then you also have to know where to read the skill to make sure that the feedback was incorporated the way that you want. It's also our job to make this flow really seamless so that it doesn't feel painful to do. [01:11:57] S1: Amazing. Is there anything else, Cat, you wanted to share? Anything else you wanted to leave listeners with? Anything you wanted to double down on that we haven't already touched on before we get to our very exciting lightning round? [01:12:08] S0: I see a lot of people playing around with AI and building prototype apps and tinkering with building workflows. I would really push people towards building apps that you're actually using every single day because I think only through that usage are you actually getting the value. If you build a prototype app that isn't helping you get more done, then the AI isn't really adding value to your day. [01:12:38] S1: And there's only so much you learn from that when it's like, okay, I just did one-shotted something, oh, that's cool, and then you never come back to it. You're not learning a lot. [01:12:45] S0: And you're not getting much leverage from it. [01:12:47] S1: And actual leverage. Yeah, that's such a good point.
01:12:47 · Lenny Rachitsky, Cat Wu
[01:12:47] S1: And actual leverage. Yeah, that's such a good point. [01:12:49] S0: I also think there's a lot of people who spend a lot of time customizing their workflow. So I think there's two ends of the spectrum. One is people who never customize or never build automations, but there's this polar opposite end of people who obsess around customizing their tool, adding a ton of skills and MCPs and these workflow improvements, and I think sometimes that can even distract from your core goal of launching some product or building some feature. I think there's a lot of fun in customizing and we definitely want to make our products very hackable so that you can make it work really well for you, but there is a limit to how much it's useful, and I think there's a camp of people who maybe spend so much time customizing that they're not sleeping and not doing the core task that they originally set out to do. [01:13:41] S1: I see a lot of that on Twitter. Just like, "Look at my setup. It's out of control. It's so optimized," and what are you actually building? No, but my setup is so awesome. It gets so much done. [01:13:52] S0: I think the simple setups actually work better. [01:13:56] S1: /powerup. Level up a little bit. [01:13:58] S0: Yeah,
01:13:58 · Cat Wu, Lenny Rachitsky
[01:13:58] S0: Yeah, [01:13:58] S1: Yeah. There's this Karpathy tweet that just came out yesterday where you talked about this divide that's interesting between people that tried ChatGPT, Claude back in the day, it was like, okay, and they're like, "Nah, this is terrible," and they kind of gave up on what AI could do for them and they're just so cynical of like, "No way, it's not actually that big of a deal." And then there's people that are using it to code essentially who see the full intense power of it and how good it is and people on both sides don't understand the other side and how they see the world. And so your advice is really good here to just actually use it for real things and see how good it actually has gotten. [01:14:38] S0: Yeah. I think the big shift is that the 2024 generation of products were chat-based and the Claude Code generation of products is action-based, and the big aha moment people have is when Claude can just do things on your behalf. It is an amazing feeling to know that the agent is capable of doing so much more than telling you what to do. The agent can actually just do it itself, and when people feel that, I think that's the eye-opening moment. [01:15:10] S1: Shout out Chrome Extension, the Claude Code Chrome Extension, which you could just watch it doing stuff and you'd be like, "Fill out this form for me," and I'm like, "All right, here I go." [01:15:18] S0: Exactly. [01:15:19] S1: Okay. Anything else before we get to our very exciting lightning round? [01:15:22] S0: No, let's do it.
01:15:22 · Cat Wu, Lenny Rachitsky
[01:15:22] S0: No, let's do it. [01:15:25] S1: Let's do it. Cat, I've got five questions for you. Welcome to the Lightning Round. There's this animation that plays, I have to make sure to say it. Are you ready? [01:15:32] S0: I'm ready. [01:15:34] S1: First question, what are two or three books that you find yourself recommending most to other people? [01:15:38] S0: I really like How Asia Works. It's a story about economic development and what are the policies and governments that make long-lasting successful economies. The other books that I'm really into are The Technology Trap. So this is actually about the past few technology revolutions, so the Industrial Revolution and the Computer Revolution and how this has affected workers. The reason that I really like this is because I think there's a lot we can learn from history to make sure that this transition goes well. And maybe on a fun note, I really like Paper Menagerie. It's just a book of short stories about coming of age and AI and just self-discovery. [01:16:30] S1: Favorite recent movie or TV show you have really enjoyed?