Lenny's Podcast: Product | Career | Growth
01:07:23 · Lenny Rachitsky
[01:07:23] S1: There's a lot of people listening, a lot of product managers, a lot of maybe founders, a lot of other cross-functional folks listening. There's a lot of worry about just how their role... Just the future of their careers. What advice would you have for just people to not just survive this transition to this very AI-driven world, but to be really successful to essentially just to thrive in this future? What are just things people need to hear, need to be doing?
01:07:49 · Cat Wu
[01:07:49] S0: I think AI gives everybody a ton more leverage than they used to, and so I would push you towards anytime you realize that you're doing some manual task multiple times, think about how you can use Claude Code, Cowork, or other AI tools to automate that for you. Most people have creative parts of their job that they absolutely love and then tedious parts of their job that they really hate doing. I think the beauty of AI is that it can do those tedious parts for you. It can learn from every time that you've done that manual task and generalize and then run it automatically and so that you can focus on the creative parts and that means you can do a lot more than you used to be able to do. So I think my immediate push for people is figure out the repetitive parts that you can pass to Claude, iterate on those automations until the success rate is very high, and then focus on, okay, what more can you be doing for your team, for your product, for your company that people haven't had the bandwidth to pick up so far, or what is that pet project that you always thought the company should do that you've never had bandwidth to do? If AI can take care of the grunt work, then you have this extra 20% time now that you might not have before. So my push is to lean into these tools, hand off the work that you're not excited to do, figure out how it can accelerate you, and then as a result, you'll be able to do so much more.
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,