Lenny's Podcast: Product | Career | Growth
00:30:07 · Fiona Fung
[00:30:07] S1: For all of us, especially to your listeners, are probably very AI-pilled. If there's anyone either in their community or their family that has like... I would start with what has something that you really have felt has made a meaningful life change for you with the AI tools and then seeing if that is a conversation starter for... Because for me, AI is a tool. Again, it's the whole light in the dark. I totally understand the frustrating part as well. But for me, I'm also felt like knowledge is power. Have to learn how to use the tools because it could actually be the light part of that light and dark equation. So I think that's something that I would love everybody's help with, whether it's a community member or even if there's a business you really like and you think, "Hey, have you ever..." It's a little awkward to start. I remember when I first reached out to my friends, I'm like, because I don't talk about what I do with them a lot, but I'm like, "Hey, I kind of work in AI. Can I..." It's even unnatural for me to do it because I'm like, "Hey, can I show you what Cowork is possible?" But we ended up having a lot of fun. So yeah, I would love for, like that conversation starter would be great of, yeah, because I just want to make sure we keep sharing the knowledge and making the tool equitable because if not, I'm concerned that the divide grows larger and larger.
00:31:29 · Lenny Rachitsky
[00:31:29] S0: Me too. I find that sharing use cases, as you said, is so powerful. I was just using Cowork the other day to fill out my son's camp forms and just sharing that on Twitter, just like a lot of people are like, "Oh wow, I didn't think about that." Yeah. It's just like these little things you don't think about that Cowork and Claude Code can do. Kind of along those lines, speaking of Cowork, if you think about it, Anthropic has been super early on uncovering these really big opportunities ahead of everyone else. For example, coding. So far ahead, like realizing this is a huge market. Whether it was intentional or not, it was just like, whoa, that's maybe the biggest new business opportunity in history. And then Cowork is a great example, just leaning into knowledge work. Let's just solve all knowledge work. Why not? So far ahead of everyone else. Another element is it feels like a focus on the personality of the model, something you all were very early on, just how important that is, not just for the experience, but just also the intelligence and success of the model. What is it that you think Anthropic and the teams do differently that allows you to uncover these opportunities and then just go big on them before other labs, let's say?
00:32:43 · Fiona Fung
[00:32:43] S1: Well, I haven't worked in any other labs, so I'm not sure how labs operate, but I will share like, yeah, with... And actually on the Claude Code team as well and Cowork, we also keep an eye on latent demand. Now, we're very fortunate with coding as a use case because so many ads that we were like our own first customers and we're able to do really rapid feedback. But latent demand has been like a, for example, like Cowork we noticing a lot of folks that were not necessarily coders were using Claude Code. Can we make that experience better? I think that's actually even outside of Anthropic, that served me well in all the different products I've worked on. And actually it's funny you mentioned the Claude for my passion with small business. After I had a few of those visits, we ended up now launching Claude for Small Business, which is really cool because I, and it totally didn't come from me, so I'm not taking credit, but I noticed it too of like when I was working because they were asking me, "Oh, does it have this plugin or at this plugin?" I'm like, "I think it does." And then we have to go and search for it. So actually now Claude for Small Business bundles it all up. So inside Cowork, you just have this little toggle and there was a wonderful team that's been doing Cowork sessions with small businesses that probably found, "Hey, we could have an efficiency gain here or make the experience better." And so I would say always, not only for products that you're on, like making sure you're always listening to feedback and always iterating, trying to make a delightful, reliable, high quality experience, but then also keeping an eye out for, "Oh, what are these other use cases that are popping up? And can we also make that experience better?" It's interesting. In software, I've learned that customers will use your product in ways that you did not intend for good or for bad. And so the best way is really, it's all about the iteration, learn and keep close to the feedback.
00:34:40 · Lenny Rachitsky, Fiona Fung
[00:34:40] S0: Weight and demand. That term's come up a bunch on this podcast. There's some there. Might be some there. So essentially, it's just watching closely for behavior that you may not have expected or that it's just kind of emerging and then just going big on that essentially, exploring it, building something awesome. [00:34:57] S1: Yeah. And having a hypothesis for, hey, because actually when you see people jumping through hoops to make something work, can you actually make that an even like, a smoother and better experience? [00:35:08] S0: Yeah. Coming back to the way that your teams operate, you guys are so at the edge of what's possible and the role of just engineering has changed so much. I'm curious what you think is the next kind of frontier of how engineering in particular is going to change. Is it like fleets of agents? Is it something else? Just what's the next big shift to how engineers operate that either you're already working on or implementing or just is starting to happen?
00:35:08 · Lenny Rachitsky, Fiona Fung
[00:35:08] S0: Yeah. Coming back to the way that your teams operate, you guys are so at the edge of what's possible and the role of just engineering has changed so much. I'm curious what you think is the next kind of frontier of how engineering in particular is going to change. Is it like fleets of agents? Is it something else? Just what's the next big shift to how engineers operate that either you're already working on or implementing or just is starting to happen? [00:35:36] S1: I would say we're shifting more towards async, like asynchronous. And so to your point, the fleets of agent, like that's why routines is so interesting because it's almost like I used to be doing a prompt and synchronously and then I would maybe kick off different props asynchronously, but now I can actually have a routine that actually generates these prompts for me. So it's almost like the level of abstraction keeps pulling up a little bit. And so yeah, I wish I have a crystal ball to see what this is going to look like. It'd be fun actually for you and me to revisit a year from now. [00:36:09] S0: No, I want to hear more about this. So help us understand what is routines and then when you say synchronous, you're writing a prompt and it just kind of goes off and is it writing it immediately? Talk about what this actually looks like.
00:36:09 · Lenny Rachitsky, Fiona Fung
[00:36:09] S0: No, I want to hear more about this. So help us understand what is routines and then when you say synchronous, you're writing a prompt and it just kind of goes off and is it writing it immediately? Talk about what this actually looks like. [00:36:21] S1: Ah. Yeah. So routines is like how you can... So if you remember, I was chatting about my... What I used to do is always wake up with my morning cup of coffee and, "Hey, look through this Slack channel for me." But then now I have a routine that I set to run every morning at a certain time. [00:36:21] S0: It's like a chronic job. [00:36:37] S1: To say hey. That's right. But then it's able to actually go and kick off agents on your behalf because even before it would be, oh, you could, yeah, do a chronic job to automate, but now it's, "Hey, look at these feedback." And then if you're seeing some of these bugs, that what are some polish fixes that you might be able to knock out? And then it would go kickoff and then I wake up and I end up having PRs that I could review versus before, which is still more of AI can have different agents. And then I'm still thinking about, okay, now what do I do with this information? So it's like that higher level abstraction of, okay, now how can I actually write a routine that also basically does prompts for me for spawning different agents? So I think we'll move more towards that kind of asynchronous style of working.