Lenny's Podcast: Product | Career | Growth
01:03:58 · Amol Avasare
[01:03:58] S1: Yeah. Effectively, there's a number of ways you can do this. I think if someone has a public profile where they've written extensively, it's helpful because Claude can just get all that information. Otherwise, you can have a project or you can have a skill, but increasingly, Claude is better at just understanding. Because you can tell Claude like, "Look on Cowork." You can say, using the Slack MCP, "Look at everything that this person has said in the last week, et cetera." And based on that, what are their top priorities? What are priorities my manager has based on how they're spending their time that I don't know? And so all of this layer of stuff, which is like, I think about it as soft coaching, I think that that is unlocked, in my opinion already. I think it's just that you're working with a coach who is kind of like drunk at times. Not drunk, but sometimes says something, you're like, "Why would you bring that up? That's clearly wrong." But other times, you're like, "Wow." There's like, one of the guys, Scott, who leads our enterprise team. There was a few cases where he found major areas of misalignment that would've caused teams to spin their wheels significantly or do overlapping work. And you think about the impact of that. Your shipping in this world as bigger companies is going to be constrained often by all the cross-functional coordination, right? And I think we're now starting to see at this cross-functional coordination layer, some of that work AI is really being able to be used to reduce that foil. And I think that six months ago, that wasn't possible. And I'm like, "Shit, six months from now, what is going to be possible there?"
01:05:45 · Lenny Rachitsky, Amol Avasare
[01:05:45] S0: Oh, man. And I think the fact that all this data is there, Slack, there's Granola, or whatever people use, all these notes from conversations and discussions are really key to this working. [01:05:55] S1: Yes. [01:05:56] S0: So for someone that wants to do something like this, how do you set this up? What's the steps? [01:06:01] S1: Yeah. You go on to Cowork, download the desktop app on Cowork, connect the Slack MCP. That's where you need to, depending on how big the organization is, you may need to get sort of team or enterprise admin permissions, someone with those permissions to enable that. But once you have the Slack MCP connected and on [inaudible 01:06:25], you just ask Claude. That's it. [01:06:27] S0: Amazing. Okay. I'm going to go into a different direction. I want to talk about the focus that Anthropic has had over the years. So if you look at the numbers that you're all putting up, what's really incredible about it is the focus that you all have had. And I think this is the reason it has worked out so well. There's a certain competitor in the market that is realizing they should have done this and are starting to shift to a similar approach. As an external observer, it feels like Anthropic has been very good at doing very few things, but going super deep. So B2B, for example, just going deep on B2B, and then going really deep on coding use cases, Claude Code being an example. And it has worked out really well. Who's been driving that focus? Who has helped keep that focus from the beginning?
01:07:16 · Amol Avasare
[01:07:16] S1: Yeah. I think it's a foundational part of the company. I think it's been there from the very, very early days. And it really comes from leadership and I think they've just done a phenomenal job of distilling that. I saw this doc come up recently. I don't know where it was shared. It was something that Ben Mann, as one of our founders that you had on the podcast, had written. It's dated in 2021, I think a few months after they started the company. And it was like, "Here's why we should just focus on AI coding." And this was like, five years ago. This was long before anyone knew what the actual market opportunities were around this. And I think this is just like a deep focus that we have had internally from the start on the importance of coding and B2B. I think there's two lenses to it. It's like maybe a view of, "Okay, that this is going to be commercially beneficial to tackle, and then also, the side of it around accelerating research." So I'd say it's a pretty mainstream view now. I've now heard people from various labs talking about this, the importance of coding to accelerate research. But that has just been a very firm view that we have been laser focused on internally of, "Okay, if you have the best models, that's going to accelerate your researches and that's going to accelerate the research loop." And I think that's something that Dario has seen very clearly for a number of years. So I would say that that's probably one of a lot. I think a lot comes from Dario. I think a lot comes from leadership and just our DNA. I think the second though is probably just necessity, where it's now changed. We're a more well-known company, raised lots of money, blah, blah, blah. But historically, we're very much the smallest, least well-funded player in this space. In many ways, it's a complete miracle that I think, we've gotten to the stage that we have. We didn't have the free cash flow or the distribution of a Meta or Google. We didn't have the first mover advantage of an OpenAI. And so what do you do? I think there's this broader principle I have just around life of like, the freedom through constraints, that when you have a bunch of constraints applied on you, whether that's in personal life or at work, I think that it can bring a lot of freedom because it just frees up all this excess choice.
01:09:40 · Amol Avasare, Lenny Rachitsky
So you're like, "Okay, this is clearly the path." And I think for us, it's like, "Okay, you don't have a ton of funding, you're a small player, you don't have distribution." You just have to really pick a very narrow focus, and even for a very generalizable technology, to maximize your chances of getting to escape velocity. And I think that that's also just related to how history played out, right? So it was well before my time, but Anthropic had a version of Claude. We had a chatbot before ChatGPT was launched. And we had ultimately chosen not to launch it for safety reasons. I think the team didn't want to kick off effectively like an AI global arms race. And ChatGPT launched and they got insane traction and that just naturally sort of pulled them towards consumer. There's another world where if Anthropic had launched Claude first, maybe did the other way around even with all that focused stuff. So who knows? It's always hard to say, looking back at some of these things. [01:10:42] S0: Wow, I didn't know that. I think also, people just don't realize how far behind Anthropic was. Right now, it's like, of course, they're amazing. But like, I just remember when people were talking about Anthropic, we were raising money. I was like, "There's no way they're going to compete with OpenAI at this point. It's so over." Just like, "They're so far ahead." And it shows the power of focus and just, I guess, I don't know, all the things you all did. It is absurd how far you all have come and how successful and how things have changed so quickly.
01:10:42 · Lenny Rachitsky, Amol Avasare
[01:10:42] S0: Wow, I didn't know that. I think also, people just don't realize how far behind Anthropic was. Right now, it's like, of course, they're amazing. But like, I just remember when people were talking about Anthropic, we were raising money. I was like, "There's no way they're going to compete with OpenAI at this point. It's so over." Just like, "They're so far ahead." And it shows the power of focus and just, I guess, I don't know, all the things you all did. It is absurd how far you all have come and how successful and how things have changed so quickly. [01:11:14] S1: Yeah. And I would say, I very much agree. I think a lot of that comes down to our leadership team. We have a number of people who've worked at, call it the best companies you know in the world, very senior people. And I think almost uniformly, everyone was like, "This is the strongest leadership team out of any of those companies." And so I think a lot comes from them, and then we're just very lucky to have incredible people. I think that helps a lot as well. [01:11:41] S0: On the coding piece, just to make sure that part is clear, I never thought about this, that the reason that the bet was so deep on coding is not just that's a huge TAM, but it's that this is a feedback loop that will accelerate us further and further. So if we get the best at coding, coding will help us do research, it'll help us build better models and it'll accelerate faster and faster.
01:11:41 · Lenny Rachitsky, Amol Avasare
[01:11:41] S0: On the coding piece, just to make sure that part is clear, I never thought about this, that the reason that the bet was so deep on coding is not just that's a huge TAM, but it's that this is a feedback loop that will accelerate us further and further. So if we get the best at coding, coding will help us do research, it'll help us build better models and it'll accelerate faster and faster. [01:12:02] S1: Yeah, that's correct. And this is something I checked. Dario has talked about this publicly, so I'm fine to [inaudible 01:12:07]. [01:12:08] S0: Okay, it makes sense. The safety piece is really interesting. So I want to spend a little time here. So famously, Anthropic, I think the official name of Anthropic is Anthropic, an AI safety research company. As a growth person, there's this balance I imagine you strike between growing and the mission being, don't grow at all costs. Our goal is AI safety and alignment. How do you balance those two things? How does that impact your job?