Lenny's Podcast: Product | Career | Growth
00:00:00 · Lenny Rachitsky, Anish Acharya
[00:00:00] S0: There's a lot of fear and worry about the future with AI. I want to talk about this idea that if you fall behind, you're going to become part of this permanent underclass. [00:00:09] S1: It's a funny dark fantasy that we seem to have as Silicon Valley collectively. Things have never been better by almost every measure. This is a technology that really amplifies our agency, it kind of unbundles skill from desire. Not only can we dramatically drive productivity, we can dramatically drive ambition. [00:00:25] S0: Can you get too ambitious? Is there a limit? [00:00:27] S1: In the old days, three years ago, we would see a company, and if what they were trying to do was too ambitious we would not engage. Today, we're almost seeing the opposite problem. An idea that's too small is not something that we want to engage with. [00:00:39] S0: Do you have this interesting take that company building more and more is going to become this kind of series of creating loops? [00:00:45] S1: We're going to see this sort of cascading set of everything from a loop per person to loops that can run large parts of the company. With that said, I think humans are a critical ingredient. The loop will help you climb to the local maxima, but then it plateaus. You need human intuition, you need somebody to actually help you land at the base of the next hill. [00:01:03] S0: We have this take that the big opportunity is this idea of, "Loop, make me happier."
00:01:03 · Lenny Rachitsky, Anish Acharya
[00:01:03] S0: We have this take that the big opportunity is this idea of, "Loop, make me happier." [00:01:07] S1: We believe that people want to be more productive, but they don't. I think more people want to spend time than save time. So, I think that the opportunity for this technology is the basics of consumer need. How do we feel more connected, more loved? How do we make progress? How do we have fun? I don't think it's a model or a capability challenge, it's just a product design challenge. [00:01:29] S0: Today, my guest is Anish Acharya. Anish is general partner at a16z, where he focuses on consumer investing. He is one of the most insightful, thought-provoking, mind-expanding, in-the-weeds product investors I've met. He's been at a16z for over seven years now, and unlike a lot of VCs, and why I loved having Anish on the podcast is that he is a longtime product builder and founder. He founded a company called SocialDeck, which he sold to Google, and then ended up leading a number of efforts within Google. Then he started a new company called Snowball, which he then again sold, this time to Credit Karma, where he moved to VP of product and then GM of the broader consumer product and the whole entire credit card business. This conversation will get your mind buzzing. Before we get into it, don't forget to check out lennysproductpass.com for a free year of the hottest and most beautifully crafted AI products in the world available exclusively to Lenny's newsletter subscribers. [00:02:33] S1: Thank you, Lenny. I'm so excited to be here, thrilled.
00:02:33 · Anish Acharya, Lenny Rachitsky
[00:02:33] S1: Thank you, Lenny. I'm so excited to be here, thrilled. [00:02:36] S0: I want to start with a very light topic. I want to talk about this meme of the permanent underclass. It's kind of this joke that people half joke about, this idea that if you fall behind and aren't just on top of all the latest AI tools, aren't becoming the most productive person ever, you're going to become part of this permanent underclass and fall behind and have a really hard time. And some people joke about it, I think a lot of people take this really seriously and stresses a lot of people out. How real of a concern do you think this really is? How seriously do you think people should take this?
00:03:09 · Anish Acharya
[00:03:09] S1: Not very seriously, and it's a funny dark fantasy that we seem to have as Silicon Valley collectively. Things have never been better, really by almost every measure, by how distributed all the opportunities are, by the kind of technology we have access to, to the types of ambition we're allowed to have, and to the number of companies that are independently working on things that are winning. And yet there's this sort of discussion of permanent underclass, being outside of the light cone, I've heard it. And it's not just something for deep insiders or outsiders, it feels like there's a real fear from researchers at foundation model labs all the way through to the Silicon Valley layman. I mean, here's a couple of points that I think are really important. So first, I think the last era of tech was a lot more centralized. If you look at network effects, that's sort of the gold standard. You worked on a network effects product, that's the gold standard of businesses from the mobile era, and those things led to dramatic centralization. Of course, all of them are definitionally sort of N-of-1 networks. If you look at what's happening now, it's like every part of the stack there's not even two relevant players, there's 20. You've got labs, you've got open weight, you've got different variations within both. If you look at coding agents, we were talking about it, your mental model for two years ago should have been, would've been, I think it should be winner take all, and yet Claude Code, Codex, Lovable, Replit, Wabi, they're all sort of working. So it's really, really encouraging to see that. The second thing, you've heard all the kind of economic data, everything from radiologists who are supposed to be cooked every year for I think about 20 years now. And of course, job postings are higher than they've ever been, as well as programmers. So, I don't know that the empirical data bears it out. I think the final thing is that there's this sort of discussion about RSI, and I know RSI is like recursive self-improvement is a fun term to throw around, but if you ask the most sophisticated individuals at the labs, it's not actually RSI that's occurring, which could lead to some sort of runaway winner because they were an epsilon ahead of the others.
00:05:10 · Anish Acharya, Lenny Rachitsky
It's auto catalytic effects, which just means you're using the technology to improve your process, but it's not truly recursive. So, I think everything from the most empirical to the most technical view points in the other direction, and yet we can't seem to let go of this fantasy. [00:05:26] S0: Something I've been thinking about recently, even seeing these crazy stories about OpenAI's models hacking Hugging Face, all these stories to me feels like there's always been this question of are we on the fast takeoff or the slow takeoff scenario? And it feels very much so that we are on the slow takeoff scenario, because every one of these milestones it's like, "Holy shit, it hacked ..." We had no idea it was doing this, but we're catching it, we're watching it, we're observing it, we're iterating, evolving. There's always this fear, "Okay, but tomorrow it's going to take off." What I'm hearing from you is that's probably not the case, which I think is the source of a lot of people's fears, this idea that all of a sudden it's going to become super, super intelligent and then we're in big trouble.
00:06:05 · Anish Acharya
[00:06:05] S1: That's right. The line of reasoning for that case is always everything up until now, then something happens that no one can quite articulate and then fast take off. So, I don't believe that that's going to happen. I do think that model progress is happening faster than ever before, but if you look at something like economic diffusion, I grew up in a small town, I went back home last summer, people's lives haven't changed that much. So if nothing else, the sort of slow rate of economic diffusion will catch it. I think the other thing that's under discussed, Lenny, is how many problems are truly intelligence bound? If you had a data center of PhDs working at FedEx or Domino's Pizza, are they going to be exponentially dominating supply chain and pizzas? I don't think so. So, I think we might be overestimating how many problems are intelligence bound versus bound by other things. I mean, I have so many thoughts on this. I don't think we give the average employee enough credit. I think we have this abstraction of a white collar employee. The white collar manager, the abstraction is like some Dilbert-esque manager who's just shuffling paper all day long. We have this abstraction of consumers that they're sort of these low agency NPCs. Of course, that would never apply to us or our friends. We have this abstraction that everybody else's job is super automatable by AI, but of course ours is not. So, I think when you actually get into the details, a lot of people are actually excited to better themselves, get more leverage. And you see this with, of course, sophisticated companies like Google, but even a company like Kavak where they sell used cars in Mexico, they've got this concept of a Jedi academy where they're teaching everybody at the company, including the mechanics, how to use the new tools and technologies and at the end of the six-week course they ship a cutting edge in-production agent. So, I actually think that more people are embracing the technology than we sort of like to discuss. I think a big change is going to be using AI versus reorganizing your entire company around AI. And a great example of this is if you look at the diffusion of electricity as a technology, it took 40 years for us to get from the inception of electricity to reorganizing factories.