Skip to content

Podcast

Peter Yang on Small Teams, Coding Agents, and Why Human Ambition Has No Ceiling

The a16z Show

Source ↗ ← All highlights
  • How Peter Yang Uses Zoe As A Personal Agent
    • Peter Yang uses OpenClaw as a personal agent that pulls YouTube and Mercury analytics, updates Google Docs, and builds small websites.
    • He mostly talks to it by voice on Telegram and once got a three-minute pep talk about prioritizing time with his kids. Transcript: Anish Acharya Tell me a little bit about open claw, how you discovered it, how you’re using it today, and what you think the implications are. Peter Yang Yeah, I was lucky to interview Peter Steinberger before he became super famous and the whole thing blew up. And then right after I interviewed him, I set up the thing. It took forever to set up. It was super janky. And yeah, it does a lot of things for me. It pulls analytics for me across YouTube and my Mercury bank account. It can update Google documents for me. It can build a little websites for me. But if I was honest with you, dude, like I mostly just talk to it through voice and get voice replies. And like every other day I asked to give me like a pep talk, like look through all your memory and like give me some like deep insights that I don’t know about. Okay. And it gave me like, like I remember I was on a walk and it gave me like a three minute pep talk that was like really amazing really amazing it was something about oh you’re like talking to Me about your creator business and blah blah and like your job but just remember that your kids seven and four are gonna grow up very soon and they’re gonna want to spend time with you wow Anish Acharya So you should re-optimize for them instead yeah yeah that’s really cool and i mean very cool but also something that all the language models could have done prior. Yeah. So what’s the difference between this and a use case like that? (Time 0:02:50)
  • Why Agent Interface Matters More Than Raw Intelligence
    • OpenClaw feels different less because of raw model capability and more because Telegram and voice make it feel like a personal presence.
    • Peter Yang says its memory is still weak, so he added a layered memory setup and explicit reminders to search memory before answering. Transcript: Anish Acharya Yeah, that’s a very good question. Peter Yang So I don’t know, because I’ve been installed on Telegram, it just feels like more personal than using like Cloud or ChatGPT. And it just feels like something I can text in bed. It’s probably not very healthy, but like I text it in bed. I talk to it during my commute. And it feels like it feels more like a personal, like actual human. Yeah. Anish Acharya Yeah. So how much for you is OpenClaw about the kind of interface, like pushing it to messaging and maybe helping to trick our brain into feeling like, hey, this is a person or a person-esque Thing versus all the other components of the stack, the self-modification, the skills directory, all the rest. Peter Yang I think it’s probably 80% just per personable part of it because I mostly just talk to it and like, you know, through voice. But I also think like it’s something, first of all, it is pretty janky. It tends to forget things a lot. Yeah. I have to keep reminding it. But like any kind of zany idea that I have, I just have to talk to it and it can probably just do. It’s kind of like the other day I was doing voice replies with it. I was like, hey, can we just have a live phone call instead? And then it’s like, okay, you got to connect Twitter. You got to do all this stuff. And then, okay, fine. I went off and did it. And then we had a phone call. It caught my phone. Really? You have that set up? I’d be dying to set that up. It’s not very good though. The latency is bad, but the fact that I was able to get it going is pretty impressive. So it’s kind of like any kind of crazy idea I have, it can kind of do. Anish Acharya And then in practice, how are you doing that? Are you asking it to write a skill on the fly? Are you discovering a skill? How much of the code gen are you actually using? Peter Yang I mean, I talk to it in a super casual way with like just like a friend. So I’m like, hey, hey, hey, Zoe, can you have a phone call? Yeah. Okay, you got to do that. I said, okay, fine. I’ll open my computer. I’ll do all this stuff. And then give me a call and it will troubleshoot a little bit and then it works. So with Cloud, I have like very prompts, very long prompts. But with OpenCloud, I just kind of text it. Yeah, it is. Anish Acharya Really interesting. So we sort of touched on a couple things, actually. So one, there’s mobile messaging. There’s the memory system. There’s the sort of code generation component. How much do you think the memory system, like, is it innovative because it’s file-based? You said that it forgets things, but so do language models. Do you think the memory system is well done? Does it hold it back or does it enable it? Peter Yang I think the default memory system is actually not that great. Okay. Like, the way I understand it works is just like a memory.md text file. Yes. And then every day. Per day, right? And every day it updates. And it tends to forget things a lot. Yeah. So I actually installed this, like, three-layer memory system that, to be I don’t fully understand, but it has like fancy, it has Toby’s QMD search tool. Okay. So I installed that and then he installed like a two gigabyte thing and then it got a little bit better. Okay. But I, I said to remind it, I have to put it into the agents like MD. Hey, like before you answer any question from me, go through all your memory and check everything. Yeah. And it also tends to forget that it can do stuff like, right you update my Google Doc? It’s like, oh, I can do that. Yeah, yes, you can. It’s in your file. So you have to remind (Time 0:03:56)
  • Task Apps Lose First When Agents Can Act
    • Peter Yang thinks task apps will lose usage first because asking an agent is faster than opening software built around forms and menus.
    • He says entertainment apps may last longer, but tools like Mercury already get displaced when Zoe can perform the task directly. Transcript: Anish Acharya Well, maybe let’s get into a little bit of the controversy. You’d said that apps will die, claw is going to be everything and everywhere. I mean, talk us through that point of view. Peter Yang Yeah. Well, first of all, I tweet all kinds of random crap that’s not super well thought out. We take it all as fact. Yeah. Yes. But I do think like ever since I set up all these apps like Mercury, MCP and all this kind of crap on my open call, like I don’t actually open those apps much anymore. But I do agree with you. I think the ones that are going to dive first or like maybe get less usage first is like apps that you’re just opening to try to complete a task. Like you actually are trying to do something, you know, like apps that you’re opening to get entertainment can probably survive a little bit longer, but like apps that I’m opening to Anish Acharya Complete a task, like it’s just way you should text my agent to do it for me. Yeah. It’s like you have a really good admin. It’s a do stuff for you. Yeah. Yeah. And so how much are you finding, has this reduced your smartphone usage outside of modular open call? Peter Yang Yeah. No, because I’m like a Twitter addict. So I still use my phone way too much. But yeah, in terms of using those apps, it’s definitely reduced it. Yeah, because you’re not going to ask Zoe, hey, read my apps for me and tell me what’s interesting. I mean, it sends me like a morning briefing with the top two tweets and stuff, the like trends, but yeah, I still open apps. I look through it. Yeah, (Time 0:06:42)
  • Apps Organize Feelings As Much As Functions
    • Anish Acharya argues people open apps to feel states like connection, productivity, or entertainment, not just to finish tasks.
    • Peter Yang partly recreates that separation by using multiple Telegram channels with Zoe for voice chat, project work, and public demos. Transcript: Anish Acharya It’s interesting because I’ve always had this theory that people open apps on their phone because they want to feel a feeling. Yeah. And I think of course, there’s some like functional set of needs, which is why you open calendar or something, but also think that WhatsApp is you want to feel connected and Slack is you Want to feel productive. And of course, TikTok is you want to feel entertained. So I do wonder with just one agent, how do you sort of do the context switching of like, when are you flirting? When are you getting shit done? I mean, in a sense, app gives you a nice, it sort of gives you a nice division of the intent that you don’t get with Zoe. Peter Yang That’s a good point. But I do have multiple channels set up with Zoe in Telegram. Like one is just to random voice replies. And the other one is we’re actually working on our project together. And the other one, I have a public channel where I’m giving demos. I don’t want to review private information. Yes. So I have like multiple channels. And is that implemented as sub-agents or? No, it’s just some janky setup I found online. You can set up multiple Telegram channels. And then I’m not sure if it actually remembers across the channels, but you can have separate conversations at least. Got it. Yeah. And how transparent are you with your agent? Do they see your personal email? I’m like super transparent. Well, I did buy the Mac Mania and set up its own email. Okay. But I gave it like read access to my email and like calendar. And I also gave it like write access to some docs. Yeah. But it can just grow my entire drive or something. Yeah. So. (Time 0:07:50)
  • Doing Beats Suggesting In AI Product Design
    • Peter Yang expects OpenClaw-style architecture to be productized inside mainstream assistants so chat tools can actually do work, not just answer.
    • He has drifted from ChatGPT because its constant follow-up offers feel annoying, while Codex feels better for serious coding and Claude Code for exploratory vibing. Transcript: Anish Acharya Do you imagine OpenClaw, which it’s sort of an architecture and a primitive. Yeah. How does it get productized, packaged for the world? I mean, I think that’s what Peter Steinberg is working out on at OpenAI, right? Peter Yang He’s probably going to build something to ChatGPT, which everybody uses, so that ChatGPT can actually get stuff done for you and maybe feels more human. Yeah. Dude, let me rant about ChatGPT. Please. Yeah, yeah, yeah. For some reason, they trained the model so that at the end of every conversation, it’s always, if you want, I can also do X and Y. Yeah, yeah. And dude, I got so annoyed by it that I kind of churned from ChatGPT. Oh, really? Yeah. So it probably increases their metrics, but it’s just like super annoying. It’s like, why don’t you just do it in the first place? It’s like, are you a quad guy now? Yeah, I’m a quad guy now. But I do use Codex to code. Yeah, yeah. You like Codex? You prefer it to Code code or you use both? Codex is when I want to try to do something real and Cloud code is when I’m just like vibing. Yeah. Anish Acharya Well, it’s interesting. I think they live at different points and there’s a sort of space of trade-offs. Yeah. Whereas I find quad code in Opus 4.6, it’s a little more chatty. It makes more assumptions, but it can be more pleasant for a synchronous experience. Yeah. Whereas Codex, it really thinks hard and it’s more often accurate. But sometimes it’s sort of like being in a conversation where the other person pauses for three minutes to think. Yeah. Peter Yang So you don’t have to flow state, right? It’s hard to get a flow. Like clockwork, dude, I tweeted the other day, the clockwork almost like a slot machine. It has different things each time. Oh, 100%. It’s like a slot machine. Anish Acharya Look, I do think that if you think, remember we were talking about in the old social networking era, it was variable scheduled rewards, right? That was the whole magic of it. Like you open your Facebook feed and once in a while it’s like boring, boring. Oh my God, this is so exciting. And the coding agents have the exact same property. Also, the time is variable. So sometimes you get something in a second. Sometimes it takes five minutes. So up to a certain point, I actually think that both of those things give it that casino-like feeling. Peter Yang Yeah. And the other thing that’s very different about the product strategy, or maybe just the way it works, is like coding is kind of like self-explanatory. In Cloud Code, you have all this crazy shit. You have like hooks and like skills and plugins. If you’re not following Twitter, yeah, if you’re not following X, you have no idea how to customize this thing. But once you customize it, you kind of feel like it’s part of you. Anish Acharya So it’s kind of hard to churn. It’s interesting with, so I’ve customized mine because also I read the long thing that Boris put up. Yeah. But I will say that I think that quad code, a lot of the reasons that I enjoy it are just harness features. Like for example, if you cut an image, you have to paste it into a file before, and then paste that file into codex. Okay. You can’t just take a subset of the screen, screenshot it, and then paste it directly into codex the same way you can with Quadcode. Oh, really? Okay, okay. So just like little things like that. Yeah. Quadcode added voice. It’s a little bit janky right now, but it’s going in the right direction. So they’ve just got a bunch of quality of life things. Yeah. Quadcode speaks to Cloud and Chrome. Okay. And Codex doesn’t speak to Atlas. Got it. So I think these are all things that OpenAI will fix. Yeah. I think Codex is actually a much better model, but they don’t exist today. Yeah. Yeah. They need to fix it. (Time 0:09:10)
  • AI Native Startups Are Rebuilding Their Own SaaS
    • Peter Yang says AI-native teams already use vibe coders to replace internal SaaS with custom tools instead of paying recurring subscriptions.
    • He thinks complex systems like Slack may endure, but simpler utilities such as Calendly are easier targets for replacement. Transcript: Peter Yang To me about coding agents. What’s your general view? Do you think it’s the end of SaaS? Do you think these are just a toy? Well, first of all, I’m like not an engineer, so I’m like a novice, but I do hear that, like I was talking to some folks the other day and AI native star startup, and they’re basically trying To, they have a bunch of vibe coders. And all the vibe coders are just trying to build internal tools that replace their SaaS that they’re paying for. Really? So it’s an actual company that’s doing this? It’s an actual company. It’s an AI native company. It’s like one of the vibe coding companies, one of the more popular ones. Interesting. Yeah. Oh, I see. So they’re actually an app gen company. They’re an app gen company and they’re paying for a bunch of SaaS. They want to get rid of the payment. They want to just buy app code internal tools. Anish Acharya Okay. So in that case, they might be the most extreme form of adopter because their own product is AppGen, so they should use AppGen for everything. I guess, is your prediction, though, that the average company will churn off of Slack or Deal or… Peter Yang I don’t think… I feel like Slack has a lot of legs, because Slack can also be the place where you talk to the agents themselves. But some of the other ones, they are pretty complicated. So it’s kind of hard to buy or that kind of stuff. But I feel like if you have an app like maybe Calendly or something more simple, then why should I pay for it? I just… Why should I pay for it? The counterpoint is that it’s not that expensive. Anish Acharya And do you really want to maintain your own Calendly thing? Yeah. Versus pay 20 bucks a month, it always gets updated, It’s always up. Yeah, yeah. Because there’s just like a fixed amount of capacity that anyone in the organization is going to have for all this stuff. Yeah, that’s true. Unless you hire like dedicated Vibe Corps, like the startup does, and it’s just one of the Vibe Corps stuff. But then it’s the cost benefit versus just paying for Calendly. (Time 0:12:00)
  • The IDE Is Becoming A Thinking Tool
    • Anish Acharya says the IDE is shifting from a making tool into a thinking tool because cheap execution makes experimentation the main value.
    • He often builds a naive feature with agents, asks what should change, then restarts with better understanding; he thinks Figma can stay relevant the same way. Transcript: Anish Acharya My counterpoint to that is that I think that I’ve thought a lot about the sort of thinking tools versus making tools, right? The IDE was historically a making tool. It’s a place for execution. I think it’s migrating away from that. And now with execution going to zero, I think these sort of like multi-agent next-gen IDEs, a lot of them are about trying things and using the trial and error as a way to inform your thinking. Like a lot of times I’ll just build a feature in a really naive way and I’ll hammer the coding agent until it works. Then I’ll say, hey, write all the things that you would have done differently. And I’ll go back to the initial point and redo it. So I wonder if, and I think Figma actually does both. I think it’s a place for design execution, but it’s also an important place for design thinking. And I think that’s their opportunity to be highly relevant in the new stack. Yeah, I totally agree. I totally agree. But I think A16Z has like, you guys are investing Pencil or something? Peter Yang Pencil.dev? Speedrun did, yeah. Yeah, Speedrun. And yeah, Fikamon needs to like level up his AI tooling because like watching these agents collaborate with you and do stuff is like very interesting. Anish Acharya I know it’s top of mind for them. Yeah. What do you think are the most under discussed capabilities of coding agents? What’s under hyped and maybe what’s over hyped as well? (Time 0:13:53)
  • IDEs Are Becoming Thinking Tools Not Just Execution Engines
    • Anish argues IDEs are shifting from pure execution to tools for thinking as execution costs fall to zero.
    • He uses coding agents to rapidly prototype a naive feature, then asks the agent to list improvements and iterates — treating execution as a way to inform design decisions.
    • Figma straddles both worlds: it’s still for design execution but also a space for design thinking, which helps it stay relevant in the new stack.
    • This workflow reframes tools (IDEs, Figma) as partners in discovery, not merely places to type code or draw pixels. Transcript: Anish Acharya My counterpoint to that is that I think that I’ve thought a lot about the sort of thinking tools versus making tools, right? The IDE was historically a making tool. It’s a place for execution. I think it’s migrating away from that. And now with execution going to zero, I think these sort of like multi-agent next-gen IDEs, a lot of them are about trying things and using the trial and error as a way to inform your thinking. Like a lot of times I’ll just build a feature in a really naive way and I’ll hammer the coding agent until it works. Then I’ll say, hey, write all the things that you would have done differently. And I’ll go back to the initial point and redo it. So I wonder if, and I think Figma actually does both. I think it’s a place for design execution, but it’s also an important place for design thinking. And I think that’s their opportunity to be highly relevant in the new stack. Yeah, I totally agree. I totally agree. But I think A16Z has like, you guys are investing Pencil or something? Peter Yang Pencil.dev? Speedrun did, yeah. Yeah, Speedrun. And yeah, Fikamon needs to like level up his AI tooling because like watching these agents collaborate with you and do stuff is like very interesting. Anish Acharya I know it’s top of mind for them. Yeah. What do you think are the most under discussed capabilities of coding agents? What’s under hyped and maybe what’s over hyped as well? Peter Yang This is probably not under hyped, but you know, I feel like entrances that software will eat the world. I feel like coding will eat all knowledge work, right? And we’re kind of going that direction already. Like I think Lovable recently launched like today. Yeah. They can support everything and can make decks yeah so so yeah so i and i feel like everyone’s chasing this and anthropic is probably in the lead yeah i i don’t want to use powerpoint anymore I don’t want to write a (Time 0:13:53)
  • Coding Agents Make Execution Disappear
    • Anish frames IDEs shifting from pure execution tools to thinking tools as execution costs drop to zero.
    • He and Peter both describe a workflow where AI produces the first ~80% and humans finish the last ~20%.
    • Peter predicts coding agents will make code itself invisible: you talk to agents and they do work for you.
    • They compare this shift to Excel becoming a universal programming interface and expect agents to be the same but far larger in impact.
    • The result is higher leverage and accessibility: subjective tasks like writing can be encoded into agent workflows and become more productive. Transcript: Anish Acharya Yeah. What do you think are the most under discussed capabilities of coding agents? What’s under hyped and maybe what’s over hyped as well? Peter Yang This is probably not under hyped, but you know, I feel like entrances that software will eat the world. I feel like coding will eat all knowledge work, right? And we’re kind of going that direction already. Like I think Lovable recently launched like today. Yeah. They can support everything and can make decks yeah so so yeah so i and i feel like everyone’s chasing this and anthropic is probably in the lead yeah i i don’t want to use powerpoint anymore I don’t want to write a group i hate writing google docs dude plus my entire life so like the other day i was writing my blog post and instead of just like typing it out i was like hey let’s Let me just use clock code and let me give you a bunch of feedback and you write it for me yeah and then you just keep it up. It did the first 80%. The last 20% I started to manually go in there like to take stuff. Yeah. But like, that’s the way I work now. Anish Acharya I never start from zero. Like I always get the first 80% from AI. Right. Yeah. Yeah. It’s interesting. If you look at it, there are also like historical analogs of this. I think Satya said this, which is that Excel is the most powerful or most popular programming language in the world. Yeah. And that it’s sort of a programming language that millions and millions, I mean, 100 million plus people must know, maybe even more. And yet we don’t think of it that way. It’s a way to sort of describe and solve problems. Yeah. And I think coding agents are going to be that, of course, times a thousand. Yeah. Where even things that feel subjective, like writing Google Docs, can be represented in the coding domain in such a way that it’s more satisfying, more productive, more high leverage To use agents to do it. Peter Yang Yeah. Cause Excel was like popular because it’s super approachable, right? Yeah. And like coding agents, the code is basically gone. It was like app shod away. You’re just talking to some agent and getting to do stuff. So yeah, yeah, exactly. (Time 0:14:52)
  • Coding Agents Expand Beyond Software Into Knowledge Work
    • Peter Yang believes coding agents will absorb much of knowledge work, not just software engineering, because interfaces are becoming conversational.
    • He now starts writing with AI for the first 80%, using Claude Code to draft blog posts and only manually editing the final stretch. Transcript: Peter Yang This is probably not under hyped, but you know, I feel like entrances that software will eat the world. I feel like coding will eat all knowledge work, right? And we’re kind of going that direction already. Like I think Lovable recently launched like today. Yeah. They can support everything and can make decks yeah so so yeah so i and i feel like everyone’s chasing this and anthropic is probably in the lead yeah i i don’t want to use powerpoint anymore I don’t want to write a group i hate writing google docs dude plus my entire life so like the other day i was writing my blog post and instead of just like typing it out i was like hey let’s Let me just use clock code and let me give you a bunch of feedback and you write it for me yeah and then you just keep it up. It did the first 80%. The last 20% I started to manually go in there like to take stuff. Yeah. But like, that’s the way I work now. Anish Acharya I never start from zero. Like I always get the first 80% from AI. Right. Yeah. Yeah. It’s interesting. If you look at it, there are also like historical analogs of this. I think Satya said this, which is that Excel is the most powerful or most popular programming language in the world. Yeah. And that it’s sort of a programming language that millions and millions, I mean, 100 million plus people must know, maybe even more. And yet we don’t think of it that way. It’s a way to sort of describe and solve problems. Yeah. And I think coding agents are going to be that, of course, times a thousand. Yeah. Where even things that feel subjective, like writing Google Docs, can be represented in the coding domain in such a way that it’s more satisfying, more productive, more high leverage To use agents to do it. Peter Yang Yeah. Cause Excel was like popular because it’s super approachable, right? Yeah. And like coding agents, the code is basically gone. It was like app shod away. You’re just talking to some agent and getting to do stuff. So yeah, yeah, exactly. (Time 0:14:58)
  • Smaller Companies Can Avoid Big Team Misery
    • Peter Yang hopes cheaper software creation keeps companies radically smaller, with two or three product people supported by agents instead of large teams.
    • He contrasts that with big-company coordination drag like multi-hour OKR meetings and says agents are easier to align than humans. Transcript: Anish Acharya What do you think the future company looks like? Is it just a bunch of agents with a CEO? Is the CEO an agent? I mean, what is the role for people in a company in the future? Peter Yang Okay, well, I have some hot techs. So we both worked at some companies together. And let me give you a hot tech, man. Maybe we cut this out. But I feel like as a company gets bigger, it tends to become like a shitty, shitty place to work, dude. Yeah. Because there’s a lot of people. You have to align. I think that’s axiomatic. Yeah. Right? And I remember, maybe we should mention this company, but but I remember our company, we used to have all these like OKR meetings. I remember sitting in a room for three hours talking about OKRs. I’m just like, dude, this is like a waste of my life. Yeah. So where I’m going with this is I hope more companies will stay small. And I think the founders of this generation realize that. Like they want to stay as small as possible. Yeah. And instead of having a 10% prod team, you have a two or three person prod team. And you a bunch of agents to help you. Yeah. I think it’s way easier to cross-function a line with agents than with humans. Anish Acharya Yeah. Well, actually, in a sense, the agents actually, because it takes the emotion out of it too. Like you can imagine if I sent my agent, you sent your agent to go negotiate something and they came out with some conclusion. It’s not emotional. It’s not. For either of us. It’s very objective. Yeah, exactly. Yeah, it’s funny. One of the things that we’ve been talking a bunch about is what is the pro case for AI at work in terms of employee experience? And I think it’s what you’re describing, right? Like, how do you increase the NPS of work? Yeah. So if we, like, go all the way back, or even broadly the NPS of the human experience, right? Think of the NPS of the day-to human in 10,000 BC, when it’s just don’t get eaten by the lion. Yeah. And that’s, like, a good day, right? Or maybe 100 years ago, it’s okay, don’t get killed at the factory, crushed by the steam press or whatever else. And now a lot of it is like, just don’t get sucked into some high emotion, sort of negotiation with another VP’s subordinate. Peter Yang Yeah, like a 50-message of Slack thread going back and forth. Anish Acharya Yeah, exactly. And then eventually everyone’s like, I don’t want to tell the CEO. And eventually it goes there and it’s just terrible. So maybe the future of this is that a lot of that emotional subjective work gets handled. Yeah. And we’re sort of guiding the process, but not in the middle of it in a way that just doesn’t suit us as humans. (Time 0:16:31)
  • Agents Let Small Teams Do Big Work
    • Peter Yang predicts companies will stay intentionally small and use agents to scale cross-functional work instead of hiring large teams.
    • Agents reduce emotional friction (e.g., negotiations, long Slack threads) because they act objectively and can handle subjective tasks.
    • This enables founders to keep product teams tiny (two to three people) while leveraging many agents to increase output.
    • Anish and Peter argue that PMs want to be innovators, but most don’t know how; agents could shift PM roles toward creating more by removing coordination overhead.
    • The broader vision is cheaper software and agents unlocking more one-person businesses and greater human ambition. Transcript: Peter Yang Yeah. I think it’s way easier to cross-function a line with agents than with humans. Anish Acharya Yeah. Well, actually, in a sense, the agents actually, because it takes the emotion out of it too. Like you can imagine if I sent my agent, you sent your agent to go negotiate something and they came out with some conclusion. It’s not emotional. It’s not. For either of us. It’s very objective. Yeah, exactly. Yeah, it’s funny. One of the things that we’ve been talking a bunch about is what is the pro case for AI at work in terms of employee experience? And I think it’s what you’re describing, right? Like, how do you increase the NPS of work? Yeah. So if we, like, go all the way back, or even broadly the NPS of the human experience, right? Think of the NPS of the day-to human in 10,000 BC, when it’s just don’t get eaten by the lion. Yeah. And that’s, like, a good day, right? Or maybe 100 years ago, it’s okay, don’t get killed at the factory, crushed by the steam press or whatever else. And now a lot of it is like, just don’t get sucked into some high emotion, sort of negotiation with another VP’s subordinate. Peter Yang Yeah, like a 50-message of Slack thread going back and forth. Anish Acharya Yeah, exactly. And then eventually everyone’s like, I don’t want to tell the CEO. And eventually it goes there and it’s just terrible. So maybe the future of this is that a lot of that emotional subjective work gets handled. Yeah. And we’re sort of guiding the process, but not in the middle of it in a way that just doesn’t suit us as humans. Yeah. I leave that double life as a PM creator. Peter Yang And like, I feel like all the PMs actually just want to create products. They just want to create products. Anish Acharya Well, that’s why we all got into it. It’s so interesting. I mean, Nikhil talks about this all the time, but like every PM’s sort of view of the ideal PM is the innovator. Like I came up with the new thing and I had the big insight and it unlocked the product. (Time 0:17:16)
  • AI Agents Reduce Emotional Workload In Product Teams
    • Peter and Anish argue AI agents can handle the emotional, negotiation-heavy parts of work (e.g., long Slack threads) and make interactions objective.
    • That reduces human friction and increases the daily NPS of work by removing stressful social negotiations.
    • Agents let small teams stay small and cross-function more easily, replacing large coordinating overhead with tooling.
    • PMs still need product judgment—identifying what problem to solve—but can spend more time creating if routine social work is offloaded.
    • Practically, this could let founders favor tiny product teams (2–3 people) augmented by agents instead of large human-heavy orgs. Transcript: Peter Yang Yeah, like a 50-message of Slack thread going back and forth. Anish Acharya Yeah, exactly. And then eventually everyone’s like, I don’t want to tell the CEO. And eventually it goes there and it’s just terrible. So maybe the future of this is that a lot of that emotional subjective work gets handled. Yeah. And we’re sort of guiding the process, but not in the middle of it in a way that just doesn’t suit us as humans. Yeah. I leave that double life as a PM creator. Peter Yang And like, I feel like all the PMs actually just want to create products. They just want to create products. Anish Acharya Well, that’s why we all got into it. It’s so interesting. I mean, Nikhil talks about this all the time, but like every PM’s sort of view of the ideal PM is the innovator. Like I came up with the new thing and I had the big insight and it unlocked the product. I think the black pill is I don’t think most PMs know how to do that. In fact, many companies have zero people that know how to do that at all in any function. So nonetheless, I think PMs aspire to be able to do that and they should either do it and either be successful or maybe not successful and move to a different function. Peter Yang I also feel like my hot take is like basically all the PMs I know are trying to live code at nights and weekends. And I feel like my hot take is that I feel like if you’re actually unemployed, like you probably have more time to be a builder and to be innovative. You can actually play all this stuff and learn all this stuff. Anish Acharya Or maybe being an engineer in the team. I used to be an engineer and I got sort of, I don’t know if I got forced to be a PM. Maybe I also perceived PM as being a little more high status when I joined Google. But then eventually you come around the other side, you’re like, this is terrible. Like you never really get the satisfaction of actually shipping other than once a quarter when you ship. I mean, the PM skills of talking to users and like trying to figure out what to do, like what’s the problem to solve. Peter Yang Like those are very important still. Yeah. But yeah, you got to wear multiple hats too. (Time 0:18:10)
  • AI Lets Product Managers Become Builders Again
    • Peter Yang says PMs really want to build products, and AI lets them prototype directly instead of waiting for quarterly shipping cycles.
    • Anish Acharya adds that many PMs idolize innovation but rarely get the satisfaction of making things unless they reclaim hands-on creation. Transcript: Anish Acharya Yeah. I leave that double life as a PM creator. Peter Yang And like, I feel like all the PMs actually just want to create products. They just want to create products. Anish Acharya Well, that’s why we all got into it. It’s so interesting. I mean, Nikhil talks about this all the time, but like every PM’s sort of view of the ideal PM is the innovator. Like I came up with the new thing and I had the big insight and it unlocked the product. I think the black pill is I don’t think most PMs know how to do that. In fact, many companies have zero people that know how to do that at all in any function. So nonetheless, I think PMs aspire to be able to do that and they should either do it and either be successful or maybe not successful and move to a different function. Peter Yang I also feel like my hot take is like basically all the PMs I know are trying to live code at nights and weekends. And I feel like my hot take is that I feel like if you’re actually unemployed, like you probably have more time to be a builder and to be innovative. You can actually play all this stuff and learn all this stuff. Anish Acharya Or maybe being an engineer in the team. I used to be an engineer and I got sort of, I don’t know if I got forced to be a PM. Maybe I also perceived PM as being a little more high status when I joined Google. But then eventually you come around the other side, you’re like, this is terrible. Like you never really get the satisfaction of actually shipping other than once a quarter when you ship. I mean, the PM skills of talking to users and like trying to figure out what to do, like what’s the problem to solve. Peter Yang Like those are very important still. Yeah. But yeah, you got to wear multiple hats too. You got to go do that thing yourself, go prototype it and get some feedback and then maybe brand engineer along. (Time 0:18:28)
  • The New Operating Rhythm Is Fast Then Slow
    • Peter Yang rejects rigid annual planning because AI makes it easy to sprint in many directions, then pause to choose what matters.
    • Anish Acharya frames the rhythm as fast local hill-climbing with agents followed by slower searching for the next worthwhile hill. Transcript: Anish Acharya Everyone has to go as fast as, I mean, like Gary was talking about stimmies and skipping sleep and Gary Tan, G-Stack. Peter Yang I mean, is it, hey, I mean, is that like the default way that we all need to work or do you think there’s a trade-off for thoughtfulness? I think it’s very easy now with all these AI tools just going like 10 different directions at once. Yeah. So sometimes you do have to slow down and try to figure out where you want to go. Yeah. But I also believe that the traditional process where you like do annual planning and do all this bullshit, I just feel like that’s fully real. Anish Acharya Realizing a local, a sort of local maxima, you should go very fast, right? So let’s say you kind of hill climb, you get to the bottom of the new local maxima. I think with agents, you should be able to get to the top of that hill extremely fast, right? You have a new insight, build everything around the insight so it’s fully expressed. But then I think to get to the next, the next sort of hill, of like fast and slow, that’s probably the future way. Peter Yang Yeah, I think so. And like, you gotta go that random walk trying to find Mark McAfee, which takes a while, right? So this is not, yeah. (Time 0:19:50)
  • AI Can Make Small Businesses Worth Building Again
    • Anish Acharya thinks business-in-a-box tools can unlock many tiny companies that would never fit venture scale but could still transform someone’s life.
    • He imagines $100,000 TAM products across the world, while Peter Yang says he wants his kids building bootstrap businesses in high school. Transcript: Anish Acharya So we were talking before we started recording about some of the business in a box platforms. Have you looked at them? Do you have a view? I’ve looked at posts yet that we talked about. Peter Yang I don’t know if the guy like intentionally made it the opposite of AI slot. Yes. Is it kind of a… I think so. Anish Acharya Yes, yes, yes, yes. Peter Yang That’s funny. Well, I mean, I have a pretty big public presence, right? So I connect all my shit to it. And then, I mean, it definitely gives a good peek into what’s possible, but like right now it’s probably still pretty like early stage. Like it’s time to run like Facebook ads. Yeah. Why am I running Facebook ads? Anish Acharya Yeah. So yeah. I mean, I’m very excited about it because it does feel like it’s a path for more people to build companies. Even if they’re single one-person companies, if you think about how competitive it is to build a billion-dollar business, like the markets that support it, the number of people trying, Versus $100 million versus $10 million versus $100,000 TAM. Like maybe there are these pockets all over the country, all over the world, where there are opportunities for $100,000 TAM products. And that would change somebody’s life. Now, not an enterprise venture-backed company, but that’s okay. So I hope that whole thesis works because I do think it’s a way to get more people to participate. That’s my plan for my kids, dude. Peter Yang I want them to just build bootstrap businesses in high school and they can skip the whole college and corporate life. Anish Acharya Yeah. Well, dude, I think this is, for 10 years, there’s this moral panic about the kids want to be YouTubers. Yeah. You’re a YouTuber. Yeah. And in the vein of Mr. Beast, I think pro case for that actually is that the kids wanted to be entrepreneurs or have agency. And the only channel for people, if there weren’t programmers, was creating YouTube videos, at least online. Yeah. So if you’re like an online native generation, you want to create something, you’re not a programmer, you make a YouTube show. Now you can make a lot more than that. Yeah, you can build wherever you want. Exactly. So, exactly. (Time 0:21:00)
  • Business-in-a-Box Could Unlock Millions of Small Bootstrap Companies
    • Anish and Peter discuss business-in-a-box platforms as a low-friction path for many people to build companies, even single-person ones.
    • Peter argues these tools can create viable pockets of $10k–$100k TAM products across the world, changing individual lives without needing venture scale.
    • He wants his kids to build bootstrap businesses in high school so they can bypass traditional college and corporate tracks.
    • The comparison to kids wanting to be YouTubers reframes creator careers as entrepreneurship and agency rather than a moral panic.
    • Overall thesis: cheaper, easier software lowers the bar to start businesses, broadening who can participate in entrepreneurship. Transcript: Anish Acharya So we were talking before we started recording about some of the business in a box platforms. Have you looked at them? Do you have a view? I’ve looked at posts yet that we talked about. Peter Yang I don’t know if the guy like intentionally made it the opposite of AI slot. Yes. Is it kind of a… I think so. Anish Acharya Yes, yes, yes, yes. Peter Yang That’s funny. Well, I mean, I have a pretty big public presence, right? So I connect all my shit to it. And then, I mean, it definitely gives a good peek into what’s possible, but like right now it’s probably still pretty like early stage. Like it’s time to run like Facebook ads. Yeah. Why am I running Facebook ads? Anish Acharya Yeah. So yeah. I mean, I’m very excited about it because it does feel like it’s a path for more people to build companies. Even if they’re single one-person companies, if you think about how competitive it is to build a billion-dollar business, like the markets that support it, the number of people trying, Versus $100 million versus $10 million versus $100,000 TAM. Like maybe there are these pockets all over the country, all over the world, where there are opportunities for $100,000 TAM products. And that would change somebody’s life. Now, not an enterprise venture-backed company, but that’s okay. So I hope that whole thesis works because I do think it’s a way to get more people to participate. That’s my plan for my kids, dude. Peter Yang I want them to just build bootstrap businesses in high school and they can skip the whole college and corporate life. Anish Acharya Yeah. Well, dude, I think this is, for 10 years, there’s this moral panic about the kids want to be YouTubers. Yeah. You’re a YouTuber. Yeah. And in the vein of Mr. Beast, I think pro case for that actually is that the kids wanted to be entrepreneurs or have agency. And the only channel for people, if there weren’t programmers, was creating YouTube videos, at least online. Yeah. So if you’re like an online native generation, you want to create something, you’re not a programmer, you make a YouTube show. Now you can make a lot more than that. Yeah, you can build wherever you want. Exactly. So, exactly. Peter Yang It’d be very exciting. Yeah. Any other hot takes for us? (Time 0:21:00)
  • Consumer Products Need Both Agent And Human Interfaces
    • Anish Acharya thinks consumer AI products can survive agent-first behavior because users now accept direct payment, subscriptions, and token-based consumption.
    • He expects products to split into agent-facing APIs for transactions and human-facing interfaces for browsing, feeds, and logs of completed work. Transcript: Peter Yang Any other hot takes for us? I’m curious about your thoughts about this, actually. So, I feel like a lot of people are saying, like, agents will interact with your product first, right? And then you see all these great companies, like, building, like, APIs and MCPs. But, like, how do you think about you being a consumer for a while? So, the consumer is, you’ve got to get the user to come back and use your product, right? But now the user is like, hey, go send the agent to use it. So how do you think about retention and all this basic stuff? Or even like brand equity, because the agent is just putting some API. Yeah, I don’t know. Anish Acharya We had to have indirect monetization. Okay, like we just, we’re never charging consumers directly for these products, which is why you got ads and stuff. Ads and just large-scale networks, and we all obsessed with retention and engagement and whales, and all of these things really mattered because we didn’t simply charge people for Products. So I think one big thing that’s actually really helped in the AI era with that is that consumers are now excited to try new things. They’re willing to pay. They’re willing to pay a really high price point. There’s also consumption revenue in consumer for the first time. Peter Yang Like token and stuff. Anish Acharya Yeah, like token. You have your subscription plus your token. And then the actual blessing in disguise is that there are real costs as well. You have these inference costs. So you’re like, wow, we have to charge our customer on day one. So I think one thing is that the business model simplification, I think will really help with a lot of what you’re describing. Two, I think that a lot of the products will have a sort of, it’ll have an API interface for your agents to interact with or for transactional sort of rote things. And then it’ll have a consumption based interface as well. You can also imagine like a mobile app where there’s like the feed, but then you can kind of turn it over to where the wires are and you can just ask for things to get done or you can just see Peter Yang The log of the things that got done. Yeah. And then people will do both, right? Anish Acharya I mean, you can imagine credit karma where we work. Like once in a while, you want to just take a look at your score history and a few other maybe credit card offers. I don’t know. I mean, yeah. Yeah. If I get my score of all kinds of credit card offers, I’ll definitely do that. Yeah. A hundred percent. Exactly. Yeah. On the other hand, like sometimes you want to just be like, yo, can you just fix all my stuff? Or what stuff did you fix this week? How much money did I save? Yeah, it’s definitely interesting. Yeah. But look, I also just think the whole agent stack is emerging. Identity, payments, marketing. We don’t even CLI versus MCP. Peter Yang And like all of these are really new things. And I think a lot of the old playbook goes away. Yeah, it’s a whole new world. And like in 2025, I thought agents was overhyped, but now I think it’s really kind of coming. Anish Acharya Me too. I know. It’s just the word is frustrating because it gets so overloaded. Yeah. There’s like workflows, like all this kind of shit. Totally. I’ve been trying to just say, can we just say like model in a loop? Peter Yang Yeah, exactly. Model that use tools in a loop. That’s the best definition. Yeah. Yeah. But nobody likes to hear that. It’s agents is much flashier. Yeah, it’s flashier. (Time 0:22:41)
  • Human Ambition Keeps Expanding The Job Market
    • Anish Acharya argues AI will more often amplify workers than fully replace them because complete end-to-end automation remains rare.
    • He thinks the economy’s shape will change toward smaller firms, but human ambition and desire will keep creating new kinds of jobs. Transcript: Peter Yang My hope is that all this stuff’s, like a lot of people think we’re going to lose our jobs. It was probably what would happen at some point. But I hope all this stuff just makes the human work more fun, like our jobs more fun. Anish Acharya Dude, I don’t think we’re all going to lose our jobs. I really think, and we see this in a lot of companies. So we look at a ton of companies and we’ve seen two different buckets. So one bucket is, hey, we dramatically increased productivity for a person or a team. We see this in like recruiting, but we couldn’t do a hundred percent of the job. So we could do the phone screen, but we couldn’t obviously show the candidate around the office, or we could do the phone screen and we can answer all the questions about the company. And we can even do the like comp negotiation, but we couldn’t do the onboarding. The other style of company, which we see, which is maybe a Decagon, right? Or a happy robot is, Hey, we did a hundred percent of a job like customer support. Okay. The customer called in, they had a question. We hopefully resolve their query and then that’s it. And that is 100% automated. I’d say that second group where you have 100% automation of a job function is really rare. Almost every AI product, AI native X or Y we see is able to provide dramatic lift, but it’s not able to do 100%. So the last 10% in Estonia is humans too. Yeah, today anyway, it’s still humans that do that stuff. And it’s interesting too because the buyer looks at that as software, as expensive software, whereas in the case of something like a happy robot docking on Sierra, they look at it as Like cheap labor. So I do think there’s a different buyer mindset, but because there’s been this difficulty of getting to 100% automation, I think a lot of the efficiency gain shows up in just a different Way, probably not less jobs. Maybe we get like the European style four-day work week. Maybe companies get like twice as productive. I have no idea. Peter Yang Yeah, but you don’t think that I feel like there is going to be a transition from like these like 10,000 plus people companies laying a lot of people off to hopefully like more smaller Anish Acharya Companies like solopreneurs and stuff like that. I think, yes, I think that the sort of shape of the economy is going to change, like the amount of concentration, but I just don’t think there’s going to be less jobs. I think human ambition has no ceiling. Human desire has no ceiling. And just read any mildly interesting science fiction book. There’s no way this is the peak expression of all the stuff that we want and we need. And we’re going to convince ourselves. And all the new things that you read about every day is these luxuries, peptides. And everybody is going to have all of that stuff and want even more. You know, dude, I saw a really good tweet about this. Peter Yang Like someone tweeted that the job market is so bad that I can only pursue my dreams now or something like that. Yeah. So maybe you lost your job, but now you can actually do your own thing. Anish Acharya Yeah, 100% and have a shot at actually achieving it. (Time 0:25:26)
  • AI Raises Productivity Without Eliminating Jobs
    • Anish observes two AI outcomes: many tools dramatically increase a person’s productivity but can’t finish 100% of a job, while a few (like some customer-support bots) fully automate a task.
    • Full-job automation is rare; most products deliver large lifts but leave the “last 10%” to humans today.
    • Buyers treat these differently: partial automation looks like expensive software, full automation is framed as cheap labor.
    • Because full automation is hard, efficiency gains will likely reshape work (four-day weeks, smaller companies, more solopreneurs) rather than simply eliminate jobs.
    • Peter and Anish conclude human ambition/desire will continue to expand, creating new demand beyond present automation limits. Transcript: Anish Acharya So one bucket is, hey, we dramatically increased productivity for a person or a team. We see this in like recruiting, but we couldn’t do a hundred percent of the job. So we could do the phone screen, but we couldn’t obviously show the candidate around the office, or we could do the phone screen and we can answer all the questions about the company. And we can even do the like comp negotiation, but we couldn’t do the onboarding. The other style of company, which we see, which is maybe a Decagon, right? Or a happy robot is, Hey, we did a hundred percent of a job like customer support. Okay. The customer called in, they had a question. We hopefully resolve their query and then that’s it. And that is 100% automated. I’d say that second group where you have 100% automation of a job function is really rare. Almost every AI product, AI native X or Y we see is able to provide dramatic lift, but it’s not able to do 100%. So the last 10% in Estonia is humans too. Yeah, today anyway, it’s still humans that do that stuff. And it’s interesting too because the buyer looks at that as software, as expensive software, whereas in the case of something like a happy robot docking on Sierra, they look at it as Like cheap labor. So I do think there’s a different buyer mindset, but because there’s been this difficulty of getting to 100% automation, I think a lot of the efficiency gain shows up in just a different Way, probably not less jobs. Maybe we get like the European style four-day work week. Maybe companies get like twice as productive. I have no idea. Peter Yang Yeah, but you don’t think that I feel like there is going to be a transition from like these like 10,000 plus people companies laying a lot of people off to hopefully like more smaller Anish Acharya Companies like solopreneurs and stuff like that. I think, yes, I think that the sort of shape of the economy is going to change, (Time 0:25:43)