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

6 Apr 2026 · 29 min · 17 chapters

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In short

Coding agents and the “agent stack” replacing many app workflows; why apps may decline as tasks shift to agents; future company structure favoring small teams; impact on work, productivity, and job markets.

Guest backgrounds

Peter Yang is a product manager at Roblox and a creator with a public X/YouTube presence. He previously worked with Anish Acharya at Credit Karma. He also discusses using “OpenClaw” (an agent) personally.

Key claims

Software will “eat” knowledge work via agents; talking to agents beats tapping apps; small teams (2–3 person product teams) plus agents can replace larger orgs; human ambition has no ceiling; AI will automate parts of jobs but full automation is rare.

Notable examples

OpenClaw “Zoe” pulls YouTube analytics and Mercury banking data, updates Google Docs, builds websites, and gives voice “pep talks.” He compares Codex vs “Cloud Code,” and predicts agents will reduce reliance on tools like Calendly/Figma while changing retention/monetization via APIs and consumption.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

The Rise of Coding Agents

0:45 to 1:50

Discussion about the evolution and implications of coding agents on work and productivity.

“Most people open their phone to feel something.”

Peter Yang's Background and Current Work

1:50 to 3:00

Peter Yang shares his journey and experiences at Roblox, including his insights on coding agents.

“Peter and I worked together at Credit Karma for a brief stint, and then we went our separate ways.”

Using OpenClaw for Personal Productivity

3:00 to 5:00

Peter discusses how he utilizes OpenClaw for various personal tasks and insights.

“Like look through all your memory and like give me some like deep insights that I don't know about.”

The Emotional Connection with Agents

5:00 to 6:20

Exploring the personal relationship users can develop with coding agents like OpenClaw.

“Are you asking it to write a skill on the fly?”

The Future of Apps in a World of Coding Agents

6:20 to 7:40

Discussion on how coding agents may replace traditional apps for task completion.

“and then it installed like a two gigabyte thing and then it got a little bit better.”

The Dynamics of Agent Usage and Task Management

7:40 to 9:30

Analyzing how agents change our approach to managing tasks and responsibilities.

“I mean, it sends me like a morning briefing with the top two tweets and stuff, the like trends, but yeah, I still open X and look through it.”

The Controversy Around Coding Agents

9:30 to 11:30

Peter shares his thoughts on the potential downsides and controversies surrounding coding agents.

“For some reason, they trained the model so that at the end of every conversation, it's always like, if you want, I can also do X and Y.”

The Future of SaaS and Internal Tools

11:30 to 13:20

Exploring whether coding agents will replace current SaaS tools and how companies adapt.

“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.”

Embracing Multi-Agent IDEs for Design and Development

14:01 to 14:35

Learn how multi-agent IDEs are transforming execution and design thinking in software development.

“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.”

The Role of AI in Enhancing Coding Capabilities

14:36 to 15:10

Explore the evolving capabilities of coding agents and their impact on knowledge work.

“But I think A16Z has like, you guys investing Pencil or something?”
Show all 17 chapters

The Future of Work: Agents and Human Roles

15:11 to 16:08

Discover how the roles of human employees might change with the rise of coding agents in companies.

“If you look at it, there are also like historical analogs of this.”

Navigating Company Dynamics with AI Agents

16:09 to 17:19

Understand how small teams and AI agents can create better working environments.

“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.”

Redefining Product Management in the Age of AI

17:20 to 18:39

Learn about the changing landscape of product management and the ideal skill sets needed.

“Well, actually, in a sense, the agents actually, because it takes the emotion out of it too.”

Balancing Speed and Thoughtfulness in Work

18:40 to 19:57

Discuss the trade-offs between speed and thoughtfulness when using AI tools in work processes.

“I had the big insight and it unlocked the product.”

The Rise of Solopreneurs and Small Business Models

19:58 to 21:58

Examine the shift towards smaller companies and solopreneurship in the current economy.

“hey, I mean, is that like the default way that we all need to work?”

Consumer Engagement and the AI Era

21:59 to 23:21

Explore how AI is changing consumer behavior and business models in the market.

“So I hope that whole thesis works because I do think it's a way to get more people to participate.”

Job Automation and the Human Experience

23:22 to 25:16

Discuss the nuances of job automation and its implications for human work and satisfaction.

“Okay, like we just, we're never charging consumers directly for these products, which is why you got ads and stuff.”
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Transcript

Automatic transcript. May contain errors.

0:00The interest in said software will eat the world.

0:02Anish Acharya:I feel like coding will eat all knowledge work, right? And we're kind of going that direction already. The whole agent stack is emerging. Identity, payments, marketing, even CLI versus MCP. 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. I hope more companies will stay small. And I think the founders of this generation realize that. They want to stay as small as possible. And instead of having a 10 % product team, you have a two or three person product team. And you have a bunch of agents to help you. Someone tweeted that the job market is so bad that I can only pursue my dreams now.

0:35So maybe you lost your job, but now you can actually do your own thing.

0:39Anish Acharya:Yeah, 100 % and have a shot at actually achieving it. Yeah.

0:45Most people open their phone to feel something. Connected, productive, entertained. Each app is a door to a different emotional state. In 2007, the iPhone gave us the app grid. 19 years later, billions of people still tap the same colored squares dozens of times a day. The interface became so familiar, it stopped feeling like technology. It became reflex. Now a generation of builders is collapsing that entire grid into a single conversation. One agent that checks your analytics, updates your documents, runs your errands, and gives you a pep talk on your morning walk. Not because the apps failed, but because talking is faster than tapping.

1:30The question is, what happens to products, companies, and careers when building software costs almost nothing? A16Z general partner Anish Acharya speaks with Peter Yang, creator and product lead at Roblox.

1:48Anish Acharya:All right, welcome everyone. I've got my friend Peter Yang here. Peter, welcome. Yeah, great to be here. It's good to see you again. Yeah, it's great to see you. Peter and I worked together at Credit Karma for a brief stint, and then we went our separate ways. and I rediscovered Peter from his prolific posts on X and your YouTube. And you've got a little bit of a Clark Kent Superman thing going because you've still got a day job, right? That's what I said with a day job, yes. Yeah, can you share where? Yeah, I work on Roblox as a PM. Amazing, Roblox. And Drees and Portfolio Company. Yes. One of my favorites.

2:16Anish Acharya:Well, incredible, man. Let's get right into it. Maybe I'll start with a softball fun question and then we're going to talk about everything in the claw ecosystem. We're going to talk about coding agents. We're talking about a little bit about maybe what students should study, advice and some of the things that you've talked about online. Yeah, sure. Maybe to start, what is the name of your, how many claws do you have? And tell me their names. I only have one. I call her Zoe. Zoe. But I have like multiple conversations going with her. Okay. Yeah. And why Zoe? I have two girls and I was going to call my younger one Zoe and I did not.

2:45So I'm like, I call my open claw Zoe instead.

2:47Anish Acharya:I see. Yeah. This is your fallback plan. Peter, 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 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 like 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 like pulls analytics for me across youtube and like my mercury banking account it can update google documents for me it can be a little web 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.

3:25Like 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, blah, and like your job. But just remember that your kids, seven and four are going to grow up very soon and they're going to want to spend time with you. Wow. So you should re-optimize for them instead. Yeah.

3:49Anish Acharya:Yeah. That's really cool. Yeah. 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? Yeah, that's a very good question. So I don't know, because I think it's still 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 to it in bed. I've talked to it during my commute and it feels like it feels more like a personal, like actual human. Yeah. 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?

4:32I think it's probably 80 % just the personal part of it because I mostly just talk to it and like, you know, sort of voice. But I also think like it's something, first of all, it is pretty janky. It tends to forget things a lot. Yeah. 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 gotta connect to it you gotta do all this stuff and okay fine i went off and did it yeah and then we had a phone call it called my phone really you have that set up i'm dying to set that up okay it's not very good though like the latency is bad but the fact that i was able to get it going is like pretty impressive so it's kind of like any kind of crazy idea i have it can kind of kind of do and then in practice how are you doing

5:14Anish Acharya: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? 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? Okay. You got to do that. I was like, 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 I, with cloud, I have like very fancy prompts, like very long prompts, but with open cloud, I just kind of text it. Yeah. It is really interesting. So we sort of touched on a couple of things, actually.

5:43Anish Acharya: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? 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 there they updates and it tends to forget things a lot. Yeah. So I actually installed this like three layer memory system that to me I don't fully understand but it has like fancy.

6:17It has Toby's QMD search tool. Okay. So I installed that and then it installed like a two gigabyte thing and then it got a little bit better. Okay. But I still have 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 can you update my Google Doc? It's like oh I can do that. yeah yes you can it's in your it's in your file yes so you have to remind it yeah yeah really

6:41Anish Acharya:interesting well 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 yeah well for first of all i 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 claw like i don't actually open those apps much anymore but i do agree with you like i i think the ones that are gonna die first or like maybe get less usage first it's like apps that you're just opening to try to complete a task like you actually are trying to do something you're not like apps that you're opening to get entertainment can probably survive a little bit longer but like apps that i want you to 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 admins it's a do stuff for it for you yeah yeah and so how much are you finding has this reduced your smartphone usage outside of modulo open call yeah no because i'm like a twitter addict so i see use my phone way too much.

7:35But yeah, in terms of using those apps, it's definitely reduced it. Yeah. 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 X and look through it.

7:49Anish Acharya:Yeah. 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 intents yeah that's what you don't get with Zoe 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 otherwise we're actually working on our project together and then I want to have a public channel where like I'm giving demos.

8:32I don't want to reveal 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. Like you can set up multiple Telegram channels and then I'm not sure if it actually remembers across contexts across the channels, but like you can have separate conversations at least. Got it. Yeah.

8:49Anish Acharya: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't screw my entire drive or something. Yeah. So how 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 at OpenAI, right? Yeah. He's probably going to build something to ChatGPT, which everybody uses so that ChatGPT can actually get stuff done for you and like maybe feels more human.

9:28Yeah. 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 like, if you want, I can also do X and Y. Yeah, yeah. And dude, I got so annoyed about 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, when I want to try to do something real and Cloud Code is when I'm just like vibing.

9:58Anish Acharya:Yeah. 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 and 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. So you don't have to flow state, right? It's hard to get a flow. Like Cloud Code, dude, I tweeted the other day, The clock almost like a slot machine.

10:25It has different things each time. Oh, 100%. It's like a slot machine.

10:28Anish 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. 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.

10:59Like 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. Yeah. But once you customize it, you kind of feel like it's part of you. So it's kind of hard to churn.

11:11Anish Acharya: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 Cloud 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 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, right. 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.

11:42Anish Acharya:So they've just got a bunch of quality of life things. Yeah. Quadcode speaks to Cloud in 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. I mean, they're going to go all in on Codex, I'm sure. Yeah. Talk 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 not an engineer, so I'm a novice. But I do hear that, like I was talking to some folks the other day, an AI native startup, and they're basically trying to have a bunch of Vibe coders.

12:17And 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 bi-coding companies. It's one of the more popular-wise.

12:28Anish Acharya:Interesting. Yeah. Oh, I see. So they're actually an AppGen company. They're an AppGen company, and they're paying for a bunch of SaaS, and they want to get rid of the payment. They want to just bi-coding internal tools. 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... Or 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.

12:57But 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?

13:08Anish Acharya:Though the counterpoint is that it's not that expensive. 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 VibeCore like the startup does, just VibeCore stuff. But then it's the cost benefit versus just paying for Calendly. Yeah, yeah. It's interesting about, for example, like a lot of people are tweeting about Figma recently. Yeah.

13:35It'll stock us down, like, you know, are you going to survive? Yeah. And I feel like the jury's out there. It's kind of hard to say. Yeah. I feel like all the designers are still on Figma, but as a designer, you kind of need to learn how to VibeCore. Otherwise, you're going to, if you want to know how to do Figma, Yeah. You're probably going to be like out of date in a couple of years. Yeah.

13:53Anish 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.

14:22Anish Acharya: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 investing Pencil or something? Pencil.dev? Speedrun did, yeah. Yeah, Speedrun. And yeah, Figma needs to like level up this AI tooling because like watching these agents collaborate with you and do stuff is like very interesting. I know it's top of mind for them.

14:52Anish 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? This is probably not under hyped but you know I feel like and just as 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 that 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 google 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 did the first 80 the last 20 i still had to manually go in there like to take stuff yeah but like that's the way i work now i i never start from zero like i always get the first 80 % from AI, right?

15:44Yeah.

15:45Anish Acharya: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.

16:20Yeah, because Excel was popular because it's super approachable, right? Yeah. And coding agents, the code is basically gone. It's like apps shut away. You're just talking to some agent and getting to do stuff. Yeah. Yeah. Exactly. It's going to be huge. Yeah.

16:31Anish 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? Okay, well, I have some hot takes. So we both worked at some companies together. And let me give you a hot take, man. Maybe we cut this out. But I feel like as a company gets bigger, it tends to become like a shittier 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 at, maybe we should mention this comment, but I remember our company together, we used to have all these like OKR meetings.

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16:59I 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. They want to stay as small as possible. And instead of having a 10 % prod team, you have a two or three person prod team and you have a bunch of agents to help you. Yeah. I think it's way easier to cross-function a line with agents than with humans.

17:20Anish 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? So if we like go all the way back or even broadly the NPS of the human experience, right?

17:48Anish Acharya:Think of the NPS of the day-to-day human in 10 ,000 BC when it's just don't get eaten by the lion and that's like a good day, right? Or maybe a hundred 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. Yeah, like a 50-month-old Slack thread going back and forth. 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 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.

18:28Anish Acharya:Yeah, I leave that double life as a PM creator and like I feel like all the PMs actually just want to create products. They just want to create products. 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. 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.

18:59Anish Acharya:and they should either do it and either be successful or maybe not successful and move to a different function. I also feel like my hot take is like, basically all the PMs I know are trying to live code at nights and weekends. Yeah. 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 like to be innovative. Yeah. You can actually like play all this stuff and learn all this stuff. A lot of PMs are trying to... Or maybe be an engineer in the team. Yeah. I used to be an engineer and I got sort of, I don't know if I got forced to be a PM.

19:24Anish Acharya:Maybe I also perceived PM as like being a little more high status. Yeah, yeah. 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 like those are very important still yeah but yeah you gotta wear multiple hats dude you gotta go put a thing yourself go prototype it and get some feedback and then maybe brand engineer along how much do you think that everyone has to go as fast as I mean like Gary was talking about stimmies and skipping sleep Gary is funny Gary 10 G stack I mean is hey, I mean, is that like the default way that we all need to work?

20:01Anish Acharya: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 do annual planning and do all this bullshit, I just feel like that is fully real.

20:26Anish 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. You know, like fast and slow, that's probably the future way. Yeah, I think so. And like, you gotta go that random walk trying to find a market fit, which takes a while, right? So this is not, yeah. So we were talking before we started recording about some of the business in a box platforms.

21:05Anish Acharya:Have you looked at them? Do you have a view? I've looked at posts, yeah, that we talked about. I don't know if the guy like intentionally made it the opposite of AI slot or is it kind of a... I think so. Yes, yes, yes. 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? Yeah. I don't know. Yeah, yeah. I mean, I'm very excited about it because it does feel like it's a path for more people to build companies.

21:37Anish Acharya:Yeah. 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 a hundred 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 a hundred thousand TAM products. And that would change somebody's life. Now that's 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.

22:06That's my plan for my kids, dude. Like I wanted to just build like bootstrap businesses in high school. Yeah. And they can skip the whole college and corporate life.

22:13Anish 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 the pro case for that actually is that the kids wanted to be entrepreneurs or have agency. And the only channel for people if they 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 be wherever you want. Exactly. so exactly it'd be very exciting yeah any other hard takes for us?

22:43I'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 like the consumer is you gotta get the user to come back and use your product right yeah 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 like how do you or even like brand equity because the agent just took point some API Yeah, I don't know.

23:09Okay, so.

23:20Anish 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. It's in 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.

23:50Anish Acharya:Like tokens and stuff. Yeah, like tokens. You have your subscription plus your token. So, and then the actual, like the sort of 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 like 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.

24:21Anish Acharya:So 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 the log of the things that got done. Yeah, I mean, people will do both, right? 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 with all kinds of credit card offers, I'll definitely do that. Yeah, 100%. Exactly. 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?

24:48Anish Acharya:How much money did I save? Yeah, yeah, I got it. Yeah, it's definitely interesting. Yeah. But look, I also just think the whole agent stack is emerging. Yeah. Identity, payments, marketing. We don't even CLI versus MCP. 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 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 yeah exactly model that use tools in a loop that's the best definition yeah yeah but nobody likes to hear that it's like Agents is much flashier yeah it's flashier yeah my hope is that all this stuff 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 makes just makes the human work more fun like our jobs more fun yeah dude i don't think we're all going to lose our jobs like i really think and we see this 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 increase productivity for a person or a team we see this in like recruiting but we couldn't do 100 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 could answer all the questions about the company and We can even do the like comp negotiation, but we couldn't do the onboarding.

26:03Anish Acharya:Yeah. 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 a hundred percent. So the last 10 % of Estonia is humans too. Yeah, it's still, today anyway, it's still humans that do that stuff.

26:35Anish Acharya: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. Yeah. But you don't think that, I feel like there's 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 companies like solopreneurs and stuff like that.

27:10Anish Acharya: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. That's true. 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's going to have all of that stuff and want even more. You know, dude, I saw a really good tweet about this.

27:39Like 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 like now you can actually do your own thing. Yeah, 100 %

27:47Anish Acharya:and have a shot at actually achieving it. Cool. Well, awesome, man. Maybe that's a good positive note to end on. Yeah, that's a good note. Yeah. Cool. Good thing you do. Thanks, Peter. Thanks for having me. Thanks for listening to the A16Z podcast. If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash A16Z. We've got more great conversations coming your way. See you next time. As a reminder, the content here is for informational purposes only, should not be taken as legal business tax or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund.

28:24Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see a16z.com forward slash disclosures.

From the publisher

Anish Acharya speaks with Peter Yang, creator and product lead at Roblox, about how personal AI agents are replacing the apps we open every day, why coding agents feel like slot machines, and what happens when the cost of building software drops to near zero. They discuss why future companies will stay radically small, how the IDE is becoming a thinking tool rather than a making tool, and why human ambition will always create more jobs than AI eliminates.

Follow Peter Yang on X: https://x.com/petergyang

Follow Anish Acharya on X: https://x.com/illscience

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.


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