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

Summary

The a16z Show — Episode Summary

Episode: Peter Yang on Small Teams, Coding Agents, and Why Human Ambition Has No Ceiling
Date: April 6, 2026
Host: Anish Acharya (Andreessen Horowitz)
Guest: Peter Yang (creator and product lead at Roblox)

---

Overview

In this episode, Anish Acharya sits down with Peter Yang to explore the evolving landscape of coding agents, the future of lean teams, and the endlessly expanding frontier of human ambition in tech. The conversation dives into the day-to-day realities of working with AI-powered personal agents, the shifting role of knowledge workers, and how new AI tools are fundamentally changing what it means to create, innovate, and organize companies.

---

Key Discussion Points and Insights

1. The Rise and Use of “Coding Agents”

• Coding as the New Software:

  • “Software will eat the world. I feel like coding will eat all knowledge work.” (Peter Yang, 00:00)

• Personal Agent Experience:

  • Peter describes using his agent “Zoe” (running on the open-source OpenClaw) for a range of daily tasks: pulling analytics, updating documents, building websites, and even for personal pep talks via voice.
    • “Every other day I said, you 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.” (Peter Yang, 03:03)
    • Notable moment: Zoe reminds Peter to “re-optimize for your kids...7, 4, are going to grow up very soon...” (03:29)

• Why Agents Are Different from Apps or LLMs:

  • Messaging and voice interfaces make agents feel more human and approachable than traditional LLMs (like ChatGPT or Claude).
    • “It just feels like more personal than using like Cloud or ChatGPT.” (Peter Yang, 03:56)
    • "I just kind of text it in bed, I talk to it during my commute..." (Peter Yang, 03:59)

• Technical Friction:

  • Current memory systems are “janky”—often forgetting things—requiring manual reminders and hacks to improve recall.
    • “The default memory system is actually not that great.” (Peter Yang, 05:59)
    • “I actually installed this like three layer memory system that to be honest, I don't fully understand.” (Peter Yang, 06:10)

---

2. Agents Displacing Apps and SaaS: Workflow Transformation

• Task-based Apps May Die First:

  • “The ones that are going to die first...are like apps that you're just opening to try to complete a task. It’s just way easier to text my agent to do it.” (Peter Yang, 06:55)

• Not Everything Is Replaceable—Yet:

  • Entertainment-focused apps still bring users back for emotional reasons (fun, connection, etc.).
    • “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.” (Anish Acharya, 07:55)

• Multiple Agent Channels:

  • Peter uses different Telegram channels with Zoe for different tasks and contexts, simulating how dedicated apps helped anchor different “intents.” (08:21)

---

3. Productization and Platform Evolution

• How Will Agents Be Productized?

  • Peter expects major LLM companies to develop more agent-like, action-oriented products.
  • Critique: ChatGPT’s conversational strategy is often annoying due to over-verbose suggestions.
    • “For some reason they trained the model so that at the end of every conversation...I got so annoyed by it that that kind of turned [me] from ChatGPT.” (Peter Yang, 09:31)

• Agent Types and Programming Experiences:

  • Differentiation between models: Codex for reliability, Claude for flow and creativity.
    • “Codex when I want to try to do something real and cloud code is when I'm just like vibing.” (Peter Yang, 09:54)
    • “Claude code, a lot of the reasons that I enjoy it are just harness features...quality of life things.” (Anish Acharya, 11:16)

---

4. The Future of Internal Tools, SaaS, and Company Structure

• DIY Internal Tools Emerging:

  • Companies, especially AI-native ones, are increasingly replacing paid SaaS tools with in-house agent-powered automations.
    • “All of vive coders are just trying to build internal tools that replace their SaaS...” (Peter Yang, 12:06)

• Limits of Adoption:

  • For complex or mission-critical tools, convenience and reliability of SaaS will still rule, unless organizations have the capacity to hire specialist “vibe coders.” (13:14)

• Design and ‘Vibe Coding’ Skills:

  • Future designers may need to code conversationally (“vibe code”) just to keep up with emerging AI-powered design platforms. (13:49)

---

5. Reimagining Knowledge Work and Creativity

• Knowledge Work as Coding:

  • “I feel like coding will eat all knowledge work. Right. And we're kind of going that direction already.” (Peter Yang, 14:58)

• AI as the New Starting Point:

  • Peter does not start writing from scratch anymore—AI does the first 80%, he tweaks the last 20%.
    • "That's the way I work now. I never start from zero. Like, I always get the first 80% from AI." (Peter Yang, 15:38)

• Excel as Proto-Agent Platform:

  • Satya Nadella called Excel “the most popular programming language in the world,” presaging mass coding via approachable interfaces; agents soon will fill this role even further. (15:44–16:20)

---

6. The Future Shape of Companies

• Lean Structures and Agent Teams:

  • “Instead of having a 10 person product team, you have like two or three person product team and you just have a bunch of agents to help you.” (Peter Yang, 17:03)

• Reduced Emotional Friction:

  • Agents can take the emotional charge out of inter-team negotiations and communications.
    • “It's not emotional. It's not for either of us. It's very objective.” (Anish Acharya, 17:20)

• Focus on High-NPS, Fulfilling Work:

  • AI’s role is seen as not to eliminate all jobs, but to automate away bureaucracy, improving the core “employee experience” and allowing humans to spend more time on creative and fulfilling tasks. (17:44–18:28)

---

7. Human Ambition & New Frontiers in Employment

• No Ceiling for Human Drive:

  • “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...” (Anish Acharya, 27:19)

• Solopreneurism and New Opportunities:

  • AI platforms could dramatically lower the barriers to building small, self-sustaining businesses, opening entrepreneurship to millions.
    • “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...I hope that whole thesis works because I do think it's a way to get more people to participate.” (Anish Acharya, 21:49–22:06)

• Education and the Next Generation:

  • Peter’s goal for his children: skip “corporate life,” learn to bootstrap and build online, leveraging AI as a force multiplier from a young age. (22:06–22:14)

---

8. Companies, Retention, and the Agent-Consumer Interface

• Business Models Will Evolve:

  • Agents’ tendency to interact directly with product APIs means companies may need new retention and monetization tactics—likely moving away from the era of obsessive engagement metrics towards more direct value capture. (23:01–24:49)

• Two Types of AI Impact on Jobs:

  • Dramatic productivity lifts (partial task automation) vs. rare cases of jobs fully automated away.
    • “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%.” (Anish Acharya, 26:12)
    • “Last 10% is still these humans.” (Peter Yang, 26:30)

---

Notable Quotes & Moments

• “I feel like coding will eat all knowledge work.” – Peter Yang (00:00, 14:58)
• On delegating with agents:
  “It’s just way easier to text my agent to do it for me. It’s like you have a really good admin just to do stuff for you.” – Peter Yang (06:55)
• On AI’s creative partnership:
  “I never start from zero. Like, I always get the first 80% from AI.” – Peter Yang (15:38)
• On lean future teams:
  “Instead of having a 10 person product team, you have like two or three person product team and you just have a bunch of agents to help you.” – Peter Yang (17:03)
• Human ambition expanding:
  “Human ambition has no ceiling.” – Anish Acharya (27:19)
• On new opportunities:
  “Maybe you lost your job, but like, now you have to do your own thing and have a shot at actually achieving it.” – Peter Yang (27:44)

---

Timestamps for Important Segments

• 00:00 – Peter Yang: “Coding will eat all knowledge work.”
• 02:34 – Naming Zoe and agent “personalities”
• 03:03–03:48 – Agents as conversation partners/pep talks
• 06:50 – Why task-focused apps will fade first
• 09:31 – Frustrations with ChatGPT UX conventions
• 12:06–13:49 – Internal agent-powered tools replacing SaaS
• 15:38 – Peter on starting creative work from AI
• 17:03 – The future of small, agent-augmented teams
• 21:49–22:06 – The promise of solopreneurism in the agent era
• 23:01–24:49 – Business model, retention, agent-consumer relationships
• 26:12–26:32 – Jobs: full automation is rare, humans still in the loop
• 27:19 – Human ambition’s limitless future

---

Conclusion

This fast-paced, candid conversation points toward a world where teams shrink, coding agents proliferate, and the very notion of “work” becomes unrecognizable compared to today. Agents may not just eat the world—they may enable millions more to build, create, and chase ambitious new ventures. The constant: as technology raises the ceiling, human drive and creativity will always push to climb even higher.

Transcript

[Peter Yang]

Interesting. Says software will eat the world. I feel like coding will eat all knowledge work.

[Anish Acharya]

Right.

[Peter Yang]

And we're kind of going that direction already.

[Anish Acharya]

The whole agent stack is emerging. Identity, payments, marketing, even CLI versus mcp. Like, all of these are really new things. And I think a lot of the old playbook goes away.

[Peter Yang]

Yeah. It's a whole, whole new world. 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.

[Anish Acharya]

Yeah.

[Peter Yang]

And instead of having like a 10 person product team, you have like a two or three person product team and you have a bunch of agents help help you. Yeah. Someone tweeted that, like, job market is so bad that I can only pursue my dreams now. So, like, it's like, you know, it's like, yeah, so maybe you lost your job, but like, now you have to

[Anish Acharya]

do your own thing and have a shot at actually achieving it, you know? Yeah.

[Podcast Narrator]

Most 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. The 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.

[Anish Acharya]

All right, welcome, everyone. I've got my friend Peter Yang here. Peter, welcome.

[Peter Yang]

Yeah, great to be here. It's good to see you again.

[Anish Acharya]

Yeah, 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. Going because you've still got a day job, right?

[Peter Yang]

That's right. I still have a day job. Yes.

[Anish Acharya]

Yeah. Can you share where?

[Peter Yang]

Yeah, I work on Roblox as a pm.

[Anish Acharya]

Amazing. Roblox Andreessen portfolio company. Yes, one of my favorites. 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. Well, how many claws do you have? And tell me their names.

[Peter Yang]

I only have one. I call her Zoe.

[Anish Acharya]

Zoe.

[Peter Yang]

But I have like multiple conversations going with her.

[Anish Acharya]

Okay.

[Peter Yang]

Yeah.

[Anish Acharya]

And why Zoe?

[Peter Yang]

I have two girls and I was going to call my younger one Zoe and I did not. So I'm not. I call my openclaw Zoe instead.

[Anish Acharya]

I see.

[Peter Yang]

Yes.

[Anish Acharya]

Yeah. This is your fallback plan?

[Peter Yang]

Yeah.

[Anish Acharya]

Peter, tell me a little bit about openclaw, 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, 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 build 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 said, you 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.

[Anish Acharya]

Okay.

[Peter Yang]

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's 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, 7, 4 are going to grow up very soon and they're going to want to spend time with you.

[Anish Acharya]

Wow.

[Peter Yang]

So you should re optimize for them instead.

[Anish Acharya]

Yeah, that's really cool. And I mean very cool. But also something that all the language models could have done prior. So what's the difference between this in a use case like that?

[Peter Yang]

Yeah, that's a really good question. So I don't know because I think install on Telegram, it just feels like more personal than using like Cloud or ChatGPT and just feels like something I can text embed. It's probably not very healthy but like I text to 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 the personable part of it because I mostly just talk to it and like, you know, through voice. But I also think like is something. First of all, it is pretty janky. It tends to forget things a lot.

[Anish Acharya]

Yeah.

[Peter Yang]

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 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 I was like, okay, you got to connect twil Twilio, you got to do all this stuff. And then, okay, fine, I went off and did it.

[Anish Acharya]

Yeah.

[Peter Yang]

And then we had a phone call. It called my phone.

[Anish Acharya]

Oh, really? You have that set up? I've been dying to set that up.

[Peter Yang]

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 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 talked to you in a super casual way with like, just like a friend. So I'm like, hey, hey, hey, Zoe, can you like, can I have a phone call? Okay, you gotta 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 would troubleshoot a little bit and then it works. So I, with cloud I have like very fancy prompts, like very long prompts. But with OpenCloud I just kind of text it.

[Anish Acharya]

Yeah, it is really interesting. So we sort of touched on a couple of 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.

[Anish Acharya]

Okay.

[Peter Yang]

Like the way I understand it works is just like a memory MD text file.

[Anish Acharya]

Yes.

[Peter Yang]

And then Every day. Per day. Right. And every day it updates and it tends to forget things a lot.

[Anish Acharya]

Yeah.

[Peter Yang]

So I actually installed this like three layer memory system that to be honest, I don't fully understand.

[Anish Acharya]

But it has fancy.

[Peter Yang]

It has Tobi's QMD search tool.

[Anish Acharya]

Okay.

[Peter Yang]

So I installed that and then installed like a 2 gigabyte thing and then it got a little bit better. Okay. But I said to remind it. I put it into the agents md. Hey, like before you answer any question for 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? Oh, I can't do that.

[Anish Acharya]

Yeah.

[Peter Yang]

Yes, you can. It's in your. It's in your file.

[Anish Acharya]

Yes.

[Peter Yang]

So you have to remind it.

[Anish Acharya]

Yeah, yeah. Really interesting. 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.

[Anish Acharya]

We take it all as fact.

[Peter Yang]

Yeah.

[Anish Acharya]

Yes.

[Peter Yang]

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. Like, I think the ones that are going to die 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. Apps that you're opening to get entertainment can probably survive a little bit longer, but apps are opening to complete a task. It's just way easier to text my agent to do it for me. It's like you have a really good admin just to do stuff for you.

[Anish Acharya]

Yeah.

[Peter Yang]

Yeah.

[Anish Acharya]

And so how much are you finding? Has this reduced your smartphone usage outside of Modulo openclaw?

[Peter Yang]

Yeah. No, because I'm like a Twitter addict, so I still use my smartphone way too much. But yeah, in terms of using those apps, it's definitely reduced. It's.

[Anish Acharya]

Yeah. Yeah, because you're not going to ask Zoe, hey, read my ex for me and tell me what's interesting.

[Peter Yang]

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

[Anish 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.

[Peter Yang]

Yeah.

[Anish Acharya]

And I Think, of course there's some like functional set of needs, which is why you open Calendar or something. But I 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.

[Peter Yang]

Yeah, that's.

[Anish Acharya]

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. Another one is we're actually working on our project together and then I want to have a public channel where like I'm giving that demos. I don't want to reveal private information.

[Anish Acharya]

Yes.

[Peter Yang]

So I have like multiple channels.

[Anish Acharya]

And is that implemented as sub agents or.

[Peter Yang]

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 contests across the channels, but like you can have separate conversations at least.

[Anish Acharya]

Got it.

[Peter Yang]

Yeah.

[Anish Acharya]

And how transparent are you with your agent? Does it. Do they see your personal email or.

[Peter Yang]

I'm like super transparent. Well, I did buy the Mac Mini and set up its own email.

[Anish Acharya]

Okay.

[Peter Yang]

But I gave it like read access to my email and like calendar and. And I also give it like write access to some docs.

[Anish Acharya]

Yeah.

[Peter Yang]

But it kind of screwed up my entire drive or something.

[Anish Acharya]

Yeah. So how do you imagine openclaw, which it's sort of an architecture and a primitive.

[Peter Yang]

Yeah.

[Anish Acharya]

How does it get productized, packaged for the world?

[Peter Yang]

I mean, I think that's what Peter Steinberg is working now at OpenAI. Right. He's probably going to build something to ChatGPT, which every uses so that ChatGPT can actually get stuff done for you and like maybe feels more human. Yeah, dude, let me rant about ChatGPT, please.

[Anish Acharya]

Yeah.

[Peter Yang]

For some reason they trained the model so that at the end of every conversation is always, if you want, I can also do X and Y. I got so annoyed by it that that kind of turned from ChatGPT.

[Anish Acharya]

Oh really? Yeah.

[Peter Yang]

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?

[Anish Acharya]

Are you a cloud guy now?

[Peter Yang]

Yeah, I'm a cloud guy now, but I do use Codex to code. Yeah.

[Anish Acharya]

Yeah, you like Codex. You prefer it to Claude code or you use both?

[Peter Yang]

Codex 1. I want to try to do something real and cloud code is when I'm just like vibing.

[Anish Acharya]

Yeah. Well, it's interesting. I think they live at different points and there's a sort of space of trade offs.

[Peter Yang]

Ye.

[Anish Acharya]

Whereas I find Quadcode and Opus 4.6, it's a little more chatty, it makes more assumptions, but it can be more pleasant for a synchronous experience. 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.

[Peter Yang]

Yeah. You don't have to flow state.

[Anish Acharya]

Right.

[Peter Yang]

It's hard to get a flow like clockwise. Dude, I tweeted the other day clock almost like a slot machine. It has different things each time.

[Anish Acharya]

A hundred percent is like slum machine. 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. Like cloud code, you have all this crazy shit. You have like hooks and like skills and you have to plug ins. If you're not following Twist. Yeah. If you're not following X, you have no idea how do you customize this thing?

[Anish Acharya]

Yeah.

[Peter Yang]

But once you customize it, you kind of feel like it's part of you. So it's kind of hard to turn.

[Anish Acharya]

It's interesting with. So I've customized mine because also I read the long thing that Boris put up.

[Peter Yang]

Yeah.

[Anish Acharya]

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 before and then paste that file into codecs.

[Peter Yang]

Okay.

[Anish Acharya]

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 cloud code. Oh really? Okay.

[Peter Yang]

Okay.

[Anish Acharya]

So just like little things like that cloud code, 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.

[Peter Yang]

Yeah.

[Anish Acharya]

Claude Code speaks to Claude in Chrome.

[Peter Yang]

Okay.

[Anish Acharya]

And Codex doesn't speak to Atlas.

[Peter Yang]

Got it.

[Anish Acharya]

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.

[Peter Yang]

Yeah, yeah, they need to fix it. I mean, they're going to go all in on code Codex, I'm sure. Yeah.

[Anish Acharya]

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?

[Peter Yang]

Well, first of all, I'm like, I'm not an engineer, so I'm like a novice. But I do hear that like I was talking to some folks the other day an AI native start startup and they're basically trying to. They have a bunch of vive coders and all of vive coders are just trying to build internal tools that replace their SaaS that they're paying for.

[Anish Acharya]

Really? So it's an actual company that's doing this?

[Peter Yang]

It's actual company?

[Anish Acharya]

Yeah, it's AI native company.

[Peter Yang]

It's like one of the vive coding companies. It's like one of the more popular.

[Anish Acharya]

Interesting. Yeah, it's interesting. Oh, I see. So they're actually an appgen company.

[Peter Yang]

They're app gen company and they're paying for a bunch of SaaS and they want to get rid of the payment. They want to just buy coding internal tools by using.

[Anish Acharya]

Okay, so in that case, that they might be the most extreme form of adopter because their own product is appgen, so they should use appgen for everything. Yeah, 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 be hard to buy code, that kind of stuff. But I feel if you have an app like maybe Calendly or something more simple. Yeah, then why should I pay for it?

[Anish Acharya]

I just. Why should I pay for it though? The counterpoint is that it's not that expensive. And do you really want to maintain your own calendly thing?

[Peter Yang]

Yeah.

[Anish Acharya]

Versus pay 20 bucks a month. It always gets updated, it's always up.

[Peter Yang]

Yeah.

[Anish Acharya]

Because there's just like a fixed amount of capacity that anyone in the organization is going to have for all this stuff.

[Peter Yang]

Yeah, that's true. Unless you hire like dedicated vibe corners, like the startup that's just some of the vibe cool stuff.

[Anish Acharya]

But then it's the cost benefit versus just paying for calendly.

[Peter Yang]

Yeah, yeah. It's interesting. For example, like a lot of people are tweeting about Figma recently.

[Anish Acharya]

Yeah.

[Peter Yang]

The stock is down. Like you know, are you going to survive?

[Anish Acharya]

Yeah.

[Peter Yang]

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 vibe code. Otherwise you're going to. If you want to do figma.

[Anish Acharya]

Yeah.

[Peter Yang]

You're probably going to be like out of date in a couple years.

[Anish Acharya]

Yeah. 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.

[Peter Yang]

Yeah, yeah.

[Anish Acharya]

And I think that's their opportunity to be highly relevant in the new stack.

[Peter Yang]

Yeah, I totally agree. I totally agree. But I think a 16Z has like you guys investing pencil or something?

[Anish Acharya]

Pencil.dev speedrun did.

[Peter Yang]

Yeah, Speedrun. And yeah. Figma needs to like level up its 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.

[Peter Yang]

Yeah.

[Anish Acharya]

What do you think are the most under discussed capabilities of coding agents? Oh, what's underhyped and maybe what's overhyped as well.

[Peter Yang]

This is probably not underhyped but you know, I feel like Anderson says 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.

[Anish Acharya]

So.

[Peter Yang]

Yeah. So. And I feel like everyone's chasing this and Robin is probably in the lead.

[Anish Acharya]

Yeah.

[Peter Yang]

I don't want to use PowerPoint anymore. I don't want to write a Google. I hate writing Google Oxidate plus my entire life. So, like, for the other day, I was writing my blog post and instead of just like typing out, I was like, hey, let's let me just use cloud code and let me give you a bunch of feedback and you write it for me.

[Anish Acharya]

Yeah.

[Peter Yang]

And then you. It did the first 80%, the last 20%, I said madly going there, like Twitter tweak stuff.

[Anish Acharya]

Yeah.

[Peter Yang]

But like, that's the way I work now. I never start from zero. Like, I always get the first 80% from AI.

[Anish Acharya]

Right.

[Peter Yang]

Yeah.

[Anish Acharya]

Yeah. It's interesting. If you look at. 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.

[Peter Yang]

Yeah.

[Anish Acharya]

And that it's sort of a programming language that millions and millions, I mean, a hundred 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.

[Peter Yang]

Yeah.

[Anish Acharya]

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. Because Excel was like popular because it's super approachable.

[Anish Acharya]

Right.

[Peter Yang]

Yeah. And like coding agents, the code is basically gone. It's like app shut away. Just talking to some agent and getting to do stuff. So.

[Anish Acharya]

Yeah. Yeah, exactly.

[Peter Yang]

It's going to be huge. Yeah.

[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 takes. So we both worked at some companies together and let me give you a hot take, man. Maybe we'll cut this out, but I feel like as a company gets bigger, it tends to get shit. It tends to become like a shitty, shittier place to work, dude. Yeah. Because there's a lot of people. You have to align.

[Anish Acharya]

I think that's axiomatic. Yeah.

[Peter Yang]

Right. And I remember. Maybe we should mention this company, but I remember our company. We used to have all these like OKR meetings and every sitting in a room for three hours talking about OKRs. I'm just like, dude, this is like wasting my life.

[Anish Acharya]

Yeah.

[Peter Yang]

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 person product team, you have like two or three person product team and you just have a bunch of agents to help you. Yeah. I think it's way easier to cross functional lines 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.

[Peter Yang]

It's very objective.

[Anish Acharya]

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?

[Peter Yang]

Yeah.

[Anish Acharya]

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 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. 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 Slack thread going back and forth.

[Anish Acharya]

Yeah. Which, 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 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. Yeah.

[Peter Yang]

I lead a double life as a PM creator and like I feel like all the PMs actually just want to create products. They want to create products and well,

[Anish Acharya]

that's why we all got into it. It's so interesting. I mean, Nikhil talks about this all the time that 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.

[Peter Yang]

Yeah.

[Anish Acharya]

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 vibe 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.

[Anish Acharya]

Yeah.

[Peter Yang]

You can actually like play all this stuff and learn all this stuff while the PM's always trying to.

[Anish Acharya]

Or maybe being an engineer in the team.

[Peter Yang]

Yeah.

[Anish Acharya]

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 like 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. Yeah. Yeah. Like you don't never really get the satisfaction of actually shipping other than once a quarter when you ship.

[Peter Yang]

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 got to wear multiple hats too. You got to go through the thing. You're so gonna prototype it and get some feedback and then may brand engineer law.

[Anish Acharya]

How much do you think that everyone has to go as fast as. I mean, like Gary was talking about stimmies and skipping sleep and Gary Tam G Stack. I mean, is, 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?

[Peter Yang]

I think it's very easy now with all these AI tools just going like 10 different directions at once.

[Anish Acharya]

Yeah.

[Peter Yang]

So sometimes you do have to slow down and try to figure out where you want to go.

[Anish Acharya]

Yeah.

[Peter Yang]

But I also believe that the traditional process where like do annual planning and do all this bull bullshit, I just

[Anish Acharya]

feel like that's fully 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 a 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, try to find market fit, which take takes a while. Right. So this is not.

[Anish Acharya]

Yeah. 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?

[Peter Yang]

I've looked at post. 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.

[Anish Acharya]

You can hesitate. I think so. 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, 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 earlier stage. Like it's time to run like Facebook ads.

[Anish Acharya]

Yeah.

[Peter Yang]

Why am I running Facebook ads?

[Anish Acharya]

Yeah. So. 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.

[Peter Yang]

Yeah.

[Anish Acharya]

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 million versus 10 million versus $100,000 Tam.

[Peter Yang]

Yeah.

[Anish Acharya]

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 that's not an enterprise venture backed company, but that's okay.

[Peter Yang]

Yeah.

[Anish Acharya]

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

[Peter Yang]

Yeah, that, that, that's my plan for my kids, dude. Like I, I want them to just build like bootstrap businesses in high school.

[Anish Acharya]

Yeah.

[Peter Yang]

And they can skip the whole college and core corporate life. Yeah.

[Anish Acharya]

Well, dude, I think this is for 10 years there's this moral panic. Want to be YouTubers? Yeah, you're a YouTuber. 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 they weren't programmers was creating YouTube videos. At least online.

[Peter Yang]

Yeah.

[Anish Acharya]

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.

[Peter Yang]

Yeah. You can build wherever you want.

[Anish Acharya]

Exactly.

[Peter Yang]

So.

[Anish Acharya]

Exactly.

[Peter Yang]

It'd be very exciting.

[Anish Acharya]

Yeah. Any other hot takes for us?

[Peter Yang]

I'm curious about your thoughts. About this actually. So I feel like a lot of people are saying agents will interact with your product first. Right. And then you see all these great companies like building APIs and MCPs. But how do you think about you being a consumer for a while? So the consumers, you got to get the user to come back and use your product.

[Anish Acharya]

Right.

[Peter Yang]

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's just like pointing some API. Yeah, I don't.

[Anish Acharya]

Okay. So. We had to have indirect monetization. Okay. Like we just can. We're never charging consumers directly for these products, which is why you got ads and stuff. Ad then 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 helpful 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 tokens and stuff.

[Anish Acharya]

Yeah. For 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.

[Peter Yang]

Yeah.

[Anish Acharya]

And then it'll have a consumption based interface as well. So you can also imagine like a mobile app or 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.

[Peter Yang]

Yeah. And then people would do both.

[Anish Acharya]

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.

[Peter Yang]

Yeah, yeah. If I get my score with all kinds of credit card offers, I'll definitely do that.

[Anish Acharya]

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? How much money did I save?

[Peter Yang]

Yeah, yeah, it's definitely interesting. Yeah.

[Anish Acharya]

But look, I also just think the whole agent stack is emerging. 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.

[Peter Yang]

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 Me too.

[Anish Acharya]

I know, it's just the word is frustrating because it gets so overloaded.

[Peter Yang]

Yeah. There's like workflows, like all this kind of shit.

[Anish Acharya]

Totally. I've 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.

[Anish Acharya]

But nobody likes to hear that. It's a. Agents is much flashier.

[Peter Yang]

Yeah, it's flashier.

[Anish Acharya]

Yeah.

[Peter Yang]

My, my hope is that all this stuff's like. A lot of people think we're gonna lose our jobs, which 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, you know?

[Anish Acharya]

Dude, I don't think we're all gonna lose our jobs. Like I really think that. 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. 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 could answer all the questions about the company and we could even do the like comp. Negotiation but we couldn't do the onboarding.

[Peter Yang]

Yeah.

[Anish Acharya]

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.

[Peter Yang]

Okay.

[Anish Acharya]

The customer called in, they had a question, we hopefully resolved 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%.

[Peter Yang]

So last 10% is still these humans.

[Anish Acharya]

Yeah, it's still. It's 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'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.

[Anish 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 CS ceiling.

[Peter Yang]

That's true.

[Anish Acharya]

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.

[Peter Yang]

You know, dude, I saw a Rika tweet about this. 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 like now you have to do

[Anish Acharya]

your own thing 100% and have a shot at actually achieving it. Cool. Well, awesome, man. Maybe that's a good positive note to end on.

[Peter Yang]

Yeah, that's a good note. Yeah.

[Anish Acharya]

Cool.

[Peter Yang]

Good thing to do.

[Anish Acharya]

Thanks, Peter. Yeah, thanks for having me.

[Podcast Narrator]

Thanks for listening to the A16Z podcast. If you enjoyed the episode, let us know by leaving a [e-mail] 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. Please 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 disclosures.