Network Effects, AI Costs, and the Future of Consumer Investing with Anish Acharya on The Kevin Rose Show

Summary

The a16z Show: Network Effects, AI Costs, and the Future of Consumer Investing

Guest: Anish Acharya (General Partner, Andreessen Horowitz)
Host: Kevin Rose
Episode Date: April 19, 2026

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Episode Overview

In this episode—originally aired on The Kevin Rose Show—Kevin and Anish Acharya dive deep into the current and future landscape of consumer technology, focusing on the rapidly changing world of AI, the shifting costs associated with AI development, and what constitutes a defensible product in an age of fast replication. They discuss infrastructural and cultural shifts, venture investing, the societal impact of AI, personal creative processes, and even longevity science.

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Key Discussion Points & Insights

1. The Changing Nature of Building and Creativity (00:00–07:59)

• Coding Accessibility & Creativity

  • Coding is becoming far more accessible, especially for those with more ideas than technical discipline.
  • Anish Acharya: “I always had the creative ideas. My ADHD was too bad... I just couldn't remember all the syntax... and so now... I just realize I don't ever have to look at code again.” (03:12)
  • AI is now writing, reviewing, and fixing code, letting builders focus on ideas over syntax.

• Information Flow & App Ephemerality

  • There’s an increasing separation between files (as lasting units of data) and applications (as ephemeral interfaces).
  • Kevin Rose: “Apps and intelligence are these ephemeral things, but files are permanent...” (05:56)
  • Markdown emerges as a practical, interoperable format for storing and moving information across applications.

2. AI as Productivity Booster & "Productivity Porn" (07:59–12:39)

• Proliferation of Micro-Apps

  • Anyone can quickly build small SaaS apps—raising questions about defensibility and value.
  • Kevin Rose: "'Productivity porn' ... we have this new way of learning which is just trying things ... there's so much information in exploration." (11:55)

• Defensibility and Moats in a Fast-Replicating World

  • Traditional moats based on engineering effort are vanishing; value now resides in network effects and community, not just tech.
    • Kevin Rose: "Consumer moats are as good as gold. Things like network effects, they're not trivially reproducible by models." (12:20)

3. Network Effects vs. Code Moats (12:39–16:16)

• Replicability of Software

  • Software can now be cloned in hours, but true defensibility remains in community, social context, and networks.
    • Anish Acharya: “Now it might be 48 hours of work, you know.” (14:40)
  • Cultural inertia and early consolidation still give rise to dominant players (e.g. Wordle, OpenClaw).

• Cost Challenges for AI Startups

  • AI inference isn’t free, shifting the venture math for new consumer applications.
    • Kevin Rose: “I need to raise like $25 million if I want to have a hundred thousand MAUs ... the money will go quickly.” (15:41)

4. Model Wars & Platform Differentiation (16:16–22:27)

• The State of the AI Model Ecosystem

  • OpenAI, Anthropic, and Mistral are all in play; OpenAI’s user numbers and model quality give it a “sort of unassailable advantage in consumer.” (16:51)
  • OpenAI’s choices (like restricting model access or “nerfing” outputs) stem as much from infrastructure constraints and marketing as safety.
    • Kevin Rose: “It's nerfed because they may be trying to free up GPU capacity...” (18:35)

• Consumer Allegiance is Transactional

  • For sophisticated users, allegiance to model providers is fluid; most users stick with household names.
    • Anish Acharya: “My credit card just transfers to whatever model and it starts working again.” (20:12)

5. Consumer Adoption & AI Pricing (21:33–23:42)

• AI Adoption Lag Among Everyday Consumers

  • “Red pilling” friends shows the adoption curve is just beginning for most; the transformative power is much clearer to deep users.
  • Model pricing is diverging: cutting-edge models may get more expensive, while older versions’ costs collapse.
    • Kevin Rose: “The most powerful models are going to be more expensive than ever ... huge deflationary effects on everything that's not cutting edge.” (21:50)

• Barbells in AI Costs and Use Cases

  • Lightweight models on devices can do most of what users need, reducing costs.

6. The Joy of Building & Shifting Budgets (23:42–27:10)

• Building as the New Entertainment

  • Time (and money) traditionally spent on entertainment is shifting towards creative building, enabled by AI.
    • Kevin Rose: “There's so much beauty in the process right now ... We're discovering this part of ourselves that has been asleep.” (25:04)
  • AI is fostering a kind of “hero’s journey” for creators—moving beyond financial incentives to personal fulfillment.

• Democratization of Tooling

  • Non-technical professionals (e.g., lawyers) are using no-code/AI tools to build bespoke SaaS for themselves, slashing costs.
    • Kevin Rose: "...a personal injury attorney ... used Claude code to basically start coding a bunch of things ... It's extraordinary." (25:47)

7. Societal Impact & Universal Basic Purpose (27:10–33:58)

• Job Displacement & Redistribution

  • Tech’s progress could necessitate legislative redistribution (UBI), as profits from AI accrue.
    • Anish Acharya: “If the bigs continue to dominate ... we're going to need some way for those profits to flow back into everyday consumers.”

• Purpose vs. Income

  • More important than basic income is “universal basic purpose”—ensuring everyone has meaningful work or a “hero’s journey.”
    • Kevin Rose: “The way you actually get the French Revolution is less that people don’t have enough money … [it’s] more that people don’t have something important to work on.” (29:50)

• AI as a Tool for Spiritual and Emotional Growth

  • Potential for AI to deepen self-reflection, help discover new crafts, and foster human connection—if balanced properly.

8. The Future of Early-Stage Consumer Investing (33:58–43:59)

• Early-Stage SaaS: Dead or Reborn?

  • Small-scale, early-stage consumer SaaS feels “dead”—products can skip early rounds and go from inception to massive valuation almost overnight.
    • Aneesh Acharya: “...I worry that what we're going to see is just a decimation of all their early stage funds...” (40:36)

• History Lessons From Web 2.0

  • The last periods of consumer stagnation (like pre-Ajax/Digg) led to new, unimagined formats—suggests another big wave is coming.

• Cultural Shifts Outpacing Tech Shifts

  • The interplay between cultural and technological innovation leads to enduring consumer products (photo sharing, ephemeral content, privacy shifts).

9. Tacit Knowledge ("Dark Data") & Proprietary Information (43:59–47:49)

• Capturing Unwritten Know-How
  • Many skills and tips (“dark data”) are not codified—future opportunity exists in surfacing, storing, and leveraging this knowledge.
    • Anish Acharya: “There’s probably a market to go raise a fund just to acquire proprietary data, to resell it.” (46:23)
  • AI can reverse-engineer missing knowledge, as with inferring dimensions of Charlie Rose’s table from image clues.

10. Predictions & Future Trends (47:49–57:15)

• OpenAI and Model Providers Will Go Public

  • Kevin Rose: “I think all the big model companies are going to go public... in the next 12 months.” (48:58)

• Technology-Driven 4-Day Work Week (American Style)

  • U.S. productivity growth via AI will enable a shorter work week—"weirder, better, faster."

• Peptides and Longevity Science

  • Aneesh Acharya: “We will probably discover and create … another 50-100 peptides that alter our longevity in a meaningful way.” (50:34)
  • Use cases and risks for peptides (“Wolverine Stack,” muscle mass support) and AI’s role in drug discovery.

• End of Code as We Know It

  • In 5 years, most won’t “look at code” again; AI will compile directly to hardware-optimized binaries.

• Agents as Ultimate Users

  • Marketing and product optimization will soon target AI agents rather than human users.
    • Kevin Rose: “There’s zero value in brand, there’s zero value in marketing. Isn’t that just a better world to be in?” (56:29)

• Financial Services & Automation

  • Consumer agents will optimize financial decisions, bypassing the need for user expertise.
  • Agents will shop between vendors, auto-benchmark, and migrate services as they find better cost/performance.

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Notable Quotes & Memorable Moments

• Kevin Rose: “The idea guys are sort of having a moment.” (00:00)
• Aneesh Acharya: "For me, markup for me is kind of like ... the lowest atomic unit of what is possible and portable." (06:28)
• Kevin Rose: “Even openclaw ... there's been a thousand forks of it ... but OpenClaw itself still dominates conversation.” (15:17)
• Aneesh Acharya: “I have yet to see the one use case where someone has come to me and been like, this is the game changer for me.” (09:03)
• Kevin Rose: “The thing I worry the most about with consumer software is that the costs are too high to have a free model … AI inference isn’t free.” (15:41)
• Aneesh Acharya: “On the consumer side ... when I talk to family members and people that aren’t deep in tech like we are ... it’s all ChatGPT.” (20:25)
• Kevin Rose: “We’re discovering this part of ourselves that has been asleep.” (25:04)
• Aneesh Acharya: “We need more than UBI ... universal basic purpose.” (29:50)
• Kevin Rose: “There’s probably a market to go raise a fund just to acquire proprietary data, to resell it.” (46:23)
• Aneesh Acharya: “...by the end of the year ... I just don’t think we’ll ever look at code again.” (54:01)
• Kevin Rose: “There’s zero value in brand, zero value in marketing. Isn’t that just a better world to be in?” (56:29)

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Timestamps for Key Segments

• 00:00 – 07:59: Creative empowerment in software, file vs. app permanence, Markdown as universal format
• 08:09 – 15:06: SaaS replicability, network effects, examples (Instagram, Wordle, OpenClaw)
• 15:40 – 22:27: AI infrastructure costs, model providers, OpenAI vs. Anthropic, consumer mass adoption
• 23:42 – 27:10: Building as new leisure, personal AI-driven tools, “digital homesteading”
• 27:10 – 33:58: Societal adaptation—employment, UBI, basic purpose, spiritual exploration
• 34:01 – 43:59: State of consumer investing, early-stage landscape, hardware resurgence
• 43:59 – 47:49: Surfacing tacit knowledge (“dark data”), proprietary datasets
• 47:49 – 57:15: Predictions—AI IPOs, 4-day week, longevity peptides, end of code, agents as users

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Final Thoughts

This episode is dense with insights on the shifting paradigms of technology creation, user empowerment, investing, societal impacts, and scientific frontiers. Kevin and Anish paint a future where creativity is democratized, “moats” are earned via connection rather than code, and both human desire and technology continue to accelerate each other—perhaps even towards American-style “leisure” enabled by relentless productivity.

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For those who want to dig deeper, listen for rich stories about:

• The tactile, emotional side of building (and how it’s supplanting entertainment)
• Tangible hardware innovations in a sea of software
• The new arms-race among AI models and how the “bigs” will shape economics
• Micro-examples of tacit knowledge, AI negotiation, and workflow optimization

This episode is a mosaic of optimism, caution, and curiosity for everyone interested in the intersection of AI, culture, and the future of consumer technology.

Transcript

[Kevin Rose]

The idea guys are sort of having a moment. In fact, it's funny. Like, I'm, like, looking for new ideas to work on. You know, in the old days, somebody would give you their app idea and you'd be like, oh, here we go again. And now I'm like, cool, how about I build it for you?

[Aneesh Acharya]

What has changed for me is, you know, someone that dropped out of computer science because I just couldn't keep up with everyone else. I always had the creative ideas. My ADHD was too bad that I just couldn't remember all the syntax and I was like, like thumbing through manuals back in the day and, like, you know, trying to, like, I had, like, the C Bible or whatever they called it.

[Kevin Rose]

You know, when you're a child, nobody tells you, Kevin, you're bad at drawing or you're good at painting. The thing that I think we need more than ubi, if we ever get to that place, is universal, basic purpose. And the way you actually get the French Revolution is less that people don't have enough money. That's part of it. And more that people don't have something important to work on. Like, everybody's gotta feel like they're on a hero's journey.

[Aneesh Acharya]

I was talking to my wife and I was like, we're getting to a lot of arguments about X, Y and Z. What if we just had a conversation with a model that built out these frameworks for us, that understands what we like, how much we care about certain things, and then we just have our models go and, like, duke it out? And she looks at me and she's like, this is one of the worst ideas I've ever heard. I'm just like.

[Narrator]

This episode originally aired on the Kevin Rose Show. When anyone can build a Slack competitor in a weekend, what actually makes a consumer startup worth backing? For decades, software moats meant engineering effort. When Kevin Systrom and Mike Krieger were hand coding Instagram's filters, copying them cost you months. That window is now 48 hours. But Anish argues the moat was never really the code. When Hipstamatic and a dozen others launched alongside Instagram, it still wasn't obvious, which would run away until it was too late. That pattern may hold, but the cost structure has shifted. One founder told aneesh he'd need $25 million just to reach 100,000 monthly actives because AI inference isn't free. So the real tension isn't whether great consumer products get built. It's whether venture economics can survive a world where the best companies skip early rounds altogether. Kevin Rose speaks with Anish Acharya, general partner at a16z focused on consumer investing.

[Aneesh Acharya]

Aneesh, we're back.

[Kevin Rose]

Nothing has changed at all. So I don't know what we're gonna

[Aneesh Acharya]

talk about exactly how long ago did we do that episode together? Four or five months, and everything has changed.

[Kevin Rose]

It's so amazing, dude.

[Aneesh Acharya]

Great to have you. Real quick primer for everyone. Your partner, general partner Andreessen Horowitz.

[Kevin Rose]

That's right.

[Aneesh Acharya]

You focus primarily on consumer investing.

[Kevin Rose]

That's right.

[Aneesh Acharya]

Anything else to mention on that front?

[Kevin Rose]

I mean, I focus on consumer, but I'm a programmer. I mean, I grew up the same way that you grew up. Just.

[Aneesh Acharya]

We worked at Google together.

[Kevin Rose]

We worked at Google together. Yeah, yeah, yeah. So I've got. Consumer is my area of focused, but I've got a ton of personal interests outside of that.

[Aneesh Acharya]

Love it. All right, we got lots to talk about. Figure this would be like, fun little variety show. Cover all the things AI. Yeah, yeah, yeah. Let's get this out fast. Get people, you know, thinking about what's coming. You've got a list? I've got a list. You want to start first?

[Kevin Rose]

Well, I want to hear more about what you've been working on because I experienced one of your products this morning. You've been obsessed with the models. You're just like, you can't stop programming.

[Aneesh Acharya]

Yeah.

[Kevin Rose]

I mean, tell me what you're working on and then tell me how much you think it's real. Productivity versus productivity porn.

[Aneesh Acharya]

Yeah. Well, I'd be curious to see how you define productivity porn. But in terms of what has changed for me is, you know, someone that dropped out of computer science because I just couldn't keep up with everyone else. I always had the creative ideas. My ADHD was too bad that I just couldn't remember all the syntax. And I was like. Like thumbing through manuals back in the day and shit, like, you know, trying to, like. I had, like, the C Bible or whatever they called it, you know, and so now there's none of that. And I finally realized that six months ago. I was going and manually looking at the code and thinking to myself, like, oh, I should just at least look at it to make sure I kind of see that, what it's doing. So I understand best practices, and now I just realize I don't ever have to look at code again.

[Kevin Rose]

Yes.

[Aneesh Acharya]

Because the next. It doesn't matter what bugs I'm creating right now. If I discover them, I can squash them. And the next model is going to be better and it'll rewrite any bad functions or anything that I have going on.

[Kevin Rose]

Yes.

[Aneesh Acharya]

Um, there is, there is a world that. What's so weird right now is you're taking a look at all these companies that are SaaS businesses and they're realizing that the moat is no longer there. Like I can spin up anything, my own personal CRM app, a Slack competitor, anything that is has definable outcomes for software. You know, I'm not making gene editing software, but anything like a SaaS like business, very easy to replicate. It's easy to say I want to go build my own workout app. Right. And like little things like that. Are those businesses? No, but like the stuff I'm working on is. Is personal, passionate areas where I believe I want to put my own time and attention. And for me, I've always cared about social news, you know, starting dig back in the day. And I believe that we are entering into a really interesting time where information is going to be platform and app agnostic, so that it should be able to traverse and meet you where you're at.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

So if you care about, you know, like the latest AI coding tools, I'm just going to pick that up. If you want it in a podcast form when you're coming into work, custom tailored to you. If you want it in a video form that you tune into Apple TV app and it says good morning Aneesh and it welcomes you by two hosts that you want. If you want it in a daily newsletter and if you want it inside of your Claude code experience or your Claude cowork experience, if you want it in your Obsidian. So there's like a little markdown file that you read every day? Yes, it doesn't matter. It is just going to. Because all the connective tissue is finally happening. Information can freely flow amongst these different diverse platforms, which I think is beautiful and I'm super excited about.

[Kevin Rose]

You know, it's so interesting. So the Obsidian founder is one of the most interesting people to follow on.

[Aneesh Acharya]

Super nice guy too.

[Kevin Rose]

Oh, really? I haven't met him. Yeah, nice to meet him. Kipano, right?

[Aneesh Acharya]

Yeah.

[Kevin Rose]

So he's got this whole theory of how apps are ephemeral sort of apps and intelligence are these ephemeral things, but files are permanent and there's something very elegant and beautiful and it sort of speaks to what you're describing, which is a file is just the basic unit of information and it can get expressed as a video, as a pod, as all of these different things. And the app with which you consume. This information may actually change from time to time. So I don't know if that's right, but something about that direction feels spiritually interesting.

[Aneesh Acharya]

Yeah, well, for me, what I'm doing is when I work with coworker or work with any of these apps, I'm always saying, write this in Markdown.

[Kevin Rose]

Right.

[Aneesh Acharya]

And I want it Markdown, because Markdown for me is kind of like the text basic, lowest atomic unit of what is possible and portable, you know, and so I know in the future, anything will be able to ingest Markdown with ease.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And so for me, that's. That's kind of how I'm thinking about my file structure, of all things.

[Kevin Rose]

You know, it's interesting if you hear Mark talk about a bunch of the design choices they made when they were designing Netscape, one of the most controversial choices they made with HTTP was actually have it be plain text on the wire. Because at the time it was like, well, that's not secure, that's not safe, that's dangerous. How can you just have plain text on the wire? So all the wire protocols were encrypted, and that was considered the best practice. And I think Mark and Ben and the team said, let's actually just make it plain text because it'll be easier to work with, easier to debug. And that turned out to be a brilliant design decision because it drove a ton of HTTP adoption. So there's something that sort of mirrors that in what we're seeing right now. All these file formats, all the cloud storage, it's just too much heaviness. And we're in this moment of beautiful interoper, you know, mashable. All the things that you guys aspired to in the late 2000s. Yeah, it never really came to fruition, and now we're getting it.

[Aneesh Acharya]

Yeah, absolutely. And I think that there's something about having this, like, if I put something inside of a database right now, I'm kind of not locked in there because I could tell any agent to go and read the tables and understand the schema and, like, have it. But for me, I just want ultimate flexibility. And the context windows are big enough and search is decent enough, and we see the compound engineering and some of these other protocols where Markdown works just fine for now.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

It depends, obviously, if you need to do large data sets where you need to do vector embeddings and you need to actually find similar documents. Like, there's other bigger tools and bigger hammers to use in those cases potentially.

[Kevin Rose]

But I'd Say that those are. The raw information should be stored in the most interoperable fashion possible. So just, I mean, one of the great things about openclaw is that all the memories are just flat files. Right. They're markdown files, I believe. So now you've got a memory file per day, plus you've got persistent memory, which is like preferences and things that don't change about you.

[Aneesh Acharya]

Right.

[Kevin Rose]

And it just means you can use it in a thousand different ways. You can try different memory architectures. Right. You just. Your information is yours in a way that it hasn't been for 15 or 20 years.

[Aneesh Acharya]

Yeah. Are you an Open Claw user?

[Kevin Rose]

I. So I love Open Claw. It's very, very interesting. I guess I haven't been as at the edge of Open Claw as others. I'm just spending so much more time in Claude code and Codex. Yeah. For some reason, it's just that form of creative direction is so much more satisfying to me than the kind of productivity 10x you get from OpenClaw. It's incredible. Incredibly important and really cool architecturally. I'm just not as obsessed with it as, you know, Chris and some of our other friends.

[Aneesh Acharya]

Yeah. How about you? I'm in the same boat where I obviously installed it. I got a Mac Mini like everybody else did, and I wanted to start playing with it and a little hesitant in the sense that I had sensitive data that I don't want out there. So I created all new accounts and all that. But I have yet to see the one use case where someone has come to me and be like, this is the game changer for me. You know, like, it does this and I'm like, wow, I want to do X. Like, that sounds awesome.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And oftentimes it's little tiny things, little tiny productivity boosts here or there. And sometimes I got one friend that is calling him with little updates and stuff and he can talk to it on speakerphone.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And those are fantastic demos. They're fun.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

But I just don't see yet. And granted it's early days, but I like, directionally, I think it's right. I think we're going to have a personal assistant likely just built into the larger models that just has their own storage. I mean, we're seeing this now with these agents that Anthropic rolled out. They now have their own storage and own containers where they can keep these things over and make them durable over long periods of time.

[Kevin Rose]

Yeah, cloud agents.

[Aneesh Acharya]

Yeah, cloud agents. Yeah.

[Kevin Rose]

I mean, I think a lot of the magic of openclaw is just the ergonomics of it. And I'll give you a specific example. So when you use a website or a mobile app, you obviously expect it to be perfectly synchronous. Like you press a button, there's an immediate response. That's your user expectation from 20 years of using apps. When you actually text someone, you don't expect me to reply right away. You're like, oh, Anish might reply in five minutes or it might take him two hours or whatever. The magic of openclaw I think is because it's in a mobile messaging channel, your sort of subtle expectation is it won't reply right away. So it has to go off and do something more ambitious. It can do it without feeling like this delayed experience. The other way that shows up if you look at the model switching settings in ChatGPT, for example, it's trying to find this balance between instant and deep thinking, which is a little bit of a user expectation contour that they're trying to meet versus just being like, hey, I'm going to go do some stuff and I'll make the trade offs and I'll let you know when I'm ready.

[Aneesh Acharya]

Right.

[Kevin Rose]

OpenCloud does that really well. So I don't know that there's any one thing. It's just the whole way it's put together I think is very elegant.

[Aneesh Acharya]

Yeah. Back to that. Your original question though, around, you know, this coding, what we're up to, what we're building.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

You're seeing a lot of entrepreneurs that. And you called it. What would you call something? Porn. Productivity. Productivity porn. And it's because everyone, you, me, everyone in this room actually has produced some type of application now. Yeah, some of that is trash. Yeah, some of that. It's going to be awesome. But I don't know how much of it is defensible.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

So as someone that's doing consumer investing.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Like what scares you?

[Kevin Rose]

Well, first of all, I think that we need to this whole mindset about defensibility and moats and it all feels so heavy. Like there's this beautiful creative direction in what you described and how you don't have to thumb through manuals. And now the cost of doing something that fails is zero. Right.

[Aneesh Acharya]

Right.

[Kevin Rose]

So you get to try every idea and there's so much information in exploration. So I say productivity porn to be provocative. But I don't actually think it's that. I think that we have this new way of learning which is just trying things. And you know, the idea guys are sort of having A moment. In fact, it's funny. Like, I'm like, looking for new ideas to work on. You know, in the old days, somebody would give you their app idea and you'd be like, oh, here we go again. And now I'm like, cool, how about I build it for you?

[Aneesh Acharya]

Right.

[Kevin Rose]

So I think there's this beautiful exploration that we're seeing that's never been possible before. And there's a lot of value in that. And then when it comes to consumer products, I still think that consumer moats are as good as gold. Right. Things like network effects, they're not trivially reproducible by models. Even if you can reproduce a software, this is what, like, it's not like Instagram has got like this software mode. Yeah, exactly.

[Aneesh Acharya]

Yes. But, okay, so that the incumbents are locked down. That's fine. Yes. I'm not moving from Instagram anytime soon. But when you're sitting there and you see a new consumer product.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

You know, five years ago, and you're like, damn, that's a good idea.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

You write a check for $10 million, you better than entrepreneur. You wait for the next five to seven years and you see what happens. Right? Yeah. Now, knowing that, damn, that's a good idea. Could be replicated by anyone else if it is a good idea.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Does that freak you out at all?

[Kevin Rose]

I don't think so, Kevin, because even in 10 years ago, the good ideas weren't obviously good at the. Like, what Systrom was up to at Instagram wasn't an obviously good idea until the network really started to take. And then it was too late to reproduce the software. So I don't think that the moat has ever been. It's like really hard to reproduce the software. I think the moat is, in part, every consumer idea is embarrassing to work on until it's obvious. You know, it's like, it seems trivial. It doesn't sound important. VCs don't know what you're talking about. Your family doesn't know why you're working on it. You just feel this pull in a direction. And ideally, when it works, the network runs away before people can replicate it.

[Aneesh Acharya]

But we live in an information when in time, where information is propagated, like instantaneous. Right. And so an opencloud comes out or whatever they call it when they first launch. I remember now. And you see 30 different clones of it. Right. And then all of a sudden, everyone's moving in different directions. And I just feel like that wasn't the case. It wasn't as easy to reproduce something like that and you see a hit than it is today. The time has shrunk dramatically. Like for example, if I launched Instagram today. I remember when he goes by Mike now, but back in the day he went by Mikey. Krieger and Kevin were working on this and it took them. I remember talking to them about developing the filters, the basic filters for Instagram. It was real work, real engineering effort. Right.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And so even if you saw Instagram sort of hit escape velocity, if you were a startup, you had to go try and copy them and catch up to them. Yeah, it was a few months of work.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Now it might be 48 hours of work, you know.

[Kevin Rose]

Yes. Even at the time there was so much noise in the ecosystem. Right. There was bourbon later, Instagram, there's Hipstamatic, there was a dozen apps that all did roughly the same thing. And it wasn't clear why Insta was special until it. Until it was clear in retrospect. So I don't know. I think that if you were to build Insta today, it would still be non obvious until it was obvious in a way that it was too late.

[Aneesh Acharya]

Right, that's fair because like there's lots of things that, lots of examples today of like wordle for example.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

You and I could clone that within 20 minutes.

[Kevin Rose]

Yeah, yeah.

[Aneesh Acharya]

It's like. But it's not. We're not going to take over wordle because they have that built in.

[Kevin Rose]

Even openclaw. Right. Which was originally called Quad. Quadbot, I think. Yeah, quadbot. So even though there's been a thousand forks of it, it's literally open source. OpenClaw itself still dominates conversation. Yeah, right. We're not talking about the 10 open clause that have equal market share, we're talking about OpenClaw.

[Aneesh Acharya]

Yeah, yeah.

[Kevin Rose]

So there are these compounding effects that sometimes, you know, less intellectually satisfying than network effects, software, moats, whatever.

[Aneesh Acharya]

Yeah.

[Kevin Rose]

The thing I worry the most about with consumer software is that the costs are too high to have a free model really for very long. Right. I was talking to Signal, who's launching a product in the next couple of weeks, a consumer product. And he was saying, hey dude, I need to raise like $25 million if I want to have a hundred thousand mouths, you know, and by the way, the money will go quickly. So the fact that you don't have this sort of zero marginal cost of distribution benefit, which has really advantaged consumer founders in the. I think is a major drag on the ability of consumers to scale. Consumer founders to scale things to A lot of people.

[Aneesh Acharya]

So let's talk about some of the actual models and how people are building these things, it seems. And you guys are investors in pretty much all the bigs, Right? Like anthropic and OpenAI. Are you in all the major model providers?

[Kevin Rose]

We're not in all of them, but we're in. We're in mistral. We're in OpenAI, anthropic or no, we're not an anthropic.

[Aneesh Acharya]

Okay. So when you think about what's happening with the moment, that anthropic is happening right now.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And you have OpenAI, which has been largely, I mean, not totally quiet, but they're cooking. Yeah, right.

[Kevin Rose]

Definitely cooking.

[Aneesh Acharya]

What's. Obviously, this isn't winner take all, or is it if someone hits escape velocity?

[Kevin Rose]

Yeah, well, I think it's, you know, it's easy to over rotate on some of the conversations on X if you sort of zoom out and you look at OpenAI. First of all, they've got, I don't know, 950 million weekly actives. Like, it's the biggest AI consumer product by many orders of magnitude. It really is. And it's the first product to hit that kind of scale in that short of a time period in the history of technology. So they've got a sort of unassailable advantage in consumer. I think that's one. And then if you just look at the model quality, I think we both experienced this. Like, the codecs models are excellent. I think the codecs harness is a little behind Claude code, and I hope they'll fix that, But I think that that's like a hill climb that they can do on model quality. They're right there. And we're hearing that the new OpenAI model, which is going to hopefully come in the next few weeks, will be just as good as the sort of super secret, you know, Mythos model that's too dangerous to release.

[Aneesh Acharya]

Do you buy that? Too dangerous to release?

[Kevin Rose]

I don't buy it. I mean, maybe. But look, I think that if you actually have a model like that, there's like four independent things that I think about. So first of all, let's even assume that it's six months ahead of our geopolitical rivals. The first thing you probably do is use it for offensive capabilities. Right. To hack others. The second thing you do is to lock down all your defenses. Yeah, exactly. I think the third question, which Mark pointed out, and I think Stratecari wrote about this first, is, do they even have the compute for it? Like, it Might just be that they have a GPU shortage, which is also why they sort of nerfed opus 4:6. I don't know if you followed this. They took down the default thinking level from high to medium and people are complaining that it's nerfed. It's nerfed because they may be trying to free up GPU capacity. So it may be an infra problem. And the last bit is just like the aura farming of them having a model that's too dangerous for the world to handle. Like how can you have better marketing than that?

[Aneesh Acharya]

There's no better marketing than that.

[Kevin Rose]

So it's unclear to me that it's actually too dangerous. There are a lot of other reasons why they might actually be holding it back.

[Aneesh Acharya]

There are rumors that they haven't coded anything internally in like since January, I believe.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Do you buy that?

[Kevin Rose]

I don't. I mean Boris has said it a few times like we don't write any code on cloud code. Like Claude code writes Claude code.

[Aneesh Acharya]

Right.

[Kevin Rose]

So I do buy it. And like, how can that not be true? It's your. And I lived experience as well. Right.

[Aneesh Acharya]

Yeah. I just, I wonder if you have a model of that capabilities if you aren't. Like one of the things I've been really impressed about with Anthropic is this the rate of shipping. It's like every freaking week, something new drops every day.

[Kevin Rose]

Dude. Multiple things. Yeah.

[Aneesh Acharya]

And so you have to imagine if you're the first one to have the model that is, let's just call it 30, 40% better than what's out there today. You have to be like, okay, let's make our tools like dope as hell

[Kevin Rose]

as fast as possible. Of course, yes.

[Aneesh Acharya]

So you turn it internally and get all that tooling and just ship. It feels like that's what's happening because of the rate of shipping.

[Kevin Rose]

You're an OpenAI investor. I think you're a anthropic investor as well. Okay, so what's your kind of view? I guess you're the most even handed having been in both.

[Aneesh Acharya]

Well, I mean, I think that. Open the eye. Listen, they, they have the, it's hard to count anyone out at this point because you know, even Google, they've got their, they've got their Tensor processing units or their self training model, they've been eerily quiet and like I, those folks are just sharp as hell. Like don't fuck with Google, like they're going to come back and get you. So I, I just, I have a hard time believing there's going to be at least from someone that's doing software engineering with the models in allegiance to anyone.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Like I will go to ChatGPT tomorrow or Gemini if it's a better model. I don't care.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Like my credit card just transfers to whatever model and it starts working again. Right.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

So on the consumer side, you know, when I talk to family members and, and people that aren't deep in tech like we are.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

It's all Chat GPT.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Because that is the household name.

[Kevin Rose]

That's right.

[Aneesh Acharya]

You know, and that's right. I think it doesn't, it does everything that they want it to do.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And it's not like they're seeing anything that we're like, oh, the, you know, that cowork feature from, from Claude is so good. Like they don't realize that yet, you know?

[Kevin Rose]

Exactly. Yeah, yeah. You mean they're not using remote control on code. Exactly.

[Aneesh Acharya]

They're not connecting their phone and leaving their, their laptop open.

[Kevin Rose]

It's. Karpathi talked about this this week and it's, it's so funny because he's like, look, the people who have used ChatGPT in the, in a somewhat cursory way, they're like, I don't know about this AI thing. Maybe it's overhyped. Like, you know, maybe the Instagram audience.

[Aneesh Acharya]

Right.

[Kevin Rose]

They sort of don't quite get it. So I think it's like. And for the ones of us who are really de. Using it to make software and we're seeing all the model progress.

[Aneesh Acharya]

Right.

[Kevin Rose]

And we're not talking to each other.

[Aneesh Acharya]

Right.

[Kevin Rose]

You know, Exactly.

[Aneesh Acharya]

Like every time I talk to someone that's not in this space, I, I try to like red pill them and I set them down and I said, let me show you what this can do for you.

[Kevin Rose]

Right.

[Aneesh Acharya]

And then within 20 minutes they're like, oh my God, I need to be spending more time here.

[Kevin Rose]

Yes.

[Aneesh Acharya]

But it is a lift to get people up to that. I think it's a multi year lift. We, we live in a world where we're trying everything, but the average consumer is going to try a couple new things per year, you know?

[Kevin Rose]

Yeah.

[Aneesh Acharya]

So, yeah, it's interesting. What about model pricing? Like the max that we're seeing, these max plans for $200 and we eat all the credits and all of a sudden we're out of credits and people are complaining about that. Like, yeah, you. Do we see a $10,000 plan? Do we see a $5,000 plan?

[Kevin Rose]

Yeah. I think at Barbells So I think and I'd love your view on this, but it feels like the most powerful models are going to be more expensive than ever. And yet the price of a token on GPT 4.0 is down 100x since the model was released. And what was that 18 months ago? And when GPT 4o was released it was this incredibly cutting edge. It had this beautiful personality. Like it seemed inconceivable that it would be cheap and now it's very inexpensive on a per token basis. Plus you have open source. Right. So it feels like there'll be inflationary effects on the edge models and maybe they'll even be unavailable as APIs and there'll be huge deflationary effects on everything. That's not cutting edge. Yeah. What do you think?

[Aneesh Acharya]

Yeah, I mean I think there's. Listen, like even when Google announced these models that now run on phones on device, there are so many instances where a lighter weight model will do most of what you need done. Yeah. And so I love that that exists because there is a ton of things that I'm building right now which are kind of like backfill and data kind of fetching and like just very non reasoning tasks that six months ago, a year ago would have cost me thousands of dollars to do what I'm doing and now I'm like oh, that was $12, you know so I, I do love that that is is happening. I, I think that the API pricing makes sense. The, the weird thing for me is I, I believe there will be a higher tier. We're already starting to see this where you can pay per pull request and pay anthropic to review it with a better, more finely tuned model.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

For those bug squashing it is a little bit weird. It is a little bit that Spider man point of Spider man situation where like I coded it for you but I'm also going to fix the bugs

[Kevin Rose]

for you for like $12.

[Aneesh Acharya]

Exactly. But the so is the OpenAI is security stuff is actually quite good as well. It's got a bunch of vulnerabilities I would have never found amazing. So yeah, I don't know but what's, what's up on your.

[Kevin Rose]

Well so actually let me ask you a related question though. When you think about your budget, I'm assuming that you don't have like a ceiling on how much you spend on the models.

[Aneesh Acharya]

Right.

[Kevin Rose]

But how much if you had to make a trade off would you trade off against say your entertainment budget? Like would you skip a movie or a bottle of Wine because you wanted to spend the money on tokens.

[Aneesh Acharya]

Yes, 100% well, but I'm building towards something.

[Kevin Rose]

Are you though, how many of your things are important and have to be durable versus are satisfying to work on?

[Aneesh Acharya]

80% are important, durable. And the other 20% are just for fun. Just because, like, I just do, you

[Kevin Rose]

know, which is which at the outset?

[Aneesh Acharya]

Yes.

[Kevin Rose]

Okay.

[Aneesh Acharya]

Okay. 100% well, largely because, like, you know, I stepped back from my venture world through ventures or my investing role there. And because it's too fun to build right now. Like, why not build? And so when I'm tackling a bigger idea, the, the, the hope is that hundreds of thousands of people will use said product at the end of the day.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And if it is not that, then it's just going to be a little tiny thing that I think should exist and I'll put a little bit of time and effort into it. And if there's a thousand people that love it, like, God bless. Like, at the end of the day, I think we, we. I don't want to optimize for just financial outcome or usage. I want to optimize for. Would I. Do I enjoy doing this? Do I enjoy building this product? You know, I've seen some of your vibe coded stuff. It is largely because you enjoy doing that.

[Kevin Rose]

It's just fun to work on. And that's why I think your language is interesting. You didn't say it's too important of a time. You said it's too fun of a time.

[Aneesh Acharya]

Yes.

[Kevin Rose]

Right. So there's so much beauty in the process right now. And that's why I think that it will eat into what would otherwise be called entertainment budgets. Because there's just. We're discovering this part of ourselves that has been asleep.

[Aneesh Acharya]

Right.

[Kevin Rose]

Both as technologists, but even as humans. Right. Like when you're a child, nobody tells you, Kevin, you're bad at drawing or you're good at painting.

[Aneesh Acharya]

Right.

[Kevin Rose]

Whatever. You're actually just good at anything you're interested in. And we're able to get back to that place again for the first time in a long time.

[Aneesh Acharya]

I know. And it meets you where you're at too, which is so awesome. Like, there's the number of things that I now know versus a year ago in terms of like, how to fix, like, faucets and shit. And like the stuff where I'm pointing. Oh, a chatgpt at. And I turn on video mode. I'm like, hey, how do I do this? What does this mean?

[Kevin Rose]

Yes.

[Aneesh Acharya]

And like, my upleveling my knowledge across an entire spectrum of different things.

[Kevin Rose]

Thanks. I've got to tell you this crazy story. So there's a guy that we met, came in and presented to us yesterday named Mike. So Mike is a personal injury attorney who won the global anthropic Claude code hackathon. Okay. So he started using Claude code to solve a bunch of his problems because he's running. He's like a startup guy sort of running a startup law firm and he couldn't afford a paralegal, so he used Claude code to basically start coding a bunch of things that would otherwise he'd have to hire someone for. And then he went so deep in the tooling, he came in, he showed us the software he's built. It's extraordinary. It's like what a whole venture backed SaaS company would otherwise do. He's so deep in it, he's using whisper flow, he's talking about slash commands. He's like, okay, I've got a slash loop that's always looking for security fixes. And this is not the guy you'd expect. You know, he's like a jiu jitsu, square jawed sort of personal injury attorney.

[Aneesh Acharya]

Right.

[Kevin Rose]

So I think there's just. This is my white pill. There's going to be so many beautiful stories of like digital homesteading or something where these unexpected people build these really incredible things based on personal need or interest.

[Aneesh Acharya]

Yeah. And I think this is where I had a company in a similar vein where they were spending something like 80k a month on SaaS subscriptions. And the founder was like, well, I'm good enough to where I can build this in house. Kind of what I want a little bit more custom tailored to me. Took him about a month and a half. And then you just complete that, cut that entire SaaS budget out.

[Kevin Rose]

So here's my only counterpoint on the kind of SaaS is over thing, which is yes, conceptually, maybe you could build a CRM. But have you built a CRM?

[Aneesh Acharya]

I have, actually.

[Kevin Rose]

Really? Jesus. All right, fine. Well, I guess SaaS is over then. I was going to say it's so fucking boring to work on all that software. Like, does anyone really want to?

[Aneesh Acharya]

I wanted a really simple personal CRM, so I just.

[Kevin Rose]

Fine, fine. Okay, how about payroll? Have you payroll Payrolls over there?

[Aneesh Acharya]

You just build some tax accounting software.

[Kevin Rose]

Richard, come on. I know.

[Aneesh Acharya]

All right, so what else is on your list? Because I know you had some really spicy fun topics to get into.

[Kevin Rose]

Yeah, dude. Well, I wanted to actually get your take on you know, obviously there's the stuff that happened with Sam's house, there's a bunch of attacks on his house, which is, you know, super tragic because whatever you think of AI politically, like, you know, he's a human running a company who has the best of intentions. What's your kind of view on the conversation we're having as a society about this new technology?

[Aneesh Acharya]

I like how OpenAI came out and said we're going to have to heavily tax this and provide some type of safety net fund and we have to work that into the legislation at some point so that when we do displace all these jobs, which it is coming in my belief, you know, it may be five, seven, ten years from now, but I believe that we're going to have to have some of that flow back to the public in some way. Yeah, I think when I, when traditionally, and of course, correct me if I'm not answering your question correctly, but traditionally when we talked about, you know, 10 years ago, Universal basic income, I was like, well, how are they going to fund that? Like, how are we just going to like print money to give people money? And now it's clear to me that if the bigs continue to dominate and disrupt and just crush jobs across every single vertical. Yeah, we're going to need some way for those profits to flow back into everyday consumers. So they are or just everyday humans so that they can live and thrive in a world where they might have been displaced from, from a job loss.

[Kevin Rose]

You know, it's interesting. So one of my good friends is an executive at Google and you know, I talked to him about this and said, hey, how much are you guys actually laying off people as a. Because you're obviously, you know, you're at the edge of the models plus you have all the TPUs, so presumably they have all the tokens that they want and need internally. And he said, look, we actually haven't laid off anyone. We're just ripping through our backlog. So we're doing like 100x more than we ever did before. So it's interesting the kind of point a lot of people have made this point on like, hey, where are all the jobs going to be? But I think there's no ceiling on human desire, there's no ceiling on company ambition. And so far we're seeing it as like companies doing more versus hey, let's do the same amount with less people.

[Aneesh Acharya]

Right.

[Kevin Rose]

So we'll have to see. I also think on the UBI point, like the thing that I think we need more than ubi, if we ever get to that place, is universal, basic purpose. I think the way you actually get the French Revolution is less that people don't have enough money. That's part of it. And more that people don't have something important to work on. Like, everybody's got to feel like they're on a hero's journey. And even if it's a little. I mean, look, arguably we both have fake jobs right now. So even if it's a little bit contrived, I think that we have to make sure people have a sense of purpose in addition to the means to kind of go achieve it.

[Aneesh Acharya]

Where do you think that's going to come from?

[Kevin Rose]

Look, again, I think there's no ceiling on human desire. I think people are going to want vacation homes on Mars. I think people are going to, like, you know, companies are going to be doing more ambitious things. We're going to have 100x more skyscrapers. Like, the history of all technology is it increases productivity and it also increases human desire. You've heard this thing of, like, luxuries become commodities, right? Therapy was considered a weird luxury 50 years ago. Now therapy is an expectation. Right. With Instagram culture, so many. Bottle service used to be something that was unheard of 20 years ago, and now it's only bottle service. Nobody wants to go to the club unless they're getting bottle service. So. So I just think we're underestimating how much human desire will continue to grow.

[Aneesh Acharya]

Productive product flying was a great example of people used to get dressed up and put ties on and suits on just for their flight because it was such a luxurious thing.

[Kevin Rose]

I mean, I wouldn't mind if we went back to that. Yeah, I'm big on manners, but. Yes, exactly. So I don't know that it's like the end of jobs. And, you know, the other thing, I'd love your take on this, since I know you're big in meditation and sort of self awareness, is it feels like this technology is a tool to explore our emotional, spiritual self in a way that no technology ever has been. Like, the fact that you can talk to it like a human and you can explore things and you can get into flow state when you're programming. It has all of these attributes that are just so different from, you know, spreadsheets and word processors and even the creative tools of the past, which are very point and click. Do you think that's overstating the case? I mean, what's your take as a Zen practitioner?

[Aneesh Acharya]

I. Listen, I think that the one thing that's exciting to me. Well, two things certainly. Human connection, real friendships, spending time together. If we can have more time to do those types of activities.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And. And we do lean into that versus just being hooked on our phones.

[Kevin Rose]

Yes.

[Aneesh Acharya]

I think it will lead to better and, and stronger emotional states, better family units at home, like a whole slew of benefits from. From that side. There are certain pieces that, you know, I'm not going to want a digital meditation instructor in terms of, like, you know, I want a real human teaching me. It might come in digital form.

[Kevin Rose]

Yes.

[Aneesh Acharya]

But I want a real human that's behind that. Not just some AI therapy. Maybe not so much. Maybe. I do like the idea of having a digital therapist. We'll. We'll see. So it's all. Not all doom and gloom. I hope that we start to shift to celebrating craft and finding. In celebrating that if you find a niche that you are into.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Then, then. And you're the best at that particular thing that we can hopefully, you know, put some value behind that. And Japan is quite good at this.

[Kevin Rose]

I mean, they've done it for 700 years, right? Yeah.

[Aneesh Acharya]

You'll find these small little artisans.

[Kevin Rose]

Yes.

[Aneesh Acharya]

They're the best. And there are people, like, I've gone to coffee shops in Tokyo where it's like one guy doing aged coffee beans and then it's like a line down the street to get in.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And it's just like, he doesn't want to become a billionaire. He's just happy to do this thing that he's found this very small little niche that people love. Yeah. You know, I hope there's more of that.

[Kevin Rose]

What's your version of that?

[Aneesh Acharya]

Oh, probably Japanese woodworking. A little bit more meditation. Okay. More time with friends and family, getting off of technology. I found that, like, I need breaks. Like, it's. We mentioned how it's. It is so fun to do coding right now.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And because it is so fun, I can literally wake up, up and kind of like out of my trance of coding and be like, wow, I've been on the computer for 11 hours today.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

It doesn't feel like 11 hours.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

But that can't be healthy. Right. So I just need to figure out what is that balance? Am I really, truly finding the time to hit the gym? Am I time to do the things that are going to benefit my body over the long term?

[Kevin Rose]

Right.

[Aneesh Acharya]

Am I staying connected with my kids, my family?

[Kevin Rose]

Yeah.

[Aneesh Acharya]

You know, I think those are very important questions to ask. And, and I, I worry a little bit that AI makes it more of a trap to get kind of get sucked in and avoid, I don't know,

[Kevin Rose]

like, maybe it's barbell, you know, so maybe you spend these really productive, satisfying, fulfilling time on your computer and then you don't have any of the overhead that you typically had, right? All the meetings, you don't go to meetings, your agent goes to meetings for you. Right. And makes decisions and handles conflict and sells customers and all this other stuff. And the rest of the time you're, you know, practicing meditation, hanging with your kids, touching grass.

[Aneesh Acharya]

Right?

[Kevin Rose]

So I think there's the potential to have this like, like really productive, satisfying technology time and this really productive maybe or satisfying sort of fulfilling human connection time. Why can't that be the shape of our life going forward?

[Aneesh Acharya]

No, I hear you. And also, I'm, I, I've. I've danced around the edges of this in a dangerous way.

[Kevin Rose]

Oh, God.

[Aneesh Acharya]

So I, I thought about, I, so I was talking to my wife and I was like, okay, listen, we're getting to a lot of arguments about X, Y and Z. And what if we just had a conversation with a model that built out these frameworks for us, that understands what we like, how much we care about certain things, and then we just have our models go and like, duke it out and be like, ah, actually tonight we go out to dinner. Because historically Daria has had the right to go out to dinner. I'm just making this up, but like. And she's like. And I explained this whole thing and I'm super proud of the idea and I think it's gonna, like, save us a ton of time and effort. And she looks at me and she's like, like, this is one of the worst ideas ever. Just like, you know, but. So I worry about outsourcing too much of that, that negotiation and conversation and just, you know, saying like, oh, the agents are just going to handle it. That said, around certain things like policy or conflict resolution between nations and things like that, it might be a little bit more of a steady hand to have two agents discussing their. And getting to a resolution faster. I don't know.

[Kevin Rose]

It's interesting. So. Well, I'm not sure about the family setting, but if you think of the corporate setting, you know, there's this old saying, like, the best way to compete with an incumbent is to pick a product area that lives between two VPs. Because the idea is the VPs hate each other so much, they won't possibly be able to collaborate to actually, like, handle the competition in this area of Crossover. Yeah. And that's like an area in which I think, look, if each VP had an agent that went in, I mean we'll have to see. And I guess there'll be agent politics, corporate politics, but. But you could just imagine conflict resolution feeling so much less personal.

[Aneesh Acharya]

Yeah.

[Kevin Rose]

I think so many issues at work come from this like misattribution of professional decisions to personal feelings where it's like, hey, the boss went against me because they don't like me. It's not because they just had a professional judgment that was in a different direction.

[Aneesh Acharya]

Right, right, right.

[Kevin Rose]

And I hope that this technology helps to lessen that.

[Aneesh Acharya]

Yeah, absolutely. What is the coolest thing you've seen in the last few weeks? Because you must see so much stuff in terms of pitches and what has you excited to be an investor still? Because for me early stage seems like. And I'm not saying that you're squarely in early stage because obviously your fund does the whole gamut. Early stage seems pretty dead to me.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Just because it's like people, entrepreneurs are just going to skip that round altogether.

[Kevin Rose]

Well, I think that there's venture exciting and then there's sort of like human exciting. And when I tell you a story like the one I told you about this guy Mike who built this incredible software and he's like, you know, Claude Pilled and all this other stuff, that's one of the most hopeful things I've seen in a long time. I mean we should put Mike on billboards. I actually pair that with a lot of the stuff that Elon's doing. Like when you see the, you know, the effort to get to the moon, when you see SpaceX, when you see Waymo, like oh my God, that's what we meant when we said technology, you know. How about you? I mean, what do you think?

[Aneesh Acharya]

No, I'm in the same boat. I worry that the kind of early stage, like sassy world, like little bite size pieces of consumer stuff is going to be largely dead. Hardware is still very capital intensive to get off the ground. I'm very bullish on actually devices that encourage us to kind of disconnect and have more shared reality together. Have you seen Tin can at all?

[Kevin Rose]

Yeah, my son has one. Yeah. Yeah, it's amazing.

[Aneesh Acharya]

Yeah. So my.

[Kevin Rose]

You should describe what Tin can for

[Aneesh Acharya]

people that don't know. Tin can is this little device that is a phone, like an old school phone that you plug in the USB C and it connects to the WI Fi and then you could as, as the parent, you can tell the App which kids they can call.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And so it was so funny because my daughter picks up, she goes. She listens to it. She goes, someone's calling us. And she hands me the phone, and it's a dial tone. And she'd never heard a dial tone before in her life.

[Kevin Rose]

Yeah. Why would you?

[Aneesh Acharya]

And she was like, someone's calling. It's ringing. It's ringing. And I'm just like, no, that's what he. That's what you had to listen for before you could dial the numbers, you know?

[Kevin Rose]

Incredible.

[Aneesh Acharya]

But now when that rings across the room, they get so excited, they don't know who's calling.

[Kevin Rose]

Yes. Yes.

[Aneesh Acharya]

And they go running to go pick it up as fast as possible. Can. But I want Tin can for grownups. Like, it would be so cool to have, like, a little phone that is only with your friends.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And you don't know who's going to call, but you're going to pick it up because you know it's a trusted friend.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

So it's little bits of technology like that that I think are just going to provide these little moments of delight and real connection that I'm excited for.

[Kevin Rose]

It's very funny. So my son has one as. And when he. So he gets. He geeks out when he gets a call, right? Yeah. Races, darts over to the phone, he picks it up, and it's his bro calling. And he'll be like, what's up? What's up? And they'll Talk for maybe 20 seconds, and they won't know what to talk about.

[Aneesh Acharya]

Right.

[Kevin Rose]

And I don't know if that's like, the kids don't know how to use this technology or that's just how men talk to each other.

[Aneesh Acharya]

Yeah.

[Kevin Rose]

So just be on the phone for, like, 10 minutes, just sort of like just grunting a little bit, and then they'll hang up and how was your call? It was great. It was really good.

[Aneesh Acharya]

It's amazing. Yeah. But he's still young, though, too. Like, it's not like they have, like,

[Kevin Rose]

a ton to talk about.

[Aneesh Acharya]

I know. It's just.

[Kevin Rose]

It's such a funny little microcosm of male relationships, you know?

[Aneesh Acharya]

Are you looking at more hardware these days?

[Kevin Rose]

Yeah, we're. We're open to everything. Actually, right now, one of the most interesting, coolest pieces of hardware I saw recently, we're not an investor, is this company Pocket. You know, a bunch of companies are doing things like this. These sort of, like, passive recorder devices. I know. You sandbar. I think you guys have invested in one that you're excited about? Yeah, it's just, it's really elegant hardware design and also just love that founders are being ambitious enough to try hardware again. Hardware has all of these like, you know, it's just a challenging place to operate, but founder ambition is higher than it's ever been. So yeah, we're definitely open to hardware.

[Aneesh Acharya]

Yeah. That's awesome. Yeah. I've been looking at the, the always on recording stuff for me has been a little bit like, eh, I don't know if I want that in my life.

[Kevin Rose]

I know, I know.

[Aneesh Acharya]

Yeah.

[Kevin Rose]

Still, it's just cool that people are building things in those directions, you know?

[Aneesh Acharya]

Yeah.

[Kevin Rose]

And I also think that you're too skeptical on consumer. Like, consumer feels like dead, dead, dead, dead. Oh my God, it's on fire.

[Aneesh Acharya]

Right? Yeah. I guess the, the question is I, I think what. The reason I am a little bit skeptical on it is I, I think it'll be dead, dead, dead. Oh my God, it's on fire. And then when it's on fire, on fire with three engineers and they've, you know, hit something and all of a sudden the first round is done at a $500 million pre. And I'm just, I worry that what we're going to see is just a decimation of all their early stage funds because they won't, they'll skip all those rounds altogether and go straight to B or C. Yeah. In which case Andreessen will do fine but like all of these other funds are just going to be completely wiped out.

[Kevin Rose]

So I have a history question for you. When you started Diggs, what did it, what did the environment feel like in terms of consumer? Like, does it feel like a good or a bad job?

[Aneesh Acharya]

It was dead.

[Kevin Rose]

Okay.

[Aneesh Acharya]

Yeah. It was largely dead because we were coming out of the dot com burst.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And then the thing that was a technology enabler, which was Ajax, that allowed for dynamic content to be refreshed, that enabled a new wave of kind of consumer apps to be built on top of it.

[Kevin Rose]

But it wasn't obvious at the time when you guys started tinkering.

[Aneesh Acharya]

No.

[Kevin Rose]

That it was going to be like a global social media. Like, you know, I mean it would be regulated, it would like you potentially influence elections. It would. Did you have any sense of how important it would be?

[Aneesh Acharya]

No, there was none of that. And I don't think it was just, it was a very, it was a time where people said what if? And then they tried it. Like, like Flickr came out and it was the first time people actually shared their photos publicly.

[Kevin Rose]

Right.

[Aneesh Acharya]

Because that was a weird thing. You're like, oh, there's a picture with my, my family. Why would I ever want to put that online?

[Kevin Rose]

Yes.

[Aneesh Acharya]

Someone might see that those are my private photos. Photos were always kept in albums in your house. Yes. You know, and like some family would come over and look at them, you

[Kevin Rose]

know, and so there was a lot

[Aneesh Acharya]

of that going on. Like, you know, Foursquare was like, oh, I'm checking in somewhere. Is it weird to tell people where I am right now?

[Kevin Rose]

Yes.

[Aneesh Acharya]

You know, like Twitter was like, what am I up to? You know, like there was a lot of strange things.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And we're seeing kind of very similar experiments happening right now. And I do believe we'll see, you know, multi billion dollar companies on the consumer side come out of this way.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

I just, I have a feeling it's going to be structured very differently than it was in the past.

[Kevin Rose]

Maybe. I mean, I don't know about venture economics, but I feel like if there's a big new consumer set of consumer categories, venture will be fine and consumers will benefit. And I love that you talked about the photo sharing thing because I feel like anytime you have new culture, new technology, and they both happen at the same time. It's amazing. Like think of the photos thing. Photos went from hyper private to being public to being public and seeming so important that you would never want to delete them. To snap. Coming around and being like, no, now they're disappearing.

[Aneesh Acharya]

Right.

[Kevin Rose]

Which felt like, whoa, why would I want it to disappear?

[Aneesh Acharya]

Right.

[Kevin Rose]

Ten years after you're like, whoa, why would I want to share it?

[Narrator]

Right.

[Aneesh Acharya]

But then it went back to Instagram saying, I actually want my photos to look cooler and stick around.

[Kevin Rose]

Yes, yes.

[Aneesh Acharya]

And so it was kind of all.

[Kevin Rose]

And now if you actually, if I shared an AI generated photo of myself with you, you'd be like, this is slop. Right. So it's just there's. So these cycles are locations. Another fascinating one. There's this whole moral panic around privacy and security and will people share location and location based ads like this whole topic now if you look at it, Gen Z's, they share their location with friends, family, exes, like everyone. Right. They have zero expectation of location privacy. There's no more like sort of distorting effect on culture than AI right now. Right. Think of even AI companions and friendships and psychosis and productivity porn. And there's so many topics here that are going to drive culture, not just technology. How can that not result in interesting new consumer products?

[Aneesh Acharya]

Yeah, I agree. So get. Let's wrap things up. Is there another? I have one final question, but if you have any we want to touch on before you go, let me know. I know you got a heart out soon.

[Kevin Rose]

I've got a little bit of time. I mean, I.

[Aneesh Acharya]

You got a good one. Let's hear it.

[Kevin Rose]

Okay, so let, let's like explore this and we can cut it if it ends up not being interesting. But we were sitting here getting ready for the pod and we were sort of trying to get our mics on the right way, and you were saying, oh, you've got to wrap the cord around the mic in a certain way. Yeah. So there's this sort of knack for getting things done, small things and big things in this world, and it's just in people's heads. Right. Nobody has sort of written that kind of thing down. You've called that dark data.

[Aneesh Acharya]

Yes.

[Kevin Rose]

Right. So what's your kind of view on that type of information? Does that have value? Does that have more or less value than traditional information that's written down? And how does that show up in the future?

[Aneesh Acharya]

Yeah, I mean, there is. I think that is a huge opportunity. I don't know how you monetize that, but it's an opportunity to unearth it, save it, and then work it into the models that we're doing. You had a great example off Mike where we were talking about, you know, the one person that knows how to adjust a carburetor in a certain way for a certain model of car.

[Kevin Rose]

That's right.

[Aneesh Acharya]

And if that person dies, that knowledge is then lost. Right?

[Kevin Rose]

That's right.

[Aneesh Acharya]

And so I, I believe that this exists kind of all around us in terms of. Of little tiny micro things of dark data that we just have yet to work in and record in little tiny preferences and nuances that just never make it their way into these models.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

So, you know, for example, this, this, this table right here. One of the things I wanted to do is I wanted to get a very Charlie Rose esque table, which was an old. He was basically was very famous for doing these interviews where he could like lean in and talk to someone.

[Kevin Rose]

Yeah, yeah.

[Aneesh Acharya]

And I actually had. There was no stats or dimensions for his table anywhere in the models. Right. And so I provided the model with like five different screenshots.

[Kevin Rose]

Right.

[Aneesh Acharya]

And then set it on the heaviest working mode. And then it calculated the size of the coffee cup.

[Kevin Rose]

Okay.

[Aneesh Acharya]

And then estimated the dimensions of the actual table.

[Kevin Rose]

Wow.

[Aneesh Acharya]

And so I could actually buy a similar table in terms of Size so I could fit up to four guests sitting around this table.

[Kevin Rose]

Yes.

[Aneesh Acharya]

As Charlie did.

[Kevin Rose]

Yes.

[Aneesh Acharya]

And that was an example of something that the data was not in the model, but I had to back my way into it. Right.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And so I just think there's a lot of that. Proprietary data sets I think are really interesting in some sense. There's probably a market to go raise a fund just to acquire proprietary data, to resell it.

[Kevin Rose]

This is what Merkor and others are doing. They're getting human data generation, some of which is like coding and math and all that. But I imagine in the future, some of which will be this type of tacit knowledge you're describing.

[Aneesh Acharya]

Yeah. So that to me is very interesting. It's not a business I would want to go build, but it's certainly, I think we're going to get a lot more of that unearthed as robotics and other sensors come online. Yeah, I mean that's, I think Google Maps was probably the earliest idea of going and mapping this kind of dark data.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

But yeah, it's, it's models. Will, this is where I think when you talk about the layoffs and you're like, ah, none of my buddies are getting laid off at Google. If anything, they're just accelerating. But that doesn't account for the models getting better. Better. Because when the models are, you know, three times as performant as they are today, or five times, or 10 times.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

Then you, you really don't need as many humans. Your backlog quickly dries up.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And you don't, you know, one person can orchestrate, you know, 20 projects or a hundred.

[Kevin Rose]

Yeah. But dude, then Sundar says, like, I want to be the first 100 trillion dollar company, you know, like, what is. Sundar is not going to say, you know what, we should like keep our market cap but just like be more profitable. No CEO thinks that way. Right. They want to shoot for the moon. So I think Sundar's ambition will grow at least or faster. As fast or faster than model progress.

[Aneesh Acharya]

Do you think government regulation steps in there and says you can't run everything? Because there is, there is a world where just it's OpenAI anthropic and Google and they're kind of just everything to everyone.

[Kevin Rose]

But we just, it's just not the world we're living in. Right. Like meanwhile here on Earth, there's hundreds of open source models. There's all kinds of distilled models. The model price token prices for what were cutting edge models three months ago are going down. There's Edge devices actually having models embedded in them. So that could happen. But I think the case for sort of outlier, you know, n of 1 outcomes was much stronger in social networks than it is in foundation models. We just don't see foundation. You said yourself, right? I've got my credit card. I'll use Opus one day and Codex and X. Yeah, yeah, that's fair.

[Aneesh Acharya]

All right. Right. Any predictions for the next six months? Let's hear the, the craziest, wildest prediction that you have.

[Kevin Rose]

I mean, weirder, better, faster, man.

[Aneesh Acharya]

Weirder, better, faster.

[Kevin Rose]

So, okay, so here a hard prediction.

[Aneesh Acharya]

The OpenAI IPO.

[Kevin Rose]

I mean, I'm not supposed to talk. Look, I think all these, look, I think all the, all the big model companies are going to go public. I think that's like.

[Aneesh Acharya]

You think it's this year or next year?

[Kevin Rose]

I mean, I don't know exactly, but I think that it's going to happen in the next 12 months with no inside information. That would be my prediction.

[Aneesh Acharya]

I agree.

[Kevin Rose]

I think that. Look, okay, so maybe like my strangest prediction is that I think we're going to get to the four day work week in a uniquely American way. And let me tell you what I mean by that. So I'll tell you a little bit of a story. So if you think back to the conversation we were having about diet and nutrition 30 or 40 years ago, there's two schools of thought, right? There is the European school of thought, which is we should eat less sugar. There was the American school of thought, which is we should eat less fat. And maybe they were sort of influenced by industrial lobbies and whatever else. So we ran the experiment for 40 years and Europeans stayed pretty slim and Americans got really fat, right? Now, probably what Americans should have done and a lot of people tried to make this better is said, hey, we need to just change our habits as a society and you know, moderate a little bit and sugar intake and all these. Of course that didn't happen, right? Instead Americans did this uniquely American thing which is we invented Ozempic GLP1. So we're like, with this breakthrough new technology to solve this problem that we really should have just solved with like perhaps different choices as a society and as individuals. I think the same way the Europeans have aspired to the four day work week and they're like, this is better for human flourishing and families. And I think that's right. But Americans have to do it the American way, which is we create this incredible new technology that makes us so much more productive that we can actually Reduce our workload from five days to four days and maybe even three and a half days. So there's some sort of a parallel here and I think we're heading to a four day work week. That is how the 20% productivity increase is going to show up in my view. And that's my strangest prediction.

[Aneesh Acharya]

Okay. My strangest prediction is that in the next three years we will probably discover and produce and create and get into humans another 50 to 100 peptides that alter our longevity in a meaningful way.

[Kevin Rose]

Can you tell me about the peptides thing? Give me the quick take.

[Aneesh Acharya]

So peptides are just small chain amino acids. They're very easy to produce in the lab them and they kind of like think of them as upstream regulators that can then trickle down and cause other things to happen in the body. So they're not as powerful as like a straight up hormone and they're not. So they're not as heavy as a hammer. They just kind of like cause things to happen.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

And so the most famous peptide is insulin. The GLPO ones are peptides. But there are, you know, 20 other candidates that are out there that I've seen people experimenting with that are producing wild results. There's one called the Wolverine Stack where literally I have had friends that had back injuries and knee pain and elbow pain.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

I had tennis elbow really bad in my. Which I don't even play tennis, which kills me, but I had tennis up in my right arm really bad. And I took the Wolverine protocol for like two weeks. And I don't. I feel amazing.

[Kevin Rose]

Really?

[Aneesh Acharya]

Yeah.

[Kevin Rose]

Literally.

[Aneesh Acharya]

Yes. And so I believe, and there's a lot of people working in the space that they're going to identify these peptides. We'll be able to easily compound them and create them. And they, the FDA has backed off a little bit. They were banning them for a while and now they're actually have approved quite a few. Okay. One for muscle mass in age AIDS patients. And so they can do like give them this peptide and they'll like gain more muscle mass. There's another one that actually I believe it's Eli Lilly that is this three agonist glp, one that you don't lose muscle with now, which is really interesting, that's in the pipeline. It's phase three trials right now.

[Kevin Rose]

Okay.

[Aneesh Acharya]

So as AI allows us to do a lot of this modeling in more real time and hopefully candidate discovery, I think peptides is just going to be a fascinating space to watch.

[Kevin Rose]

So. Okay, so I have two questions. One is what's the basic stack. For somebody playing with peptides, like what would you recommend? What's safe, what's the right amount of risk to take?

[Aneesh Acharya]

I would say go listen to Huberman's two podcasts. He has two podcasts on peptides. Yeah, and they go in depth about each one. Some of them are for sleep, some of them are, are, you know, they really increase your deep sleep and you sleep better. I have one buddy that says he sleeps like he's 18 again. He just like wakes up like fully rested and doing these peptides. I have one buddy that's removed all of his visceral fat and is but done by a DEXA scan which we know visceral fat is like really the bad type of fat that you don't want to have around your organs. And yeah, there's almost a peptide for everything now, which is just really insane. And these are largely. You gotta be very careful though, cause as human will talk about, there's gray markets, there's contaminants that can get in there. You gotta work with a, like a high quality company when you're thinking about this stuff.

[Kevin Rose]

So my second follow up question is, you know, if we radically extend human life, do you think we're sort of emotionally, spiritually, societally prepared for people to live to 120, 150, 200.

[Aneesh Acharya]

So no, sadly not in America. We just don't have the support infrastructure for the elderly nor the care, which is a huge bummer.

[Kevin Rose]

But what if we controlled for that and said people live, you know, their, their full, most flourishing 25 year old lives.

[Aneesh Acharya]

Agree. The thing you don't want to do is have extend dementia for an extra 20 years because they're taking peptides. You know, it's like. So that's, that's the, the tricky part. But you know, there are candidates like Clotho and some of these other. That's a protein that looks like it's in the pipelines for a potential treatment for a lot of dementia. So it's a very exciting time on the science front. So that to me is. And then I would say my other prediction by the end of the year is that I just don't think we'll ever look at code again. I think that Elon talked about how why are we actually writing languages, like writing code in languages. If the AI is smart enough to understand the inner workings of every single cpu, GPU and every piece of silicon that it's going to touch. Yeah, it can just compile directly to binary and just work. Which is wild because then that rewrites all of how we think about infrastructure in general. You don't have to pick databases anymore. You don't have to like think about any of these things. It's that, that I believe is going to be in the next five years. There won't be weird questions like should I be using a graph database for this? Or you know, it'll just kind of be solved. Which is.

[Kevin Rose]

I think it'll be interesting to see what happens when agents make these choices on our behalf. Because there'll be technology with trade offs.

[Aneesh Acharya]

Right.

[Kevin Rose]

Presumably there'll be marketing, but not to humans, to agents. Because ultimately it's going to be Codex that chooses the database. So how does that marketing show up? What are the. I mean it'll just be very wild.

[Aneesh Acharya]

Yeah, I don't think it'll have to be marketing. Yeah, I think it'll just go spin up an instance, run it, benchmark it for its use case, maybe come back and be like, yeah, I just test that out. This is the best one. And then, and then actually Chamath had a really interesting point about it that a lot of people were calling bullshit on. But I kind of believe, which is he said that these agents will just shop around.

[Kevin Rose]

Yeah.

[Aneesh Acharya]

They'll go and they'll be like, okay, that graph database that was serving us well six months ago is now more performant on this type of database, on this infrastructure for this cost. Yeah, I'm just gonna do the migration. Yeah. And so you have to imagine that just happens like seamlessly at some point.

[Kevin Rose]

Dude, it's so cool. So when I worked at Amazon when I was a Kid, which was 2003. Delivering packages. Yeah, exactly. Going door to door.

[Aneesh Acharya]

No, hell no, dude.

[Kevin Rose]

As a programme. I was a programmer. So Jeff used to say this thing, he said a lot of things which were, you know, forward looking. But one was we should assume that we're going to live in a world where our buyers have perfect information. Right. And if you think of like how much of industry and commerce is based on either buyer laziness, apathy or this asymmetric sort of information between sellers and buyers, what if that goes away?

[Aneesh Acharya]

Yes.

[Kevin Rose]

What if like you have to win by product quality always 100%. There's zero value in brand, there's zero value in marketing. Isn't that just a better world to be in? 100% in so many of these areas? I think financial services, another big one. We were talking about Hero before the show, right. Which is a company that was acquired by OpenAI yesterday. Really talented founder Ethan, who started Digits prior with this sort of consumer fintech mission that many of us had, which is like, hey, why can't we just make this system efficient and work for the everyday consumer?

[Aneesh Acharya]

Right.

[Kevin Rose]

And it's like, why should they have to know how the credit system works and how to play the game and how to do all of these things? And I think with agents, a lot of that just goes away. Your agent goes and makes great financial choices on your behalf given your constraints.

[Aneesh Acharya]

Yes.

[Kevin Rose]

And I think that's going to happen in a lot of product categories and it'll be a much better sort of world and society as a result.

[Aneesh Acharya]

Yeah, absolutely. Well said. Awesome. Well, always a pleasure to have you on the show.

[Kevin Rose]

Thank you so much.

[Aneesh Acharya]

Glad we did this. Come back. Let's just keep doing these. Man, I love these little round tables.

[Kevin Rose]

It's so fun.

[Aneesh Acharya]

Especially because every four to five weeks everything changes all over again.

[Kevin Rose]

I mean, we could do this once a week.

[Aneesh Acharya]

I know we run out of time. Brand new topics to talk about. Awesome.

[Kevin Rose]

Thanks for having me, man.

[Aneesh Acharya]

Good to see you, brother.

[Kevin Rose]

Fun. Cool.

[Narrator]

Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to, like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts and Spotify. Follow us on X16Z and subscribe to our substack @A16Zone. Thanks again for listening and I'll see you in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third party and may include paid promotional advertisements, other company references, and individuals unaffiliated with A16Z. Such advertisements, companies and individuals are not endorsed by AH Capital Management, LLC, A16Z or any of its affiliates. Information is from sources deemed reliable on the date of publication, but A16Z does not guarantee its accuracy.