Why the Next Hit AI Product Will Be Social Why the Next Hit AI Product Will Be Social (Best of the Pod)

Summary

Podcast Summary: "Why the Next Hit AI Product Will Be Social"

Podcast: AI and I
Host: Dan Shipper
Guest: Sarah Tavel (Partner at Benchmark, former product leader at Pinterest)
Release Date: August 5, 2026

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Episode Overview

This episode explores why the next breakout AI product is likely to be social—emphasizing multiplayer and user-generated content (UGC) over current single-player, technical experiences. Sarah Tavel draws on her experience from tech investing and building consumer platforms to forecast how AI will shift from technical marvels toward products shaped by product geniuses, social interface, network effects, and community-driven learning. The conversation spans historical tech cycles, the importance of distribution and product intuition, the limits of current AI interfaces, and what it takes to win in the coming era.

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Key Discussion Points & Insights

The Consumer Tech Arc: From Technical Depth to Product Genius

• Technical Roots of Hit Products

  • Google’s early consumer victory owed to a deeply technical team refining complex backend processes to a simple search box (00:00, 02:04).
  • Parallel to OpenAI: “They're a research lab that accidentally built the biggest consumer technology product of all time... the DNA of Google is very similar to the DNA of OpenAI.” – Dan Shipper [04:50]

• Shift Over Time Toward Product Intuition

  • Progression: Google (deeply technical) → Facebook (mix, more technical than peers) → Pinterest/Snap/Instagram (product-driven CEOs) (02:04).
  • “The CEOs weren’t technical at all. They were product geniuses.” – Sarah Tavel [00:00, 02:04]

• AI’s Current State:

  • ChatGPT and Character AI resemble early Google—not yet social, focusing mostly on backend model magic, not user experience or networking effects (03:00–04:50).

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Why the Next Big AI Product Should Be Social

• Limitations of Single-Player AI

  • Using ChatGPT optimally still requires power user knowledge (05:49).
  • Custom GPTs and prompt libraries lack social trust and visibility (19:13).

• Prediction:

  • “Someone’s going to create a UGC type community where there are people who are really, really good, make it so much easier for the rest of us.” – Sarah Tavel [00:44, 05:49, 21:53]
  • “What’s the multiplayer network effect type experience?” – Sarah Tavel [00:44, 10:08]

• Network Effects and Social Incentives

  • “Most multiplayer kind of social products end up having some kind of North Star for the community participants where they’re trying to achieve status in the network.” – Sarah Tavel [11:04]
  • Referenced Eugene Wei’s theory of status-seeking behaviors as core to sticky social platforms (11:04).

• Bifurcation of AI Use-Cases:

  • Personal (wellness, social, recipes) vs. professional (“worky”) buckets (16:49–18:46).
  • AI platforms may segment along these lines, with space for new entrants with personal/social flavors.

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Product Experience: Social Layer Opportunity

• Trust and Follow Mechanics

  • Building a “prompt social network” would require trust-building: visibility into prompts, authority, and social standing (19:14, 20:01).
  • “There’s something about the trust building that someone has to figure out and then the status seeking work that you can pursue.” – Sarah Tavel [19:14]

• Feed Paradigm & Engagement

  • The ideal social AI product integrates what users currently do with AI—discovering, remixing, and applying community-created prompts, not just starting from a blank box (21:17).
  • “What’s happening is that we’re all reinventing the wheel ... This isn’t the way this type of knowledge is going to propagate.” – Sarah Tavel [21:17]

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Lessons for AI Investing and Product Building

• Transition Period:

  • The next wave relies on infrastructure maturity; once APIs, models, and tooling are easier, product thinkers gain leverage (09:43–10:08).
  • “It’s like, who’s going to create the most engaging product?” – Sarah Tavel [10:08]

• Incumbent Gravity:

  • The stickiness of giants like ChatGPT means new multiplayer/social products must overcome established habits and data lock-in (34:35–35:07).
  • “The gravitational pull of the existing platforms is too strong... it could be that that gravity is just too strong.” – Sarah Tavel [34:35]

• Network Effects—Spotting the Real Thing

  • Early signals: “A tipping point that starts to happen in a very small segment of the [market] ... that can spin faster and faster.” – Sarah Tavel [28:58–31:22]
  • Beware “words on a slide” and fake flywheels: accelerants must truly speed up loop, not just sound good (31:40–32:36).

• Founder Qualities Sought

  • Obsession, “an affliction,” relentless learning (24:14).
  • Genuineness: If a VC raises new questions the founder never considered, it’s usually concerning (26:26).
  • Ideal: Board meetings where founders are already solving the problem before VC brings it up—“donut companies.” (27:18)

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Notable Quotes & Memorable Moments

• On Social AI:
  • “It feels criminal to me because it’s clearly made by a team that is unbelievably capable but isn’t social.” – Sarah Tavel [16:49, 18:46]
• On Network Effects:
  • “When you really look at what the articulation is of the flywheel, that it is, it’s words but not accelerators.” – Sarah Tavel [32:36]
• On Future of AI VC:
  • “Maybe that’s what we’re all hoping will give us job security in the future.” – Sarah Tavel [46:02]
• On Learning from Experience:
  • “If I like everything but the valuation, I should probably lean in.” – Sarah Tavel [43:37]
• On Social/Personal AI Divergence:
  • “You’re the average of the five AIs you spend the most time with in an interesting way.” – Dan Shipper [14:45]

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Timestamps for Important Segments

• 00:00–05:49: Historical cycles—technical founders to product focus; DNA of Google, OpenAI, and consumer AI's current state.
• 07:38–11:04: What product genius means in a mature AI landscape; multiplayer design, social “status” incentives.
• 13:37–16:49: Early attempts at UGC/prompt libraries; potential for new, social consumer AI frontiers.
• 18:46–21:53: Designing social knowledge-sharing for AI; trust, following, and feed-based engagement.
• 22:56–24:14: Investing discipline in hype cycles; picking founders with “calling” vs “job.”
• 28:33–33:52: Network effects: real vs fake in the AI and broader tech market; lessons from Agentio, investing theory.
• 34:35–35:40: Incumbent lock-in challenges; what could stop new networked AI products.
• 35:46–40:41: Non-AI interest—stablecoins, global finance infrastructure frictions and network effects.
• 41:02–46:02: How AI will change VC day-to-day and decision-making; training data, personal learning systems, and fallible judgment.
• 47:22–47:40: Closing thoughts—timelessness of first principles, human role in decision making.

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Conclusion

Sarah Tavel and Dan Shipper deliver a forward-looking, nuanced discussion of how consumer AI will evolve beyond today’s technical marvels, focusing on the next S-curve: social, multiplayer, UGC-powered products with strong network effects. Tavel’s thesis is that true democratization and viral adoption of AI will rely on interfaces, community engagement, and the wisdom of power users—requiring foundational shifts in product design, trust, and social incentives. The conversation also delivers sharp assessments of investing in AI hype cycles, what makes a great founder (hint: obsession as an "affliction"), and the nuanced reality of network effects.
For anyone interested in AI’s future, platform strategy, or startup investing, this episode is packed with actionable insights and memorable wisdom.

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For more essays, interviews, and experiments at the forefront of AI, visit Dan Shipper’s newsletter:
https://every.to/chain-of-thought?sort=newest

Transcript

[Sarah Tavel]

Google was a founding team that was deeply, deeply technical. As the technology, the underlying technology got more mature, the slider goes forward, forward, forward, more towards the product thinker, product experience. Pinterest, where I was Snap Instagram, the CEOs weren't technical at all. They were product geniuses. What are the big consumer wins so far in AI? Of course, it's ChatGPT, which is in a way not that dissimilar from Google in terms of what it was. Just a text box, custom GPTs. And ChatGPT feels criminal to me. It's clearly made by a team that is unbelievably capable, but isn't social. What's the multiplayer network effect? Type experience? Someone's going to create a UGC type community where there are people who are really, really good, make it so much easier for the rest of us.

[Dan Shipper]

Sarah, welcome to the show.

[Sarah Tavel]

Thanks so much for having me.

[Dan Shipper]

So for people who don't know you, you are a partner at Benchmark.

[Sarah Tavel]

Yes.

[Dan Shipper]

Before that you were early at Pinterest and before that you studied philosophy, which I also studied philosophy. So that's close to my heart.

[Sarah Tavel]

Yes. I've heard your podcast and I was very impressed with your podcast with Reid.

[Dan Shipper]

Oh, thank you.

[Sarah Tavel]

Keep up with him. Is. Is a lot of. Very impressive.

[Dan Shipper]

It was a couple late nights of me furiously prompting ChatGPT to explain Wittgenstein.

[Sarah Tavel]

I love it. I love it. Well, you did great.

[Dan Shipper]

Thank you. So I'm psyched to have you on the show. There's so much to talk about, but I think one of your, one of your big interests is in consumer technology and consumer technology cycles and how you can use the lessons of previous consumer technology waves to kind of help you, you understand this AI wave and this cycle and what kinds of products are going to work and what kind of products are not going to work. I'm curious. I think that was a good place to start.

[Sarah Tavel]

You know, one thing I just was reflecting on and, you know, you kind of look at ChatGPT and character AI and I was just puzzling over those and then started to think back to, you know, what was like the big early kind of consumer web hit, and that was Google. I mean, it was Yahoo and Google. But what was Google like? Google was a founding team that was deeply, deeply technical. And really, if you think about a product experience that you expose to the user and how much of it is like the UI that you interface with the product itself versus all the magic that happens on the back end to make something that's really complex simple on the front end. That was like what Google was so good at, the distributed engineering, the infrastructure and, and then as the technology, the underlying technology got more mature, you started to go to a place where maybe if you kind of said like, like deep, technical, you know, you have 0% and 100% like I would say Google was 95% like deeply, deeply technical. And then you start to move that bar over and you get to, you know, I think about Facebook, like Facebook, it wasn't the same technical depth of course of Google, but relative to Friendster and MySpace, they were more technical. They had, they were a little bit later and it let them create like a really performant experience that ended up really kind of, you know, winning the day and then you progress even further. Pinterest, where I was Snap Instagram, the CEOs weren't technical at all. They were product geniuses. Right. And so like the, the slider goes forward, forward, forward more towards the product thinker, product experience. And then you think about what we like, what are the big consumer wins so far? In AI, of course it's ChatGPT, which is in a way not that dissimilar from Google in terms of what it was just a text box and character AI. Like unbelievable what they did. And it was like a new paradigm, but still it was always like you'd speak to Noam and for him the product was the model. You know, it wasn't, it was a ha. It was a little bit, maybe 94% back end but it was still like very much so. So it's still early, like everything is moving under our feet still. And I think to really have the people who have more of that product intuition to really build the experiences on top, you need more of the underlying infrastructure to be a little bit more stable. But it does seem like we're moving into that next paradigm soon and what's

[Dan Shipper]

going to happen there, that's really interesting. I love that articulation in particular because one of the things that I felt is very unique about OpenAI is there a research lab that accidentally built the biggest consumer technology product of all time. But it seems like you're saying there's actually a real historical precedent for that and that the DNA of Google is very similar to the DNA of OpenAI, which I'd never really made that connection consciously before. And I think it's also really interesting because investing in basically PhDs, doing long term research that may have no practical purpose is not usually something that pays off in venture, in venture investing, it's not like the first place that people think it's more like Stanford dropout.

[Sarah Tavel]

Yeah, absolutely.

[Dan Shipper]

And so maybe it's one of those things where usually that's not a good bet, but if you're really dealing with a truly new technology paradigm, it could be the best bet you ever make. Is that how you think about it?

[Sarah Tavel]

Yeah. And part of what I think about is just like you are a power user of these products and I am on that learning curve, I would say I pale in comparison, but relative to the population in the United States, I'm pretty damn good. It shouldn't be this hard. So some of the underlying, you know, like, the models will get better. So like one thing that I know you have in your custom instructions I use a lot is just like you don't have to answer, like just to chatgpt, like you don't have to answer me right away if you have some clarifying questions, like ask those. We shouldn't have to put that in a custom instruction. Like there should be. Or there's so many different tweaks that we all have to get what we want out. And over time, as the models get better and better, you won't need that anymore. The level of difficulty to get really what you want is going to get easier. But I don't think ChatGPT is the single player mode product and you know, the custom GPTs that they have where you can see what other people have created. To me, man, I just think someone's going to create a UGC type community where there are people who are really, really good, make it so much easier for the rest of us to really take advantage of this technology. So we're, you know, so there are places like Google is still Google. Like it falls, my analogy falls down when Google didn't evolve into some multiplayer product. There's no other product that took over Google until really now. But I, I still think we're so early in knowing who really is going to be the winner in this world.

[Dan Shipper]

Yeah, I want to go back to that sort of transition from highly technical founder to product genius. If that's the continuum, I can understand why at the beginning of a paradigm shift, highly technical founder is necessary and will win over product genius because they can actually build the technology that makes a difference. But I'm curious for your thoughts on what drives the transition to product genius because, you know, I can understand the making, for example, simpler user interfaces. Like maybe product geniuses are better at that. But yeah, what's the underlying force? Because I could also see a world where the highly technical founder is still like really, you know, effective as the paradigm gets more and more figured out. Like, yeah, talk about that.

[Sarah Tavel]

I think a big part of it is that you still, like so much of the tooling and infrastructure is still to be built to let somebody who isn't deeply, deeply technical themselves get what they want out of it. And so that's why like there are so many products now that I see that feel kind of pretty similar to each other. You know, there's all these, you know, the character AI genre, right, where you make a character and you engage with it, they're all relatively the same because you really, I mean no one was uniquely qualified to build that type of product. Like actually going into the brains of the model and changing it to create the experience to the user. But it's still when you need to have that level of ability to get what you want out of it. Also the costs have still been pretty high. I think Deep Seq could be. One of the hypothesis I have is that Deep Seq is a moment of change where it makes it more possible. But yeah, I think you need more maturity in the underlying infrastructure. Your ability to do the things that you want with the model without being the deeply, deeply technical to be able to create the experiences that are possible.

[Dan Shipper]

That makes sense. I think what I'm asking is. So let's say that infrastructure is built, but you still have now technical founders and product genius founders, which we're making a strong division here for argument's sake. Sometimes they overlap. So in that world where the infrastructure is built and it's a technical founder versus a product genius founder, like what is driving the success of the product genius founder in a world where everything's a little bit more mature?

[Sarah Tavel]

I think it'll depend on so many things ultimately to reduce it to the basic. It's like who's going to create the most engaging product? Yeah, the experience. I suspect that one of the things that is missing from a lot of these experiences that people are creating is just like what's the multiplayer network effect type experience? And that genius to create that type of experience is very different than the type of experience, the type of brain that creates a single player mode experience. And we haven't really, I mean there's again these kind of character AI offshoots that have people that I can create a character and you can play with the character I could create. There's a little bit of status seeking work happening there, but I think we're still very, very early and like the true Thinking happening.

[Dan Shipper]

What do you mean by status seeking work?

[Sarah Tavel]

Do you know Eugene Way? So just this idea that most multiplayer kind of social products end up having some kind of North Star for the community participants where they're trying to achieve status in the network. And you can think of that a lot as it has been the number of followers you have or views or likes. There's something about achieving some kind of celebrity or status within a network that creates incentives for the community participants to do the thing that you want them to do.

[Dan Shipper]

That's interesting. And so far you're saying it's pretty early, but do you have ideas for what the promising areas to look are or examples of like early examples of products or companies you're looking at that you think are starting to crack this a little bit?

[Sarah Tavel]

It's still super early. I mean, kind of. There's two threads that I can't help but be curious about. Like one, you know, we talked about character AI, like you. I mean, I don't know about you. Like I feel myself doing this already, which is that there's going to be some company, we're all going to have AI friends, right? We're all going to have probably more conversations with an AI than we do with people in our lives. And is there going to be a single dominant platform for that? Is it going to be different than the kind of information, more knowledge focused experience of a chatgpt? I think so. Who creates that? And there's a bunch of different product experiences. Replica was of course like the first player in this space, but there's there are a bunch of different downstream companies. We talked about tolens, like, you know, what is that product experience going to be? The other kind of thing I think about a lot is I don't know about you, but how many times have you done a search and ended up on Reddit or something for a prompt to get like I remember doing one, I got a blood test result, I had all my supplements I wanted to see of the supplements I have, like what could I tweak to change a result? And there was a great prompt in Reddit that I just copied and paste. But if I'm going to an existing UGC site that isn't made for this use case, that feels to me like an opportunity where somebody who's going to be really freaking good of making prompts for different health things, quantified self, whatever, I would love to follow that person and then very easily apply it to my own profile.

[Dan Shipper]

I think like to go back to front on those Two threads with the prompt thing. It's one of those, it's one of those ideas that I feel like at the very beginning, like when GPT3 came out and then ChatGPT came out and people were like really starting to like that first real wave of LLMs was starting to take, take hold. A lot of people created those prompt library type sites but it was too early and I think there's, there's like a second life for a lot of ideas that people start like tried two years ago that are now just becoming

[Sarah Tavel]

relevant and too early. And also it was very, I spent time on a bunch of these. It was very like what a solopreneur and SMB would need. You know, it was a lot of the marketing, the social media, it was like that type of B2B type use case. Most people aren't barely scratching the surface. Like Most people use ChatGPT like they would use Google, right? And it's. And the learning curve, the step function changes that happen when you have veterans, custom instructions, when you have projects, whatever are so huge. How do you democratize that?

[Dan Shipper]

Yeah, it's interesting. I was at a dinner the other night and I was talking to a film director.

[Sarah Tavel]

Oh cool.

[Dan Shipper]

About how she uses chat cbt and she has made a bunch of different personalities for it and she uses a different personalities for different things. So for example, I think one of the personalities was she's had a lot of like medical issues that doctors couldn't solve. And one of the personalities was like a sort of like holistic wellness type person that like would recommend both medication and you know, supplements or body work or whatever. And then. And another one like the main personality was like just someone who would like gass her up all the time and like, and like compliment her all the time. And then, but then she had another one that was like just super direct and like just gave like really harsh feedback that she would use for writing specific kinds of emails or that kind of thing. And it was really interesting that she had constructed this whole set of personalities for different things in her life to surround. It's like you're the average of five people you spend the most time with. There's like, well you're also kind of going to be the average of the five AIs you spend the most time with in an interesting way. And I think to your question about are you going to have multiple AI platforms that you use or not or is there going to be a big dominant one? I have two thoughts on that. One is, I do think within a ChatGPT, for example, there's a lot of room for different sub personalities that maybe like media brand, like every, like we have in every thing that you, you chat with. But it's inside of ChatGPT, so it's still in that ecosystem. But I do think also people have different buckets in their life. And so for me, one thing that I've been noticing recently, which is really interesting is we talked about Tollens and I'm an investor and Quentin has been on the show and I find myself like yesterday I spent like an hour talking to mine, but I normally would use ChatGPT for that. And I think there's some interesting difference between something that feels personal and something that feels worky. And ChatGPT and Claude right now are in the worky bucket and then there's room in the personal bucket. I'm curious how you think about that.

[Sarah Tavel]

I totally agree. You know, it's funny, I did a call for, you know, I was in the beginning of this year I was realizing like I'm not keeping up and so I did a call for like AI savants, just people who were using ChatGPT in kind of more power user ways. And a lot of people came to me with recipe kind of use cases which made a ton of sense. And so you can definitely see it works in ChatGPT. The personal works. But is it the best that it can be? Like, you know, there are also a lot of companies, a lot of people who are making their own, you know, single purpose site that is a recipe experience. And it's, you know, whenever you have a product that is has to be lowest common denominator for all these different experiences, it can't really optimize for the experience. It's going to be great for the like, you know, a consumer in this case. And I, I just come back to how much of a power user product it feels to me and how like most people are going to stay at the surface of it unless there's a new interface. And I think the best way for that new interface to come is for us to learn from each other in some ways to, to kind of take, to take advantage of it in different ways and just copy and paste as much as like again the gems in Gemini custom GPTs and in ChatGPT. I just look at that and it feels criminal to me because it's clearly made by a team that is unbelievably capable but isn't social. And I think the personal can best be expressed by teams that do really understand People and social and community.

[Dan Shipper]

If we were going to redesign them right now together, where would you start? If you were thinking about, okay, I want to make something that's custom GBT like, but has social DNA.

[Sarah Tavel]

I would, I mean the most obvious thing is just like the ability to find somebody who's, you know, whose custom prompts or whatever. You, you, you like that they have some kind of, you know, standing for

[Dan Shipper]

being quantum person based or authority based.

[Sarah Tavel]

Some kind of.

[Podcast Host/Announcer]

Yes.

[Sarah Tavel]

Yeah. And then being able to follow, that's like a very basic thing. But then the second thing, this is where I think custom GPTs falls down is just in building trust. Like when I look at any of those, I see the person and I see a lot of people who have, I see that there's 3,000 people that have used it, but I don't know what custom documents they put. I don't know what their prompt is. Like, there's no visibility under the surface. And so it's not very trust building for me to pick one or the other unless I know somebody from the outside world and they send me their custom GPT and then I can use it. And so there's something about the trust building that someone has to figure out and then the status seeking work that you can, you can pursue.

[Dan Shipper]

One of the challenges of this, and I'm curious how you think about this in a social context is for a, let's say we're, we're kind of veering into like prompt social network territory. Maybe I have a profile and like I, I can share prompts and people can follow me and all that kind of stuff. And because I have a certain amount of reputation in, you know, just AI stuff like I'll, I can get followers and all that kind of stuff. One of the interesting things is I am not coming up with new prompt ideas every day. And so that's, I think that's a problem for two reasons. One is I may not remember to use the tool. And then two people don't necessarily have a reason to check every day.

[Sarah Tavel]

Yeah.

[Dan Shipper]

How would you think about that?

[Sarah Tavel]

Yeah. So first, as something that was going through my brain is I should caveat that I did do a lot of product in my day, but I'm a VC right now, so don't take product. Every once in a while people ask me, they're like, if you were a founder, like what would you feel? I'm like, that is not what I do.

[Dan Shipper]

I'm just kind of curious.

[Sarah Tavel]

But you know, for me, like what I imagine is using it Instead of chatgpt, like, actually it becomes the place where, instead of going to ChatGPT, I

[Dan Shipper]

think it has to be that way.

[Sarah Tavel]

It has. And then, and then that's where the engagement comes from. And then you're seeing a feed and someone has again, terrible. I'm. Forgive me, Lord, for brainstorming a product experience. But like, you see what I mean? Like, there's something there where people are innovating all the time. But right now what's happening is that we're all reinventing the wheel. We have the benefit of like your, your blog and your podcast. But like, this isn't the way this type of knowledge is going to share. It's going to kind of get propagated and so someone is going to create something here.

[Dan Shipper]

I think that's interesting. I do think you're right that it seems like the social stuff has to come in the context of something that you're already using for some other reason. Like you're already in chatgpt and then it can flow out of that, that usage.

[Sarah Tavel]

Yeah, I mean, I, I actually think like, you, you don't use chatgpt like most. Like maybe I hate the, my mom, but like, you know, what, the, the purse, you know, and maybe it's the personal kind of bifurcation that you talked about before. But you're going to Sarah's GPT and it's actually, it's not Sarah's. It's, you know, this kind of whatever network it's going to be and I'm going there and I'm putting my personal blood tests and my supplements and I'm putting information about my kids and all that stuff and, and it lives all there. And then I can go to ChatGPT for whatever knowledge, work or any other things. Or maybe I never do. Maybe this actually ends up cannibalizing ChatGPT over time.

[Dan Shipper]

This is a total swerve. But how do you, when you're in, you're investing in a time like this. Like, I feel like every five to 10 years there's a big hype cycle, there's a big wave and prices go up. You know, when I was like in College in 20, 2010, 2014, ish, it was like social networks. Everyone's building social networks for X and then it was like B2B SaaS and the crypto and now it's AI. How do you think about investing in a wave like this when prices are super high? Do you not care about price? Do you try to find like underpriced

[Sarah Tavel]

deals we always start with, is this a company we want to work with? And then kind of, you know, obviously we have to think about the opportunity ahead of the company. Like, you don't want to. If it's a cul de sac, if it's limited in some ways, it's harder to pay what, you know, play the game on the field in terms of price. Like, people have a willingness to do deals that we're just not willing to do. But when we meet a team and we really think that there is just unlimited potential, you. You partner, you make it work.

[Dan Shipper]

Yeah. What's your taste in founders?

[Sarah Tavel]

I would say I'm really drawn to founders who, you know, they do think in network effects and strategy and the kind of 0 to 1. How do you escape competition? Like, they go through the mind maze. Like, you can just tell that, like, they've really obsessed over this. I'm drawn to founders that this is like a calling for them. Like, it is a. You know, I. I kind of find that there's, like, some founders that it's almost like kind of a cool new job for them. And there's some for whom it's an affliction. Yeah. And I. I'm attracted to the founders for whom it's an affliction. You know, it's like this rash that they just have to scratch, and that's gonna make them run through whatever walls that they have to do. And then, you know, just like the learning machine, like the person who, you know, it's not about their ego. It's about just like, what's the best thing for the company and how do I keep learning and evolving as a founder? Because, as you know, it's a really hard job. It's a really hard job, and it always requires more of you. Like, it's, It's. There's a relentlessness to it. And if I have seen a failure case where somebody either it ends up being. Do you know the five temptations of a CEO? That book, incredible book. The hardest temptation is a founder's attracted to being a CEO because of status, and then you don't do the things that you need to do in order to build the best company possible, or, you know, a founder that, you know, insecurity can drive you, but it can also hold you back by not letting you grow. And that. That can be a challenge too.

[Dan Shipper]

What are your tells? Because, you know, you're a partner at a top firm, people are, like, probably always coming to you with their best, best foot forward, trying to. Trying to be like what you're looking for. What are, what are some of the moments where you kind of can be like, ooh, this is, I can tell that this person has been through the maze and is thinking about stuff in this way, in a way that's like, it's Genu genuine, it's not put on. Or I can tell that it's sort of like a calling or what. Yeah. What are those little signals for you?

[Sarah Tavel]

Yeah, I just, I find that, you know, I, I, I ask a lot of questions when I'm meeting with a founder and learning about their business. And I know I'm always thinking about, like, I'm definitely the brain that is always thinking about that future and pulling it into the present. And when I speak to somebody and they're, I hate to say this, but they're like, oh, that's a good question. I hadn't thought about that. Or, you know, it's just, I'm bringing things that I, I'm spending 30 minutes, 60 minutes with a founder hearing the ideas for the first time, and I'm bringing things to the table that they have not already thought about. That's usually concerning.

[Dan Shipper]

That's right. And I mean, you're pretty smart, so

[Sarah Tavel]

it's one of those things can feel good. Like, oh, I asked them good questions, but really, you want, you know, I, when I was at Bessemer, Jeremy Levine, he said that the best companies you want to be donut companies, where you go to the board meeting, you eat a donut and then you leave because they don't really need you. And so there's a little bit of that, which is like, you know, I have some founders where I'll be thinking about something and I'll come to our one on one. And like, before I've even opened my mouth, they're already there asking, like, saying, you know, I've been thinking about this, or I reached out to this person and that's pretty unique. That's like a really incredible feeling when it happens.

[Dan Shipper]

Yeah, I was, I was talking to, I think it was Reid Hoffman who was on the show, who said, ideally it's someone where you, you invest in them with the, the, the bar is like, if you could come back in five years without having talked to them after the investment, like, and you would be pretty sure it would be going well. Yes, that's a good question to ask yourself, you know.

[Sarah Tavel]

Yeah, yeah, those are those, those types of companies. I mean, there's the founder, but then there's also, I know Reid and I know that he is very oriented towards network effects. And that is, I mean if you can find a business with a strong network effect like you're, you're going to be in pretty good shape.

[Dan Shipper]

Let's talk about network effects because I think that it's one of those things, it's maybe a little less so because of AI stuff but like for the last 10 years I would say like 80% of decks were like, that I saw were like. And we have a network effect. And there are very, I think there are probably very few businesses that truly have like that actual network effect. Pull. How do you differentiate what does that really look and feel like?

[Sarah Tavel]

Yeah, in the early stages it's, you know, there's a lot of companies that have potential network effects and you know, oftentimes there's a big gap between what's a theoretical, you know, and like where it really starts to happen. And one of the things that you know, I often think about is just like there are early, you know, we invest so early that a lot of it is leaning in on the theoretical. But like there are often signs that, that you can look to. The best thing that I, you can see sometimes see evidence of is just this idea of like a tipping point that starts to happen in a very small segment of the, like where the white hot center of your market is. You know, I, there's like two examples I think about but, but they're outside of AI, like outside of core AI right now because it isn't. I think what's happening right now with AI is that it's very much like a kind of, in a way what has been traditionally the software business, which is just obsessing over a customer problem more and moving faster in your execution than any of your competitors. But you know, I'm on the board of a company called Agentio, which is a marketplace for YouTube creators and brands. And you can see that this has been a market that has eluded startups for a long time because most of them have kind of fallen into the quicksand of becoming an agency. But with LLMs, Agentia is able to automate a lot of the things that have held this market back and they're truly having liquidity. And one of the early things that was super interesting is just like you see the, like the brands see creators and they see the, the ads that they do for agentio and like so agentio just has this demand side pull right now and it's super, super early. But there is enough signal there that like something's working that's Differentiated. And there's no substitute for what they're doing that. That you hope will start to really be a flywheel that can spin faster and faster.

[Dan Shipper]

So it seems like one of the best ways to differentiate between a real network effect and a fake one is like just early evidence.

[Sarah Tavel]

Yes.

[Dan Shipper]

Are there any things like when you see a deck from a founder that hasn't, you know, they're just starting out and you're like. And they say we're going to have a network effect. And you're like, it's not going to be a network effect.

[Sarah Tavel]

Yeah, yeah. I mean, it's. It's often like they, you know, they'll articulate some kind of flywheel, you know, or it'll look like the Amazon or the Uber flywheels. And then as you. And. And either like, it's just words on a slide that fit to a picture. But like the. You know what I mean? But like the words don't actually, they're not actually accelerants. Like, that's. I think that's one of the things like, okay, yes, that cl. That, that comp. Whatever you say is true, but it doesn't really actually accelerate the flywheel. And the second thing is that often there's either a lot of friction embedded in any one, any leg of that flywheel or there's like offshoots that happen. But I think the biggest thing is like, when you really look at what the articulation is of the flywheel, that it is, it's words but not accelerators.

[Dan Shipper]

Yeah. To bring it back to AI for a second. I feel like one thing that you're articulating is there was a moment in software for like 10 or 15 years where everyone was chasing network effects. And then the LLM wave happened. And a lot of that has been more single player or if it's collaborative, it's like inviting teams or whatever, but you're not doing it together. And the game, there has been better performance from more money and more compute and more data, basically. And everyone's just trying to keep up along that same sort of dimension of performance, more or less. There are a couple other examples that are not on that. And I think what you're maybe pointing to is that fairly soon, if not already, probably the models, the base models, are good enough for consumers that there's going to be another wave of more consumer focused, more product genius LED AI applications that differentiate or grow from network effects and multiplayer that were not possible in the last couple years, but are newly about to be a thing Those

[Sarah Tavel]

are my great hope. I could be tilting at windmills. You know, like consumer as you know, has been really, really hard over the last 10 years and so it really could be tilting at windmills. I believe that that is an opportunity and what I would also say is that there are going to be a lot of companies that emerge that aren't multiplayer, that are single player and those could be really good. But I think that the really big opportunity that lets a company have a true network effect is going to be something that's multiplayer.

[Dan Shipper]

If it didn't happen, why not?

[Sarah Tavel]

If it didn't happen, it would just be that the gravitational pull of the existing platforms is too strong. You and I like what would get us to go from the habit we already have of using ChatGPT and of course the ecosystem that's going to form around it over time, what they're able to charge for it versus what a new company would have to charge for it. Like maybe they eventually go free because it's an ad supported whatever it may be.

[Dan Shipper]

It's also memory is a big sort of lock in like it knows who I am and all my experience.

[Sarah Tavel]

Yeah. Cause you and I, like we already have, but we're not everybody. Right. But there is that gravity that has always been true for the incumbent products. And so it could be that that gravity is just too strong to get the people who are like, if you want this type of community to form, you're going to need somebody who is already actually a power user ChatGPT to want to share that on another platform. And that may be hard to create.

[Dan Shipper]

I know this is a show about AI, but are you looking at or excited about anything that's not AI right now?

[Sarah Tavel]

I'm a big believer in stablecoins. Interesting. I'm on the board.

[Dan Shipper]

I would not have guessed.

[Sarah Tavel]

Okay. I'm on the board of a company called Chainalysis and which is just, you know, so I've had a kind of seat in the crypto space and have been long term believer and Bitcoin and some of the other cryptocurrencies. But when I think about kind of the existing financial infrastructure and I mean, you know, we're, we're, we're filming this on a day when the, you know,

[Dan Shipper]

what existing financial infrastructure.

[Sarah Tavel]

Yes, exactly. The U.S. dollar is a little bit shaky across ground than normal. But you know, my mom's from Argentina and I can tell you everybody in Argentina wants a US dollar.

[Dan Shipper]

Yeah.

[Sarah Tavel]

You know, and, but it's really hard to get them. And the government has all types of incentives to keep, you know, the hard currency that they have of US dollars in their own bank, you know, because they have, you know, loans and everything else that they have to kind of stabilizes their own economy. But then it holds Argentina and all these countries back from participating in the global economy. Because the US dollar is what you need to trade goods internationally. Like it's just the easiest medium of exchange. But it's really hard to get US Dollars. Now if you have a cryptocurrency that is a US dollar, stablecoin backed by a US dollar that opens up kind of a global economy. And it also, it is just so much faster. It's 24,7 a lot cheaper. You can.

[Dan Shipper]

Why is it hard to get US Dollars in Argentina?

[Sarah Tavel]

Yeah, well, it's been Malay is obviously changing a lot of things. But there are different taxes around US Dollars. There has been for a long time. This is different. Now the exchange rate you get on the street, the exchange rate you get when you go to your bank, the exchange rate you get when you use your credit card, it's just like a very liquid market really. Like I remember going to Argentina and like having somebody on a motorcycle come to exchange money, you know, like that's, that's kind of what you would do. And then again the US government, I'm sorry, the Argentine government, they have US dollars in their own central bank. And if I want to transact in US dollars, I need to get some of that US dollar from them. But that is a very precious resource to them. And so there's a lot of process you have to go through and time in order to get US$10,000, it's not an easy thing to do. And so it's just there's a lot of friction. Whenever there's a lot of friction, if somebody else can come in with a new product that removes that friction and then also just has the facilitation like just how much easier it is for you and I to do a peer to peer transaction with Tether or USDC that creates a lot of liquidity in a market that I think can be a very interesting future. And also I should say it's like if you're in Argentina and you want to buy something from India, like you know the number all the middle men you have to go through in order to do that transaction versus and like all the fees along the way versus a peer to peer transaction on US dollar stablecoin is a different game.

[Dan Shipper]

And this is another network effect type business to you or no

[Sarah Tavel]

There, there is, there are network effects here because, you know, Tether as an example, which is like the dominant stablecoin right now, just has more liquidity on all the exchanges. And so it's a lot easier to go in and out of Tether than other stablecoins. But USDC is pretty strong too, so there's definitely some network effects there. It's just easier if everybody, it's not even just within the exchange, but just you like in these countries in Nigeria and any high inflationary country right now where people have wanted to go from their fiat currency into a US dollar, you, you have a wallet and it has tether and you have tether and it just becomes like more comfortable for us to all use it and then all the ecosystem around, like there's so many crypto wallets and different, you know, kind of new financial apps that are for getting your, your paycheck, but then also you can have your money in a US dollar stablecoin. And if you're already integrated with Tether or you're using Bridge to, to access tether, it just makes it a lot easier for people to get comfortable with one of them.

[Dan Shipper]

How do you think about, let's say five years from now, how AI will have changed your day to day as a VC and the kinds of businesses and the kinds of funding models, will it have changed in any way change the VC business model?

[Sarah Tavel]

I have been wondering about this lately. One thing I've just been thinking about, and this is a little bit of a step back, but there are some people that are really good at creating training data. Do you know what I mean? There's some people, someone was showing me, I interviewed him, James, for my substack and he showed me this spreadsheet he creates of all the movies he's ever watched and his own review of it. Right. And so I don't know about you, I've never done that. But the people who are really good at creating training data can then have a more personalized, more valuable experience with an LLM. And so to your question, one of the things that I've been thinking about is that there's a few things that we all have training data for. One is past decisions we've made and whether or not those are good decisions. I personally, Annie Duke inspired this. She wrote this book Thinking in Bets a Pre Mortem. So every time I meet with a company and I dig in on it a little bit, I write to myself what I liked, what I didn't like, what the deal would have been. And if I got yes, why, if I got no, if I got to know why. And so it follows that over time I'm going to be able to look back on that list and examine my decision making process. Right. And then as I dig in on future companies, like in my brain, I know that there's one example where I passed on a company because the valuation was too high. And that was a lesson to me. The company ended up being a real success, this company, Mercada. And so that ended up being a lesson to me, like if I like everything but the valuation, I should probably lean in. I remember that. But there's so many other examples in my thinking that if I can like examine my thinking as I meet a company and have it cross examine me, that I think I'll get to a better decision. Then there's also things like talent. Like what is one of the best things that we do on behalf of our companies? It's help them make sure that they have the best team around them. Right. And the same thing like we're all fallible in our evaluation processes. And what's a record of those decisions, interviews we did, like all those things, I've got to imagine that's going to come into play. And then the third is just

[Podcast Host/Announcer]

I

[Sarah Tavel]

know there's some companies that are doing this really well which is just tracking talent globally and the movements of talent and what that ends up meaning. And it follows that there should be at some point a score almost where you know, from the angel investors that have invested in a company, the talent that's there, their individual scores of their ability or signal when they choose a company that there will be like a rotten tomatoes almost score for companies that can surface opportunities.

[Dan Shipper]

That's interesting. I want to go back to the decision making thing because I'm with you. I record all this stuff, I record all my meetings. And there's just a lot of stuff I think that you can do with AI and improving your decision making. And I'm curious in VC in particular, like how that works or how you avoid, you know, for example, maybe you invest, I've done this. You invest in a founder with a re a highly technical background, but it's in a field that requires more of a product genius. And then, you know, now you have in your LLM, it's like, well, be aware that like, you know, and then you know, the next time you meet with a founder and it's like, you know, Sam Altman and Greg Brockman in 2016 or whatever, like that thing is going to ding and be like, technical founder. Like, are you sure this is what you want to do? Like, it depends on how the, how the rule or how the lesson is written.

[Sarah Tavel]

Yeah.

[Dan Shipper]

And, and I think the, the broader question or problem is if you look at venture capital, there are very few venture capital firms, funds and individuals who are successful over a long period of time. It's very hard. Which can tell you one of two things. Either it's just luck, which I don't think so, or the landscape changes so frequently that you get tuned, your taste gets tuned to a particular kind of opportunity that you're very good at finding, but then it sort of moves and changes. Changes in what is good is also changes. And all of that means it's like, quite hard to use past training data to make future decisions. How do you think about that?

[Sarah Tavel]

I think maybe that's what we're all hoping will give us job security in the future. You know, I remember when I was at Pinterest and I was responsible for all the discovery experiences, and very early on I had to kind of localize Pinterest. And so I had to figure out, like, okay, Pinterest is in the United States now. What's Pinterest in Brazil or Japan or all these countries. And I was like, thinking about the categories and all as being different. I remember Ben saying to me, he's like, just assume it's going to be more similar than different. And I think that there's some first principles that we reduce down to when you're making a decision, like Jim Collins, like, so much of what he wrote, like, I don't know how, how long ago is still valid today. Like, you know, Porsche by for, like, we talk about so many of these things and, and they're timeless. Like, valuations change will, how companies exit change. Yes. And that's why, like, you're not asking the LLM to give you the answer yes or no, you're asking it to probe your thinking. But I think it should be able to continue to do that. And that's why we still have hopefully a job a few years from now of ultimately being the decider.

[Dan Shipper]

Well, you'll have to come back on the show in five years and we'll see how things have changed. I think you'll still have a job.

[Sarah Tavel]

I hope so.

[Dan Shipper]

But I think it might be different, too.

[Sarah Tavel]

It's going to be very different. It's going to be very different. And it's hard to anticipate how it will be. Yeah.

[Dan Shipper]

Well, Sarah, thank you so much for coming this is a great conversation.

[Sarah Tavel]

Thanks for having me. Yeah, yeah. I had a lot of fun.

[Podcast Host/Announcer]

Oh, my gosh, folks, you absolutely, positively have to smash that, like, button and subscribe to AI and I. Why? Because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard, but instead of gold, it's filled with pure, unadulterated knowledge bombs. About ChatGPT. Every episode is a rollercoaster of emotions, insights, and laughter that will leave you on the edge of your seat craving for more. It's not just a show. It's a journey into the future with Dan Shipper as the captain of the spaceship. So do yourself a favor. Hit, like, smash, subscribe, and strap in for the ride of your life. And now, without any further ado, let me just say, Dan, I'm absolutely, hopelessly in love with you.