The New AI Agents That Shop, Plan, and Gossip

- We have so many different facets of our life, whether it's how we're managing our finances or planning trips. Agents are gonna be able to fill different facets to these. - From 147 different assistants that have come across my place so far, the number one fear that people talk about, 22% of the messages are talking about trust as the main year. - What are the aspects of ourselves that we don't either want to think about or reveal? Whoever is able to build that type of trust, almost like a dark agent. - We'll actually have something really fascinating on their hands. - It is a very, very sensitive space. It's almost gonna be like a new social network where businesses have to put a lot more thought and value into the quality of what they're getting out. - What I've seen from 30 years in consumer product is the paternalism will kill any product. We talk about productivity and goals sort of achievement, but maybe people want the exact opposite of it. - Everyone right now really is approaching this world as just like a general assistant. As time goes on, we'll start to see, a month ago, we took stock of the race to build a personal AI assistant. Since then, the agent landscape has already changed dramatically. In this episode, Anisha Charya is back with David Paulin, creator of Assistant Benchmark and Josh Elman, to look at what's changed and where agents are heading next. David has now tested more than 140 AI assistants and they get into what's separating them from memory and judgment to trust, shopping, and social experiences. They also explore what happens when our agents start talking to each other. And why the next breakthrough may not be an agent that makes us more productive, but one that feels like a secret superpower. - Welcome back to the A16Z show. I'm here with my partner, Josh and David, who's been leading a ton of the agent bench and assistant efforts. We're gonna talk about all things agents and a ton has happened since we last connected. What was it about to go? - About a month ago. - Oh my god, dude, I feel like we should record an episode like 2DPN style. - Almost every day. - Absolutely, in fact, agents are changing every day. - That's totally right. So okay, so maybe let's start with last night, you hosted an agent meetup. Kind of tell us about the event, tell us about the vibes, tell us about the topics. - It was great. So we had just over 100 people come out, all just proud agent nerds, loving everything to do with agents in that whole world. And as people just hanging out talking, we did have a pitch competition of sorts. So a bunch of the 10 different AI assistant builders were able to pitch their startup and what they're working on. And it was just good conversations. It's interesting how the general thing that really stuck out to me was that people are craving community, even in the agent web world. Everyone was like, "Why don't we have more of these meetups? "Why don't we have these opportunities to get to know each other?" Which is, it's kind of funny hearing it from people who are spending all their day, all their time just messaging agents. - And it's funny because it feels like, so many of these products are at least overlapping in a cursory way that founders might be a little bit more cagey, but that's not what you're saying, huh? - No, everyone is incredibly open minded, just very interested to be getting feedback. I think because we're so at the frontier of this, nobody really knows what the landscape is really going to shake out to be. And so we're all just kind of playing in the sandbox together. - Well, isn't it also that we have so much more time because we're just using our agents to do all these things? But we have more time to actually hang out together and be in person, so maybe that's part of it too. - That's right, that's right. - It is actually fun. I mean, it reminds me a little bit of the early days of social gaming or social networks broadly. I mean, do you think that's right, Josh? - I mean, I think what's really cool is this is not a zero sum game. I mean, at some point, it might be that there might be one or some agents that have the majority of the behavior, but right now, we're at such a beginning like Cambrian phase of, we're inventing so much. And we're trying to figure out so many things that everybody can learn from each other, can share these best practices, can figure out what things people are enjoying, what things are, work ones, but don't actually work reliably. And these are going to be built in so many directions. I mean, we're not just going to all have one agent that does one thing in our lives and I'll use it. And you guys will only all have to use the same agent. We're going to have so many different products that do so many things for us that I'm excited for why we're all inventing it together. - So I totally agree that we're going to have a whole world of agents as many different types of humans as we might have or archetypes of humans. I think we'll have a similar number of agents. But maybe talk about what you think are the different axes for differentiation. Like there's a sort of spectrum between really serious and productive to really playful and maybe even sort of adversarial. And I'm sure there are many other ways to think about these things. - Yeah, I mean, I think what's going to be really interesting is we have so many different facets of our life, whether it's how we're managing our finances or planning trips or dealing with our health. They're just getting through our day or managing our calendar or sometimes just wanting to think something out loud. And agents are going to be able to fill different facets of these. And you call different friends for different things. You spend different friends who have different expertise that you call when you need expertise. And I think we're going to get used to having kind of an army of agents that will do this. And some will be very matter of fact. And we'll be like, "Hey, I need to get this thing done. "It'll be your productivity agent." Some will be plugged into your email and it'll be like, "Here's the five emails "you need to get done right now." And some are going to be sort of these agents. You'll kind of want to talk to all day. That'll be fun. That might even be a little bit gossipy. I've been playing with a few agents that are very kind of playful and gossipy and they're connected to a few of my friends too. And they'll share information back and forth. One just told me that my friend's power had been out all weekend because he'd been doing some renovation and they'd cut the power. And I called him that evening and I was like, "Dude, you didn't tell me your power is out." The agent told me. He was like, "Yeah, yeah, I knew that's how you'd find out." And I was like, "That's creating these better connections." But that has nothing to do with booking a trip or saving money or getting anything done. - Right. I think from 147 different assistants that have come across my plate so far, I've seen them really broken down into four categories. You have the general, you have the work oriented, you have the multiplayer and then you have the travel. And the one that I have not really seen come to fruition yet is more of like the finance side of things. - Yeah. - And I think it actually does make sense when you start digging into the numbers. So of all the different group chats that I'm running of AI power users, there's about 3,600 give or take messages. So far, and when looking at the pain points of what are the fears of the space, the number one fear that people talk about, 22% of the messages are talking about trust as the main year. And so it's really interesting to see because you have one camp that's this productivity and aspects of fun that's just interesting and brings a different sense to life. But then you have another camp that really still is sitting in this kind of fear space of being a little trapped and not really knowing where the space is moving. And I'm really curious to see how things are gonna play out on that trust layer. And if we can solve that trust layer, then what do we end up seeing on more with the finance side of stuff? - And if you looked at what Shane Mac has been talking about recently about trust, he's been talking about this concept of something called picnic. And the other analogy that I really liked, which is, if you have a kid and you don't have any fences on your yards and you let them go right outside, you're actually very worried about them and you try to protect them and you don't want them to run very far from the house. And you actually don't really want to do them without watching. And then the moment you actually put up a little fence in your yard, you say you can just go roam free within the fence boundaries and be very, very safe. And so he's really kind of like, how do we build the right fences? We let our agent play in this fence, give it access to some of our data, some of our apps, some of our other things and be able to actually do everything it can within that fence boundaries. He had a problem where I think a personal agent spanned over into work and he actually like blasted his finances on this company slack. And I think that's the whole point of like, wait, okay, that I personally agent should have access to my personal things and my personal communication channels but not my work ones and not let those bleed. And so that idea of fences and permissions and more controlled permissions and better monitoring is really how we're gonna have to build a lot more trust totally. - It's interesting though because I think we have this traditional mental model of what it means to have a sandbox which is you have a hard set of constraints and rules that must be followed or not followed. And somebody was describing this framing of instead of giving models rules, we should give them laws and principles. And I think a similar thing may apply here, which is like, look, here's how to dial in your presumptuousness and it's very qualitative and the model will have to make a judgment call based on your qualitative sort of advice to it just as an employee would have to. - Yeah, I mean, I think that's part of why the analogy is you know, a fence for children 'cause in some ways these agents, they're incredibly capable. But at the same time, they're kind of children sometimes and how they may behave and not know all the nuances of like, hey, is this a good idea or not? And they don't always have that logic and the most important thing, I think we keep talking about agents being autonomous. Book me the trip, make me the reservation. And I think as humans, we actually don't want to give away that sense of control. I think we actually want it to check in with us but do all the groundwork, save me all the time and coming up with the best options and the right trade-offs and now let me make the final decision and also let me make sure I've qualified the final decision, the cost, anything else before my agent acts is I think a place and maybe over time we'll even learn to trust it. - Right. - But I think right now we don't need to just still have a really, really effective agent. - Right, I mean, it's we're at like the 1990s of e-commerce where I think the last data was in 1997 or so it was 60 to 90% of individuals on the internet thought that putting your credit card online was a preposterous idea. And here we are today, it's just everyone's talking their credit card wherever you want. And I think we'll eventually hit that in this era as well but it's gonna take a little bit of time. - I think there's like a stated versus revealed preferences thing here 'cause I think in revealed preferences consumers will share any amount of data for even the most trivial amount of upside. - Right. - You know, like people have been connecting their cards, their credit cards and the bank accounts via plaid since the Venmo era. So I don't know that people, but when you ask them, they're like, oh yes, I'm very concerned about trust and safety. I think an example though of where consumers very important. concerned about sort of trust and assumptions is around being embarrassed and social signaling. And actually, the most interesting thing about the Shane McStroding was horrifying visceral thing is that it embarrassed him. That's right. It really embarrassed him. And that's why I think some of the kind of agent to agent network thing because you can imagine somebody you're just getting to know, maybe you're going on a second or a third date and your agents are talking, you're like, whoa, what are they saying about me? How are they kind of positioning what it's? You know what I mean? Like there's just the social mechanics actually feel so much higher stakes than the actual like real world implications. And it's a good point. And there is a recent proof point of it in Hark had a huge marketing campaign. They offered a million dollars to anyone that wanted to use their product to get free pizza, right? Each person get $30 a pizza. In order to get that $30 pizza, you were granting access to your entire Google workspace, all of your emails, all of your data for 30 bucks. And it just proves it, you know, right there that people are willing to just give up all that data for some free pizza. Yeah, I mean, I tend to think though there's always this tradeoff of privacy versus utility, which is if you can give me better utility, then I'm willing to make some privacy tradeoffs. But at the point at which we're basically equal on utility, people always choose a more private option. Maybe there's a world that Apple's lived in very much. Privacy is obviously a forefront of Apple's devices of the work they do to make these devices and the software secure. Even on AI, they've talked about private cloud compute. You know, we used to talk about that a lot. It's like the center of why your data doesn't actually go anywhere and get shared with anything. But I think we've also seen that people want the most powerful AI and they won't always choose that. Right. So we have to find that intersection of trust. I think the comparison point is really, really important to because I think you want your agent to understand you and have all your personal preferences and it like, let's just say you're like lactose intolerant and then you get this order of free pizza and you're like, you're doing you with a friend and like, what do you do there? Do you have like, whose agent tells them that you can't eat the cheese and it creates that really awkward situation. And so we need to figure out how they have the same kind of discretion that you'd expect. And we all learn discretion over time and we all occasionally make mistakes ourselves. We have to hold a pretty high bar for our agent to be able to do that. And it also then comes down to like personal embarrassment and professional embarrassment. I think something that town has done remarkably well is really nailing the tone and building that trust layer of being able to send out emails on your behalf. And it is a very, very sensitive space. I mean, the level of embarrassment, if I were to send out an email to someone who I care about and it's just a horrendous email and after respond, oh, sorry, that was my AI that I didn't do enough oversight on. It's a, it's a tricky space. It's interesting. I sign all the email that I write with AI with the model that I use. I write my own name plus the model number. So that I'm just signaling to the person like, hey, I'm acknowledging that I use AI for this. I think actually people are pretty flexible as long as they don't feel hoodwinked. You know, it's interesting is we're talking about privacy, but there's privacy and there's judgment, which is different. And discretion is maybe somewhere in between. You know, you did this sort of test where you asked a whole bunch of agents to order flowers. Talk a little bit about which displayed the best judgment and how did you even define judgment in that case? So the main intention of that test was to see how do agents balance two different strengths. One was cost and the second was time preference. So I wanted flowers to be delivered to me today and I wanted them to be as cheap as possible. So how is it going to actually go and discover based on the ability to actually deliver it then also compound in the actual pricing? Instinct really did a phenomenal job. And it is something, it's interesting how news cycles come and go and it seems like they're kind of not in the conversation as much as they use. I mean, we're talking the weekly changes. Right. But it is true. But they instinct really did continuously bring back the best price. There's another app called Kicker which did a phenomenal job and one way that I think it was able to have an edge is that it has you install a chrome browser. And so it's browser use has a little bit of an advantage from that point and it was able to define some really really great options. Season also did a really good job. All the other ones kind of struggled on the price component. So they're all able to find flowers that could be delivered that day. But they really seem to take a step back in prioritizing the price. Whereas you know, the other three were able to really put equal weight to those two. And so it's interesting to see as you start giving these agents more complex preferences, where do they really start to fall? Do they only prioritize the first thing you say? Are they able to hold multiple? I ran another test that was I had three different agents test in booking travel to LA. So I said, okay, book me a flight to LA plan and tire weekend for me. And I want a luxurious cost-efficient weekend. And so I tried to like, you know, put those at odds with one another. And it was quite interesting to see how Grocbot compared to dots compared to instinct. They all approached their interpretation of cost-efficient and luxury in different ways. Where you know, one maybe thinks that cost-efficiency is the most important. And I'm going to take a red eye flight to ensure that I can, you know, have the most cost-efficient path. Whereas others found cost-efficiency or sorry, so luxury as time. You know, I'm going to prioritize time as much as possible. So having the most amount of time there that weekend is going to be a luxurious experience. And which were which? So instinct was pretty much right down the middle. Okay. Grocbot did a little bit more on prioritizing time and dots was a little bit more on prioritizing costs. And did they just get to work or did any of them actually work with you to understand this tension that you were building? Because I think what's really human about something like that is actually understanding what you mean by that and presenting you trade-offs. Because there are times where I'll totally take the red eye to save both some time and money. But then I want like the hotel room on the other side so I can get a little nap in the morning, which then undercuts the money, but still maximizes my time spent. And so I really think it's just like getting to know the individual person and break down those tensions and present the trade-offs and different options is really important. Did any of them kind of get to what you were about? So they all did ask questions. And I responded those questions honestly. I tried to be a little ambiguous and invading my response. I didn't want to lead them too much. But the most interesting part of this little experiment was I put them all in a chat room. And I made it three rounds of building the itinerary. And after each round, the agents would present their itinerary and their explanation as to why they believe that was the best proposal. Because I wanted to see did the agents actually get biased by the other agents and didn't actually have that influence their plan. And Grockba was actually the only one that, you know, very methodically took value from the other ones and implemented it into its own plan. Okay. And I have one more question on the flowers. Yeah. Because so you were just ordering flower for yourself, I guess, just to like test their flower friendship. Okay, very good. You got a nice delivery of flowers. Okay. So this is actually really important because if you're delivering to somebody else, you were talking about saving money, saving money, saving money. But like, you don't want your girlfriend to think you just got the cheapest flowers possible. I hope, well, maybe, you know, she likes your, you know, penny saving nature. But otherwise, like I would think you also want to like impress her and also be able to get her the ones if she's really into orchids, get her orchids. So did it do anything to try to make sure also that it wasn't just this pure price saving, but also something that's going to actually make you, you know, earn the excitement, stand out a little bit for it. So for this experiment, no. And the purpose of this was I want to test two different dimensions. And if I'm going to run this test, I might as well have a beautiful consequence of my girlfriend getting flowers. Fair enough. As the outcome. But it's a great point, right? Like in the real world, if you're going to ask that question, there's going to be added dimensions that are, you know, second layer dimensions to cost efficiency or to delivery time. And make sure the price doesn't show up when she actually gets the flowers or like a note as an example, some of them did ask, do you want me to write it? Leave a note with the flowers when they arrive. Yeah. It's interesting because there's this sort of thing that has to happen when you talk to the agent about these things, which is your implicit preferences have to be made explicit. Yeah. You know, and there are people who like to think like, oh, I'm not cheap. I just like to save money. Right. But you're not going to have to kind of maybe like get over that and tell the agent, I'm actually pretty cheap. Right. And I just need you to actually run with that. Whereas when you're actually taking these actions on your own behalf, you can build those preference in without having to like sort of look in the preference mirror. Yeah. So there's also something very fascinating about how does the agent interact with you in a way that sort of maintains your sense of identity and safety and doesn't cross any of these boundaries. Totally. And I think something that is really interesting with that specifically as dots because it has so much of this contact that you've already built with chat GPT. Interesting. When we filmed the first podcast, it hadn't come out yet. And then I think a few days later, it came out. That's right. By and large, most people I talk to still are not using as their preference of the, I did a survey of, you know, AI power users, 354 people, only 3% were actually using it as their primary agent. However, it does have this kind of added value of the main thing that people pointed to as to why they really preferred them, why they liked it and why they wanted to try it was because it has all this building context of you just from your chat threads. People are using chat GPT as a therapist. And so it has so much context on you. Interesting. Where it's going to know that when you say, well, I'm not cheap, it knows it's like, you're a little cheap. A little bit. A little bit. I'm curious why people think that chat GPT has this great set of preferences from them. Did you actually get any sense if they said they really liked dots, like what they had been giving their chat GPT over the years? And do you think they think that's replicable? Or do you think it's like, hey, once it's already been a few years, we're now in this point where like, my memory is there, why would I switch? It's totally replicable. It's just the matter of fact that they've been using it the longest. and so it has the most context on them. But then that brings up another good point of the friction to switch. And I ran the tester out across the top 15 agents on the benchmark of which ones can you actually pull context from and say, OK, I want to switch to another one, give me an empty of all of my memory that you have. So I can switch easily. All but one, we're actually willing to do it. And so you could just get a memory file, everything you need, submit it to the next one. And was it good or was it uncanny? It was pretty solid. I mean, obviously, I'm sure they're caging some of the fruits of your labor. But by and large, it did really break everything down. I'm not sure if you've ever looked at any of those markdown files, but it's a little-- I terrifying is a wrong word, but it's like, wow, you really got your finger on me. Yeah, it's kind of like chaf against me. I don't want you to know me as well as you seem to think you know me. Yeah, after the first few, I decided to stop reading them. Yes, yes, yes, yes. It's actually a really interesting and now common onboarding pattern, where we'll say, hey, go and paste this prompt into chat GPT, download the file, upload it to me. We'll see how long that lasts. Totally. Another cool onboarding thing I've seen is you jump on-- it asks you to jump on a call. And it's like, hey, let's just talk to me for a few minutes. Yeah, yeah. Ask some questions. And it's really interesting to see what context it can pull from those questions. And they're very disarming. They just get you talking. It's kind of crazy. Totally. But I think it brings up another variable context, which is photos. This new paradigm of using photos to pull an incredible amount of context on you in ways that you wouldn't even think to describe. Yeah, I think you tried dazzle. Is dazzle gotten into your benchmark set yet? That's from Merissa Mayer's new company. And I think the idea of looking over your entire life that you've captured that have been moments that are important enough to you to actually save or screenshots or other things tells so much about somebody. An incredible amount. It hasn't been added to the benchmark yet. It's quickly on the top of the list to test through. I'm still manually testing all these. So I actually get the personal experience and understand what the feeling is with each one. But what I really like about how she's approached it is they put a lot of emphasis on this trust layer. And because I think it's a huge variable is giving you all my photos. That's pretty terrifying. But they have this one thesis that if you don't need it, they're going to forget about it. And so if a photo seems as though it has context that it doesn't necessarily need or things that you probably wouldn't want it to know, they're going to try to get ahead of that and just forget it and not even include it in the set. So it's going to be interesting to see how these different players do approach the photo context and how that actually does then influence the behavior of the agent and how well it knows you. It'll be interesting to see. I'm a tiny bit more skeptical. I built an app because I've always been fascinated by screenshots because screenshots are sort of the only way on the mobile phone to be able to capture context across every app. So it's actually a really interesting kind of data asset. And you go back and look at your screenshots and it gives you a little view and you're working your world at the time and also your interests and preferences. So I built an app that just extracts key information from all the screenshots on my phone. And it was fine, but I didn't find myself coming back to it. Like the value of the information sort of decayed quickly over time. Now it will be really fascinating if people start to then take more screenshots. That's what I was going to say, right? Knowing that it will feed the model on the agent. I mean, I think that's actually the idea is that if you actually get used to capturing information you want to retain and being able to then poop it back in your life, that's great. I talked to a one founder who's building something he's calling it taste for now that actually takes all the screenshots and things you save. You can actually then organize them like on Pinterest mood boards. And then whenever you go to actually go code and build an app, you're like, hey, use the examples that I saved here. So it's actually you're building your real fun of flavor profile. So it actually is actually able to use your styles. And so as you navigate the world, the web, apps on your phone, you can actually create this kind of really cool, you know, reservoir of stuff that you like and actually organize it in a way that you can then use it later. And so that will actually make you create a lot more content in that loop. - Right. And so I'm curious with the app that you built in this context for it. So of in the same survey of what people are purchasing the second most popular category was Amazon retail, 35% saying that they're doing some form of shopping. And so this context that you're gathering-- - Sorry, Amazon shopping or just some form of shopping. - Amazon plus retail. - Let's see. - Yeah, I've got it. - So for your app and the context it's building, where my mind goes is, okay, if it has thousands of photos, and it has pictures of what I'm wearing, does it now know what I want to shop for better than I actually do? - It's actually, yeah, potentially. I think that's actually really interesting when you can do some stuff there. And I also think that there's a, you know, we've discussed the ones who are restricting access, like Amazon, Delta, you know, we're not at all talking about who are the net winners. And actually I think the long tail are going to be huge structural winners in this, because they're ones who presumably have better products but worse marketing. - Yeah. - They certainly have worse marketing. I'm not sure if they have better products. And the agent, you know, has the sort of infinite patience to go search for things and find things that are exactly tailored to your taste, even if they're not on the top 10 internet sites. - Right. - I mean, I think it's really direct shopping, right? We've all talked to a direct consumer. It's been a category where you build your own brand, you build your own storefront, you sell things. Now the agents can know about those at a much bigger scale than you ever knew the hunt and peck work to find it on your own. It's kind of why Shopify is really empowered and is making things available to these agents because they are the ones that support so many of these direct brands. And I think about the idea that like maybe aggregators are the ones that actually get compressed, which is why they're doing so much defensive work here. Because, you know, if I can figure out, you know, that sweater looks great or I want that shirt and they can figure out who the actual maker is and I can go buy it direct from them, they no longer have to pay all those transaction in, you know, you're going to sell to retail costs in the middle. Well, if you want this shirt, your agent can buy it for you too. That's great. But it goes to Patrick Collison's tweet, right, of talking about this future where consumers become a lot more rational because our agents are doing all the work on our behalf. It's really going to create a world where businesses have to put a lot more thought and value into the quality of what they're giving out. And it's going to be really interesting to see that. So somewhat, I'm an acquibble with this point. I love Patrick's vision. And I think that broadly that will be true that agents will make often better choices on our behalf than we might make for ourselves. But I do think that agents are going to have their own revealed preferences and their own sort of directions of irrationality that will not be of a human mind. It will be of an alien mind. And I'll give you an example. I think agents may have an irrational preference for clean APIs with great docs. - Okay. - You know, and they may actually have a lot of value to that. It's a proxy for something and they may really dislike janky APIs with Java code behind it. Like I don't know. So I do think it's really interesting to see 'cause they too are going to need shortcuts. How will the agents actually know what product quality is? So one part of it is they'll probably have these revealed preferences. And then another is we'll need some sort of a consumer research but for agents that will then presumably be paid per transaction to do the research. - To know their ratings. I don't know. I'm also more biased than I just think people are people and people are gonna make the choices that they wanna make that are most satisfactory. So the question then is the agent is gonna be very careful in curating the set of options that it presents. 'Cause again, like all of a sudden, you're like, "Hey, I'm really hungry. I wanna eat." And my agent knows I need to like lose some weight or something. Like it's like, "Well, here's the four meal options that you have. Like, is that actually where you wanna be with your agent?" So I'm actually not as convinced that agents are gonna make us more rational. I think they're just gonna give us better faster access to things we really want. And actually be able to like unlock things that were hard to get to otherwise. But I think we're still gonna be people with our own preferences and tastes. And if the agent's not meeting us where we are, we'll just switch another agent. We'll import our stuff and be like, "Oh, this other agent's gonna meet me on my preferences better." - Right. It's really interesting is what I think we are speaking to is like paternalism, right? And what I've seen from 30 years in consumer product is like paternalism will kill any product even a hint or a whiff of paternalism will. And in a sense, we talk about productivity and goals sort of achievement. But maybe people want the exact opposite of it, which is like, hey, what do I love? I love spending money. I love being perhaps irrationally optimistic about what my future looks like. I love, you know, like see myself in a better light than perhaps I appear to the world. Like there are all of these things which we may say are the sort of shadow of the, you know, the things that the agents are trying to get us to do that are what we actually want to do. So who's like designing with that in mind? - Right. I'm curious what you're seeing on that. - Yeah, so I mean, I think you have, I kinda see it split up into two categories. You have the commodities where I think there's going to be a lot of the point where people actually don't care about preference, right? You're just ordering paper towels to your home. You're like, I don't really care. Just get me the cheapest, the highest quality one. Go for it. But then you do have the ones where you want to actually have some preference. And you have, everyone right now really is approaching this world as just like a general assistant. And people are really taking a quite similar approach into how they're thinking about this space. We're seeing some cool stuff with multiplayer. I think Robbie is going to be really interesting because it does create a lot more, it creates a different world where you can now be interacting with other humans and have crossover and preference and see how it behaves. And it becomes a little bit more like entertainment. Scout is an interesting shopping one which adds a unique kind of like swipe type flavor to learn your preferences and adds a little bit more entertainment there. So think we're still so early in the space that I think people are jumping on the bandwagon of what's popular at the moment, which is just your general productivity. The thing as time goes on, we'll start to see a little bit more experimentation and some other avenues. Well, and I think you mentioned Wabi. One of the things I really like about Wabi, and it just, I think launched just this week, great yesterday, is it's not even just experimenting with an agent, but it's just experimenting. like how to interact with multiple threads of your life. Like, Wabi goes through my email and other things and actually gives me a whole bunch of different threads of life and actually when things come up on email on those things that actually feeds them into the different threads, I have one thread with Wabi that I built a little watch list of all the shows that I want to watch and books I want to read and shows I want to go see. And it keeps track of all that. And then I can like, oh, I heard about this new book from John Grisham, like add that to my list. And hey, I've just finished the first dungeon crawler carl. Can you give me the next one and like, you know, what do people say about it? And it's become this really interactive thing on like the media that I want to consume but it gives me all these different threads and it even gives you UI's who actually like these widgets to like envision everything. So I think again, it's showing us like a very different experience just a general agent that is more like a search box and is more like task, task, task. - Right, I think one of the interesting things that Wabi does is and perhaps gets right is that when you create the message channel with your friends in the agent and everybody's on an equal playing field on D0, it actually creates a new kind of blank piece of paper where you can establish your social contracts together. Whereas when you have I message group threads and you add the agent, there's some certainly if it's an existing thread, then it's very uncomfortable 'cause it's like, well, what can the agency? What do they extract? But even for a new thread, there's a set of implicit expectations about how you interact with people on I message. And I don't know that we're quite comfortable with agents in that space yet. - I mean, I always think then do I end up with two threads with the same group of people and I have to pick which one to use. Like I'm finding that much harder versus an email chain. You know, it's very much specific about like a task and it can even go on for a long time. But that feels much more specific to, hey, we're talking about this topic, everything's contained back to privacy and trust around this topic. We're getting great help from the agent, you know, in the case of like a Wabi thread around this topic, but it's not bleeding into everything else we might also discuss. - Totally. I wanna quickly hear from both of you on what are some of the more, I don't know far-flung or, you know, sort of insightful approaches that you've seen. - You know, one of the things I've started seeing is more of these agents that are kind of like fun and gossipy and will actually get you to invite your friends and will ask you a bunch of questions and be really, really curious about you and what's going on in your life. And then they'll share some of that with your friends and then they'll share some things back with your friends. And I was talking to the founders and they actually can read some of the transcripts between the agents that they're talking about. And they haven't figured out how to productize that, but they said it's incredibly exciting and very intriguing to see how these agents kind of relate to each other and the sort of gossipy background. And so far I've found them just to be like, probably some of the most joyful moments I've had with agents. Again, I mentioned the beginning, how my friend had like lost his power over the weekend, but when we were first both onboarding onto this agent, I was like, how'd you guys meet? And we told slightly different stories. And the agents were kind of like poking us both to like rationalize the two stories of how we met and we met at a friend's house and they were like, which one of you knew them better? And it was like this really kind of fun curiosity game that made it just like, whoa, I'm like having a good experience and my friend now we're texting on the side too. And it was just a thing that if we hadn't had an agent doing it, we wouldn't have had that same moment, right? What I love about that is it provides a degree of social indirection that actually makes you closer, you know, because we were friends, they're like, I don't know how to text Josh and tell my powers out. It's over sharing, you know? And I think we also have been very trained to be cautious about sharing now with existing social products. So something that can create almost a social lubricant in a very sort of low key way is really cool. - No, that's great. It definitely was bringing us together. - Yeah. - It's almost like the early days of chat GPT where I remember like my friends and we go on and we would just be generating images or doing stuff. And it's, you know, incredibly, AI slop images, the earliest version of them. But you still send in a group chat and it's just, it's just laughter. It's just pure laughter of the ability to create a whole new world and it's just fun. I mean, I give-lified everybody I could possibly imagine. - I was doing a lot of them, the H.S. video covers. - Oh, yeah. - My friend groups. - I love that. - What are some of the wild things that you've seen? I mean, you've seen them all. - So, I've been seeing a lot of stuff working at the infrastructure layer. And I think the interesting point is so, if you look at the pain points of consumers again, it's not all individuals using them, but at least of the power users I've surveyed. Trust obviously, it's a huge one. But another one is just getting blocked and they're day-to-day and people get really frustrated when you try to perform a task and it doesn't work. And they're like, well, why am I even using AI at this point? I could have just gone on the browser and done it myself. So, seeing some really cool innovation on that layer of commerce of the browser use of direct integrations to check out against inventory itself, some whether it's browsers that are built in and really, like, Hark does a really cool way of displaying the browser and seeing it move along. And it looks to be really fast when you're watching it. Who knows if it's actually that fast behind the scenes, but really cool, that way, again, kicker, as I mentioned, Chrome extension to tackle the browser use in that way. So, I've seen that as a really interesting kind of differentiator. I think that something that has stood out to me that isn't necessarily something that's different, but has made me kind of question this whole concept that software is becoming a commodity, is that there is pretty stark performance difference when you're looking at these products at scale. And I think people are talking about, you know, software is no longer a moat and all of that kind of conversation, but there really still is some moat there. Maybe that moat will be able to be crossed in a year or so, but at least for today, the agents that are able to perform with hundreds of thousands of users, there are some that are starting to scale up and the performance just degrades immediately. And the founders are dealing with outages and figuring out how to scale and there's a pretty clear difference in performance there. And so, it's really interesting to see as I'm kind of working through these. I feel like I've almost become, you know, blinded from some of the more social components to it 'cause I'm just talking to these agents all day and I'm starting to geek out a lot more on the actual infrastructure layer behind the scenes and like, how is it actually working and what are the tweets that different ones are making? So, it'll be interesting to see like, you know, how do we view this space growing from a scalability point of view? - Yeah. - But then how do we also view it to solve the pain points that currently exist, whether it's trust, whether it's actually being able to complete a task, memory is another one. It's a ability to actually continuously have context on you and not forget the little things and. - And, you know, you mentioned Kicker, which, you know, you said runs in your current local browser. But if you looked at other on-device assistants yet, whether that seems like underdog or a lot that are trying to like bring models, run locally, you know, totally use your own infrastructure as opposed to needing to use something on a cloud and running the browsers on clouds. - Totally, so it's a really cool paradigm. I've spent most of my time in the pre-configure, just plug-and-play type world. Because I tend to find that it's easier to compare them with the board when you're not responsible for the setup itself. But it is really interesting. And I think that there's totally a world where you're gonna start bringing all of that in-house. Because if you can control the model, if you can, you know, tailor it to how you want, like thinking machines is doing some really cool work of being able to allow people to really tinker their models however they want. And if we can eventually hit a world where that takes into the consumer form in a really easy way, it's gonna be an interesting space. - I mean, that was kind of how this all started with, you know, this brilliance of open-claw that was this thing where you had to, you felt like you had to get your home-back mini to set this all up, plug-and-to-one of the models that you were using, whether local or a cloud model on the server. And that was where you got started. And we've moved into like plug-and-play products where you just download an app. But I am interested to think if that like sheer power of you setting it up and owning it yourself will become a paradigm again. - Yeah. - It'll be really interesting. I'm glad you mentioned open-clox. It feels like one of the unasked questions right now that's sort of hiding in plain sight is if instinct and news were the kind of consumer product version of open-claw, what is the, you know, mass market version of mulpook? - Yeah. - And mulpook was just like open-claw was far ahead of its time. And I think we'll, something like that will exist, how can it not? - It's gonna be interesting. So at the event that we did last night, everyone who was there was able to scan a QR code and there was the human meetup. And then we also had an agent meetup. - Oh wow. - And so while all the humans were hanging out, you could scan in and send your agent into the agent meetup and just let them kind of freeform talk. And it's interesting. There's, you know, got to the point where after like 150 messages, some of these agents are just speaking gibberish. And it's like, I have no idea how you got that concept and why you're talking about that. The initial prompts did start off with the little guidance of introduce yourself, who's your human? What are they working on? What type of help do they need? But it is gonna be really interesting to see this paradigm of what happens when our agents can just hang out and communicate with one another. - Well, and again, what I get really excited about is not just hang out and communicate with each other, but discover new things, learn about things from each other, learn about an individual's preferences, you know, learn about a way that like, hey, Josh is really into this. Oh my gosh, you're doing that too. You're, you know, your human is doing that too. You could help Josh, hey, Josh, do you wanna actually meet this person? They could be very complimentary to you. Like, I think when we have these agents that are not just hanging out, 'cause they don't know what to do, which was kind of what was initially happening as you got went and read those like very long notebook threads that were incredibly fascinating. But like, when it becomes, each one of these has a little bit of a goal, which is to help their human. It might get so much more interesting. And, you know, I'm looking for a great wine for a dinner party, you know, some night. And you meet somebody else who's like, you know what, I've been working with this incredible, you know, winery and they've been trying to advertise something. I mean, that's gonna be how the world gets out and that'll come back to me through the agent network. Totally. And that's, Tomo actually has a feature. It's called interest groups. And the use case they use that they talked about with really cool is we have a bunch of people on our application who are studying for the LSAT. Let me help put them together in a group chat. And if they want, their agents can connect them and they can all study together. And it's a really cool kind of new social contract of connect to people purely by interest. You know, I do who they are. - Well, I'll take it one step further. So it gets us all chatting and that's really cool. It's an awesome Tomo feature. I've tried it and haven't totally known what to say in the groups yet, but I find it really fast name that's putting us together around goals. Imagine now that it's like, hey, all of you, now that you've done the LSAT, go hang out at this bar Friday night and it like books through time at the bar, opens that up. And all of a sudden, it takes us from this digital world where agents are actually putting people together to do that connection, kind of like your meetup last night. - Right, right. - I love this so much. So I think a really important under-discussed topic in AI right now is just entropy. - Yeah. - How do you create things that you didn't expect to have a curve and serendipity is a form of entropy, right? That's sort of what you're just doing where it's like, wow, isn't it wild that we're here right now having this moment as a result of these products that none of us sort of intended to happen? - It's almost gonna be like a new social network home. Like the potential to allow people to hang out who don't know each other instead of a Facebook where you're only connecting with people that you know, you're new to a city, you're hanging out. Oh, hey, this person's also here and they have this similar interest and they just went to this baseball game. You guys should go meet up at a bar. - I'll be curious to see what is the catalyst for the serendipity though, 'cause I think the interest-based thing has been tried. And there's a little bit of an interesting social hierarchy thing, which is everybody wants to hang out with somebody who feels like they're one step ahead in some direction. - I don't know though. I think the agents can also create a set of trust. Again, it all comes back to, do we trust them to have our interests at heart, to explain enough of what's going on with the other people, to create a little magic of a secret. Like I'm gonna tell you a little secret, they're gonna know a little secret. You're gonna have a secret phrase you have to pass between you. - Right. - All of a sudden that might be enough to cause you to otherwise, you know, turn off the TV or turn off the quiet Friday night coding at home and go out and so that's the, like this is sort of what the notebook, the agent network running behind the scenes can actually do for us. - And it'll also be in my opinion, it'll come down to desires, right? If you have a bunch of transplants in a new city and they don't have enough, they want to meet people, they're gonna be a lot more interested to just go meet random people 'cause they want new friends. But if you make that same offer to someone who has an established friend group, they're like, well, how do I go do that? - Also Seattle versus Francisco. (laughing) You gotta know what city you're operating again. - Exactly. I've been thinking a lot back to this photo role about what are the other data sources that we haven't tapped into yet. So, you know, we've talked a lot about messages and people are doing those crazy things to get access to your entire Mac full disk access just to read your messages. You know, we've obviously got email, we've got calendar, we've now started talking about the photo role. What are some of those other core life, you know, things that people haven't connected yet to agents that would actually really open up personalization or open up new connectivity? - So it's something that comes to mind, I don't know how much data this would actually provide. Maybe it's more of a habitual thing. And again, it's dependent on the hardware and how smart that hardware is and how much data it's able to store. Wageo just released the MCP, the ability to connect to hardware. And I find that, you know, that I think it's gonna be really interesting where, okay, if you can connect your assistant to your AC unit or you can connect it to your vacuum, and now your assistant has contacts on how frequently is your vacuum cleaning? More, how frequent, you know, what's the typical temperature you sleep at night? It's gonna start to develop these, you know, very passive understandings of, oh, you're kind of a neat freak or you really prefer cold weather over warm weather. And that's gonna then influence its understanding of your context of shopping. So I think there could be some interesting stuff there. Again, it's heavily dependent on the hardware itself and I think we're still at the earliest of innings in that world. - So connecting to your homes, super interesting. You know, I still think a lot about connecting and again, Amazon may be blocking this, but I think connecting to my Amazon history is something that I haven't heard anybody talk about. But like, you know, we all had those days where you like, you can scroll all the way up and see like your very first order ever on Amazon. And I can just do this on like the Apple App Store too, where you go back and you see like every app I've ever downloaded. And I think like histories like that, they're very part of my life, but until an agent has access to those, it just doesn't understand all of that. And so I think there's so much more and a shopping history that if we could package up and give to our agents, could do even richer things for us. - Yeah, look, I think bringing agents to social events is really interesting. Like, you talked about the home, like have it be there for a family dinner one day? - Right. - Have it be there when we watch the, you know, the Seahawks game on Sunday. Have it be there for a party or a bachelor party or who knows what. So I think of course there's all kinds of questions about permission and the Shreddinger's cat thing, which is, you know, does the active observation, changes the quality of the interactions, but I bet even a snapshot of you being yourself in that environment would provide so much more signal than, you know, a lifetime of hardware. - Totally. - I think. - Yeah. I think that's right. You know, so much of it is on the written word and they understand exactly what we typed or texted and tries to build a personality, but we're so different. One of the other things I think a lot about with agents is the things we often use agents for or even search for are things we don't know about. Things that aren't fundamentals for our lives. You know, I was doing all this searching when the World Cup was on this summer. And all of a sudden Chechi Beach, he thought I was like a soccer fiend. I was like, no, no, no, I was in the World Cup. That was it. Right, we're done. That was good. And you know, I go on these curiosity journeys all the time. My daughter's into an artist and suddenly go like, learn about the artist and listen to music to get to know it, but it's not my habitual artist or taste. And so how can it know that when we're on these curiosity journeys, that is not actually who we are or what our real preferences are? I mean, I still haven't figured out into the agent. So I actually go into like the invisible mode a lot in order to not have things stored, which then isn't really helping either. So I'm curious of, you know, how we can actually get our agents to get to know us better. And I like this idea of our real world raveers. Now, how do you capture that data of the real world behavior? It's going to be the interesting piece. I don't know. I mean, there's going to be a thousand capture devices. I mean, unless you're going to, you know, the new set of bars are going to emerge that exist in Faraday cages, which I definitely think is going to happen in San Francisco. Yep. I think people are going to increasingly assume that they're being recorded, you know, in all environments. I mean, I bought the new Apple Watch because they have talked about some features like Siri, recap, live rewind that are coming out. I don't think they're quite out yet, but I upgraded my watch and expectation for those. 'Cause I think it'll be really interesting to have this thing that's at least kind of capturing tidbits across my day. Right. I mean, it's like Amazon B, it's a 24/7 ambient listener that's wearing your wrist. Okay, maybe to wrap it up. So the first is we're going to get back to the other, let's say in three or four weeks. Yeah. What do you think we'll have changed? Okay, I think we're going to see a lot more innovation in the enterprise world. We were chatting briefly before. It really seems like the whole world is focusing on consumer with not as much attention to the enterprise. And I think that we're going to start to see a little bit more shift in that direction. I think we're going to start talking more about fun. I think we're going to see agents that don't just feel like they're here to do something for us, but they're here to actually let us think out loud and help and get through our day. A little bit more making us laugh, doing little gossip in the background because I think that's what's going to then make us build a relationship that'll make us trust it more to get all these other stuff done. So I think we're going to start seeing the next wave of users taking hold of these, that's seeing how they behave. And one reason I pointed that is I gave my mom instinct. And I'm just watching her and I'll play it around with it. She's having so much fun. She's technophobic, hates technology. It is just having a blast. It's like a kid in a candy shop. And it's quite interesting to see how someone who struggled with the concept of chat GBT and how it works is just having such an easy time texting an AI assistant in a recent use case she did was our family dog passed away last year. And she wants one that looks just like that, just like our old dog. So she sent it a picture. I was like, find me a breeder that has this exact type and negotiate for me. And so I think it's going to be really cool to see, we know how tech lovers are using these assistants and what they're starting to do. But how is the everyday individual going to start adopting these behaviors? And are they going to be focusing on a lot more fun and just creativity tasks? Or what's going to be their preference of surface? What's going to be their preference of behavior? So I agree with you both. I'm going to take it one notch further. That's just fun, which is what are the aspects of ourselves that we don't either want to think about or reveal to perhaps even ourselves or to these agents? I think whoever is able to build that type of trust, almost like a dark agent will actually have something really fascinating on their hands. Because in a sense, starting from productivity, starting from email, it's a bit of a constant reminder of the things that we haven't done, the tedious tasks. And I don't know that people want to spend as much time there. I think people want to aspire to be a whole different superhuman version of themselves. And whether they believe in their heart of hearts, it's going to happen or not. I don't know that we have an agent yet that really speaks to those aspirations. Or desires, you know? It's like the maximum hierarchy in need of agents. Perhaps, perhaps, perhaps. I mean, I think that's a really interesting idea that in a sense, one of these agents flip from getting something done to take it off our plate to giving us a secret superpower. Right. When it's, David, how did you get that cool shirt? You're like, my agent ordered it. And I'm like, oh, why don't I have an agent that orders me shirts? Or, hey, I've noticed you're starting dressing better. I was like, yeah, I gave this agent access to my camera roll. I said, upgrade me. Started ordering a few things. That's why I'm dressing better. Like, I think that when we get to the point where agents are giving us superpowers to feel better about ourselves, that's when people are going to take notice and want that to versus, you know, I think a lot of the examples they get thrown around, save some money, book a trip. Like, I like planning a trip. I don't necessarily- I want you to take care of all of that for me. Like, we need examples that are like, "Oh, wow, I should use that for myself." - Right, I think that's gonna happen. It's like, can it help you become the human that you've always wanted to be, but have struggled achieving your success? - And do you start to consider it your secret weapon in your pocket? - I love it, guys. Should we wrap there? - Yeah, it's great. - Incredible, thank you. - Awesome, very cool. (upbeat music) - Thanks for listening to this episode of the A60Z podcast. 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