---
author: a16z
date: '2026-11-04'
guest: ''
layout: post.njk
source: https://www.youtube.com/watch?v=dSiTwPl0t1U
speaker: a16z
tags:
- ai-agent
- consumer-ai
- trust-layer
- social-dynamics
title: A16Z 对谈：AI Agent 从生产力工具迈向社交、信任与消费超能力
summary: A16Z 播客讨论了 AI Agent 的最新演变。对话探讨了用户在隐私与信任（22%用户视信任为主要担忧）之间的权衡、Agent 间网络与社交八卦机制、电商购物中理性决策与父爱主义的冲突，以及 Agent 如何从基础任务代劳转向赋能个人欲望与超能力。
insight: ''
draft: true
series: ''
category: ai-application
area: tech-engineering
project: []
people:
- Josh
- David
companies_orgs:
- a16z
products_models: []
media_books: []
status: evergreen
---
### 引言与 Agent 现状
**>>**: 我们的生活有太多不同的面向。无论是管理财务还是规划旅行，Agent 都将能够填补其中的各个面向。在我目前接触过的 147 多个不同助手中，大家谈论最多的担忧——有 22% 的消息都在将信任视为主要的担忧。
Original English
>> We have so many different facets of our life. Whether it's how we're managing our finances or planning trips, agents are going to be able to fill different facets of these. From over 147 different assistants that have come across my plate so far, the number one fear that people talk about, 22% of the messages are talking about trust as the main fear.
Original English
>> 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 will actually have something really fascinating on their hands. It is a very very [music] sensitive space. It's almost going to be like a new like social network where businesses have to put a lot more thought and value into the quality of what they're giving out.
Original English
>> What I've seen from 30 years in consumer product is paternalism will kill any product. [music] We talk about productivity and goals sort of achievement, but maybe people want the exact opposite of it.
Original English
>> Everyone right now really is approaching this world as just like a general assistant. As time goes on, we'll start to see
Original English
>> Welcome back to the A16Z show. I'm here with my partner Josh and David who's been leading a ton of the um agent bench and assistant efforts. We're going to talk about all things agents and a ton has happened since we last connected. What was it a month ago?
Original English
>> About a month ago.
Original English
>> Oh my god, dude. I feel like we should record an episode every like TVPN style, you know, almost every day. [laughter]
Original English
>> Absolutely insane.
Original English
>> Agents are changing every day.
Original English
>> That's totally right. So, okay. So, maybe let's start with um last night you hosted an agent meetup. Y
Original English
>> kind of tell us about the event. Tell us about the vibes. tell us about the topics.
Original English
>> 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 it was just people just hanging out, talking. Um, we we did have a pitch competition of sorts. So, a bunch of 10 different AI assistant builders were able to pitch their their startup and what they're working on. And it was just good conversations. It's interesting how like the general uh the the general thing that really stuck out to me was that people are craving community even in the agent web world and everyone's like why don't we have more of these meetups why don't we have more of these you know these opportunities to get to know each other which is uh it's kind of funny hearing it from people who are spending all their day all their time just messaging agents
Original English
>> and it's funny because it feels like a so many of these products are at least overlapping in a cursory way that the founders might be a little bit more ky, but that's not what you're seeing, huh?
Original English
>> No. Everyone is incredibly open-minded.
Original English
>> Uh, 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.
Original English
>> 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.
Original English
>> That's right. That's right. It is actually fun. on. 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?
Original English
>> 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 you know work once but don't actually work reliably and these are going to get 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 know you guys will only all have to use the same agent. We're going to have these things do 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. You know, as many different sort of types of humans as we might have, you know, or archetypes of humans, I think we'll have a similar number of agents. But maybe talk about what you think are the um the different axes for differentiation. Like there's a sort of spectrum between really serious and productive um to like really playful and maybe even sort of adversarial. Um and I'm sure there are many other ways to think about these things.
Original English
>> Yeah. 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 or 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, you know, you know, friends 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 matterof 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 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 um that my friend's power uh had been out all weekend because he'd been doing some renovation and they'd cut the power. And you know, 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 [laughter] I'm like, "That's like creating these like better connections." But that has nothing to do with booking a trip or saving money or getting anything done,
Original English
>> right? I think from over 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.
Original English
>> Yeah.
Original English
>> 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 uh so far. And when looking at like 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 fear.
Original English
>> And so it's it's really interesting to see because you have one camp that's this productivity and 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 fierce space of being a little intrepid and not really knowing where where the space is moving. And I'm I'm really curious to see how things are going to play out on that trust layer. And if we can solve that trust layer, then what do we end up seeing on more of like the finance side of stuff?
Original English
>> And if you looked at what Shane Mack has been talking about recently about trust, he's been talking about this concept of something called picnic. Yep. And they had an analogy that I really liked which is um you know if you have a kid and you don't have any fences on your yard and you let them go run around go run 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.
Original English
>> 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 and so he's really kind of like how do we build the right fences? So, 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 it actually like blasted his finances on his company Slack.
Original English
>> And I think that's the whole point of like, wait, okay, my personal agent should have access to my personal things and my personal communication channels, but not my work ones, right? 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 going to have to build a lot more trust.
Original English
>> Totally.
Original English
>> It's interesting though because we 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 like instead of giving models rules we should give them laws and principles. Yeah. Yeah. And I think a similar thing may apply here, you know, 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.
Original English
>> Yeah. I mean, I think that's part of why the analogy is, you know, a fence for children because 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 you know, the most important thing I think we keep talking about agents being autonomous. Book me the trip. Yeah. 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 ground work. Save me all the time and coming up with the best options and the right tradeoffs. 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?
Original English
>> But I think right now we don't need to to still have a really really effective agent,
Original English
>> right? I mean, it's it's we're at like the 1990s of e-commerce where I [laughter] think it was I think the like last stat I read was in 1997 or so is 60 to 90% of individuals on the internet thought that putting your credit card online was a preposterous idea.
Original English
>> And here we are today, it's just everyone's tossing their credit card wherever you want.
Original English
>> And I think what we'll eventually hit that in in this era as well, but it's it's going to take a little bit of time. I I think there's like a stated versus revealed preferences thing here because 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 their bank accounts via Plaid since the Venmo era. So, I don't know that people, but when you ask and they're like, "Oh, yes, I'm very concerned about trust and safety." I think an example though of where consumers are very concerned about sort of trust and assumptions is around being embarrassed
Original English
>> and social signaling. And I actually think the most interesting thing about the Shane Max story, I think, the most horrifying visceral thing is that it embarrassed him. That's right. It really embarrassed him, you know, and that's why I think some of the kind of agent to agent network thing, cuz you can imagine somebody you're just getting to know, maybe you're going on a second or third date and your agents are talking, you're like, "Whoa, what are they saying about me? How are they kind of positioning what?" 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.
Original English
>> And it's it's a good point and there was 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 of pizza.
Original English
>> In order to get that $30 of pizza, you were granting access to your entire Google Workspace, all of your emails, right? All of your data for 30 bucks.
Original English
>> 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. Yeah, I mean I I tend to think though there's always this trade-off of of privacy versus utility, which is if you can give me better utility, then I'm willing to make some privacy trade-offs, but at the point at which we're basically equal on utility, people will always choose a more private option. And this is 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 as like the center of why your data doesn't actually go anywhere or 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. So we have to find that intersection of trust. I think this embarrassment point is really really important too because I think um you want your agent to understand you and have all your personal preferences and 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 it 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's [clears throat] it creates that really awkward situation, right? 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. So we have to hold a pretty high bar for our agent
Original English
>> um to be able to do that.
Original English
>> And it also then comes down to like personal embarrassment and professional embarrassment. I think something that Town has done remarkably well is is really nailing the tone and building that trust layer of being able to send out emails on your behalf. Yes. And it is a very very sensitive space. I mean the 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 I have to respond, oh sorry, that was my AI that I didn't do enough oversight on. It's a it's a tricky space.
Original English
>> It's interesting. I sign all the email that I write with AI with the model that I used. Like 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 used AI for this. I think actually people are pretty flexible as long as they don't feel hoodwinkedked by it.
Original English
>> Um,
Original English
>> you know, it's interesting because we're we're talking about privacy, but there's privacy and there's judgment, which is different, and discretion is maybe somewhere in between. Um,
Original English
>> 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 and how did you even define judgment in that case?
Original English
>> So, the main intention of that test was to see how do agents balance two different constraints. One was cost. Mhm. And the second was uh 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 uh based on the ability to actually deliver it then also compound in the the actual pricing. Instinct really did a phenomenal job. And it is something it's it's interesting how news cycles come and go and it seems like they're kind of not in the conversation as much as as they used.
Original English
>> I mean we're talking the weekly changes, right? But [laughter] uh true.
Original English
>> It is it is true. But they Instinct really did continuously bring back uh that you know the best price. Um there's another app called Kicker which did a phenomenal job and and one way that I think it was able to have an edge is that it has you install a Chrome browser and so its browser use has a little bit of an advantage from that point and it was able to to find 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 were all able to find uh flowers that could be delivered that day,
Original English
>> but they really seem to take a step back in prioritizing the price, whereas uh 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? Um, I ran another test that was I had three different agents uh test in booking travel to LA. So I said, "Okay, book me a flight to LA,
Original English
>> plan an entire weekend for me and uh I want a luxurious, costefficient weekend." And so I tried to like, you know, put those at at odds with one another. And it was quite interesting to see how Grockbot compared to Dots compared to Instinct, they all approached their interpretation of costefficient and luxury in different ways. Um where you know one maybe thinks that cost efficiency is the most important and I'm going to take a redeye flight to ensure that I can you know have the most cost efficient path. Whereas others uh found cost efficiency or sorry saw 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.
Original English
>> And which were which?
Original English
>> So Instinct was uh pretty pretty much right down the middle.
Original English
>> Okay.
Original English
>> Um Grockbot did a little bit more on prioritizing time and DOTS was a little bit more on prioritizing cost. 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. Cuz there are times where I'll totally take the redeye 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 this like 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?
Original English
>> So they all did ask questions and I responded those questions. Honestly, I tried to be a little ambiguous and vague in my response cuz 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 believed that was the best proposal cuz I wanted to see did the agents actually get biased by the other agents and didn't actually then influence their plan.
Original English
>> And uh Grockbot was actually the only one that you know very methodically took value from the other ones and implemented it into its own plan.
Original English
>> Okay. And and I have one more question on the flowers because so you you were just ordering flowers for yourself, I guess, just to like test their
Original English
>> girlfriend. She got a nice delivery of of flowers.
Original English
>> 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 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 and stand out a little bit for
Original English
>> So, for this experiment, no. And 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 [laughter] getting flowers as the outcome. But it it's a great point, right? Like in 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 uh delivery time.
Original English
>> Yeah. And make sure the price doesn't show up when she actually gets the
Original English
>> flowers or like a note as an example. Some of them did ask, do you want me to write leave a note with with the flowers when they arrive?
Original English
>> Yeah.
Original English
>> 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,
Original English
>> you know, and there are people who like to think like, oh, I'm not cheap. I just like to save money, right?
Original English
>> But you're not have to kind of maybe like get over that and tell the agent, I'm actually pretty cheap, right?
Original English
>> 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.
Original English
>> Y
Original English
>> 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.
Original English
>> Totally. And and I think something that is really interesting with that specifically is dots because it has so much of this context that you've already built with chatbt.
Original English
>> Um when we filmed the first podcast it hadn't come out yet and then I think a few days later it it came out.
Original English
>> That's right.
Original English
>> Um by and large most people I talked to still are not using it as their preference. Of the 300 I did a survey of you know AI power users 354 people only 3% were actually using it as 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 it and why they liked it and why they wanted to try it was because it has all this built-in context of you just from your chat threads. People are using chat GBT as a therapist and so it has so much context on you
Original English
>> where
Original English
>> it's going to know that when you say, "Well, I'm not cheap." It knows it's like
Original English
>> you're a little cheap
Original English
>> a little bit. A little bit. [laughter] I'm curious why people think that Chacht has this great set of preferences from on them. Did you actually get any sense if they said they really like dots like what they had been giving to chatbt 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 memor is there why would I switch?
Original English
>> It's totally replicable. Um it it's 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 the friction to switch. Yeah. And um I I ran the test around across the top 15 agents on the benchmark of which ones can you actually pull context from and say like, "Hey, I want to switch to another one. Give me an empty of all of my memory that you have so I can switch easily."
Original English
>> All but one were were actually willing to do it.
Original English
>> And so you could just get a memory file, everything you need, submit it to the next one.
Original English
>> And was it good or was it uncanny?
Original English
>> It it was pretty solid. I mean, it obviously I'm sure they're they're caging some some of some of the fruits of of your labor, but by and large it it did really break everything down.
Original English
>> I'm not sure if you've ever looked at any of those markdown files, but it's a little terrifying is the wrong word, [laughter] but it's like, wow, you really got your finger on me. You kind of like chafe against like maybe I don't want you to know me as well as you seem to think you know me.
Original English
>> Yeah. After the first few, I just I decided to stop reading them.
Original English
>> Yes. Yes. Yes. Yes. It's actually a really interesting and now common onboarding pattern
Original English
>> where it will say, "Hey, go and paste this prompt into chat GPT, download the file, upload it to me." Um, we'll see how long that lasts.
Original English
>> Totally. Another cool onboarding thing I've seen is uh you jump on like it asks you to jump on a call
Original English
>> and it's like, "Hey, let's just just talk to me for a few minutes. Just ask some questions." And it's it's really interesting to see what context it can it can pull from those questions.
Original English
>> Um, and
Original English
>> they're very disarming. Like they just get talking like it's kind of crazy.
Original English
>> Totally. But I think I think it brings up another uh variable of context, which is photos, right? Like this 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.
Original English
>> Yeah. I mean, I think have you tried Dazzle? Has Dazzle gotten into your benchmark set yet? That's from Marissa Mayer's new company. And I think the idea of like 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. Um, it it hasn't been added to the benchmark yet. It is quickly on the the top of the list to test through. I'm still manually testing all these, so I actually [laughter] get the personal experience and understand what the feeling is with each one.
Original English
>> 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
Original English
>> I'm giving you all my photos. That's it's pretty it's pretty terrifying. But they they have this one thesis that, you know, if you don't need it, they're going to forget about it. And so if a photo seems as though it it has context that it doesn't necessarily need or things that you probably wouldn't want it to know, um they're 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 these different players do approach the the photo context and how that actually does then influence the behavior of the agent and how well it knows you.
Original English
>> It'll be interesting to see. I'm a tiny bit more skeptical. You know, I built an app because I've always been fascinated by screenshots because screenshots are sort of the only way on the mobile phone
Original English
>> Yeah. to be able to capture context across every app, right?
Original English
>> So, it's actually a really interesting kind of data asset and you go back and you look at your screenshots and it gives you a little view into your work and your world at the time and and also your interest and preferences.
Original English
>> So, I built an app that just extracts key information from all the screenshots on my phone and
Original English
>> 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 or say knowing that it will feed the model and the agent.
Original English
>> 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 loop it back in your life, that's great. I talked to 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, you know, the examples that I saved here." So it's actually you're building your like real kind of flavor profile. So it it actually is actually able to use your styles. And so as you navigate the world, the web apps on your phone, it 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'll actually make you create a lot more content in that loop.
Original English
>> Right. And I'm so I'm curious with the app that you built in in this context for it. So, of in the same survey of what people are purchasing, the second uh most popular category was Amazon retail, 35%.
Original English
>> Saying that they're they're doing some form of shopping. And so this context that you're gathering,
Original English
>> sorry, Amazon shopping or just some form of shopping?
Original English
>> Amazon plus retail.
Original English
>> I see. Got it.
Original English
>> Um 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? Yeah, potentially. I think that's actually really interesting and you can do some stuff there. I also think that [clears throat] 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, right? And I actually think the longtail are going to be huge structural winners in this because they're ones who presumably have better products but worse marketing.
Original English
>> Yeah,
Original English
>> they certainly have worse marketing. I'm not sure if they have better products. and the agent, you know, has this sort of infinite patience to go search for things and find things that are exactly tailored to your taste,
Original English
>> even if they're not on the top 10 internet sites,
Original English
>> right? I mean, I think it's really direct shopping, right? We've all talked to direct to consumer has 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 having to do 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 and you know, wholesale to retail costs in the middle. Well, if you want this shirt, your agent can buy it for you, too. That's great.
Original English
>> But, uh,
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>> oh, please.
Original English
>> I say it goes to Patrick Hollison'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.
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>> It's really going to create a world where businesses have to put a lot more thought and and value into the quality of what they're giving out. And it's going to be really interesting to see that.
Original English
>> So, somewhat I'm going to quibble with this point. I love Patrick's vision and I think that that like 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 uh sort of directions of irrationality though it 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.
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>> Okay?
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>> You know um and they may actually ascribe a lot of value to that. proxy for something and they may really dislike janky APIs with you know Java code behind it like I don't know.
Original English
>> So I do think really interesting to see because they too are going to need shortcuts you know how will the agents actually know what product quality is.
Original English
>> 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 like that will then presumably be paid per transaction to do this research do all the ratings. I don't know. I'm I'm also more biased and I just think people are people and people are going to make the choices that they want to make that are most satisfactory. So the question then is is the agent going to be very careful in curating the set of options that it presents because [laughter] again like like all of a sudden you're like hey I'm really hungry. I want to 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 want to be with your agent? So I'm actually not as convinced that agents are going to make us more rational. Well, I think they're just going to 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 going to be people with our own preferences and tastes. And if the agent's not meeting us where we are, we'll just switch to another agent. We'll import and export our our stuff and be like, "Ah, this other agent's going to meet me on my preferences better."
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>> Right.
Original English
>> Um, it's really interesting because what I think what you're speaking to is like paternalism, right? Uh 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 the sort of the we talk about productivity and goal 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 seeing 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?
Original English
>> Right. I'm curious what you're seeing on on that.
Original English
>> Yeah. So I mean I think you have I I kind of 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, best, highest quality one. Go for it. But then you do have the preference and you have
Original English
>> it's 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 how they're thinking about this space.
Original English
>> We're seeing some cool stuff with multiplayer. I think Wabby is going to be really interesting um because it does create a lot more,
Original English
>> you know, uh it creates a a different world where you can now be interacting with other humans and have crossover and preference and see how it behaves and that and it becomes a little bit more like entertainment. Um 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. M I think it'll be we're 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. I think as time goes on we'll start to see a little bit more experimentation in some other avenues.
Original English
>> Well and I think you mentioned Wabby. One of the things I really like about Wabby and it just I think launched you know just this week or yesterday um is it's not even just experimenting with you know an agent but it's experiment with like how to interact with multiple threads of your life. like goes through my email and other things and actually gives me, you know, a whole bunch of different threads of life and actually when things come up on email on those things, it actually feeds them into the different threads. I have one thread with Wabby um 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. Um and it keeps track of all that. Then I can like, oh, I heard about this new book from John Gisham. Like add that to my list and hey, I 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 even gives you UIs that actually like these widgets to like envision everything so I think again it's showing us like a very different experience than just a general agent that is more like a search box and it's more like task test task
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>> right
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>> I think one of the interesting things that Wabby does is and perhaps gets right is that when you create the message channel with your friends and 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 a social contract together. Whereas when you have iMessage group threads and you add the agent, there's some certainly if it's an existing thread, then it's very uncomfortable because it's like, well, what can the agents see? What did they extract? But even for a new thread, there's a set of implicit expectations about how you interact with people on iMessage. And I don't know that we're quite comfortable with agents in that space yet.
Original English
>> 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, you know, 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 wobby thread around this topic, but it's not bleeding into everything else we might also discuss.
Original English
>> Totally. Um, I want to 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.
Original English
>> You know, one of the things I've started seeing, um, is more of these agents that are kind of like fun and gossipy and we'll actually get you to invite your friends and we'll ask you a bunch of questions and be really really curious about you and what's going on in your life and then it'll share some of that with your friends and then it'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 an incredibly exciting and very intriguing to see how these agents kind of relate to each other in this sort of gossipy background. And so far, I found them just to be like probably some of the most joyful moments I've had with agents. Again, I mentioned at the beginning how my friend had like lost his power over the weekend, but when we were first both onboarding onto this agent 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 and I were 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
Original English
>> right
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>> what I love about that is it provides a degree of social indirection that actually makes you closer you know because for your friend they're like I don't know how to text gosh until my powers out. That's oversharing, 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.
Original English
>> Yeah.
Original English
>> In a very sort of uh low-key way is is really cool.
Original English
>> No, it's great. It definitely was bringing us together.
Original English
>> Yeah. It's 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 the earliest version of them, but you still send it in a group chat and it's just it's just laughter. It's just pure laughter of of the ability to create a whole new world and it's just fun.
Original English
>> I mean, I giblified everybody I could possibly imagine.
Original English
>> I was doing a lot of um VHS video covers [laughter] for my friend groups. I love that. What are some of the wild things that you've seen? I mean, you've seen them all.
Original English
>> So, I've been seeing a lot of stuff working at the infrastructure layer. Um 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 I've surveyed uh trust obviously is a huge one but another one is just getting blocked in and their 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 of the browser use of direct integrations to check out against inventory itself um some whether it's browsers that are built in and really like HARC 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 um really cool in that way. Again, Kicker, as I mentioned, uh Chrome extension to tackle the browser use in that way.
Original English
>> Mhm.
Original English
>> So, I've seen that as as a really interesting uh 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
Original English
>> um maybe that moat will be able to be crossed in a year or so but at least for today the the agents that are able to perform with hundreds of thousands of users.
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>> Yeah,
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>> 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 and there's a pretty clear difference in performance there. And so it's 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 because 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 tweaks that different ones are making.
Original English
>> So it'll it'll be interesting to see like you know how do we view this space growing from a scalability point of view.
Original English
>> 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. Um, memory is another one. its ability to actually continuously have context on you and not forget the little things and all that.
Original English
>> And you know, you mentioned Kicker, which you know, you said runs in your current local browser, but have you looked at other ondevice assistants yet, whether that's things 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.
Original English
>> Totally. So, it's it's a really cool paradigm. I've spent most of my time in the preconfigured just plug-and-play type world. Um because I tend to find that it's it's easier to compare them across 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 going to 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. Um right, 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 going to be an interesting space.
Original English
>> I mean, that was kind of how this all started with, you know, this brilliance of OpenClaw. That was this thing where you had to you felt like you had to get your whole Mac mini to set this all up, plug in to one of the models that you were using, whether local or 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 that she setting it up and owning it yourself will become a paradigm again.
Original English
>> Yeah,
Original English
>> it'll be really interesting. I'm glad you mentioned OpenClaw cuz it feels like one of the unasked questions right now that's sort of hiding in plain sight is if Instinct and Muse were the kind of consumer product version of OpenClaw, what is the, you know, mass market version of Moltbook?
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>> Yeah.
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>> And Moltbook was just like OpenClaw was far ahead of its time. And I think we'll something like that will exist. How can it not?
Original English
>> It's it's it's going to be interesting. Um, so at at the event that we did last night, uh, everyone who was there was able to scan a QR code and there was the human meetup and then I we also had an agent meet up.
Original English
>> Oh wow.
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>> 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 free form talk.
Original English
>> And it's it's interesting. There's, you know, it got to the point where after like 150 messages, some of these agents are just speaking gibberish. It's like I have no idea how you got that concept and why why you're talking about that. Um the the initial prompts did start off with a little guidance of you know introduce yourself, who's your human, what are they working on, what type of uh help do they need, but it's it is going to 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 you're you know, your your human is doing that, too. You could help Josh. Hey, Josh, do you want to 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 because 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 malt book 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, right?
Original English
>> 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 going to be how the world gets out and that'll come back to me through the agent network.
Original English
>> Totally.
Original English
>> And that's uh Tommo actually has a feature uh it's called interest groups
Original English
>> and uh the the use case they use that they talked about was really cool is we have a bunch of people on our application who are studying for the ELSAT.
Original English
>> Why don't we all put them together in a group chat and if 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 connecting people just purely by interest. You have no idea who they are.
Original English
>> Well and I'll take it one step further. So, it gets us all chatting and that's really cool. It's a it's an awesome Tommo feature. I've tried it and haven't totally known what to say in the groups yet, but I find it really fascinating. That's putting us together around around goals. Imagine now that it's like, "Hey, all of you, now that you've done the ELSAT, go hang out at this bar Friday night." And it like books the time at the bar, opens that up, and all of a sudden it it takes us from this digital world where agents are actually putting people together to do that connection. Kind of like your meet up last night, right?
Original English
>> I love this so much. So I think a really important underdised topic in AI right now is just entropy. Yeah. Like how do you create things that you didn't expect to, you know, have occur and serendipity is a form of entropy, right? That's sort of what you're describing 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.
Original English
>> It's almost going to be like a new like social network 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.
Original English
>> Yeah.
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>> 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, you know, go meet up at a bar.
Original English
>> I'm I'll be curious to see what is the catalyst for the serendipity, though, cuz I think the interestbased thing has been tried and there's a little bit of an interesting sort of social hierarchy thing, which is everybody wants to hang out with somebody who feels like they're one step ahead in some direction.
Original English
>> 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 interest 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 going to tell you a little secret. They're going to know a little secret. You're going to have a secret phrase you have to pass between you. 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 and go out. And so, that's the like this is sort of what the molt book, 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 friends, they want to meet people,
Original English
>> they're going to be a lot more interested to just go meet random people because they want they want new friends. But if you make that same offer to someone who has an established friend group, they're like, "Well,
Original English
>> why would I go do that?"
Original English
>> Also, Seattle versus San Francisco, [laughter] you got to know what city you're operating in.
Original English
>> Exactly. I've been thinking a lot back to this photo roll 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 disc 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 roll. 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 um personalization or open up new connectivity?
Original English
>> It's so it's something that comes to mind. I don't I don't know how much data this would actually provide. Maybe it's more of a habitual thing and and again it's dependent on the hardware and how smart that hardware is and how much data it's able to store. Um, Way Joe just released the MCP, the ability to connect to hardware. And I find that, you know, 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 context on how frequently is your vacuum cleaning or how frequent, you know, what what's the typical temperature you sleep at night. It's going to start to develop these, you know, very passive understandings of, oh, you're you're kind of a neat freak or you really prefer cold weather over warm weather. And that's going to 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 on the hardware itself. And I think we're still at the earliest of in that world. So connecting to your home, super interesting.
Original English
>> You know,
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>> 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'd like you can scroll all the way up and see like your very first order ever on Amazon. I occasionally 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 kind of shopping history that if we could package up and give to our agents could do even richer things for us.
Original English
>> Yeah. Look, I think bringing agents to social events is really interesting. like you like have it be there for a family dinner one day have it be there when we watch the uh 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 this shreddinger's cat thing which is you know does the active observation change 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 input
Original English
>> totally I think.
Original English
>> Yeah.
Original English
>> No, I think that's right. You know, so much of it is on the written word and they understand exactly what we've 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 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 fundamental to our lives. You know, I I was doing all this searching when the World Cup was on this summer and all of a sudden Chad T was like a soccer fiend. I was like, "No, no, no. I was into the World [laughter] Cup. That was it. Like, we're done." That was good. Um, and you know, I go on these curiosity journeys all the time. My daughter's into an artist, and so I'm going to go like learn about the artist and listen to the 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? It's something I still haven't figured out how to do with the agent. So, I actually go into like um 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 our real world behaviors.
Original English
>> Now, how do you capture that data of the real world behavior is going to be the interesting piece?
Original English
>> I don't know. I mean, there's going to be a thousand capture devices. I mean, unless you're going to the, 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.
Original English
>> Yeah.
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>> I think we people are going to increasingly assume that they're being recorded, you know, in all environments. I mean, I I bought the new Apple Watch because they have talked about some features like Siri recap and live rewind that are coming out. I don't think they're quite out yet, but I upgraded my watch in expectation for those because I think it'll be really interesting to have this thing that's at least kind of capturing tidbits across my day,
Original English
>> right? I mean, it's like Amazon B. It's a 24/7 ambient listener wearing your wrist.
Original English
>> Okay, maybe to wrap it up. So, the first is we're going to get back together, let's say, in three or four weeks.
Original English
>> What do you think will have changed? Okay. I think we're going to see a lot more innovation in the enterprise world. Um, you know, we were chatting briefly before. It really seems like the whole world is focusing on consumer with not as much attention to enterprise. And I think that we're going to start to see a little bit more shift in that 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. um making us laugh, doing little gossip in the background because I think that's what's going to then make us um build a relationship that'll make us trust it more to get all this other stuff done.
Original English
>> So, I think we're going to start seeing the next wave of of users uh taking hold of these, seeing how they behave. Um and and one reason I point to that is I gave my mom Instinct and I'm just like watching her now play around with it. She's having so much fun. She's technophobe, hates technology, and is just having a blast. It's like a kid in a candy shop.
Original English
>> And it's quite interesting to see how someone who, you know, struggled with the concept of chatbt and how it works is just having such an easy time texting an AI assistant. And, you know, a recent use case she did was um our family dog passed away last year and she wants one that looks just like that, you know, just like our old dog. So, she sent in a picture was like, "Find me a breeder that has this exact type and negotiate for me." Um, 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 they're starting to 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 their preference of surface? What's going to be their preference of behavior?
Original English
>> So, I agree with you both. I'm going to take it one notch further than just fun, which is
Original English
>> what are the aspects of ourselves that we don't either want to think about or reveal
Original English
>> to perhaps even ourselves or to these agents. I think whoever is able to build that type of trust, you know, almost like a dark agent um will actually have something really fascinating on their hands because in a sense starting from productivity, starting from email, like 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 that it's going to happen or not. I don't know that we have an agent yet that really speaks to those aspirations
Original English
>> or desires you know
Original English
>> it's like the Maslo hierarchy in need of of agents. Perhaps, perhaps, perhaps.
Original English
>> I mean, I think that's a really interesting idea that that in a sense, when do these agents flip from getting something done to take it off our plate to giving us a secret superpower, right? Like, you know, when it's, you know, David, how did you get that cool shirt? And you're like, my agent ordered it, you know, 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. It's 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 too versus, you know, I think a lot of the examples that get thrown around, save some money, book a trip. Like I like planning a trip. I don't necessarily 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.
Original English
>> I think that's going to happen.
Original English
>> It's like, can it help you become the human that you've always wanted to be but have struggled achieving yourself? and you start to consider it your secret weapon in your pocket.
Original English
>> I love it, guys. Should we wrap there?
Original English
>> Yeah, it's great.
Original English
>> Incredible. Thank you.
Original English
>> Awesome.
Original English
>> Very cool.