The Personal Agent Race Is Here | Anish Acharya & David Pawlan

20:17Like you get a traffic ticket, you have to go pay for that traffic ticket. Great, just take a picture and let your agent go do it for you. It's going to be interesting to see.

20:25Anish Acharya:So the next thing I wanted to talk to you about was social. You know, we talked in multiplayer generally. You know, we talked about how iMessage is this sort of privileged place to be, which is actually one of the cool things about Instinct. However, in my experience, building agents that you add to group chats somehow feels intrusive or like it diminishes social capital. Have you seen anything that works well? And what are your kind of theories for how these agents get to a multiplayer state? A lot of people have tried it. I think I've seen three different approaches. The first approach is your traditional attitude group chat.

20:58And it's just like the group chat and your companion. The second approach I've seen is how instinct did it, where you have like an agent network where you invite another agent and they're talking behind the scenes on your behalf and they'll update you as to what's going on. The third way that I've seen it, which I think is the most interesting, it's a new one called Doc by this guy Shane Mack. I think also an A16Z company, XMTP. And they are approaching it more like granola. So you add an agent to a group chat, but that agent is silent and it's purely a listener. It's taking notes on what people are talking about.

21:34And if it has an action item, it independently will ping the person in a separate message thread. And then if you want to see what people are talking about, you can go into the actual docs and see what it's taken notes on. And that way it's more of, again, it's your invisible agent. You don't know it's there. It's doing all the admin work that you would want out of a multiplayer function. And if it needs action items, it doesn't bother the majority of the group. Really, really cool approach.

22:00Anish Acharya:I've got to try that out. I love that. I love that it's an A16Z company already, of course. Of course. You know, my theory on this, if you look at this, and Nir from Obo said it, and I think he's right, which is the progress the models are making on verifiable domains like coding are, of course, exponential. But the progress they've made on just prose quality and even like bedside manner has maybe plateaued or maybe is even getting worse. So I actually think that with the models as they are today, and perhaps with our own expectations, you know, in terms of these social dynamics, I don't think there's a lot of ways that the agents can contribute and enhance the sort of social connectivity of the group.

22:39Anish Acharya:You know, conversely, I think agents that are very utilitarian, you know, one of the experiments I've been doing is adding it. I'm a collector, you know, I collect records and a bunch of other things. Adding an agent to the chats where I talk to my fellow collector friends and trying to catalog our respective collections and our tastes. And I haven't quite hit it, but it at least feels like it's something that's genuinely additive to the group rather than this sort of low EQ robot that's chattering when we don't want it to. Yep, totally. You should give Doc a try. I think you're going to be quite fascinated by it.

23:13Anish Acharya:I will, yeah. Yeah, the other interesting take that I heard this week was that something about messaging in particular doesn't lend itself to these agent interactions because in messaging, it's as if somebody has the mic and it feels uncomfortable to give the agent the mic. Whereas if you look at something like maybe closer to a Discord or even a traditional web forum, that's actually something where an agent can make a post and you can either engage with the post or not, Reddit style. But for some reason, it feels less intrusive than group chat. I don't know. Yeah, interesting. It's almost as if we're trying to humanize these agents a little too much.

23:49And I think that comes to another component where if you look at the actual design of the character of the agent, I see some companies that have it try to be like an AI generated human. And then you have other companies like Muse that it's this like adorable Yeti. And I think it's really interesting to see how the world has fallen in love with this Yeti. It's just so cute and adorable. And the like AI generated human, to your point, like I think people feel a little uncomfortable. Like it feels weird to humanize these assistants so much in your personal space.

24:22Anish Acharya:So one related question I wanted to ask you is, do you think that the market segments by personality or archetype, you know, we were chatting a bit about this on our walk, but, you know, some people prefer a kind of serious, gruff, authoritative doctor. And some people prefer a, you know, warm and friendly, you know, sort of a doctor that feels like a peer. And those are just two different archetypes of doctors. obviously no doctor is both of those things. They're in opposition. Do you think the same will be true of agents? I think everyone for sure prefers a different style of communication. Poke came out of the gates hot, right?

24:57The personality of poke is quite distinctive and it's something that I have a lot of friends who are like, I refuse to give poke any of my personal information because it's so sassy and it actually makes me uncomfortable to engage in a conversation with it. But I don't think personality is really a defensible moat because it's quite easy to configure. It's like you as a consumer, you text your agent, you say that you would prefer it responds in a certain way, it just saves that to its memory or its sole file, and then you're good to go and it changes. I think we'll get to a place where whatever general agent ends up being the leader, that it'll be quite configurable and each person can kind of tailor the agent to speak to them however makes them most comfortable.

25:37Anish Acharya:So that's interesting and I agree with you, but maybe let me try the steel man here for not just personality, but kind of, you know, constitution, for lack of a better word, which is an example of a kind of defining characteristic is presumptuousness. You know, we've talked a little bit about this. And there are some jobs for which you want the agent to be highly presumptuous. And you'd rather have it make mistakes 10 % of the time, as long as it often gets things done. And there are other styles of agents, like our finance agent, perhaps, where you want it to be highly cautious. So I sort of wonder if some of these things, which we're now describing as personality start to push down into sort of capabilities and how it tie breaks in a position of ambiguity.

26:20Anish Acharya:And perhaps there's a bit more defensibility around that. I think there is massive defensibility around proactivity. I think that's actually going to be something that separates the winner from the meat of the pack. The agent that can be most proactive, that can serve as an invisible assistant and start doing things on your behalf without you even asking. I think the best like gimmick, cool, aha moment that we've seen so far is checking into your flight for you. To your point, though, it really does come down to two categories. There's some workflows where you want to retain control and you don't really want an agent to be acting too proactive on your behalf.

26:58Yeah. And I think those are workflows that require a change in action on your side. So maybe that is an agent identifies that the insurance you're using is charging too much money and thinks you should switch insurances.

27:11Anish Acharya:Yeah. It should probably get your permission before it actually makes that switch because that's a direct action on your behalf that impacts you. However, the proactiveness of, hey, I drafted this email for you or I got a flight credit on your behalf. Yeah. There's no action needed on your side. It's just saving you money. It's saving you time. So I think it'll be interesting to see how do we really categorize and break down those type of behaviors. But it will be a very fine line because if you cross that line once, I think you immediately lose all trust with your user. Yeah, it'll be interesting.

27:43Anish Acharya:We were joking internally, like we're days away from an agent messaging someone saying, I noticed you weren't that into her, so I went ahead and broke up with her for you. Yep, saw that one. It's going to happen, man. But, you know, I think a lot of the magic comes from the presumptuousness. And I think that if you didn't see people posting on X about, oh, the agent did this, the agent did that, it would probably be a sign that the agents are not pushing hard enough in this direction. Like, I think there's going—and actually, I'd be curious to know. First of all, I'm, you know, a little suspicious of whether the Bong Chang post was even real.

28:18Anish Acharya:and for folks who don't know, there's a person who tweeted that Instinct checked him into a flight and hallucinated his middle name as Bong Chang and he wasn't able to get on the flight. So I'm not sure if that's just shit posting or if that really happened. But I'd be curious to know if that person is still using Instinct. I'm guessing they are. I would assume so, purely given the traction of that post. They're probably beating for more content there. If nothing else, at least just a source of comedic popular tweets. Right, right. Maybe Taka, you know, it feels like one of the big things that's happened is that the kind of primitives that were developed during the open-claw period have now been productized in a way that the mass market consumer can sort of, you know, digest and appreciate.

29:01Anish Acharya:Do you think there are, and also POKE, which you had mentioned a couple of times, like POKE was extraordinary. I think they did a super clever job. And I think if they had started six months later, they might've ended up being the winner. I think the team is really, really talented there. and I'll be curious to see what they actually have in store for us next because I'm sure that now that they're a part of Cognition, they haven't stopped working on this. I'd be very curious to know if there are capabilities or lessons from the OpenClaw era that you noticed that you think are going to tell us what's coming next in consumer agents.

29:31Right now, I honestly see the consumer agent is literally just a replication of OpenClaw, but it's just preconfigured. I don't see much happening in the personal assistant space that you can't do with OpenClaw or Hermes. It's just a matter of fact that you don't have to configure everything and you're not getting error messages popping up every seven hours. And it's really easy to use. It's an easy interface. So we'll see what happens. I think the direction of the space will continue to move towards proactivity. I think the direction of the space will continue to see more hyper-specialization, which I think goes to your point in your thesis of narrow startups.

30:17And how does the space look as we see more of these long tail opportunities, whether it is, you know, instead of being a generalist, I'm going to spend all of my time focusing my assistant to be an expert for single mothers with children under the age of three.

30:36Anish Acharya:Yeah. And it knows everything about how a mother operates her day-to-day life, child development where it literally feels like that assistant is reading their mind. Yeah. And that could maybe be a plugin into the generalist. But, you know, I'm curious with this being your thesis, how do you think about, you know, I guess first give us some more insight on what narrow startups are to you and how do you see that playing? Yeah, the theory with narrow startups is that, you know, you can now build software that's incredibly ambitious and incredibly valuable for a very small number of people. and we have this precedent of people paying, you know,$200,$250,$300 a month.

31:12Anish Acharya:So you can build, you know, a$100 billion run rate business with tens of thousands of people, which has never really existed in the past. A lot of it also is that the capabilities can be specialized to such an astounding degree. And then as we think about what you're discussing, I totally agree with you. I think there will be this kind of comparative advantage. I think it's going to be a combination of taste and proprietary knowledge. You know, there may be just as you, you know, you have a doula that may subscribe to a certain sort of style of, you know, helping women give birth. You may have a personal agent that actually subscribes to a certain school of thought or style or, you know, even a set of lessons that aren't well understood.

31:54Anish Acharya:And you're going to hire that agent to sort of provide that service to you. And then proprietary data, you know, you'd mentioned potentially having a personal agent just for New York City. I think, you know, just as there might be a concierge that's got A-plus taste that's hard to replicate, that knows all the best spots that you're going to love, and there may be another dozen for, you know, another dozen different people or archetypes of people, I do think that there'll be this sort of subjective and objective specialization that happens. It's going to be interesting to follow. I'm also curious from your lens, even just noticing our conversation here.

32:26We interchange between assistant and agent. and it's been a constant conversation I see people talking about on Twitter. Is the future of this ecosystem, is it going to be a personal assistant or a personal agent? And what do those mean to you?

32:43Anish Acharya:Oh, that's such a great question, man. I mean, to me, assistant is a sort of lesser form than agent. You know, for me, an agent is somebody, you could imagine them being a peer in a social group, you know, and maybe we need a better word than agent, but an assistant can only sort of definitionally do what you ask it to do. It can assist you in doing something that you've directed it to do. While an agent has agency and can just make good things happen in the world. And maybe this parallels a little bit, you know, the sort of agents and AI in the enterprise where they've sort of started as interns.

33:21Anish Acharya:And through, you know, doing work and improved intelligence, they're able to get promoted into doing higher order forms of work in the enterprise? Like, what does it mean for an assistant and later an agent to be promoted in the consumer's life to do more specialized and delicate work? I'm super aligned. I'm also very interested what ramifications it might have and just like the social layer of humanity where, you know, does the word agent allow us to, you know, not personify AI enough? You know, is assistant, does it add too much human to the experience? And does that make society uncomfortable?

34:05And it'll be interesting to see like how the, we're in bubbles, you're in a more bubble, you're in SF. So you're in like the tech hub of the world. I would say New York is a little behind SF. And then, you know, the rest of the world catches up after. So it'll be interesting to see how people actually think about the vernacular of the space.

34:22Anish Acharya:I don't know if it's a bubble. I just think it's like the future, you know? It's like, you know, we're in the near future. Yeah. Yeah, I don't know. I actually think that it could increase and improve a lot of social dynamics as well. Because you start to think about the agent as a non-human, it can provide a layer of social indirection, you know? So there might be something that's sort of awkward for me to say to you or an uncomfortable social dynamic that's occurring in a group. And with a very carefully designed agent, I think the agent can, you know, help to, I don't know whether it's provide feedback or sort of organize a conflict in a way that feels non-emotional.

35:00Anish Acharya:Because you know that it's not. It's like an arbiter of confrontation. Potentially, yeah. Yeah, yeah. Now, I'm not advocating for a more passive aggressive sort of social system, but I do think it's interesting that they can be a sort of source and a destination for social indirection, if that makes sense. Right, right. And I think that it will have a lot of like significantly positive influences in the world. How do you see AI impacting, right? If we look five years down the line, where do these agents, where do these assistants actually take us? how do they make us happier human beings? It's a great question, man.

35:38Anish Acharya:I mean, I do think that those are the problems that we're really after at the root of things. You know, we talked about productivity. We talked about finances and health. There's a lot of mundane things. You know, I was looking this up yesterday, but 1.5 million people a year in this country get a DUI. And look, like I can, the amount of administrative burden that's probably implied by that and how many of those people have access to attorneys. And so I do think there's almost this sort of bureaucratic pressure that's applied to the average consumer. So I think step one is how do we sort of relieve that bureaucratic pressure and have people, you know, be financially optimized, have their health be optimized and have them have the same access to whether it's an attorney or a kind of family office that somebody who's wealthy might have.

36:24Anish Acharya:Then I think the bigger question, you know, I grew up with my mother saying the hardest part about getting what you want is knowing what you want. is like, what are we all truly after? And what are the ways that these assistants can sort of engage us? And I don't think it's as simplistic as just goals. I don't know how many people even have goals. I think a lot of it is people are just trying to, you know, find out who they are and turn into the best, most authentic versions of themselves. And this kind of interplay between our own self-development and our subjective experience in the world and these machines could be a very beautiful future for us.

36:59Totally. I see this future where I envision this world where my future kids are going to be looking at old videos of the current generation walking down the street, you know, next crane down, staring at your phone. Yeah. What are you doing? Like, it is a beautiful world out there. Why are you spending all of your time staring at a screen?

37:19Anish Acharya:Yeah, I love that. Because in, you know, hopefully it's going to allow us to automate so many of those things. So as a parent, you can actually spend more time with your kids. As an adult in your 20s, you can actually spend more time talking to friends. And I'm really curious to see how it will just change life for the better in so many ways of reducing the things that you just really hate to do, but it's like the life admin work. Yeah, that's right. And that's also why I think that so many times coding agents are not computing with human programmers because they're doing things that no human programmers are doing.

37:52Anish Acharya:Whether it's building this ridiculous side project, I've been building a virtual record shop that you can walk into. I'll send you a link to it after. It's awesome. Like I would never hire a programmer to work on that five or seven, 10 years ago. I would have never spent the year of my life that it would have taken. So all of this stuff is the sort of things that never would have happened otherwise. And I think that there's a lot of versions of this technology in our life where we're just getting to explore things we never would have explored anyway. It's not about cost reduction. It's about possibility expansion.

38:24Anish Acharya:Yeah. makes life more fun. It makes life more interesting. You know, to kind of come back to the near term, a thing that I've been thinking a bunch about that I'm curious for your take on is, you know, the lessons of Moldbook and what are these sort of agent-native systems that are going to need to be built? And maybe this is some of what Instinct is doing with their kind of instinct-to-instinct network, but it does feel like there's going to be infrastructure and products that exist only for agent-to-agent interactions that doesn't exist today. What do you think? It's going to be a whole new paradigm.

38:57I think it opens up, and I think that can be a 10-hour conversation on its own. You have agent emails, you have agent phone numbers, you have what does the world of service look like when it's no longer human booking to human and no longer agent booking from human, but it's now agent booking from agent, and how does that redefine the entire service industry as a whole? And then you have the whole cybersecurity component of all this stuff, which is, okay, well, you know, internet came first, then came cybersecurity. Agents came first. Now comes the security component of these agents. And what industry is that going to create?

39:36The beautiful part of it, although I think that's the beauty of capitalism. There's like so much opportunity and so many problems to solve with these agents. And I think it is inevitable that we're going to see so many startups popping up trying to figure out all of these niche problems to really build this like new wave of internet and digital connectivity.

39:56Anish Acharya:Yeah, it's going to be cool to see, you know, because especially commerce, you know, I always think of the web as kind of, there's three webs within the web, you know, just like there's two wolves inside me. The three webs are the commerce web, the application web, and the content web. And the content web has been in trouble for a while. I think that the commerce web has actually done really well. And then the application web has definitely been on a huge upswing ever since coding agents were released. But the commerce web is fascinating. You know, you saw this week how Shopify embraced Muse and Amazon blocked Muse.

40:28Anish Acharya:I think part of the calculus is who's going to be a winner or a loser when you actually have a new front door for how traffic flows to these marketplaces. I mean, do you have a view on what specifically happened with Amazon and Shopify and maybe more broadly who the winners and losers are likely to be? Yeah, so I think, you know, first off, Shopify and Amazon are two completely different business models. You have Shopify that's hyper-focused on more democratizing commerce. You have Amazon that makes all of their money on ad revenue. And so the whole ad structure of commerce is going to be really fascinating to watch because when you remove human eyeballs, it defeats the entire purpose of the system.

41:05And so I think that's where Amazon was coming from. Like if you let Muse and these agents start to purchase without them getting any ad revenue out of that, it really takes a lot of the profit out of the experience. So I think there's likely going to have to be some new paradigm for how they're able to profit in this world where agents are purchasing on their behalf versus a Shopify that is empowering the everyday individual to sell as much as possible. And agents democratize this space even further. So it's just unbelievably advantageous. I think it's going to be even more interesting when we look at industries that have yet to be touched.

41:46and that's something we chatted about last week was restaurants, where if you look at the booking space, like you go to make a reservation, I think we saw Resi started shutting people's accounts down because they were using browser use and they didn't want bots. So it defeats the whole business of if you just let agents take these reservations instantaneously, then it kind of defeats the purpose of the platform of this human-oriented booking experience. And so what happens though, when everyone has an agent. Now everyone's on the same playing field. Everyone can go to book the restaurant at the same time.

42:22Do we enter a world where one, power goes back to the restaurants and they can maybe choose who they want to give the reservation to based off of loyalty or average spend or whatever it be? Or two, do we go into this world of bidding where everything becomes a bidding war between these agents? Curious your thoughts on kind of what that future looks like.

42:43Anish Acharya:Yeah, I think you're super right. I mean, very interesting because I think there'll be things that are supply constrained, like hot restaurant tables, things that are demand constrained, like people that want to fly to SF tomorrow. I think for restaurants, if you think about with perfect information, who do they want? To your point, it's the highest AOV, highest LTV, which means AOV over multiple visits. Plus, they actually want to ensure that they're at, you know, near 100 percent capacity as much as possible. So that's actually a more sophisticated calculation. And I don't quite know how they're going to do it.

43:13Anish Acharya:But I'm sure that proprietary supply is going to become more and more important, you know, versus relying on kind of friction and motivation from the end consumer to act as something that sort of prevents this DDoS. So I think supply constrained sort of aspects of commerce will be really interesting. And then demand constrained will be completely different, you know, where you almost have a group buying experience where you have a set of buyers that are willing to buy a product or a service or an experience. And then you have the supply side, the merchants that could potentially fulfill that need, come and, you know, bid to see who can do it, the best experience, maybe at the lowest price.

43:51Anish Acharya:So we've always had this kind of aggregation of demand, but we've never really had aggregation of supply in the same way, especially not in an auction system to benefit the consumer. So I think that's really interesting. You know, in the Amazon Shopify thing, I think that the Amazon, Amazon probably is rightly taking the bet that they don't want to be disintermediated and that they'll lose not just advertising revenue, but impulse shopping. I'm kind of curious to know if the agents themselves will be impulse shoppers to some extent, because I think the point around proactivity means the agents are going to try to make delightful guesses.

44:24Anish Acharya:And, you know, what is more delightful than a surprise or a gift? So I'm guessing that one of the really interesting sort of dynamics we're going to play out is that these agents are not perfect reflections of their principles. They're not perfectly rational. They're going to be non-rational in completely new ways. And I don't know that things like marketing, things like impulse purchases, things like advertising won't matter. I just think they need to be transformed. Totally. And I think that opens up a whole new conversation as well, which is what is the recommendation engine of this agentic commerce space actually look like.

45:00Because AI and LLMs feels like it's kind of broke the internet in terms of quality search. But then if you use an agent and you say, hey, buy me some white socks. There's like 20 ,000 different types of white socks out there. It's going to send you, it doesn't actually know what exact type of white socks you prefer. And so I think it'll be really interesting. I think Muse has probably a head start on this. and this is Zuck's whole thesis of attacks on all commerce where they have your Instagram data, they have your Facebook data, so they probably have a little better understanding of what you actually prefer.

45:33But it'll be really interesting to see what this recommendation layer looks like in this world of commerce.

45:40Anish Acharya:Well, I think it could be fun for the long tail, because you can imagine to your white socks example, I could go to Amazon and get white socks, but maybe my agent comes back and says, hey, I found someone awesome on Etsy that can knit you the socks. you know, Grandma Nebraska. And she just knits these amazing white socks. It's going to take three weeks. Are you down? I'm like, sure, I'm down. That sounds interesting. So I kind of wonder if it brings more serendipity in because of course, you know, it can examine all the options and perfectly tailor these things to you with no adverse incentives.

46:12Right. I would love that. I think that'd be so fun. It would definitely add a little flavor to the mundane life of shopping today.

46:20Anish Acharya:Exactly. Mundane from my point of view. as someone who, you know, doesn't take joy in sock shopping. Well, dude, and look, you can even imagine a world to get a little more futuristic where it starts to now catalyze things in the real world. So maybe instead of grandma who knits white socks and sells them on Etsy, you know, maybe it messages the agent of a grandma and says, hey, would you be up for doing this? So I think this is where the kind of agent-to-agent spaces get really interesting, where they're all acting on behalf of their humans, you know, Some to provide products, services, knowledge, and some to make money.

46:57Anish Acharya:And maybe there's this sort of secondary economy that's much more dynamic, much more high frequency, and just much more interesting than the one we have today. I'm just imagining now a grandma in Nebraska receiving a text message saying, hey, this guy in SF wants you to knit white socks for him. Why not? You want to do it? Why not? Yeah. Yeah. Why not? That'd be awesome. Yeah. So I'm actually very hopeful. You know, it also, it sort of sets the incentives in the right way because if the agents are doing the right thing, they're choosing great products based on product quality and they can assess product quality for themselves rather than, you know, the thing that has the best marketing or the best brand.

47:32Anish Acharya:And by the way, if they are choosing on a brand basis, it's at least with the explicit sign off of their user. Like, I just want to have Nikes because I love Nikes, not because, you know, there's sort of this cognitive dissonance that's happening in the marketing and the consumer is actually doing something that's not optimal for themselves. Right. It opens the door to a truly consumer-aligned internet, which I think we have been lacking for quite some time. I agree, man. We touched on the economics of the agents. Of the 122 that I have looked through, so I personally tested 26 of them. Okay. Of the 122, 65 are paid.

48:13Interesting. 35 of them are fully paid. 30 are a freemium model. so once you hit a limit, then you have to pay. Only 13 of them are actually free. When you have Muse and Instinct that are both free, that are also the dominant ones, and then you have OpenAI that supposedly is going to be releasing something cool maybe next week, who knows. How does a long-tail startup actually win this space? And why are they charging money when the big dogs are giving it to you for free?

48:44Anish Acharya:Man, it's going to be really challenging. You know, by our estimate, it's costing something like$20 per user per day to do this in a really ambitious way. You know, potentially hundreds of millions a year for a startup. I mean, I think the two positive trends to bet on are that browser use should get, should be deflationary, get exponentially cheaper very rapidly. Now, if you're a startup that is raising today, that's betting on that happening in six months, maybe it's a little bit of a game of chicken. but we have seen kind of token prices depress dramatically and sort of emerging capabilities depress.

49:17Anish Acharya:So the price of them. So I think it's very possible that browser use gets cheap enough that more products can offer this for free. I guess the flip though is that I don't love the idea of, you know, a customer subsidy being the primary value prop. So I'd love to see the agent that costs$1 ,000 a month that the consumer is so excited about that they're willing to pay. Like people spend$1 ,000 a month on a lot of different things that are not necessarily necessities. They're sort of desires. So what is the agent that is exciting enough that you're willing to pay that kind of price for it? And then that agent will benefit from both extreme market fit as well as sort of deflating costs.

49:56Right, right.

49:57Anish Acharya:I think it'll be interesting to see. Super interesting. Well, David from Assistant Bench, make sure everybody checks it out. Thank you so much for joining us. We're going to do this frequently. I mean, I feel like we could do this every week, dude. Things are happening every single day. So please follow him on X, follow me as well. We'll all keep up to speed and sort of learn together in the X community and sort of happy day to you and your agents. Appreciate it. Same to you. This was fun. All right, brother. Thank you. Awesome. Thanks for listening to this episode of the A16Z podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family.

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