I Gave Meta's Muse The Most Boring Job I Had. It Found $5,350 A Year.

You probably have a subscription you've You probably have a subscription you've meant to cancel, a bill you suspect is meant to cancel, a bill you suspect is meant to cancel, a bill you suspect is too high, or a refund you never found too high, or a refund you never found too high, or a refund you never found time to chase. You know there's MONEY time to chase. You know there's MONEY time to chase. You know there's MONEY THERE. GETTING IT BACK means finding the THERE. GETTING IT BACK means finding the THERE. GETTING IT BACK means finding the account and reading the rules and maybe account and reading the rules and maybe account and reading the rules and maybe spending lunch break with customer spending lunch break with customer spending lunch break with customer support. So, another month goes by and support. So, another month goes by and support. So, another month goes by and the money keeps getting spent out of the money keeps getting spent out of the money keeps getting spent out of your wallet. So, I had that problem, your wallet. So, I had that problem, your wallet. So, I had that problem, too. I gave that job to Meta's new too. I gave that job to Meta's new too. I gave that job to Meta's new assistant, Muse. It found 5,350 assistant, Muse. It found 5,350 assistant, Muse. It found 5,350 bucks a year that I am spending on bucks a year that I am spending on bucks a year that I am spending on subscriptions. So far, it's canceled subscriptions. So far, it's canceled subscriptions. So far, it's canceled 1,285 of that, which is money I WAS 1,285 of that, which is money I WAS 1,285 of that, which is money I WAS GOING TO SPEND IN the future by default GOING TO SPEND IN the future by default GOING TO SPEND IN the future by default on stuff I don't use. So, yeah, it's on stuff I don't use. So, yeah, it's on stuff I don't use. So, yeah, it's kind of good to have it back. And this kind of good to have it back. And this kind of good to have it back. And this is what I didn't expect that the boring is what I didn't expect that the boring is what I didn't expect that the boring job that I just described for you is job that I just described for you is job that I just described for you is exactly why Amazon locked it out of the exactly why Amazon locked it out of the exactly why Amazon locked it out of the store. Amazon has its own stated store. Amazon has its own stated store. Amazon has its own stated reasons, and I'm going to get into them, reasons, and I'm going to get into them, reasons, and I'm going to get into them, but I don't think that one of the but I don't think that one of the but I don't think that one of the biggest companies in the world blocks an biggest companies in the world blocks an biggest companies in the world blocks an AI assistant over paperwork. I think it AI assistant over paperwork. I think it AI assistant over paperwork. I think it blocks an AI assistant that changes blocks an AI assistant that changes blocks an AI assistant that changes where you spend your attention. Meta where you spend your attention. Meta where you spend your attention. Meta Ship Muse on September 8th. Inside two Ship Muse on September 8th. Inside two Ship Muse on September 8th. Inside two weeks, it has become the number one weeks, it has become the number one weeks, it has become the number one iPhone app in America. It is being iPhone app in America. It is being iPhone app in America. It is being adopted much faster than Chat GBT at adopted much faster than Chat GBT at adopted much faster than Chat GBT at this stage. So, this video is about two this stage. So, this video is about two this stage. So, this video is about two things. Number one, what is it actually things. Number one, what is it actually things. Number one, what is it actually like to hand a real life job that saves like to hand a real life job that saves like to hand a real life job that saves money to Muse and have it save me the money to Muse and have it save me the money to Muse and have it save me the time and the money that it would time and the money that it would time and the money that it would otherwise take to do that job? And then otherwise take to do that job? And then otherwise take to do that job? And then number two, why does doing that small number two, why does doing that small number two, why does doing that small personal job have one of the largest personal job have one of the largest personal job have one of the largest retailers in the world paying attention?

retailers in the world paying attention? retailers in the world paying attention? But first, let's get into Muse. Look at But first, let's get into Muse. Look at But first, let's get into Muse. Look at the jobs people are already handing the jobs people are already handing the jobs people are already handing over. Uh Chris Abraham said Muse found a over. Uh Chris Abraham said Muse found a over. Uh Chris Abraham said Muse found a book subscription his family had book subscription his family had book subscription his family had forgotten to cancel and cancelled it, forgotten to cancel and cancelled it, forgotten to cancel and cancelled it, checked the refund policy, and recovered checked the refund policy, and recovered checked the refund policy, and recovered a year's worth of payments. He doesn't a year's worth of payments. He doesn't a year's worth of payments. He doesn't give a dollar figure for that, but it's give a dollar figure for that, but it's give a dollar figure for that, but it's going to be sizable. The interesting going to be sizable. The interesting going to be sizable. The interesting part is that Muse went ahead and pursued part is that Muse went ahead and pursued part is that Muse went ahead and pursued and went after that refund. How often do and went after that refund. How often do and went after that refund. How often do you cancel something and decide arguing you cancel something and decide arguing you cancel something and decide arguing about the old charges you didn't intend about the old charges you didn't intend about the old charges you didn't intend would take more effort than it was would take more effort than it was would take more effort than it was worth? Another early news user named worth? Another early news user named worth? Another early news user named Brad, these are all reports that I found Brad, these are all reports that I found Brad, these are all reports that I found around the internet, right? They're around the internet, right? They're around the internet, right? They're publicly available. He reports that news publicly available. He reports that news publicly available. He reports that news spent 98 minutes on the phone with AT&T spent 98 minutes on the phone with AT&T spent 98 minutes on the phone with AT&T through multiple transfers while also through multiple transfers while also through multiple transfers while also contacting Verizon and T-Mobile to contacting Verizon and T-Mobile to contacting Verizon and T-Mobile to compare phone offers. She says it spared compare phone offers. She says it spared compare phone offers. She says it spared him more than 3 hours of calls. Getting him more than 3 hours of calls. Getting him more than 3 hours of calls. Getting those hours back is something that you those hours back is something that you those hours back is something that you can't put a price on. Imagine can't put a price on. Imagine can't put a price on. Imagine multiplying that across 100 million multiplying that across 100 million multiplying that across 100 million people. Now, these phone call stories people. Now, these phone call stories people. Now, these phone call stories are early. Reuters has reported that are early. Reuters has reported that are early. Reuters has reported that Meta tested having human contractors Meta tested having human contractors Meta tested having human contractors handle some Muse calls for employees and handle some Muse calls for employees and handle some Muse calls for employees and the company rolled the experiment back the company rolled the experiment back the company rolled the experiment back after concerns about disclosure and after concerns about disclosure and after concerns about disclosure and privacy. And so one of the things that privacy. And so one of the things that privacy. And so one of the things that we need to be aware of is that Meta we need to be aware of is that Meta we need to be aware of is that Meta doesn't tell you clearly when another doesn't tell you clearly when another doesn't tell you clearly when another person will receive information and act person will receive information and act person will receive information and act for you. At the moment it seems like for you. At the moment it seems like for you. At the moment it seems like Muse is saying it handles the calls Muse is saying it handles the calls Muse is saying it handles the calls autonomously, but there's not as much autonomously, but there's not as much autonomously, but there's not as much transparency around that as as I would transparency around that as as I would transparency around that as as I would like to see. But I view that as an early like to see. But I view that as an early like to see. But I view that as an early teething issue. We are going to get to teething issue. We are going to get to teething issue. We are going to get to the phone call piece. Meta may have

the phone call piece. Meta may have the phone call piece. Meta may have already rolled out that automated phone already rolled out that automated phone already rolled out that automated phone call piece well enough in many cases and call piece well enough in many cases and call piece well enough in many cases and it just hasn't told that story as it just hasn't told that story as it just hasn't told that story as clearly as we'd all like to see. And the clearly as we'd all like to see. And the clearly as we'd all like to see. And the larger story is around the work saved larger story is around the work saved larger story is around the work saved for for so many of us. The bills, the for for so many of us. The bills, the for for so many of us. The bills, the subscriptions, these problems have subscriptions, these problems have subscriptions, these problems have existed long before AI models came existed long before AI models came existed long before AI models came around, right? How long have you looked around, right? How long have you looked around, right? How long have you looked at paperwork and said, "I can't do all at paperwork and said, "I can't do all at paperwork and said, "I can't do all of this." Or looked at charges and said, of this." Or looked at charges and said, of this." Or looked at charges and said, "I don't have time to investigate this." "I don't have time to investigate this." "I don't have time to investigate this." Or maybe a health bill you can't trust. Or maybe a health bill you can't trust. Or maybe a health bill you can't trust. Or haven't had time to get on the phone Or haven't had time to get on the phone Or haven't had time to get on the phone and call. And so when you see value and call. And so when you see value and call. And so when you see value there, you can see how that spreads there, you can see how that spreads there, you can see how that spreads virally and that's part of why Muse is virally and that's part of why Muse is virally and that's part of why Muse is the number one app in the Apple download the number one app in the Apple download the number one app in the Apple download store. So another couple of stories. I store. So another couple of stories. I store. So another couple of stories. I love these stories because they show love these stories because they show love these stories because they show concrete value for AI in a way that so concrete value for AI in a way that so concrete value for AI in a way that so many of the stories out of the valley many of the stories out of the valley many of the stories out of the valley don't. And again, these are all publicly don't. And again, these are all publicly don't. And again, these are all publicly reported. So Joe Devoy reported reported. So Joe Devoy reported reported. So Joe Devoy reported thousands in annual car insurance thousands in annual car insurance thousands in annual car insurance savings cuz he worked with Muse. Jason savings cuz he worked with Muse. Jason savings cuz he worked with Muse. Jason Longo saw an insurance post and tried a Longo saw an insurance post and tried a Longo saw an insurance post and tried a similar job while he was at the gym and similar job while he was at the gym and similar job while he was at the gym and reported $1,156 a year in savings on reported $1,156 a year in savings on reported $1,156 a year in savings on insurance. So, he was exercising while insurance. So, he was exercising while insurance. So, he was exercising while Muse sorted that out. What we can see in Muse sorted that out. What we can see in Muse sorted that out. What we can see in these stories that's really fun is that these stories that's really fun is that these stories that's really fun is that people are realizing that this is people are realizing that this is people are realizing that this is possible. That Muse can save you money.

possible. That Muse can save you money. possible. That Muse can save you money. Phone call or not, Muse can save you Phone call or not, Muse can save you Phone call or not, Muse can save you money. And they're just sharing it money. And they're just sharing it money. And they're just sharing it around and Muse is going around and around and Muse is going around and around and Muse is going around and helping each person sort of figure out helping each person sort of figure out helping each person sort of figure out what works for them with their data to what works for them with their data to what works for them with their data to the degree that they're comfortable the degree that they're comfortable the degree that they're comfortable sharing it. And that's really exciting sharing it. And that's really exciting sharing it. And that's really exciting because it becomes this sort of viral because it becomes this sort of viral because it becomes this sort of viral sharing moment of, "Hey, I got Muse to sharing moment of, "Hey, I got Muse to sharing moment of, "Hey, I got Muse to help me save. Hey, I got Muse to help me help me save. Hey, I got Muse to help me help me save. Hey, I got Muse to help me save." And I love that because we all save." And I love that because we all save." And I love that because we all could use some dollars back in the could use some dollars back in the could use some dollars back in the pocket. And it extends beyond money, pocket. And it extends beyond money, pocket. And it extends beyond money, too. A parent reports using Muse to too. A parent reports using Muse to too. A parent reports using Muse to combine schedules for four different combine schedules for four different combine schedules for four different kids in four sports across four kids in four sports across four kids in four sports across four messaging apps in one daily messaging apps in one daily messaging apps in one daily notification. Look, I I have I have notification. Look, I I have I have notification. Look, I I have I have kids. Dealing with that kind of kids. Dealing with that kind of kids. Dealing with that kind of coordination, that speaks to me. Knowing coordination, that speaks to me. Knowing coordination, that speaks to me. Knowing where the information lives is not where the information lives is not where the information lives is not enough. Someone has to go through and enough. Someone has to go through and enough. Someone has to go through and collect it and reconcile it and remember collect it and reconcile it and remember collect it and reconcile it and remember what matters today. That was one of the what matters today. That was one of the what matters today. That was one of the early uses for Open Claw. And here we early uses for Open Claw. And here we early uses for Open Claw. And here we see something that is sort of packaged see something that is sort of packaged see something that is sort of packaged virally that sits there with a nice virally that sits there with a nice virally that sits there with a nice little avatar that just sorts it out for little avatar that just sorts it out for little avatar that just sorts it out for you. And this kind of load, we call this you. And this kind of load, we call this you. And this kind of load, we call this adulting. We call this parenting. This adulting. We call this parenting. This adulting. We call this parenting. This is work many of us have simply accepted is work many of us have simply accepted is work many of us have simply accepted as a part of life. uh like you you may as a part of life. uh like you you may as a part of life. uh like you you may be the person in your life who's be the person in your life who's be the person in your life who's connecting the calendar to the email to connecting the calendar to the email to connecting the calendar to the email to the website to the phone call for the the website to the phone call for the the website to the phone call for the family and the possibility of actually family and the possibility of actually family and the possibility of actually having real useful help there. That's having real useful help there. That's having real useful help there. That's way way better than having a frontier way way better than having a frontier way way better than having a frontier model. It's actual value for you. But model. It's actual value for you. But model. It's actual value for you. But when you have to carry that whole thing when you have to carry that whole thing when you have to carry that whole thing in your head, it's a lot of in your head, it's a lot of in your head, it's a lot of responsibility. Muse is built for things responsibility. Muse is built for things responsibility. Muse is built for things like that. It's the kind of ordinary like that. It's the kind of ordinary like that. It's the kind of ordinary benefit that I think the AI industry has benefit that I think the AI industry has benefit that I think the AI industry has been remarkably bad at explaining. Just been remarkably bad at explaining. Just been remarkably bad at explaining. Just to be very honest, people hear about

to be very honest, people hear about to be very honest, people hear about data centers. We hear about the next data centers. We hear about the next data centers. We hear about the next intelligence breakthrough. We hear about intelligence breakthrough. We hear about intelligence breakthrough. We hear about arguments about what happens to jobs. arguments about what happens to jobs. arguments about what happens to jobs. And those concerns are real. But someone And those concerns are real. But someone And those concerns are real. But someone looking after a family needs an answer looking after a family needs an answer looking after a family needs an answer to what this tech will do for them now to what this tech will do for them now to what this tech will do for them now and whether it's useful. And so getting and whether it's useful. And so getting and whether it's useful. And so getting real useful help with their priorities real useful help with their priorities real useful help with their priorities gives them a reason to participate, gives them a reason to participate, gives them a reason to participate, gives us a reason to participate. We all gives us a reason to participate. We all gives us a reason to participate. We all have families. We get to decide what is have families. We get to decide what is have families. We get to decide what is important enough to ask for help with. important enough to ask for help with. important enough to ask for help with. And Muse gives us a tool that is And Muse gives us a tool that is And Muse gives us a tool that is genuinely helpful and accessible to genuinely helpful and accessible to genuinely helpful and accessible to everyone, whether you're technical or everyone, whether you're technical or everyone, whether you're technical or not. I've made a lot of this YouTube not. I've made a lot of this YouTube not. I've made a lot of this YouTube channel around how you learn to use channel around how you learn to use channel around how you learn to use these tools because they're not these tools because they're not these tools because they're not self-explanatory. self-explanatory. self-explanatory. Muse is a lot more self-explanatory. You Muse is a lot more self-explanatory. You Muse is a lot more self-explanatory. You get one main conversation with a get one main conversation with a get one main conversation with a companion you can name. Uh I named mine companion you can name. Uh I named mine companion you can name. Uh I named mine Marvin because I like Douglas Adams. You Marvin because I like Douglas Adams. You Marvin because I like Douglas Adams. You can open side chats and set goals and can open side chats and set goals and can open side chats and set goals and give it more information, but you can give it more information, but you can give it more information, but you can also just come back and ask the next also just come back and ask the next also just come back and ask the next question. You can switch topics. You question. You can switch topics. You question. You can switch topics. You don't have to begin again by deciding don't have to begin again by deciding don't have to begin again by deciding where this part of your life belongs in where this part of your life belongs in where this part of your life belongs in a collection of projects and threads.

a collection of projects and threads. a collection of projects and threads. And the avatar, it gives you a sense And the avatar, it gives you a sense And the avatar, it gives you a sense that you're having a relationship with a that you're having a relationship with a that you're having a relationship with a familiar face, right? And I think people familiar face, right? And I think people familiar face, right? And I think people people want that. We remember our people want that. We remember our people want that. We remember our Tamagotchis from the '90s. something Tamagotchis from the '90s. something Tamagotchis from the '90s. something people feel comfortable talking to, people feel comfortable talking to, people feel comfortable talking to, something that remembers us enough to be something that remembers us enough to be something that remembers us enough to be useful, that is there when we need help. useful, that is there when we need help. useful, that is there when we need help. And so, a company logo in a new And so, a company logo in a new And so, a company logo in a new conversation doesn't create that conversation doesn't create that conversation doesn't create that feeling. But a character, a cute fuzzy feeling. But a character, a cute fuzzy feeling. But a character, a cute fuzzy bear kind of character, that makes it bear kind of character, that makes it bear kind of character, that makes it easier to imagine coming back and asking easier to imagine coming back and asking easier to imagine coming back and asking for help. Another detail I noticed is for help. Another detail I noticed is for help. Another detail I noticed is the way status is communicated to the way status is communicated to the way status is communicated to non-technical audiences. When I looked non-technical audiences. When I looked non-technical audiences. When I looked at how Marvin was searching through at how Marvin was searching through at how Marvin was searching through sources or checking sites, it just gives sources or checking sites, it just gives sources or checking sites, it just gives you a little emoji and it gives you a you a little emoji and it gives you a you a little emoji and it gives you a little phrase for what Marvin is doing little phrase for what Marvin is doing little phrase for what Marvin is doing and then Marvin visually changes. and then Marvin visually changes. and then Marvin visually changes. Marvin's a 3D avatar and visually starts Marvin's a 3D avatar and visually starts Marvin's a 3D avatar and visually starts typing away at the laptop and you know typing away at the laptop and you know typing away at the laptop and you know that Marvin is working. is just super that Marvin is working. is just super that Marvin is working. is just super intuitive and I think it gives you a way intuitive and I think it gives you a way intuitive and I think it gives you a way to immediately without reading without to immediately without reading without to immediately without reading without thinking distinguish a proposed action thinking distinguish a proposed action thinking distinguish a proposed action from a completed action an inrogress from a completed action an inrogress from a completed action an inrogress action from a completed action. And so action from a completed action. And so action from a completed action. And so it was really really simple for me to it was really really simple for me to it was really really simple for me to see when I was kind of working through see when I was kind of working through see when I was kind of working through the subscription cancellation process the subscription cancellation process the subscription cancellation process when was Marvin working and what was when was Marvin working and what was when was Marvin working and what was Marvin doing. A good assistant needs to Marvin doing. A good assistant needs to Marvin doing. A good assistant needs to make those stages clear without make those stages clear without make those stages clear without requiring you to even think about the requiring you to even think about the requiring you to even think about the fact that you know that like it should fact that you know that like it should fact that you know that like it should just disappear. Onboarding follows the just disappear. Onboarding follows the just disappear. Onboarding follows the same logic of simplicity. With Muse, all same logic of simplicity. With Muse, all same logic of simplicity. With Muse, all you do initially is get a phone number you do initially is get a phone number you do initially is get a phone number and then everything branches out from

and then everything branches out from and then everything branches out from there. It will connect an account like a there. It will connect an account like a there. It will connect an account like a Gmail or a calendar when it makes sense Gmail or a calendar when it makes sense Gmail or a calendar when it makes sense conversationally as a choice you can conversationally as a choice you can conversationally as a choice you can make and you can tell it about yourself make and you can tell it about yourself make and you can tell it about yourself gradually. Uh, in fact, when I asked gradually. Uh, in fact, when I asked gradually. Uh, in fact, when I asked Marvin, how do you know stuff about me? Marvin, how do you know stuff about me? Marvin, how do you know stuff about me? How Marvin was really clear to say, and How Marvin was really clear to say, and How Marvin was really clear to say, and this was coming straight from the this was coming straight from the this was coming straight from the project instructions given by Muse, project instructions given by Muse, project instructions given by Muse, given by the Muse team, it doesn't fish given by the Muse team, it doesn't fish given by the Muse team, it doesn't fish for information. It will let me share for information. It will let me share for information. It will let me share and it will keep track of what I choose and it will keep track of what I choose and it will keep track of what I choose to share, but it doesn't want to go to share, but it doesn't want to go to share, but it doesn't want to go fishing. And I think that's also fishing. And I think that's also fishing. And I think that's also something that builds trust when Meta is something that builds trust when Meta is something that builds trust when Meta is a company that has a ton of your data. a company that has a ton of your data. a company that has a ton of your data. Anyway, now these details are all things Anyway, now these details are all things Anyway, now these details are all things you can copy, right? You can copy an you can copy, right? You can copy an you can copy, right? You can copy an avatar. You can copy a status pill. You avatar. You can copy a status pill. You avatar. You can copy a status pill. You can copy continuous conversation. I can copy continuous conversation. I can copy continuous conversation. I still think even in that world, Muse is still think even in that world, Muse is still think even in that world, Muse is a product masterclass in making useful a product masterclass in making useful a product masterclass in making useful capability for AI approachable. The capability for AI approachable. The capability for AI approachable. The individual choices don't have to be individual choices don't have to be individual choices don't have to be unprecedented. They have to work unprecedented. They have to work unprecedented. They have to work together coherently and well enough that together coherently and well enough that together coherently and well enough that someone who has never cared about AI can someone who has never cared about AI can someone who has never cared about AI can use it to get help. And the reason I use it to get help. And the reason I use it to get help. And the reason I started this video with all these started this video with all these started this video with all these individual stories is because that is individual stories is because that is individual stories is because that is what is happening with Muse. That is why what is happening with Muse. That is why what is happening with Muse. That is why Muse is special. And ordinary use is Muse is special. And ordinary use is Muse is special. And ordinary use is free, which I think is how consumer AI free, which I think is how consumer AI free, which I think is how consumer AI is going to go. Meta offers paid is going to go. Meta offers paid is going to go. Meta offers paid subscriptions for people who need more.

subscriptions for people who need more. subscriptions for people who need more. But the main stated plan is to make Muse But the main stated plan is to make Muse But the main stated plan is to make Muse free for most of what people want to do. free for most of what people want to do. free for most of what people want to do. Mark Zuckerberg described a substantial Mark Zuckerberg described a substantial Mark Zuckerberg described a substantial free allowance when it launched. You free allowance when it launched. You free allowance when it launched. You don't need to understand or think about don't need to understand or think about don't need to understand or think about token count to understand the decisions. token count to understand the decisions. token count to understand the decisions. I haven't run into issues with the I haven't run into issues with the I haven't run into issues with the usage. Meta wants a very large number of usage. Meta wants a very large number of usage. Meta wants a very large number of people to not only try this but use it people to not only try this but use it people to not only try this but use it regularly without facing costs and that regularly without facing costs and that regularly without facing costs and that changes who the product can reach and changes who the product can reach and changes who the product can reach and there's limited international roll out there's limited international roll out there's limited international roll out but there's very very aggressive but there's very very aggressive but there's very very aggressive interest and I expect Muse to continue interest and I expect Muse to continue interest and I expect Muse to continue to roll out globally as they can kind of to roll out globally as they can kind of to roll out globally as they can kind of get the regulatory pieces figured out get the regulatory pieces figured out get the regulatory pieces figured out and feel comfortable launching. What and feel comfortable launching. What and feel comfortable launching. What happens next? Let's say it's the number happens next? Let's say it's the number happens next? Let's say it's the number one app store. Where do we go from here? one app store. Where do we go from here? one app store. Where do we go from here? How do you build an app that people find How do you build an app that people find How do you build an app that people find useful over time? I started this video useful over time? I started this video useful over time? I started this video by talking about the fact that, you by talking about the fact that, you by talking about the fact that, you know, Muse helped me save $1,200 over know, Muse helped me save $1,200 over know, Muse helped me save $1,200 over the next year. How do I then trust Muse the next year. How do I then trust Muse the next year. How do I then trust Muse with more stuff? Look at the habit that with more stuff? Look at the habit that with more stuff? Look at the habit that you form when you work with AI. Let's you form when you work with AI. Let's you form when you work with AI. Let's say you've asked your AI assistant to say you've asked your AI assistant to say you've asked your AI assistant to help sort through your spending. Later help sort through your spending. Later help sort through your spending. Later you need a new appliance. Later you need you need a new appliance. Later you need you need a new appliance. Later you need to book a hotel. Later you need a better to book a hotel. Later you need a better to book a hotel. Later you need a better phone plan. Do you go back to the AI phone plan. Do you go back to the AI phone plan. Do you go back to the AI avatar that already understands some of avatar that already understands some of avatar that already understands some of your preferences and has done really your preferences and has done really your preferences and has done really useful work for you or do you go useful work for you or do you go useful work for you or do you go somewhere else? The world we're living somewhere else? The world we're living somewhere else? The world we're living in is a world where the company that is in is a world where the company that is in is a world where the company that is selling you the product, the company selling you the product, the company selling you the product, the company selling the hotel, the company selling selling the hotel, the company selling selling the hotel, the company selling the flight, the company selling the the flight, the company selling the the flight, the company selling the appliance, they may only enter the appliance, they may only enter the appliance, they may only enter the conversation after you and the agent

conversation after you and the agent conversation after you and the agent have already started to work together. have already started to work together. have already started to work together. And I think that is why so many And I think that is why so many And I think that is why so many companies including Walmart have lined companies including Walmart have lined companies including Walmart have lined up, including Shopify, have lined up to up, including Shopify, have lined up to up, including Shopify, have lined up to do deals with Muse early because they do deals with Muse early because they do deals with Muse early because they want to make sure that Muse doesn't want to make sure that Muse doesn't want to make sure that Muse doesn't disintermediate their consumer disintermediate their consumer disintermediate their consumer relationships. That's how a platform relationships. That's how a platform relationships. That's how a platform develops. Businesses have to think about develops. Businesses have to think about develops. Businesses have to think about how to serve you through the place you how to serve you through the place you how to serve you through the place you already go for help. Amazon and Amazon's already go for help. Amazon and Amazon's already go for help. Amazon and Amazon's response to Muse makes the stakes here response to Muse makes the stakes here response to Muse makes the stakes here really, really clear. And I used to work really, really clear. And I used to work really, really clear. And I used to work at Amazon. This was very very obvious at Amazon. This was very very obvious at Amazon. This was very very obvious what they were going to do. When you what they were going to do. When you what they were going to do. When you search for a product on Amazon, the search for a product on Amazon, the search for a product on Amazon, the Amazon has an opportunity to influence Amazon has an opportunity to influence Amazon has an opportunity to influence what you buy, right? Sellers pay for what you buy, right? Sellers pay for what you buy, right? Sellers pay for sponsored placements in search results sponsored placements in search results sponsored placements in search results and on product pages and they are paying and on product pages and they are paying and on product pages and they are paying to reach you while you are on that page to reach you while you are on that page to reach you while you are on that page thinking about a purchase. Owning that thinking about a purchase. Owning that thinking about a purchase. Owning that moment is a tremendously valuable moment is a tremendously valuable moment is a tremendously valuable business for Amazon. Amazon in fact business for Amazon. Amazon in fact business for Amazon. Amazon in fact reported $68.6 reported $68.6 reported $68.6 billion in ad revenue in 2025. A lot of billion in ad revenue in 2025. A lot of billion in ad revenue in 2025. A lot of people don't know that advertising people don't know that advertising people don't know that advertising profit isn't disclosed separately, so we profit isn't disclosed separately, so we profit isn't disclosed separately, so we can't put an exact profit number there, can't put an exact profit number there, can't put an exact profit number there, but ad businesses are typically but ad businesses are typically but ad businesses are typically extremely profitable. And the ad extremely profitable. And the ad extremely profitable. And the ad business is enormous. And the ad business is enormous. And the ad business is enormous. And the ad business as a whole tends to drive more business as a whole tends to drive more business as a whole tends to drive more bottomline value than the retail bottomline value than the retail bottomline value than the retail business for Amazon. And a lot of people business for Amazon. And a lot of people business for Amazon. And a lot of people don't know that either. They think don't know that either. They think don't know that either. They think Amazon makes a ton of money off of Amazon makes a ton of money off of Amazon makes a ton of money off of retail. They don't. Generally, retail. They don't. Generally, retail. They don't. Generally, advertising matters a lot to keep retail advertising matters a lot to keep retail advertising matters a lot to keep retail sustainable. Now imagine asking Muse to sustainable. Now imagine asking Muse to sustainable. Now imagine asking Muse to find an appliance that fits your space

find an appliance that fits your space find an appliance that fits your space and your budget and has a delivery date and your budget and has a delivery date and your budget and has a delivery date and it compares options and brings you a and it compares options and brings you a and it compares options and brings you a recommendation and if you accept the recommendation and if you accept the recommendation and if you accept the retailer gets a purchase from someone retailer gets a purchase from someone retailer gets a purchase from someone whose decision has been made elsewhere whose decision has been made elsewhere whose decision has been made elsewhere and the opportunity to sell visibility and the opportunity to sell visibility and the opportunity to sell visibility to that customer has has moved. Are you to that customer has has moved. Are you to that customer has has moved. Are you selling to the agent now? And this is selling to the agent now? And this is selling to the agent now? And this is why Amazon's decision is a platform why Amazon's decision is a platform why Amazon's decision is a platform fight and why I wasn't surprised at all fight and why I wasn't surprised at all fight and why I wasn't surprised at all coming from Amazon. Amazon says that coming from Amazon. Amazon says that coming from Amazon. Amazon says that Muse didn't properly identify itself and Muse didn't properly identify itself and Muse didn't properly identify itself and accessed its store without agreement and accessed its store without agreement and accessed its store without agreement and appeared to capture and store customer appeared to capture and store customer appeared to capture and store customer credentials. Now, those are stated credentials. Now, those are stated credentials. Now, those are stated objections and that's fair, but the objections and that's fair, but the objections and that's fair, but the larger commercial reason is not larger commercial reason is not larger commercial reason is not something they're going to say publicly something they're going to say publicly something they're going to say publicly because ultimately the conversation is because ultimately the conversation is because ultimately the conversation is not about Meta having credentials that not about Meta having credentials that not about Meta having credentials that go into protected storage, although it go into protected storage, although it go into protected storage, although it does. um it is about who owns the does. um it is about who owns the does. um it is about who owns the customer relationships. It's not about a customer relationships. It's not about a customer relationships. It's not about a dispute over technical rules. So my read dispute over technical rules. So my read dispute over technical rules. So my read is that Amazon is focusing on protecting is that Amazon is focusing on protecting is that Amazon is focusing on protecting its ability to shape the purchase its ability to shape the purchase its ability to shape the purchase journey and it wants to make sure that journey and it wants to make sure that journey and it wants to make sure that that ad business is supported and safe.

that ad business is supported and safe. that ad business is supported and safe. Now Mark Zuckerberg has described how Now Mark Zuckerberg has described how Now Mark Zuckerberg has described how Meta might earn money here. Over time, Meta might earn money here. Over time, Meta might earn money here. Over time, Mark expects to take a small fee on Mark expects to take a small fee on Mark expects to take a small fee on transactions potentially paid by the transactions potentially paid by the transactions potentially paid by the businesses involved. And that gives us a businesses involved. And that gives us a businesses involved. And that gives us a very clear explanation of how a consumer very clear explanation of how a consumer very clear explanation of how a consumer product stays free over time. If Muse product stays free over time. If Muse product stays free over time. If Muse becomes a source of customers, becomes a source of customers, becomes a source of customers, businesses have a reason to pay for the businesses have a reason to pay for the businesses have a reason to pay for the commerce that Muse helps create. And commerce that Muse helps create. And commerce that Muse helps create. And some of the infrastructure for that is some of the infrastructure for that is some of the infrastructure for that is already taking shape. So, Shopify added already taking shape. So, Shopify added already taking shape. So, Shopify added Meta. As I mentioned, it's an AI channel Meta. As I mentioned, it's an AI channel Meta. As I mentioned, it's an AI channel for its merchants. Stripe has equipped for its merchants. Stripe has equipped for its merchants. Stripe has equipped Muse with link payments, including a Muse with link payments, including a Muse with link payments, including a virtual card that is limited to approved virtual card that is limited to approved virtual card that is limited to approved purchases. Uh, I've already set it up purchases. Uh, I've already set it up purchases. Uh, I've already set it up for you. Those connections can make it for you. Those connections can make it for you. Those connections can make it easier for a useful suggestion to become easier for a useful suggestion to become easier for a useful suggestion to become a order that just gets done without you. a order that just gets done without you. a order that just gets done without you. I It was very seamless when I used it to I It was very seamless when I used it to I It was very seamless when I used it to plan date night. For businesses, this plan date night. For businesses, this plan date night. For businesses, this makes it possible to serve a customer makes it possible to serve a customer makes it possible to serve a customer that started and ended the journey that started and ended the journey that started and ended the journey without ever touching the site. and without ever touching the site. and without ever touching the site. and those platform connections start to add those platform connections start to add those platform connections start to add up. If your assistant can deal with more up. If your assistant can deal with more up. If your assistant can deal with more and more and more and more of the and more and more and more of the and more and more and more of the businesses that you work with as a businesses that you work with as a businesses that you work with as a consumer or as a business owner, there's consumer or as a business owner, there's consumer or as a business owner, there's less work left for you to finish less work left for you to finish less work left for you to finish somewhere else. And so each business somewhere else. And so each business somewhere else. And so each business connecting into Muse makes it easier for connecting into Muse makes it easier for connecting into Muse makes it easier for another customer to try Muse. That's how another customer to try Muse. That's how another customer to try Muse. That's how distribution and execution start to distribution and execution start to distribution and execution start to build on each other with network build on each other with network build on each other with network effects. Very long term, I see this as a effects. Very long term, I see this as a effects. Very long term, I see this as a run at some of the economic value that run at some of the economic value that run at some of the economic value that Amazon and Google capture through Amazon and Google capture through Amazon and Google capture through attention. So, Amazon captures through attention. So, Amazon captures through attention. So, Amazon captures through advertising, Google captures through advertising, Google captures through advertising, Google captures through advertising. Meta can get paid through advertising. Meta can get paid through advertising. Meta can get paid through transaction fees when it helps to

transaction fees when it helps to transaction fees when it helps to influence purchases, which is also the influence purchases, which is also the influence purchases, which is also the business Google and Amazon are in. And business Google and Amazon are in. And business Google and Amazon are in. And so, the valuable relationship is the so, the valuable relationship is the so, the valuable relationship is the person choosing where to spend and person choosing where to spend and person choosing where to spend and owning that relationship. And that's owning that relationship. And that's owning that relationship. And that's something that Mark Zuckerberg sees an something that Mark Zuckerberg sees an something that Mark Zuckerberg sees an opportunity for. Now, it's instructive opportunity for. Now, it's instructive opportunity for. Now, it's instructive to compare Amazon and Walmart here. to compare Amazon and Walmart here. to compare Amazon and Walmart here. Walmart has a different calculation. Walmart has a different calculation. Walmart has a different calculation. Meta named it among the retailers Meta named it among the retailers Meta named it among the retailers joining Musea Connect. Walmart competes joining Musea Connect. Walmart competes joining Musea Connect. Walmart competes with Amazon online, of course, and has a with Amazon online, of course, and has a with Amazon online, of course, and has a re reason to welcome a new way for re reason to welcome a new way for re reason to welcome a new way for customers to find products. If an customers to find products. If an customers to find products. If an assistant brings in someone who would assistant brings in someone who would assistant brings in someone who would otherwise have started on Amazon, that otherwise have started on Amazon, that otherwise have started on Amazon, that can be a really useful opportunity for can be a really useful opportunity for can be a really useful opportunity for them. Walmart does have an advertising them. Walmart does have an advertising them. Walmart does have an advertising business as well, uh, but it's smaller, business as well, uh, but it's smaller, business as well, uh, but it's smaller, right? It's $6.4 billion in the last right? It's $6.4 billion in the last right? It's $6.4 billion in the last fiscal year. So, it has something to fiscal year. So, it has something to fiscal year. So, it has something to protect, but it's about 10 times smaller protect, but it's about 10 times smaller protect, but it's about 10 times smaller in terms of ad revenue than Amazon at in terms of ad revenue than Amazon at in terms of ad revenue than Amazon at this point. So I think the difference is this point. So I think the difference is this point. So I think the difference is in competitive position right a new in competitive position right a new in competitive position right a new shopping starting point can look shopping starting point can look shopping starting point can look attractive to a challenger in a space attractive to a challenger in a space attractive to a challenger in a space and threatening to the company namely and threatening to the company namely and threatening to the company namely Amazon that is defending an existing Amazon that is defending an existing Amazon that is defending an existing shopping habit. [snorts] Other retailers shopping habit. [snorts] Other retailers shopping habit. [snorts] Other retailers and Shopify merchants have their own and Shopify merchants have their own and Shopify merchants have their own reasons to participate and we can get reasons to participate and we can get reasons to participate and we can get into that but ultimately it's about into that but ultimately it's about into that but ultimately it's about connecting with what they perceive as a connecting with what they perceive as a connecting with what they perceive as a winner which in turn makes it more winner which in turn makes it more winner which in turn makes it more likely to be a winner in the space. Now likely to be a winner in the space. Now likely to be a winner in the space. Now there's a really useful wrinkle here.

there's a really useful wrinkle here. there's a really useful wrinkle here. Walmart has told Wired that checkout Walmart has told Wired that checkout Walmart has told Wired that checkout inside chat GPT did not convert well. inside chat GPT did not convert well. inside chat GPT did not convert well. Namely, that it converted at about a Namely, that it converted at about a Namely, that it converted at about a third of the rate for products requiring third of the rate for products requiring third of the rate for products requiring a clickout as they would expect it to. a clickout as they would expect it to. a clickout as they would expect it to. And Walmart and OpenAI decided And Walmart and OpenAI decided And Walmart and OpenAI decided ultimately to replace that flow. Yet, ultimately to replace that flow. Yet, ultimately to replace that flow. Yet, Chad GPT brought new customers at Chad GPT brought new customers at Chad GPT brought new customers at roughly twice the rate of search roughly twice the rate of search roughly twice the rate of search engines. So what we're seeing here from engines. So what we're seeing here from engines. So what we're seeing here from Chad GPT may or may not be what we see Chad GPT may or may not be what we see Chad GPT may or may not be what we see from Muse. But it's worth noting that from Muse. But it's worth noting that from Muse. But it's worth noting that there are brands that have already gone there are brands that have already gone there are brands that have already gone into this space with AI and are already into this space with AI and are already into this space with AI and are already bringing learnings when they come and bringing learnings when they come and bringing learnings when they come and talk to Muse. And I think ultimately talk to Muse. And I think ultimately talk to Muse. And I think ultimately that's to Muse's advantage because it that's to Muse's advantage because it that's to Muse's advantage because it means that you have that experience in means that you have that experience in means that you have that experience in the AI space and you're going to bring the AI space and you're going to bring the AI space and you're going to bring that learning to bear when you make a that learning to bear when you make a that learning to bear when you make a new institutional partnership like this new institutional partnership like this new institutional partnership like this one. Over that same period, I would look one. Over that same period, I would look one. Over that same period, I would look for evidence from Muse's retail partners for evidence from Muse's retail partners for evidence from Muse's retail partners that the assistant brings in customers that the assistant brings in customers that the assistant brings in customers who complete purchases in return. Right? who complete purchases in return. Right? who complete purchases in return. Right? If you are going to say that Muse is If you are going to say that Muse is If you are going to say that Muse is going to be helpful to you, then you going to be helpful to you, then you going to be helpful to you, then you would want to look for not just would want to look for not just would want to look for not just partnership announcements, but that partnership announcements, but that partnership announcements, but that teams like Walmart are able to leverage teams like Walmart are able to leverage teams like Walmart are able to leverage learnings from previous AI partnerships learnings from previous AI partnerships learnings from previous AI partnerships and really bring revenue and customers and really bring revenue and customers and really bring revenue and customers to the table with this one. I'm to the table with this one. I'm to the table with this one. I'm optimistic, but it's early days, right?

optimistic, but it's early days, right? optimistic, but it's early days, right? We haven't proved it out yet. And as We haven't proved it out yet. And as We haven't proved it out yet. And as much as we've talked about the consumer much as we've talked about the consumer much as we've talked about the consumer impact on shopping, we also should talk impact on shopping, we also should talk impact on shopping, we also should talk about Muse's ability to put pressure on about Muse's ability to put pressure on about Muse's ability to put pressure on businesses that depend on you leaving businesses that depend on you leaving businesses that depend on you leaving things alone. Subscription companies, things alone. Subscription companies, things alone. Subscription companies, like phone companies, have always had like phone companies, have always had like phone companies, have always had customers who stopped getting value customers who stopped getting value customers who stopped getting value before they stopped paying. An assistant before they stopped paying. An assistant before they stopped paying. An assistant that helps you review the charges brings that helps you review the charges brings that helps you review the charges brings those two decisions into tension. those two decisions into tension. those two decisions into tension. Economists studying 10 different Economists studying 10 different Economists studying 10 different subscription services used payment card subscription services used payment card subscription services used payment card data from 2017 to 2021. And what they data from 2017 to 2021. And what they data from 2017 to 2021. And what they found is replaced cards created a moment found is replaced cards created a moment found is replaced cards created a moment when people had to actively renew and when people had to actively renew and when people had to actively renew and they saw cancellations rise. This makes they saw cancellations rise. This makes they saw cancellations rise. This makes sense, right? An inattention model is sense, right? An inattention model is sense, right? An inattention model is actually a technical model that can actually a technical model that can actually a technical model that can estimate how people do not reconsider estimate how people do not reconsider estimate how people do not reconsider their subscriptions and how that impacts their subscriptions and how that impacts their subscriptions and how that impacts increased revenue for a large business's increased revenue for a large business's increased revenue for a large business's existing subscriber pool. That study was existing subscriber pool. That study was existing subscriber pool. That study was published in the American Economic published in the American Economic published in the American Economic Review in 2025. The inattention model Review in 2025. The inattention model Review in 2025. The inattention model estimated that people not reconsidering estimated that people not reconsidering estimated that people not reconsidering their subscriptions actually increased their subscriptions actually increased their subscriptions actually increased revenue from a given subscriber pool, so revenue from a given subscriber pool, so revenue from a given subscriber pool, so think your phone company by 87% on think your phone company by 87% on think your phone company by 87% on average. The increase ranged from 14% to average. The increase ranged from 14% to average. The increase ranged from 14% to more than 200% depending on the service.

more than 200% depending on the service. more than 200% depending on the service. Um, and so any other subscription Um, and so any other subscription Um, and so any other subscription service also applies there. And that's service also applies there. And that's service also applies there. And that's evidence that inertia can be valuable if evidence that inertia can be valuable if evidence that inertia can be valuable if you're a cable company, for example. you're a cable company, for example. you're a cable company, for example. Businesses will have to adjust how they Businesses will have to adjust how they Businesses will have to adjust how they offer products because we are now in a offer products because we are now in a offer products because we are now in a world where even non-technical users can world where even non-technical users can world where even non-technical users can use a product like Muse very very easily use a product like Muse very very easily use a product like Muse very very easily to aggressively go after subscriptions to aggressively go after subscriptions to aggressively go after subscriptions in their life and save money on stuff in their life and save money on stuff in their life and save money on stuff they didn't intend to spend but just they didn't intend to spend but just they didn't intend to spend but just haven't had the administrative headspace haven't had the administrative headspace haven't had the administrative headspace to cancel. This is where I think we've to cancel. This is where I think we've to cancel. This is where I think we've misunderstood the competition. We've misunderstood the competition. We've misunderstood the competition. We've spent a long time, years now, assuming spent a long time, years now, assuming spent a long time, years now, assuming that the company with the smartest model that the company with the smartest model that the company with the smartest model is just going to by by default win the is just going to by by default win the is just going to by by default win the most important position in people's most important position in people's most important position in people's lives. I don't think that's true. Yes, lives. I don't think that's true. Yes, lives. I don't think that's true. Yes, better intelligence matters. You you better intelligence matters. You you better intelligence matters. You you don't want an assistant that gets the don't want an assistant that gets the don't want an assistant that gets the cancellation wrong or books the wrong cancellation wrong or books the wrong cancellation wrong or books the wrong date. You have to be capable enough to date. You have to be capable enough to date. You have to be capable enough to do the job. But once that capability is do the job. But once that capability is do the job. But once that capability is there, and in 2026, that is not a there, and in 2026, that is not a there, and in 2026, that is not a frontier capability. people. The next frontier capability. people. The next frontier capability. people. The next improvement that matters is just knowing improvement that matters is just knowing improvement that matters is just knowing you, knowing your circumstances. Which you, knowing your circumstances. Which you, knowing your circumstances. Which subscription is a duplicate? Well, I had subscription is a duplicate? Well, I had subscription is a duplicate? Well, I had to run across that. Which one do you to run across that. Which one do you to run across that. Which one do you keep because a family member needs it?

keep because a family member needs it? keep because a family member needs it? That was me, too. Which trip are you That was me, too. Which trip are you That was me, too. Which trip are you referring to? What did you already try? referring to? What did you already try? referring to? What did you already try? A very capable model that starts every A very capable model that starts every A very capable model that starts every conversation without that information is conversation without that information is conversation without that information is still going to make you do a tremendous still going to make you do a tremendous still going to make you do a tremendous amount of work. So having access to amount of work. So having access to amount of work. So having access to information matters, but then the information matters, but then the information matters, but then the assistant has to understand what it assistant has to understand what it assistant has to understand what it means for the decision. An occasional means for the decision. An occasional means for the decision. An occasional charge could be waste or it could pay charge could be waste or it could pay charge could be waste or it could pay for something you rely on twice a year. for something you rely on twice a year. for something you rely on twice a year. And maybe that matters and maybe it And maybe that matters and maybe it And maybe that matters and maybe it doesn't. So you want the AI, you want doesn't. So you want the AI, you want doesn't. So you want the AI, you want Muse to remember that difference, ask Muse to remember that difference, ask Muse to remember that difference, ask when it doesn't know, use what you've when it doesn't know, use what you've when it doesn't know, use what you've told it next time. And that's how told it next time. And that's how told it next time. And that's how personal context gets sort of translated personal context gets sort of translated personal context gets sort of translated into judgment. And what's interesting into judgment. And what's interesting into judgment. And what's interesting here is that Muse built heavily on an here is that Muse built heavily on an here is that Muse built heavily on an OpenClaw foundation to do that. And that OpenClaw foundation to do that. And that OpenClaw foundation to do that. And that was actually a public conversation was actually a public conversation was actually a public conversation between Peter Steinberger, the inventor between Peter Steinberger, the inventor between Peter Steinberger, the inventor of OpenClaw, and Nat Freiedman, who of OpenClaw, and Nat Freiedman, who of OpenClaw, and Nat Freiedman, who helped build Muse. And what they helped build Muse. And what they helped build Muse. And what they discussed on X is that Muse absolutely discussed on X is that Muse absolutely discussed on X is that Muse absolutely borrowed some of the markdown file borrowed some of the markdown file borrowed some of the markdown file patterns that made OpenClaw memory patterns that made OpenClaw memory patterns that made OpenClaw memory successful, but they built it in their successful, but they built it in their successful, but they built it in their own way. But let's zoom back out of the own way. But let's zoom back out of the own way. But let's zoom back out of the architecture piece to the strategy side.

architecture piece to the strategy side. architecture piece to the strategy side. Meta has an enormous potential advantage Meta has an enormous potential advantage Meta has an enormous potential advantage here. Billions of us already use Meta here. Billions of us already use Meta here. Billions of us already use Meta services. It has years of experience services. It has years of experience services. It has years of experience building consumer products that people building consumer products that people building consumer products that people return to, tracking relationships return to, tracking relationships return to, tracking relationships between people, tracking ways to between people, tracking ways to between people, tracking ways to introduce an assistant well beyond the introduce an assistant well beyond the introduce an assistant well beyond the audience following AI news. Muse also audience following AI news. Muse also audience following AI news. Muse also lets people connect services that lets people connect services that lets people connect services that contain useful information about their contain useful information about their contain useful information about their lives to further enrich that data set. lives to further enrich that data set. lives to further enrich that data set. Now, that doesn't mean Muse Now, that doesn't mean Muse Now, that doesn't mean Muse automatically inherits everything Meta automatically inherits everything Meta automatically inherits everything Meta knows about you. What it can access, knows about you. What it can access, knows about you. What it can access, what you permit it to access, and what you permit it to access, and what you permit it to access, and whether it uses that information are all whether it uses that information are all whether it uses that information are all going to matter a lot. They could use going to matter a lot. They could use going to matter a lot. They could use more transparency and its early days. more transparency and its early days. more transparency and its early days. The product needs to earn more context The product needs to earn more context The product needs to earn more context ultimately by being useful to you. And ultimately by being useful to you. And ultimately by being useful to you. And that is the pattern I see in usage is a that is the pattern I see in usage is a that is the pattern I see in usage is a positive pattern like as it's more positive pattern like as it's more positive pattern like as it's more useful, it asks for contextual useful, it asks for contextual useful, it asks for contextual connections that you trust it with. And connections that you trust it with. And connections that you trust it with. And I think that's the right pattern. uh I think that's the right pattern. uh I think that's the right pattern. uh distribution has a similar condition. distribution has a similar condition. distribution has a similar condition. Meta can put a product in front of a lot Meta can put a product in front of a lot Meta can put a product in front of a lot of people, but it's going to have to of people, but it's going to have to of people, but it's going to have to earn trust in their lives through earn trust in their lives through earn trust in their lives through execution. And the the number one in the execution. And the the number one in the execution. And the the number one in the app store only matters if you can keep app store only matters if you can keep app store only matters if you can keep people using it. And this is where the people using it. And this is where the people using it. And this is where the team that Mark Zuckerberg put together team that Mark Zuckerberg put together team that Mark Zuckerberg put together to tackle this begins to matter a lot.

to tackle this begins to matter a lot. to tackle this begins to matter a lot. So Meta already had money. Meta had So Meta already had money. Meta had So Meta already had money. Meta had distribution. Meta had consumer distribution. Meta had consumer distribution. Meta had consumer relationships. But what appears to have relationships. But what appears to have relationships. But what appears to have changed is its ability to turn those changed is its ability to turn those changed is its ability to turn those advantages into a coherent personal advantages into a coherent personal advantages into a coherent personal agent. There was a secret sauce there. agent. There was a secret sauce there. agent. There was a secret sauce there. And Alexander Wang and Natt Friedman and And Alexander Wang and Natt Friedman and And Alexander Wang and Natt Friedman and the team they put together are actually the team they put together are actually the team they put together are actually putting their long-standing ambitions putting their long-standing ambitions putting their long-standing ambitions into a product that people will use. How into a product that people will use. How into a product that people will use. How do we get there? Well, we start with a do we get there? Well, we start with a do we get there? Well, we start with a scale deal. Now, Scale was a data scale deal. Now, Scale was a data scale deal. Now, Scale was a data labeling startup. And it was widely labeling startup. And it was widely labeling startup. And it was widely panned when Mark decided to bring panned when Mark decided to bring panned when Mark decided to bring Alexander Wang over to lead all of his Alexander Wang over to lead all of his Alexander Wang over to lead all of his AI efforts after a 14.3 billion deal for AI efforts after a 14.3 billion deal for AI efforts after a 14.3 billion deal for 49% of scale and Alexander Wang coming 49% of scale and Alexander Wang coming 49% of scale and Alexander Wang coming over. Alexander Wang's uh reputed pay over. Alexander Wang's uh reputed pay over. Alexander Wang's uh reputed pay package is somewhere in the range of $5 package is somewhere in the range of $5 package is somewhere in the range of $5 billion. Uh it's probably worth more now billion. Uh it's probably worth more now billion. Uh it's probably worth more now as Meta's stock is up $200 billion as Meta's stock is up $200 billion as Meta's stock is up $200 billion because of the launch of Muse. And so in because of the launch of Muse. And so in because of the launch of Muse. And so in that world, everyone assumed, well, this that world, everyone assumed, well, this that world, everyone assumed, well, this is a data labeling guy. What is he gonna is a data labeling guy. What is he gonna is a data labeling guy. What is he gonna do? Uh, and why are we having him lead do? Uh, and why are we having him lead do? Uh, and why are we having him lead AI efforts? It was widely panned. Uh, AI efforts? It was widely panned. Uh, AI efforts? It was widely panned. Uh, Yan Lun left, uh, ultimately and it's Yan Lun left, uh, ultimately and it's Yan Lun left, uh, ultimately and it's been Wang's show for a bit and they've been Wang's show for a bit and they've been Wang's show for a bit and they've just put their heads down and shipped just put their heads down and shipped just put their heads down and shipped and they brought in Nat Friedman. Nat and they brought in Nat Friedman. Nat and they brought in Nat Friedman. Nat Friedman is another key part of this Friedman is another key part of this Friedman is another key part of this story. Nat Freiedman brings experience story. Nat Freiedman brings experience story. Nat Freiedman brings experience leading GitHub and building products for leading GitHub and building products for leading GitHub and building products for developers. That doesn't seem like a developers. That doesn't seem like a developers. That doesn't seem like a consumerf facing product experience set consumerf facing product experience set consumerf facing product experience set either. It's really interesting how this either. It's really interesting how this either. It's really interesting how this team has come together. It reminds me team has come together. It reminds me team has come together. It reminds me that people can come from very diverse that people can come from very diverse that people can come from very diverse backgrounds to build really interesting backgrounds to build really interesting backgrounds to build really interesting product in the right environment.

product in the right environment. product in the right environment. Another key part of the team was Sheng Another key part of the team was Sheng Another key part of the team was Sheng Xiao who brought model research Xiao who brought model research Xiao who brought model research leadership into the space. So working on leadership into the space. So working on leadership into the space. So working on the model around Muse and how model the model around Muse and how model the model around Muse and how model calling works and all of that and the calling works and all of that and the calling works and all of that and the technical work that matters there is technical work that matters there is technical work that matters there is that the technical work disappeared. And that the technical work disappeared. And that the technical work disappeared. And so that's where like that simplicity so that's where like that simplicity so that's where like that simplicity comes through again. like all of the comes through again. like all of the comes through again. like all of the work these brilliant people brought to work these brilliant people brought to work these brilliant people brought to the table had to disappear into a cute the table had to disappear into a cute the table had to disappear into a cute little avatar assistant that little avatar assistant that little avatar assistant that non-technical people would use. And I non-technical people would use. And I non-technical people would use. And I keep coming back to that because that is keep coming back to that because that is keep coming back to that because that is what is making this the number one app what is making this the number one app what is making this the number one app in the app store right now. AI needs to in the app store right now. AI needs to in the app store right now. AI needs to not feel like AI to deliver AI value. not feel like AI to deliver AI value. not feel like AI to deliver AI value. Ultimately, if we zoom out across these Ultimately, if we zoom out across these Ultimately, if we zoom out across these different hires, I think Mark recognized different hires, I think Mark recognized different hires, I think Mark recognized an execution problem on his team with an execution problem on his team with an execution problem on his team with AI, and he paid an extraordinary amount AI, and he paid an extraordinary amount AI, and he paid an extraordinary amount of money to change the pace of execution of money to change the pace of execution of money to change the pace of execution that Meta could deliver at. You can that Meta could deliver at. You can that Meta could deliver at. You can debate the price, but this is what those debate the price, but this is what those debate the price, but this is what those hires were supposed to make possible. hires were supposed to make possible. hires were supposed to make possible. They're supposed to deliver a model, a They're supposed to deliver a model, a They're supposed to deliver a model, a product, and a service around it that product, and a service around it that product, and a service around it that all work together seamlessly. [snorts] all work together seamlessly. [snorts] all work together seamlessly. [snorts] And the return is going to show up in And the return is going to show up in And the return is going to show up in equity if they do it right. And that's equity if they do it right. And that's equity if they do it right. And that's exactly where we see the markets exactly where we see the markets exactly where we see the markets rewarding Meta as they launch Muse.

rewarding Meta as they launch Muse. rewarding Meta as they launch Muse. Right now, your phone currently Right now, your phone currently Right now, your phone currently organizes access to much of your life. organizes access to much of your life. organizes access to much of your life. Maybe for many of us, it's an iPhone. Maybe for many of us, it's an iPhone. Maybe for many of us, it's an iPhone. For some, it's an Android. You open an For some, it's an Android. You open an For some, it's an Android. You open an app, you work through its choices, you app, you work through its choices, you app, you work through its choices, you move to another app, you keep track of move to another app, you keep track of move to another app, you keep track of the relationship between them. And right the relationship between them. And right the relationship between them. And right now, it's if it's iPhone, it's Apple now, it's if it's iPhone, it's Apple now, it's if it's iPhone, it's Apple that controls so much of that operating that controls so much of that operating that controls so much of that operating system layer and the rules under which system layer and the rules under which system layer and the rules under which those businesses reach you. Mark those businesses reach you. Mark those businesses reach you. Mark Zuckerberg knows what that dependence Zuckerberg knows what that dependence Zuckerberg knows what that dependence feels like. Apple's app tracking feels like. Apple's app tracking feels like. Apple's app tracking transparency changes in 2021 transparency changes in 2021 transparency changes in 2021 dramatically constrained how Meta's dramatically constrained how Meta's dramatically constrained how Meta's advertising business can operate. advertising business can operate. advertising business can operate. Facebook wasn't removed from the phone, Facebook wasn't removed from the phone, Facebook wasn't removed from the phone, but another company could change the but another company could change the but another company could change the rules in a way that materially affected rules in a way that materially affected rules in a way that materially affected Meta. Owning a successful app had not Meta. Owning a successful app had not Meta. Owning a successful app had not given Mark control of the platform given Mark control of the platform given Mark control of the platform underneath it. But with Muse, it's you underneath it. But with Muse, it's you underneath it. But with Muse, it's you can ask for an outcome and let the can ask for an outcome and let the can ask for an outcome and let the assistant coordinate across those apps. assistant coordinate across those apps. assistant coordinate across those apps. Yes, right now Apple still owns the Yes, right now Apple still owns the Yes, right now Apple still owns the device and operating system. For many of device and operating system. For many of device and operating system. For many of us, it has a dominant position in the us, it has a dominant position in the us, it has a dominant position in the ecosystem. Meta could gain influence ecosystem. Meta could gain influence ecosystem. Meta could gain influence over a different and potentially more over a different and potentially more over a different and potentially more significant part of the experience.

significant part of the experience. significant part of the experience. Understanding what you want and Understanding what you want and Understanding what you want and arranging how it gets done across your arranging how it gets done across your arranging how it gets done across your whole life. That's the kind of position whole life. That's the kind of position whole life. That's the kind of position I think Mark is looking at building over I think Mark is looking at building over I think Mark is looking at building over the next 20 years. Chad GPT faces that the next 20 years. Chad GPT faces that the next 20 years. Chad GPT faces that same competition for your starting same competition for your starting same competition for your starting point, your initial attention. OpenAI point, your initial attention. OpenAI point, your initial attention. OpenAI has already built an enormous consumer has already built an enormous consumer has already built an enormous consumer habit around asking its assistant for habit around asking its assistant for habit around asking its assistant for help. It has agents. It has tools. The help. It has agents. It has tools. The help. It has agents. It has tools. The question is which service you trust with question is which service you trust with question is which service you trust with ongoing responsibility. That's why I ongoing responsibility. That's why I ongoing responsibility. That's why I keep coming back to that. And which one keep coming back to that. And which one keep coming back to that. And which one understands enough of your life to make understands enough of your life to make understands enough of your life to make the next task, the next ask easier. A the next task, the next ask easier. A the next task, the next ask easier. A lead in model intelligence does not lead in model intelligence does not lead in model intelligence does not automatically settle that choice. Right automatically settle that choice. Right automatically settle that choice. Right now, Google has a data advantage, right? now, Google has a data advantage, right? now, Google has a data advantage, right? Google has Gmail, it has calendars, it Google has Gmail, it has calendars, it Google has Gmail, it has calendars, it has search, it has Android, it has has search, it has Android, it has has search, it has Android, it has useful context and distribution. What useful context and distribution. What useful context and distribution. What Muse demonstrates is how much depends on Muse demonstrates is how much depends on Muse demonstrates is how much depends on bringing all of those advantages bringing all of those advantages bringing all of those advantages together and executing really well with together and executing really well with together and executing really well with a great team to build something that a great team to build something that a great team to build something that people want to use. and the competition.

people want to use. and the competition. people want to use. and the competition. That will include good models, but it That will include good models, but it That will include good models, but it will also include building connections will also include building connections will also include building connections that work, having useful memory, having that work, having useful memory, having that work, having useful memory, having sensible interruption management, all sensible interruption management, all sensible interruption management, all these little details that make an app these little details that make an app these little details that make an app great. That's the bar. And this helps great. That's the bar. And this helps great. That's the bar. And this helps explain that little Tamagotchi looking explain that little Tamagotchi looking explain that little Tamagotchi looking thing that Zuckerberg showed at Connect. thing that Zuckerberg showed at Connect. thing that Zuckerberg showed at Connect. Muse Charm is a small device with a Muse Charm is a small device with a Muse Charm is a small device with a screen built around talking to your screen built around talking to your screen built around talking to your assistant and interacting with the assistant and interacting with the assistant and interacting with the character. It's been announced. It's character. It's been announced. It's character. It's been announced. It's something that's coming out in December. something that's coming out in December. something that's coming out in December. And Meta has also announced plans to And Meta has also announced plans to And Meta has also announced plans to bring Muse to its new AI glasses. Those bring Muse to its new AI glasses. Those bring Muse to its new AI glasses. Those are all part of the larger story of Meta are all part of the larger story of Meta are all part of the larger story of Meta building more ways for you to connect building more ways for you to connect building more ways for you to connect with its software without always with its software without always with its software without always beginning on somebody else's interface, beginning on somebody else's interface, beginning on somebody else's interface, somebody else's phone, often Apple's somebody else's phone, often Apple's somebody else's phone, often Apple's phone. Ultimately, I think this launch phone. Ultimately, I think this launch phone. Ultimately, I think this launch matters because people can recognize matters because people can recognize matters because people can recognize that AI can solve their problems without that AI can solve their problems without that AI can solve their problems without realizing it's AI or even caring about realizing it's AI or even caring about realizing it's AI or even caring about the AI industry at all. They can just the AI industry at all. They can just the AI industry at all. They can just find solutions. We've spent years asking find solutions. We've spent years asking find solutions. We've spent years asking ordinary people to be impressed by what ordinary people to be impressed by what ordinary people to be impressed by what models can do. Muse is giving all of us models can do. Muse is giving all of us models can do. Muse is giving all of us a reason to ask what an assistant could a reason to ask what an assistant could a reason to ask what an assistant could do. And I think that's a much more do. And I think that's a much more do. And I think that's a much more important question. Mark Zuckerberg has important question. Mark Zuckerberg has important question. Mark Zuckerberg has wanted a platform for a long time. He's wanted a platform for a long time. He's wanted a platform for a long time. He's made no secret about it. uh data and made no secret about it. uh data and made no secret about it. uh data and distribution have given him advantages, distribution have given him advantages, distribution have given him advantages, but really I think one of the moments but really I think one of the moments but really I think one of the moments we'll look back on with him is the way we'll look back on with him is the way we'll look back on with him is the way he put this team together. This team he put this team together. This team he put this team together. This team appears to have given him an execution appears to have given him an execution appears to have given him an execution boost at a moment when he really needed boost at a moment when he really needed boost at a moment when he really needed it for AI. And I think that it means it for AI. And I think that it means it for AI. And I think that it means that Muse has a chance to become the

that Muse has a chance to become the that Muse has a chance to become the platform that Mark as a founder has platform that Mark as a founder has platform that Mark as a founder has always wanted to build. And notice how always wanted to build. And notice how always wanted to build. And notice how Mark got there without Frontier AI. Mark got there without Frontier AI. Mark got there without Frontier AI. Mark's models are not frontier AI, but Mark's models are not frontier AI, but Mark's models are not frontier AI, but maybe that doesn't matter. And what's maybe that doesn't matter. And what's maybe that doesn't matter. And what's really fascinating about all this is you really fascinating about all this is you really fascinating about all this is you you can talk about Mark's strategy, but you can talk about Mark's strategy, but you can talk about Mark's strategy, but the hero of the story is you and me. And the hero of the story is you and me. And the hero of the story is you and me. And that's that passion for the consumer that's that passion for the consumer that's that passion for the consumer that comes through in the Muse app. That that comes through in the Muse app. That that comes through in the Muse app. That is why this is a number one app is that is why this is a number one app is that is why this is a number one app is that people feel the tangible help. That people feel the tangible help. That people feel the tangible help. That little avatar, the little furry bear little avatar, the little furry bear little avatar, the little furry bear character feels like it cares for you. character feels like it cares for you. character feels like it cares for you. Like I felt a connection. Even though I Like I felt a connection. Even though I Like I felt a connection. Even though I am a jaded product person with years in am a jaded product person with years in am a jaded product person with years in the industry, it speaks to a subliminal the industry, it speaks to a subliminal the industry, it speaks to a subliminal part of me. They did a good job with it. part of me. They did a good job with it. part of me. They did a good job with it. And so for us, what really matters is, And so for us, what really matters is, And so for us, what really matters is, as I keep coming back to, the money in as I keep coming back to, the money in as I keep coming back to, the money in your pocket, the tangible help. I your pocket, the tangible help. I your pocket, the tangible help. I started this video talking about saving started this video talking about saving started this video talking about saving $1,200 over the next year. There are so $1,200 over the next year. There are so $1,200 over the next year. There are so many stories like that. I was frankly many stories like that. I was frankly many stories like that. I was frankly inspired to do that with Muse because I inspired to do that with Muse because I inspired to do that with Muse because I read some of the stories I shared with read some of the stories I shared with read some of the stories I shared with you. What makes Muse powerful is that we you. What makes Muse powerful is that we you. What makes Muse powerful is that we are the heroes of the AI story with are the heroes of the AI story with are the heroes of the AI story with Muse. And I think that is one of the Muse. And I think that is one of the Muse. And I think that is one of the things that Nat Freiedman and Alexander things that Nat Freiedman and Alexander things that Nat Freiedman and Alexander Wang have done a great job of in terms Wang have done a great job of in terms Wang have done a great job of in terms of execution with this app. They have of execution with this app. They have of execution with this app. They have taken AI and and AI is not the hero of taken AI and and AI is not the hero of taken AI and and AI is not the hero of the story here. [snorts] AI is just the the story here. [snorts] AI is just the the story here. [snorts] AI is just the magical way behind the scenes that you magical way behind the scenes that you magical way behind the scenes that you are enabled to get more done with your are enabled to get more done with your are enabled to get more done with your version of Marvin, right? your muse, version of Marvin, right? your muse, version of Marvin, right? your muse, whatever you name your muse. And so I

whatever you name your muse. And so I whatever you name your muse. And so I think that's really exciting. It think that's really exciting. It think that's really exciting. It certainly makes it easy for me to talk certainly makes it easy for me to talk certainly makes it easy for me to talk about AI this Thanksgiving when I'm about AI this Thanksgiving when I'm about AI this Thanksgiving when I'm around the table with family. And I around the table with family. And I around the table with family. And I think it moves the conversation in a think it moves the conversation in a think it moves the conversation in a really useful direction. We are supposed really useful direction. We are supposed really useful direction. We are supposed to be building this to help other to be building this to help other to be building this to help other people. The whole reason I have this people. The whole reason I have this people. The whole reason I have this channel is to help other people. channel is to help other people. channel is to help other people. Products like Muse make it easier to do Products like Muse make it easier to do Products like Muse make it easier to do that. And so I know that there are folks that. And so I know that there are folks that. And so I know that there are folks out there who are going to be like, you out there who are going to be like, you out there who are going to be like, you know what, data is a problem for me. I know what, data is a problem for me. I know what, data is a problem for me. I already give Mark Zuckerberg too much already give Mark Zuckerberg too much already give Mark Zuckerberg too much data. I just don't trust Muse. I get data. I just don't trust Muse. I get data. I just don't trust Muse. I get that. That is a decision that you get to that. That is a decision that you get to that. That is a decision that you get to make. But a lot of people, especially make. But a lot of people, especially make. But a lot of people, especially from the evidence we have so far, are from the evidence we have so far, are from the evidence we have so far, are deciding that no, they trust Muse and deciding that no, they trust Muse and deciding that no, they trust Muse and they're going to let Muse help them out. they're going to let Muse help them out. they're going to let Muse help them out. And I think whether or not you trust And I think whether or not you trust And I think whether or not you trust Muse with your data is less important Muse with your data is less important Muse with your data is less important ultimately than recognizing what this ultimately than recognizing what this ultimately than recognizing what this moment means for the industry. We are moment means for the industry. We are moment means for the industry. We are finally building AI that is helpful to finally building AI that is helpful to finally building AI that is helpful to people and that matters. So you let me people and that matters. So you let me people and that matters. So you let me know how much you saved in the comments know how much you saved in the comments know how much you saved in the comments or what you're doing with Muse or maybe or what you're doing with Muse or maybe or what you're doing with Muse or maybe let me know why you're not using Muse.

let me know why you're not using Muse. let me know why you're not using Muse. I'd love to hear that too. Uh and we'll I'd love to hear that too. Uh and we'll I'd love to hear that too. Uh and we'll have a conversation.