Marissa Mayer Is Back with Dazzle, the New AI Assistant That Learns From Your Camera Roll

0:00Carlos: You're able to get information at a very granular level, right? So I'm curious to know how you're able to get the taste of a person based on their camera roll.

0:07Marissa Mayer: The photos I took of fun ski trips, it could figure out my mother's favorite ski brand, her ski style, where she was, and probably the appropriate ski length.

0:15Carlos: We've seen the examples of Amazon shutting down access from agents, but we're also seeing Walmart, and you're a board member there, how they are creating an agentic protocol to allow agents to just sign up as an agent instead of a human. So I'm curious to know your take on this agentic commerce.

0:27Marissa Mayer: The problem is that they're kind of like people, but they have this always-on superhuman productivity level that just means that they are, in fact, slightly different. And so I think having a protocol for them to interact with commerce websites so they're not constantly crawling and scraping and trying to get prices, and they can do this in a way that's more metered and less wasteful of resources, really.

0:46Carlos: How would you define success now as a startup founder for you?

0:54Carlos: Hey, this is Carlos, CEO at Product School. and your host on the product podcast. My guest today is Marissa Mayer, Google's first woman engineer, employee number 20, then VP of search, then CEO of Yahoo for five years. She also started the APM program at Google, which is the reason Product School exists. Today, she's a founder again. Her company Dazzle just launched, and it's a personal assistant that learns everything about you from your camera roll. Here are the things we'll cover. 40 % of your photos are not memories. their tasks, how it picked her mother's ski length from vacation photos. First task done in 45 seconds.

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2:16Carlos: You can generate structured starting points right on the canvas instead of moving outputs between tools. Keep all of your context in one place. And compatible AI agents can contribute alongside the team, bringing in context from the tools they already know. The future of work is still human.

2:38Carlos: Learn more at mural.co slash mural-ai. Welcome to the product podcast, Marisa.

2:44Marissa Mayer: Thank you very much for having me. I'm excited to be here.

2:47Carlos: You know, I thought you didn't need an intro, but then I talked to a couple of Gen Z employees at my company and told them, hey guys, Marisa Mayer is coming on the pod. And like, who? You don't understand. You are the main source of inspiration behind my company. You started the Associate Product Manager program at Google and in a way that inspired me to start product school as the first Associate Product Manager program outside of Google.

3:12Marissa Mayer: So, well, yeah, the Associate Product Manager program is amazing. So, you know, and what really defines it is the people in it. But yeah, I'm excited to hear that inspired the work you're doing. Because I just think product thinking and product management is so important. And it's also evolving so much with AI.

3:30Carlos: The rest of the Gen Zers who might not know who you are, obviously, you joined Google as one of the first 20 employees as a software engineer.

3:36Marissa Mayer: I was Google's first woman software engineer. And I was in the first 20 or so. I interviewed and there were just seven people there and started in the first 20. And then I stayed there as a software engineer, product manager, then became director of consumer products, then became the vice president of search and user experience. And then in the end was the vice president of maps, local and contextual searches, which eventually became Google Assistant. And then I went to Yahoo. I was CEO there for five years. And since then, I've been doing startups. So I had a startup, Sunshine, and now my second startup, Dazzle, which bought my first startup, Sunshine, is just recently launched.

4:16Marissa Mayer: So harkening back to days of Google Now and Google Assistant, we're building a personal assistant using AI.

4:23Carlos: We're going to talk about all things with your new startup, but the first question I have is what made you consider becoming a startup founder after having such an incredible career as a big tech executive?

4:33Marissa Mayer: Well, I've discovered that I just love all phases of companies. I like small, I like single digits, every order of magnitude, single digits, tens, hundreds, thousands, tens of thousands. I like being an IC, I like being a manager. And I love all phases of companies, hyper growth, turnarounds. And so I really wanted, it was inspired to try and build something. In my career, I've been lucky to be surrounded by amazing founders, Larry, Sergey, Philo and Yang at Yahoo, obviously, and many others of companies we've acquired, teams inside of companies. And so I really wanted to start something. And I'm very passionate about consumer tech.

5:09Marissa Mayer: My career has been in consumer technology. So I wanted to start a company to see if I could have an impact on the world the same way I had the opportunity to at Google and Yahoo.

5:20Carlos: So tell me more about what is Dazzle.

5:23Marissa Mayer: Dazzle is a personal assistant that learns from your photos. So we use your camera rule. We ask for permission. You can give us full select or no photos at all. And the more photos we have, the better we work. And what we do is we look at your historical photos, your past photos, to try and understand your tastes, your lifestyles, important people and places. And we do that at a pretty granular level. I'll come back to that later. And then the other thing we do is we look at the photos you took today to try and make your camera button a get it done button. If you need to buy something, you need to fix something, book something, add it to your calendar.

6:00Marissa Mayer: Take No Sound off a whiteboard. You just snap a picture of it. And Dazzle figures out what your intention is. We ask the question, why did Carlos take this picture today? And then we try to help you get it done. So we basically form a to-do list. We call it a get-it-done list because it's a to-do list where it does itself with AI agents.

6:21Carlos: One of the conversations we had before this, you mentioned something around 40 % of the camera roll photos are actually tasks and not memories.

6:29Marissa Mayer: Yeah, that's the transition point from Sunshine to Dazzle. At Sunshine, we were doing various utility applications, one of which was photo sharing, and we had built a really excellent share-worthy model. When was it likely that a photo was worthy of being shared? When we were looking at that, we were looking at precision and recall, and we realized that only about 60 % of the camera roll, even after you remove blurry photos or near duplicates, was actually passing our share-worthy model. So then that begs the question, well, what's the other 40 %? And the other 40 % is generally things you need to get done, things you need to remember, things you need to coordinate with someone else.

7:06Marissa Mayer: And so we thought, well, if we have an AI agent that's on the camera roll waiting for you to take a picture and then says, okay, if it's just a happy memory, I'll let it go. I might try and glean some information from it for future. But if it's something that you might need help with to get done, it can swing into action and offer to do those actions.

7:26Carlos: You mentioned before that you're able to get information at a very granular level. So I'm curious to know how you're able to get the taste of a person based on their camera roll.

7:35Marissa Mayer: Photos are the richest source of personal information available with the lowest friction. So some examples of things that we've done. Just a few weeks ago, we had a user. We were doing a session here to understand how people use Dazzle. And she said she was a prolific reader. But she had a list of books she needed for book club that she hadn't bought because she feels like she had some already. So she said, so to use Dazzle, should I just go and take pictures of all my bookshelves? And I was like, maybe, but let's do something else first. why don't you just give Dazzle the reading list and see what it does?

8:10Marissa Mayer: She's like, well, how will that work? And I was like, let's just see if it does. And sure enough, she gave it to Dazzle and Dazzle came back and said, actually, you do have this book. And you don't have these other two books, but you do have books by the same author. And I said, because basically the principle is like, unless your bookshelves are in the closet, when you take a picture in your living room of family or friends of cute kids, right? We're also getting all that information in the background. Dazzle knows, for example, all the appliances in my house. Makes, model numbers, everything because it's all in the background of my photos.

8:42Marissa Mayer: Just like it knew this user's book, what was on her bookshelves in a really granular level. Another example, early in our prototyping phase, my mother wanted some new skis last ski season. It was right after we had gotten Dazzle kind of up and running. And so I said, you know, my mom would like new skis. And Dazzle came back and said, well, because Margaret, because it knows Margaret is my mother, but I hadn't told it that, because Margaret is 76 years old and she often skis in Jackson Hole, Wyoming, and she usually wears Rossignol skis, these are the skis we would recommend for her. And then I even got a recommendation on length that I said, you know, she would like, she's thinking about the 164s versus the 157s.

9:24Marissa Mayer: And I came back and said, well, because Jackson Hole is very steep and because she's actually a little bit on the older side, shorter skis will be easier to maneuver. And I said, my mother's pushing back because she says her friends all have skis that are in the 160 centimeter length. And it said, yes, but in the photos, your mother is usually shorter and slighter than her friends and therefore needs a shorter ski. Which is like, I mean, it's like incredible that it like from the photos I took of fun ski trips, it could figure out my mother's favorite ski brand, her ski style, where she was, and even probably the appropriate ski length.

10:02Marissa Mayer: So it's really amazing things like that.

10:05Carlos: It's an amazing angle. And one of the things that comes to mind as I think about product is, we also have examples of how companies saw something happen and then copied that, right? In social media, you have Instagram copying stories from Snapchat. Now we're seeing the same with AI meeting note takers, granola and whisper flow coping each other all the time like how are you thinking about keeping

10:25Marissa Mayer: your moat well i mean i think that in the fast moving world of ai there isn't much of a moat we do have a lot of intellectual property i do think that we were you know we found we created some really amazing technology here and we have patents pending on what i think will be foundational patents in terms of how to use images to help llms and ai understand context for a person we are thoughtful about really wanting to protect that intellectual property because we think it is unique. But I think that there are also things that are obvious to those skilled in the art. Now there's a whole crop of personal AI assistants that have launched.

11:00Marissa Mayer: And it was interesting because many of them launched invite only, as we did. Many of them launched on iMessage, which we've been working on since the spring. So it's interesting to see some of the ideas as we We're building the product validated now by other competitors. The photos piece does remain unique.

11:19Carlos: Your product is focused on consumer applications, right? It's not in a business context.

11:23Marissa Mayer: That's right. And we think that, you know, I think consumer AI is going to be much larger. I've been fascinated by AI since my college days. I've always worked in consumer. I think consumer AI is going to be huge. And when we were pitching Dazzle last year to VCs, one of the things I learned was that basically today only about 6 % of investment in AI goes to consumer, yet the consumer market is expected to be twice the size of the enterprise market by 2030. So it just points to the fact that there's a big opportunity there. And it also means that I loved to build for consumers because I think it's easier for me to adopt that consumer mindset, that user mindset to really build something they want that works for them.

12:07Marissa Mayer: But it presents unique challenges. So one of the things that we've been most fixated on at Dazzle is how quickly can we get someone who isn't tech savvy up and doing their first task with an AI agent? Because when you look at things like OpenClaw and many of the others, you have to do so much setup, connectors, everything else. You really have to understand the technology to do it. And it's a point of pride that at Dazzle, from the moment you first open the app to actually doing your first task on your get it done list, is usually 45 seconds or less. And I think that's remarkable. I have friends, you know, I grew up in the Midwest.

12:42Marissa Mayer: And so I have friends I've tested the product with and they just can't believe they're like, it doesn't even really necessarily, it doesn't feel like there's a lot of setup. It doesn't feel like you're using an AI agent. It really just feels much more fluid and natural and it's really fast. And I think that's really a key element for consumers.

13:00Carlos: I agree. I think the reason why we're leading through this super cycle with AI assistance now is because finally, regular consumers can use these capabilities within their current apps. Like WhatsApp, iMessage, you do not need to download anything if you don't want to, you don't need to worry about connectors. At the same time, Marisa, I see that you raised around$8 million, at least that's what was publicly reported, but you have an involved team and you are up against news, instinct, rock, but now I'm sure OpenAI and Cloud are also going to come up with their own solution for this. So how are you thinking about staying competitive given that they can subsidize this product for a very long time?

13:39Marissa Mayer: Yes, well, Dazzle is currently free as well, so we also are subsidizing. But I think that for us, we're really focused on our early users, what do they like about the product, and the feedback's been very strong. The engagement's been really incredible, as has the retention. So these products, when they meet users' needs, are very sticky. So we need more distribution, so we're working on that, and we also need to keep evolving for new features, because it's a really quickly evolving space. But we're really focused right now on the users and on building the best product while keeping an eye on how do we get this in the hands of as many people as possible and keep it really simple, keep it really easy to set up and use.

14:15Marissa Mayer: Because in my view, there's a shockingly small number of people who are really using AI at all, let alone to its fullest capabilities. And the gap in terms of what people know that AI can do is just getting ever wider between the people who use AI and the people who don't. And that's really one of the things that Dazzle is designed to address is how do we take people who are maybe skeptical of AI, hesitant to use AI in a way that really helps them in their personal lives outside of the work context. It's something that's just purely a help that's trying to give you the gift of time.

14:46Carlos: And so speaking of monetization, you mentioned the example with your mom that she was recommended a pair of skis. And I saw that you also have a human concierge team, right, that in a way is acting as a human in the loop depending on what products are being recommended. So how are you thinking about the agentic commerce application on top of your own platform?

15:03Marissa Mayer: Yeah, we do use agentic commerce. And the vast majority of transactions that Dazzle does go through agents. But if something is particularly expensive, particularly complicated, we route them to our human concierges for a final check. In the end, this might end up being something that's done where we have agents checking agents. But right now, we know one of our investors is Sam Lesson. and he previously ran a personal assistant company called Finn. And he commented to me, you know, you have no idea how quickly you lose a user when they're expecting red shoes and green shoes show up. And I was like, you believe it, because, you know, people are picky, and when they decide to splurge or use a personal assistant to get something they really want, it needs to be right.

15:45Marissa Mayer: And some of these soft goods in particular are really complicated. Last week, I was trying to buy something that came in clear, mirrored clear, and mirrored smoke. and I mean you know the agent understandably got confused we saw a low confidence signal and we intervened right and just make sure like that we could actually get it right but there's also the commerce itself is really complicated for Halloween my daughter was doing a group costume and they decided on a t-shirt that came in a two-pack and we went to order the two-pack of t-shirts and it was sold out not available to November 17th consternation like really upset about it and it took me a minute to think about it and then I was like oh maybe the two-pack maybe the black t-shirt we need is available in a different two-pack and sure enough while black and red was sold out till November 17th black and light pink was was available so we bought it got the t-shirt no problem but that's hard at this point maybe in 2027 agents are gonna be able to figure that out but that you sometimes need that human intuition of being able to see your human insights and be like, wait, given how this is packaged, I wonder if I can get the same product packaged a different way.

16:59Marissa Mayer: And sure enough, you could. So there are things like that where in personal assistant tasks, if you can figure out a way to make it happen, that's what you have to do. And that's what our concierges are focused on.

17:09Carlos: I think the other challenge we're seeing with agents trying to do commerce is that the web is still designed for humans. So we're seeing the examples of Amazon shutting down access from agents, But we're also seeing Walmart, and you're a board member there, how they are creating an agentic protocol to allow agents to just sign up as an agent instead of a human. So curious to know your take on this agentic commerce and the agents are going to be able to identify themselves as an agent and not just as a fake human.

17:34Marissa Mayer: Well, I think agentic commerce is a really good approach to it. And I think having proper protocols for agents just eliminates a lot of problems. A few months ago, I remember I was reading, because basically these agents, they come in and they look like humans. but then they behave almost like a denial of service attack. I remember reading about one story where someone was trying to find kiss cam footage of themselves and their boyfriend, and they sent their agent out to find it. And I think it emailed a production assistant at a local TV station 1 ,800 times in nine hours. So the problem is that they're kind of like people, but they have this always on and superhuman productivity level that just means that they are in fact slightly different.

18:18Marissa Mayer: And so I think having a protocol for them to interact with commerce websites so they're not constantly crawling and scraping and trying to get prices and they can do this in a way that's more metered and less wasteful of resources really, I think is actually a good and prudent idea. Here at Dazzle in the meantime though, we have a slightly different view in how to approach this, which is we like to do things on your behalf as opposed to as you. So what that means is our agents, both AI and human, have their own email addresses, their own phone numbers, their own credit cards, their own accounts at most of the major vendors, and therefore they can go and they're not acting as Carlos when they go to do a purchase.

19:02Marissa Mayer: Because we've also seen instances where when AI can impersonate you and it does the wrong thing, it can cause big problems. We've heard stories about canceled flights with other assistant apps and you'd be like, well, how can that even happen? But the AI is calling the airlines pretending to be you and they have all the credentials to make that happen. I have a personal assistant. I understand that it's a point of privilege and it's a real luxury, but she never has to impersonate me, right? She always calls as herself on my behalf, not as me. And she's really effective in that way. And we think that that's, at least at this current moment of AI, how we should approach it.

19:41Marissa Mayer: When you go and buy something, it's either the AI agent buying it as the AI agent, and they have names and accounts as such, or it's the human. And then we ultimately have you reimburse us for the cost, and we obviously get the items shipped to you. But the way we behave in this agentic commerce model and agentic inquiry model when we're doing things like booking home repairs and things like that is quite different.

20:06Carlos: I want to switch gears for a second and talk about the magic behind the scenes because you have a nimble team and you are working hard, right? So first of all, start with what is your real involvement as CEO of the company?

20:19Marissa Mayer: I'm here five, six days a week in person and I'm working every day in person, but I love it. I have a great team. I think we have a great idea. It's been really amazing to see how our early users respond to it. It's been really positive. And so it's a lot of fun. But this is my full-time gig.

20:37Carlos: What's the kind of the secret sauce in a way? How can a team of 10 engineers and a few others really compete with those giants?

20:45Marissa Mayer: I think one is focus. As a smaller company, we have to. It's not a luxurious necessity that we have to decide, this is what we're going to focus on. We're going to focus on how do we take photos and make them incredibly useful? well, how do we work on this task? So a part of it is just making sure you're not spread too thin. But I also have to say, with the power of agentic coding, you know, we have a team, 10 to 12 engineers, and they code more like a team of 100, right? Because each of them is running so many different agents, right? We generally have most people running five, 10, sometimes even more agents at any given time to get tasks done.

21:18Marissa Mayer: So we're able to produce in a way that usually would require, just a few years ago, would have required many more people.

21:25Carlos: In terms of model usage and how you're architecting the company behind the scenes so you can focus on your competitive advantage, what can you tell me about it?

21:34Marissa Mayer: Sure. Well, the harness itself that's part of the Dazzle product is model agnostic. So whenever there's a new model that comes out, we assess which task is it good for. And by the way, at any given time, we usually have three or four frontier models in play. We also have a few smaller models, you know, some classifiers and things on device and some models on device, as well as some others that work on server side. So we're constantly looking at how can we swap out to the best technology? How can we use whatever is highest quality and most efficient? Because speed also matters for people, too, in the product.

22:11Marissa Mayer: And here at the startup, we all use AI a lot, right? Both for coding, for strategy planning, for trying to analyze the data that we have coming off of our early users. It's been an invaluable tool.

22:23Carlos: So Marisa, you came out of stealth recently and the launch seems to be going well. At the same time, you've achieved such a level of success kind of in your previous life as a big tech executive that there's a big gap to fill, right? So as you think about the future, when you look back, Like, how would you define success now as a startup founder for you?

22:44Marissa Mayer: Yeah, I mean, I think that we want to have a meaningful, positive impact on a large number of users. And so right now, I think that I can see the green shoots where our users really love what we're doing and they really value the gift of time and how easy we're making it to do things. And I know myself, I find it incredibly useful. And so, you know, that is fulfilling for me to see that we're really helping people. Now we need to do it at scale. and to do it at scale that means you know we have to get more distribution also means we need to keep evolving the products we need to win more and new users with new features and new capabilities so for for me it really comes down to the positive impact on individuals lives and then hopefully a large number of individuals 0 0 0 Thank you.