The Best Consumer Startup Ideas Were "Impossible" Until Now
39m 35s
The discussion centers on the evolving landscape of consumer startups, emphasizing the critical role of timing and cultural relevance in their success. AI is highlighted as a transformative force, enabling platforms like Suno to democratize music creation and Anchor to simplify podcast production, much like Instagram did for photos. However, distribution remains a persistent hurdle, as traditional channels have consolidated, forcing startups to build their own audiences. The conversation underscores the importance of betting on visionary product builders who can leverage AI to unlock new opportunities. Additionally, founders are encouraged to revisit previously dismissed consumer ideas, as AI may now make them feasible. The Anchor story illustrates how embracing user feedback and pursuing unscalable solutions—like manually creating RSS feeds—can drive growth when paired with disciplined, iterative strategies such as targeting consistent week-over-week growth. Ultimately, while AI enhances retention and opens new creative avenues, mastering distribution and timing is essential for consumer startup success.
I think increasingly we're finding ourselves betting on people who are just great at building products and kind of trusting that maybe there's an opportunity that we can't see that this person can through the opportunity of AI. The hardest thing with consumer is not only identifying the trend and the team but getting the timing right. Like when is this thing actually going to tap into the culture and be relevant with the culture and that's like almost an impossible thing to predict? I just think it's a great time to be betting in any category. I'm thrilled to be sitting down with Mike Mignano, a partner at LightSpeed Ventures. Before LightSpeed, Mike founded Anchor, a podcast platform that's acquired by Spotify in 2019. At LightSpeed, Mike's invested in some of the most legend companies in consumer and in tech overall. Neuralink, XAI, Suno, and Grenola. In addition to his work as a VC, Mike recently co-founded Obo Labs, an AI-powered learning platform. Mike has a ton of thoughts about consumer startups and how AI is reshaping media and what founders should be paying attention to right now. Mike, thanks for being here. Thanks for having me. Actually, I'd love to start off with your founder experience. I mean, we're doing a podcast now got involved and built one of the major pieces of Infra that, you know, everyone uses. What was that like? Never intended to build podcast Infra company or even really a podcasting company overall. Mike, co-founder, near Zikerman and I, when we first started building Anchor, we were actually trying to make a social audio platform. We had both kind of fallen in love with podcasts. This was back in 2014, 2015, kind of like when, if you remember, serial and kind of Grantland and all that stuff. We got into it and we realized that it was really hard to make them. And so we had just built all of this photo editing technology for mobile phones and this company Aviary. And we thought, wait, could we do the same thing for audio and podcasts? But at the time, if you remember, like everything that was launching on product time or the app store around the time, it was all social networks. So it was like, oh, we need to build the social version of audio as if that hadn't been tried before. And through a bunch of pivots and starts and stops and sort of near death moments, we ended up landing on the easiest podcast creation platform, basically a mobile podcast recording studio, like we have here, but in your pocket and easy enough to just tap a button to end up on Spotify, Apple podcasts, start monetizing, you know, right away. Yeah, that was sort of the 2014 era was sort of that right at that moment when people went from almost all startups were consumer. And then they became all sort of prosumer in B to B. It sounds like that was actually part of your story as well. It's like you started off, you know, consumer like quite a lot of other people. And then, you know, that was also sort of the moment when the social platforms were sort of coalescing. Totally. And then the platforms were closing down a little bit. So, you know, the explosion in consumer in, you know, sort of the 2008 to 2012, 2014 period, that was an opening up of platforms. And then as the consolidation happened, you know, distribution closed down, which sort of spurred, you know, this move over to B to B. Yeah. And I think like our our thesis was, you know, similar to how Instagram had made it really, really easy to create and share photos, but to do it in a format that kind of existed uniquely just in their own platform. We wanted to do the same thing for audio. We wanted to make it such that, you know, on on your phone, you could tap a button or you could hold the phone right up to your ear, talk, maybe do some light editing. And then people would just come into this app to listen and interact with this content just inside of anchor. But what we found was increasingly, like over over many iterations, people were good to create content on anchor. But when it came to listening, it was like, why would I listen to this like not great quality audio in this other random app when I have all these podcasts like every podcast in the world on Apple podcasts and Spotify. And I can listen over here. I was looking at sort of the ranking listings of all the top consumer AI startups today. And you have sort of two of the absolute top. Yeah. And and I think actually, Sino is an interesting one because I think the thesis of Sino is actually quite similar to the thesis that I just described for anchor. And and again, for a number of these kind of media platforms that came up and in the years you mentioned, maybe 2012, 2013, 2014, you know, if you go back to that time or if you go back even earlier and it's probably connects to some of the work you did with your startup, it's easy to forget just how hard it was to publish content, right? It had a right content and publish it on the internet or to take a photo and put it in a feed that millions and millions of people are scrolling through or take a video and upload it to YouTube. Like maybe, you know, we'll just use Instagram as an example that made it not only really, really easy to create something beautiful with minimal effort, but then find a distribution channel where you can start to get it out there, build an audience. If you look back at the the history of all the pot, all the products that have done this in one form or another over the past 25 years, nobody's done it for music. The reason, you know, we believe is that technology up until AI did not make music creation easier, right? The camera made photo taking easier, the camera made photo taking easier, the microphone made podcasting easier, the camera made video easier, but we never really had a technology that, you know, democratized music creation and so the thesis with Suno from the beginning was, well, now with AI, anyone can make music, you know, you have like the most popular format, maybe in the world. Everyone listens to it. What happens if you can get everyone creating it as well? Has that one sort of evolved? I mean, initially, I imagine it's, you know, maybe they were going after there's a ready-made, almost like, prosumer B2B audience, you know, it was, when did they get started? Yeah, I mean, it's still relatively new. The company's more or less like two years old. Oh my god. Yeah, so even two years ago, yeah, I imagine like, you have this tech and you're like, how are people going to buy this or use it? What kind of business are we going to build? Yeah. And, you know, I imagine the obvious start would be, let's go after prosumer creators, but, you know, that's not sort of how it worked out. Yeah, you, you, you, you should talk to Mikey, the CEO, but, you know, if you were sitting here, what I think he would say was the vision has always been to enable more and more people to experience kind of that, that joy of making music that previously only professionals could. I think early on, when we were evaluating it, one of the, you know, a lot of the behavior we were seeing, it felt a little bit like a novelty. I mean, chat you if you feel like that. Yeah, totally. But increasingly, I think what we've seen and what we've observed is that more and more people are using it to make something that's meaningful to them, right? Something that they're serious about. They're becoming creators, right? I think the other behavior we saw as we dug in, which was super fascinating, was people were making music for themselves. They're creating the music that then they will go listen to. I think it's super interesting. I can't really think of a behavior we've seen like that in any other format. Like, people don't write for, you know, to read their own stuff. I mean, we're just such an early stage. I mean, I think both of us really, well, you're doing it. You're actually finding some of the biggest new categories. I mean, you guys are doing it. Yeah, we're working on it. I think this last batch I funded enough to have an entire section. You know, it's about six startups that are all consumer based. Oh, wow. Yeah. What's your, you're seeing a lot more consumer, though? Yeah, exactly. But I think we're a little bit in the minority. Like, why do you think that is? About consumer? Yeah. I mean, B2B like sort of ate everything over the last 10-ish years. I think that's it. I mean, I think the reality is there was a, especially pre-AI, there was kind of like a playbook for B2B and SaaS. And if you have the right team and the right wedge, like you could, you could much more easily, I would say. I don't want to like trivialize any of this stuff. But it was more straightforward, I think. But consumer has kind of always been a little bit more lightning in a bottle, right? And I think the hardest thing with consumer is not only identifying the trend and the team, but getting the timing right. Because so many things are attached to cultural moments, like when is this thing actually going to tap into the culture and be relevant with the culture? And that's like almost an impossible thing to predict. You know, with Suno, I feel like we kind of got lucky that we met the team at a certain time and were able to invest, like kind of just as it was inflecting. And yeah, sometimes you just, you just get lucky and maybe overpay, just to be able to do it. But no, I mean, there are obviously so many great consumer investors out there that you look back at some of these bets they made and you just think, wow, like the timing was impeccable. But the bottom line is we have AI now and we have all these new opportunities and things we can create that we previously couldn't. So I just think it's a great, it's a great time to be betting in any category. I think increasingly we're finding ourselves betting on people who are just great at building products and kind of trusting that maybe there's an opportunity that we can see that this person can through through the opportunity of AI. Yeah, that makes sense. I guess the framework that I've been using that I hope turns out to be true. We'll see is like AI will actually increase retention, but you're sort of still subject, unless you have like there aren't new types of distribution yet, like it sort of classically, the death of consumer in like the 2013 era was about the platforms like collapsing in like APIs closing down like you have to bring your own distribution, but the platform won't give you more distribution. There's sort of this one time opening and then a shutting and then suddenly you have to charge, you have to have a subscription consumer service. AI interestingly is expensive. Yep. On the one hand, people are willing to pay. On the other hand, it's $20 a month or up to $200 a month if you're doing work with it. So basically retention will go up. So certain paid models will be possible now that weren't possible earlier, but then you still got to solve the distribution problem. That hasn't changed. That hasn't gone away. I do think there will be new distribution opportunities as AI becomes ubiquitous. I mean, we're seeing this now through AI new distribution channels will emerge that people will exploit and find opportunities in, but you're right for like a SaaS product or a pure net new consumer product today. You still have to just go and build the distribution yourself, which is arguably the hardest thing. Yeah, it's funny. I was hanging out with Eugene Yev from Repuka. She has a new startup. Of course. But I was asking her about, you know, for a lot of these consumer startups, how do you hire your head of growth for a consumer startup? And she's like, actually, you can't hire them in the United States anymore or in the West. Like they're all in Eastern Europe. Yeah, I've heard that a little bit as well. Which is interesting. It became like a lost start. We forgot how to do consumer distribution and we forgot how to create the SR-71. It's been so long, you know. I think that her product does an example. I think it's a great example of you could see her and that type of product borrowing from the previous playbooks of Instagram and Twitter and maybe trying to leverage existing channels distribution to get that out there. I don't know. What are the ways that you can distribute an app on an existing channel? I think it's going to be, basically, it's like toy apps right now, but it's very well done. Totally. I mean, it's kind of the kind of stuff you could do in co-gen tools today, but having it be entirely contained to your mobile phone is, I mean, that's like an Instagram moment right there. 100%. Yeah, that's why. And then I think like, basically e-groups, Yahoo groups, like all of these things were trying to scratch an itch and, you know, you're just not willing to go through like a customization step and group software is just like the perennial problem. But this is a perfect example of what we were talking about earlier. Like, you would never, without AI and co-gen, you know, two years, you're like, why would I, why would I invest in it? Why am I so lucky to work on that right now? Yeah, but, but now because of AI and co-gen, it's like, oh my god, like maybe there's actually a really interesting opportunity here. Maybe you and I have missed the the browser opportunity. Now that we have Dia and comment, but I think back to two, three years ago, I saw these browsers and I just, I just passed on the opportunity because I'm like, oh, you, you can't compete with Chrome or Safari because they're embedded in the OS. And it's like, no, actually AI creates like a really interesting opportunity for the browser to be an investible service. But if I were a consumer founder going through YC right now, I might be thinking to myself, what are all the opportunities that have sort of been written off that I can inject AI into inside of consumer? What's funny is you should try all the things and, and then you're only limited by distribution. And then the funny thing is like, you know, what do you, what's your take on? You can access, I mean, hundreds to at least maybe, maybe 10,000, maybe tens of thousands of early adopters who are, uh, non's on X. Yeah. So that's turned out to be, uh, a whole way to, you know, get online and get customers. I actually was telling your, your team before the show that, um, one of PG's essays was like a big, it was like a big, big inspiration to, uh, how anchor actually survived and not to survive, but like, ended up figuring it out. That's right. And we were dying. We were running a money. We had like three months to, before we shut it down, we, we told the team, we're like, this isn't going to work. This product is just kind of bouncing along. Like it's growing, but it's not growing great. And then we implemented this framework where like we have to hit 15% week over week growth every single week from here on out for the next three months. And it forced us to challenge our assumptions and it forced us to pivot to something that we didn't want to pivot to, but the users were asking for. And oh, so there was pull from the market for, you know, sort of going in that anchor direction. Yeah. So that we wanted to do the social thing. We wanted to be the, the platform because again, that would have been a bigger opportunity. But what we were hearing from the users is, hey, we love your tools. We don't want, we don't want to bring listeners over here. We want them to be able to listen where they're already listening. Help us get our content on Spotify and Apple podcasts. And these, these things didn't have APIs at the time. There was no way for us to port that content over. And so we actually, we built out a whole framework where we literally had physical human beings manually creating RSS feeds and submitting them to the Apple podcast store, honor users behalf when they tapped a button in the app. User didn't know it, but they would tap the button, do something unscalable. Yeah, do something that doesn't scale and then scale it. Exactly. And that worked. And we only got to that because we had this rule that we had to hit 15% week over week growth every single week. And it was, it was startups equals, equals growth. And then otherwise, like, don't do it or do something else. Yeah. Yeah. And every, every week of something else, like, what are we going to do this week to hit the growth? What do you think changed? I mean, I guess before implementing that, the default for startups is, well, you have a bunch of money in the bank. You have some users. And then the classic trap sometimes is, oh, well, we have some technical debt. We're going to take it on just to like work down the technical debt, which is basically like, you know, treading water or like, like slowly sinking into the water. Yeah. And then you're drowning. I think, I think you don't realize, uh, you're drowning until you kind of like look at the calendar. And you're like, okay, this is the date where if we don't figure it out, it's over. And like, really staring that in the face and being like, okay, we actually have three months to figure this out. And yeah, I think there is this trap that happens often, especially now where startups get over capitalized and they never, never feel that pressure. And they feel that they can just keep going forever. Yeah. There's this other aspect. How many people were you at when we were about like eight? Okay. Yeah. So we get everyone in the room. Yeah. And we could be like, this is going to happen. We are going to fail unless we don't figure this out. But if you had raised like, you know, today's seed and, you know, you had three times more money. Yeah. And maybe you had, you know, hired up and had like twice the size of three times the size of team and you couldn't fit them in a room. Yeah. That would be harder. Although maybe we would be spending it differently because of AI. Maybe we would be, maybe we would still have a small team. Maybe we would be investing more in marketing and distribution, TikTok influencers or something. I think our burn would probably be higher. But we wouldn't necessarily be a bigger team. Yeah. I'm hoping that some of the labs start experimenting even more with distribution. Like you saw that with the GPT store at opening eye a little bit. But I think that was a little bit of a failed experiment. Like I think they might have even removed the GPT store. Or maybe it's down there. Yeah. It doesn't feel like a supernatural way to make an app. Like a GPT doesn't really feel like an app in some sense. Clearly they still want to chase this opportunity though. Right. Like it feels like multiple times. They've announced partnerships with companies. Like recently, didn't they announce integrations with Spotify and all these other products that you could invoke right within the command line? You could imagine a world that that turns into a platform and anyone can integrate. I don't know how you would solve discovery in that sense. But yeah. I mean, I think there's something there or an MCP. But it's such a mess of an ecosystem. Like just barely. The integration is just barely work. I'm sure I will stop looking at it at some point in the next couple of months and then magically in like six to nine months when I'm not watching. It's actually going to work really, really well. I mean, some of the consumer things that we're seeing are literally taking large data sets that are somewhat hard to get at. And then just plugging them into LLMs. What's an example of that? I mean, there's a company called Nori in the current batch that it's literally Apple Health. Oh, right. Dropped in LLMs. Yeah, Dave's all right. Yeah, fellow hot cat. Yeah, he did chartable and sold that to Spotify. Yeah. So I think that's really interesting actually. I think I think I think that's an opportunity. We actually invested in a company called Doctronic, which is right now doing, you know, kind of medical triage. Similar to what you can do in chat, you be T today. But, you know, they have a model that's that's trained on a gigantic corpus of health information and data and, you know, medical research. And you can imagine a world in which similarly, like you're getting your your medical records in there and you're able to chat with it. I'm doing this today just in like a cloud project, but it's super manual, right? Like uploading all this stuff. So I think Nori sounds super interesting. My dad went to the hospital and he was fine, but he, you know, passed out. He'd never done that in the restaurant and we went, you know, hurried over to the hospital and, you know, I logged in with his Kaiser login to get all of his, oh, wow, I could see the labs come in on the website. So I downloaded them PDF, uploaded a chat GPT and then it just told me exactly what was going on. Even though like the emergency room doc hadn't come by, but the funniest thing was like, when he did come, I asked my three questions and then actually helped get him a better standard of care from that. That's amazing. Because I was like, well, had you thought about this? And, you know, I have expected him to be like, don't use chat GPT on me. Oh, the doctor appreciated it. The doctor was like, oh, yeah, that's a good idea. Oh, wow. For that. I'm sure they're seeing this all the time now. Yeah, you have to wonder, are they welcoming it or are they like, come on, please, enough with the chat. But I mean, I think it's that good. I think it's all in distribution now. So one area I'm thinking a lot about is social. Interesting to see Sora at least. Sora, I think, is really interesting. I kind of think of it as in a way the end of social media or like the last phase of social media. I currently bucket social media into like three phases. The first is true social media where, you know, companies are building up social graphs. You know, people are following each other. Content is being distributed based on who you follow. And so you follow your friends and maybe some random influencers. And then when they make content, you get served that content. And it's like pretty efficient. Some of the content is relevant to you. Some of it isn't, but it kind of works. And then the second phase is like the TikTok kind of, I call it recommendation media where they figure out what you like and creators make content. And then they program that content against your interests. Sora to me feels like this third, the start of this third phase where eventually they don't really need creators to make content, right? Yes, today people are prompting, but you could very easily imagine a world in which you're just coming into the feed and the content is just being created immediately, dynamically on behalf of you. And I think that's really interesting. Interesting in a couple scary ways, but obviously there are also some interesting opportunities. The thing that I like to think about in this last phase is what is the role of the human to help kind of shape that experience. Obviously, one of the roles is just to consume and let the model train on your interest. But maybe the more interesting thing, and we've sort of seen hints of this with Sora. I think Sam published a blog post that kind of hinted at this is kind of the creation and distribution, potentially monetization of name and likeness and uniqueness. Oh, yeah. It's like when you cameo somebody on Sora, maybe that person is getting compensated somewhat. Maybe brands are servicing as cameoable. You talked about distribution earlier, like that could be a new, that maybe is the new form of distribution in social where you're sort of like injecting some uniqueness or personality or likeness into a model that will then get distributed through no sort of manual human creation at all. That feels like the next phase. It's a little it's kind of scary because there's probably no like actual pure human creation in that model, but there's the prompting. There's some art in the maybe, but does that just go away, right? Like eventually, why do you need that? They just know what Gary wants to. It's just going to be the auto AI slot machine. So I'm a little bit terrified of that, but I also think that there's probably going to be some interesting opportunities. And I'm totally expecting that TikTok and Instagram will start having pure AI generated content and eventually gets to this place as well. But all in all, I do wonder if we're in kind of like this third and final phase of like human created media. Yeah, it's a little terrifying. If you use Sora, it's a very promising super funny, but also extremely frustrating, like 80% of the time. You mean on the output when you get out? Yeah. And it'll get better. Yeah, it'll get better. But also the mobile app itself, it's clear that they're experiencing crazy GPU scaling issues. Yeah. So I think it's still very number one of the app store. It's crazy. Yeah. It is funny to see XAI and Meta sort of like struggle to capture that vibe. I think Cameo was the feature that really did it for them. But I also noticed that they didn't really invest a lot. Maybe it was intentional. Maybe it was just prioritization in some of the graph stuff we mentioned. Like it almost seems like that's not going to be important. You know, it's more going to be about we just know what to program for each user. Right. It's like this person seems to click like on all of the chat cameos for some reason. Yeah. That's me. The chat cameos are good. Everyone's cameoing. Yeah. So yeah, I don't know. I don't know what happens to social media. And I'm not totally sure yet what the opportunities will be for builders there. Yeah. Distribution in the end. I mean, even TikTok. I'm hopeful that Cheshpd comes around and realizes like that was one of the most amazing things that TikTok did. And you know, that's what the YouTube algorithm does today. Those are the most potent places to get distribution. Right. Right. I mean, I think X is there. Like thanks Nikita. He's doing a great job. He's doing it. He's changing up the field. You're creating the web view. Yeah. Gotta love the new web view. Yeah. Yeah. Yeah. Maybe the model is the distribution then. Like we're saying. And maybe similarly how for TikTok, it became about obviously the videos and we can create a video. But you could also like you could let creators pull from the song the song catalog. You know, Instagram has things like stickers and filters and things like I don't know, maybe the model is a new place for some form of creator distribution. It's not your video. It's something else. It's your likeness. It's your brand. It's a meme. Right. That others can then invoke through the model. So we talked a little bit about media and then a lot of people watching who might be, you know, just starting their builder career. Is that like sort of the model for consumer founders in the future? You should people be creators. I don't know whether or not people should be creators. I mean, I'm not saying they shouldn't, but it is also time consuming. I mean, you're sitting here in the set. I don't know how many of these you do a week, but I'm sure it takes up a chunk of your time. And I do think there is a new consumer playbook for distribution that I previously maybe maybe a couple of years ago kind of maybe was too dismissive of. And now I almost feel like it's table stakes, which is leveraging creators. Maybe it's TikTok influencers, you know, reels influencers, whatever kind of creators you can you can tap into to reach some massive scale of distribution. It almost feels like you have to be doing that now. And what it can drive in terms of downloads or installs or signups is crazy compared to, you know, the early growth we saw from consumer startups five years. Yeah, I mean, this is literally the definition of organic then. When you say organic, like ultimately the most potent form of organic is x-feed, YouTube feed, TikTok feed. Yeah. And it's actually not organic, if you think about it, right? A lot of these companies they're they're figuring out kind of what works on TikTok. And then the TikTok algorithm takes over and does the work and puts it in front of a million people. It's not really organic, right? Like organic, I would say is you built some incredible product and there's this word of mouth dynamic where everyone and their friends are talking about. It's just growing. But just because it's not purely organic doesn't mean you shouldn't do it. I think every one correction. It's not organic, it's non paid. It's non paid. Well, you you still pay you pay for it in your time. Yeah, in your mental space. Or you pay the influencer or the creators or whatever. Right. When you're paying someone else, like the reason why that's interesting for consumer products is it's a mispriced asset. Exactly. Exactly. I mean, Mr. Beast is not a mispriced asset. He's like getting his value from us. Yes. Like, he's, you know, but it does seem like the mispriced assets are sort of the creators with like a thousand to 10,000 followers. Right. And if you can wrangle up enough of those, you can get some real scale. Yeah. I mean, I think I used to be dismissive of this as a tactic because it felt inorganic to me, but now I think it's table stakes. Yep. I mean, all of the best consumer startups that are pitching us, they have these crazy growth charts and they're all doing exactly this to do it. Now, there's obviously then the question of, what's the retention lag? Is anyone paying? What's the funnel look like? And if the funnel is trash, it's, you know, it might not be both. It might not be a viable investment. If you're a bad builder, but you're a good troll, then you still build nothing. But if you're, you know, enough of a troll marketer who's actually got the goods, then you could build something pretty big. Huge, I think. And I think the reason I was previously dismissive of it is because I just assumed that at some point it would go away. It's like if you're tapping into this inorganic channel that you don't control, at some point, it's going to turn off or it's going to do something else, but it's been years now. Yeah. And it seems as reliable as ever. So back to the original question, maybe you should be a creator, maybe you shouldn't, but you definitely should be leveraging creators and these distribution channels that creators tap into to get the crazy amount of eyeballs and things you have to. The big question I see founders asking a lot and I'd love to get your perspective on this is, should you wait until you have product market fit or some level of stable retention before you start doing the inorganic, you know, social distribution play? So would you encourage a founder to seek distribution before they've found product market fit? I mean, maybe as a side project, it might be useful to, you know, start in a non-account, but just to learn, like, how do other people think? What do people click on? Oh, that's interesting. Then it's like a background process that you can call on later. A lot of the time we spend with especially consumer founders at YC is helping them with their launch and, you know, how do they talk about it? What's their launch video when they meet someone in a person setting or an investor or a potential user? Like, what do you say literally in the first 10 or 15 seconds? It's like, first, you have to let someone know what the heck it is. And then right after that, you have to make sure that they know that what you're doing is awesome in some way, like that you're worth spending, like, you know, that was 10, 15 seconds and then it's worth at least a minute conversation. And if you can make it to a minute, you might have, like, this amazing, like, 10, 20 minute conversation. They might try your product. They might tell their friends. They might, you know, they might invest, like, all these different things happen. And it's sort of comes out of being, like, perceptive, good communicator, like, kind of funny. Yeah. That's pretty interesting. And the idea of doing it at doing that or doing some of that, learning some of this as a non is really interesting because you just lower the stakes. You're not really, like, burning anything. I'm, you know, thinking about how many times have you heard, like, don't, don't do your big marketing push or your press announcement until you're ready because you'll never get these users again. You know, you'll, like, you'll, like, burn the opportunity. But if you're doing things like testing from an anonymous account or, you know, testing a TikTok influencer strategy, even that, like, there's always going to be more eyeballs on Twitter. You can get an, or on TikTok, you can get in front of. And so maybe the lesson is you just should be practicing that you should find a way to be practicing this stuff with lower stakes even before you're ready to launch or you're ready to, like, you know, blow the thing up because figuring this stuff out is going to be hard. Yeah. So taste is, taste matters. And there are lots of ways to develop that taste. And like it or not, you've, you know, sort of got to put on your fighting gloves if you're going to especially do the X thing. Yeah. And it might actually be worth it. I feel like there was a lot of talk, maybe six months ago, a year ago, of kind of taste as a moat. It's becoming easier to build products because of AI. So whatever you build, you got to have great taste and great, great craft to be able to stand out. You know, I think granola was a great example of this. I think the question is to what extent is that now a durable asset given we've seen how aggressive some of the labs are? Like, can taste really stand the test of time? Or is it really just a thing to give you a first mover advantage? Yeah, I guess I don't know yet. I know. Every version of the model, it has bigger and bigger model energy. Yes. Got some bigger and yeah, it's got some BME these days, you know, like Opus 4.1 is, it like feels vast. Going back to Sora, I mean, it's touching on this, this topic a little bit, like, so Sora kind of surprised me a little bit because it's a new product. It's a new app. And it's good. Yeah. You know, I think there was a belief among some startups and founders that you know, as long as you're not doing exactly what Chat GBT is doing or exactly what Claude's doing, like, you'll be okay because that's where they're focusing their energy into these products. But Sora is kind of proof that, no, these labs, like, they have the taste and capability and the horsepower and the execution to build and ship net new products that also might run you over. I think the point is though, all the more reason why like, you gotta have taste, you gotta be willing to put your product out there, but you have to, like, we're in this environment that is just so hyper competitive, like, you have to, you have to move fast, you have to be aggressive, you can't just kind of like sit back and iterate and like, wait for your moment. I mean, the machines don't quite have taste of their own yet. No. Like, that's what the e-vals are for. Most people are in these consumer scenarios, even they're just, they're writing prompts, and then they're trying to give a certain experience to the end user. And then there's still, you know, a craft to that. Totally. So Mike, you're one of the most legendary consumer AI investors. And I think a lot of people out there would love to know, like, what are you seeing? What would impress you? What, you know, what would get over the line so that they could be, you know, get the chance to work with you? There's a huge opportunity right now to reexamine opportunities that have been previously overlooked. You know, I mentioned earlier that we recently invested in a mail app, a category that I think we previously would have ignored because it's been a graveyard, typically. But AI has presented brand new opportunities. And I think we're seeing spaces like that over and over again, like these, these surfaces that maybe got a lot of investment and building early on in terms of like the internet or maybe like advertising and things like that that we've, we've just like moved on from as an industry because we consider them baked and done. And I think AI is presenting an opportunity to just completely like rebuild a lot of the stack that we've already built. I would also encourage people to think about what are the large data sets that exist, either sort of that are publicly accessible or that are private and personal to someone that if you layer an LLM on top of it or maybe a photo model or, you know, an image model or video model or music model, like what are interesting things that you can do with these data sets that have sort of been untouched. You know, we talked a little bit about health data and going into the doctor's office, like that's a huge opportunity. Obviously a lot of people are building for that right now. But what are some of the other data sets that no one has really like put AI around and given you access and insight to that you haven't really thought of before? That kind of gives me an idea for a request or start up a little bit. I mean, there's just a lot of data and it's in your phone and it's, I mean, frankly, in your medical records, it's just, it's in Apple Health. Simultaneous to that, like there are great start-ups like Mem0 that are kind of trying to be like a memory layer. But like inside the system of record, you know, inside someone else's app, it feels like there's some space in here around like an enabling tech where you want a layer that basically knows everything about a given person. I mean, and then you could even break down that down even further, right? Like, there's probably a bunch of really cool things to be built on top of your camera roll. Yeah, I don't know what they are. And maybe they're social experiences, right? But if we look, if we used AI to kind of look at your photos and the things that are in them, maybe the places you've been, maybe your geo locations, you could build an interesting thing. I mean, I think it would know who you hang out with, who you spend time with. Like, are you, you know, do you spend a lot of time with your family? Do you are an archer? Like, what your favorite beer is? Like, there's probably all kinds of stuff that's like implicit to that. Yeah, Dennis Crowley just launched something. Dennis Crowley is the founder of Forest Square, you know. I still use Swarm. Yeah, amazing consumer product builder. I think you're super creative. You know, he just launched something where when you put your AirPods in, kind of AI goes to work based on your geo locations. So, you know, it might know because you've, you've done it a bunch of times that you like really good coffee or margaritas. And then if you're near something, it's going to tell you it's just going to like chime into your ear. Based on your previous history. So, like, I just think there's a lot of opportunity to take this memory, this sort of like personal information that you're talking about and break it down on a bunch of different levels, run it through AI and create new consumer experiences. Aside from that, you and your co-founders are starting a new company as well called Obo. How do you decide to work on that? And, you know, how do you pick that idea? Yeah. So, I think again, this is another opportunity that AI, I think, presents and that is education. I mean, the highest level premise is that we've spent billions, maybe trillions of dollars to invent artificial intelligence. And obviously, there's amazing opportunities that are coming out of that. But what if we sort of took that artificial intelligence and invested it into human intelligence? And obviously a lot of people have been talking about this for a while. AI is going to be a great tutor. It's going to be great at teaching you things. But nobody's really gone in and built the product for that yet. And so, so Obo, and it's available now, obo.foi, it is a product that anything you want to learn, it will magically create a course for you on that subject in any format you want, podcasts, you know, long-form lecture. It'll create the study materials for it and over time, you know, to work to the point that we're talking about with personalization and data. It's obviously going to know how you like to learn in terms of the format, but it's going to know what you already know. And so, each subsequent lesson is going to get more and more personalized and then therefore more efficient at teaching you because obviously the way in which we all learn right now, it's like extremely one size fits all. All the content is the same. It's kind of a blunt instrument that's just kind of like forced upon you, whether it's reading a Wikipedia article or, you know, going to college or whatever, it's just one size fits all. But AI presents an opportunity to highly, highly personalized education and get better and better and smarter and smarter the more you learn. And so, the hope is that we can literally make humanity smarter through AI. In my opinion and in my experience, the way to build startups, it's to take these large service areas where there's kind of obvious opportunity. And yes, you start with a point of view, but like your point of view may be wrong. And then you iterate, right? You get punched in the face. Exactly. And then you alternate your plan. Yeah, you're still like kind of pointed at the same nor star, but you're just, you're just taking a different path. I mean, that's what we did with anchor where like we want to democratize audio. We think it's through social audio and short form voice notes. Oh, nope, it's not. Like, let's add more tools. Oh, that wasn't it. Let's add distribution to Spotify. And I think that that is a recipe for a successful startups. Like, take a really ambitious space, point in a certain direction and just keep iterating to find the best path until you get there. Amazing. Mike, do you want to give a brief plug for your podcast? Yeah, so when AI kind of exploded a few years ago, we at Lightspeed did the thing that every VC does and we started a podcast and the whole idea was to talk to people that are building in the space, but then after a few months or whatever, we realized that frankly, I got bored. I was like, I'm having the same types of conversations. And then so a friend of mine, Samil Shah was like, why don't we just go outside and record a podcast and we'll make it like Anthony Abourdain parts unknown or comedians and cars. So we tried it out and we had a blast. The audience loved it as well. People are like, oh, this is cool. This is different. And so now we've launched a new podcast called Out of Office. It's going to be fun. And you're going to come on, right? Yes. All right. Can't wait. Watch out for that one real soon. Yes. Well, we're out of time, but Mike, thank you so much for hanging out with us. Thank you. Really appreciate it. Yeah. Thank you. This is fun.
Podcast Summary
Key Points:
Investing in consumer startups requires identifying trends, teams, and precise timing, as success often depends on cultural relevance, which is difficult to predict.
AI is enabling new consumer opportunities by democratizing creation (e.g., Suno for music, Anchor for podcasts) and improving retention, though distribution remains a key challenge.
Founders should revisit previously overlooked consumer ideas, as AI can transform them into viable products, but growth and scalability demand focused, iterative approaches like aggressive growth targets.
Summary:
The discussion centers on the evolving landscape of consumer startups, emphasizing the critical role of timing and cultural relevance in their success. AI is highlighted as a transformative force, enabling platforms like Suno to democratize music creation and Anchor to simplify podcast production, much like Instagram did for photos. However, distribution remains a persistent hurdle, as traditional channels have consolidated, forcing startups to build their own audiences.
The conversation underscores the importance of betting on visionary product builders who can leverage AI to unlock new opportunities. Additionally, founders are encouraged to revisit previously dismissed consumer ideas, as AI may now make them feasible. The Anchor story illustrates how embracing user feedback and pursuing unscalable solutions—like manually creating RSS feeds—can drive growth when paired with disciplined, iterative strategies such as targeting consistent week-over-week growth.
Ultimately, while AI enhances retention and opens new creative avenues, mastering distribution and timing is essential for consumer startup success.
FAQs
Mike Mignano is a partner at LightSpeed Ventures, a former founder of Anchor (acquired by Spotify), and co-founder of Obo Labs, an AI-powered learning platform.
Anchor started as a social audio platform but pivoted to become a mobile podcast creation tool after realizing users wanted easy distribution to major platforms like Spotify and Apple Podcasts, not a closed social network.
Suno aims to democratize music creation using AI, allowing anyone to make music easily, similar to how cameras simplified photography, tapping into a universal format where everyone can become a creator.
Timing is hard because consumer success often depends on tapping into cultural moments, which are nearly impossible to predict, requiring luck alongside identifying trends and the right team.
AI enables new product possibilities and can improve retention, making paid models more viable, but distribution remains a key challenge as traditional platforms have consolidated.
Anchor implemented a strict growth metric (15% week-over-week) that forced pivots based on user feedback, leading to manual but scalable solutions like creating RSS feeds to distribute podcasts.
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