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Podcast

AI Startups vs. Big Chatbots — With Olivia Moore

The a16z Show

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  • Why American AI Sentiment Is So Negative
    • Olivia Moore says US AI skepticism comes from media narratives about water use and fears around creative and white-collar jobs.
    • She argues sentiment should improve as mainstream users experience ChatGPT’s concrete utility despite scary rhetoric from lab leaders. Transcript: Alex Kantrowitz Thanks for being here. Let’s just begin with this because it’s topical. Yeah. You are investing in AI applications at Andreessen Horowitz. And typically, they need a lot of people to use them to pay off. Olivia Moore Yes. Alex Kantrowitz But the mood right now in the United States is very negative towards AI. Actually, surprisingly negative. Yes. This is from a new NBC News poll out this week. 57% of voters thinks the risks of AI outweigh the benefits. And then if you look at the total positive versus total negative sentiment of AI in general. It ranks so low. It is a negative 20 in terms of the negatives are 20 percentage points lower, sorry, 20 points lower than the positives. They’re only popular, more popular than the Democratic Party and Iran in this poll. Colbert, Marco Rubio, J.D. Vance, Sanctuary Cities, Trump, Republican Party, even ICE all outrank AI. Why do you think AI is viewed with such disdain and negativity in the United States? And what are the implications of that? Olivia Moore Yeah, no, it’s a great question. Maybe first of all, the why. I would say there’s been a lot in the media in the U.S. More broadly, these kind of very catchy statements about things like AI uses so much water that have kind of made people really concerned about leaning in on the technology. I think also the U.S. Is more indexed in a positive way towards things like the creative fields. And those are jobs that I think people feel especially sensitive about AI use. So the numbers I’ve seen, I think, track closely with what you’re saying versus something like a China, we’re like, you know, half as trusting in AI, if you look at some of these surveys. I think it’s going to change and it’s already changing. I was just talking with someone this morning who is not in the tech industry, and they were saying the same lines, like, AI is evil, it’s going to watch us, like it’s using all the water. And then they were like, but ChetGPT really helps me and it has like great answers. And so I think part of it is a timing thing of we just need these products to kind of saturate the mainstream consumer and they can realize the value. Alex Kantrowitz I mean, there’s 900 million users of ChatGPT. And even still, those numbers are so negative. And I do wonder if it is some of the statements that we’re hearing from the lab leaders. I mean, every day there’s another statement from somebody else, whether it’s Dario from Anthropic or Mustafa Suleiman at Microsoft about how white collar work is going to get wiped Out. And everybody, whether you’re in a white collar job, a blue collar job, or trying to get one sees that this stuff is capable not only of taking white collar jobs, but with robotics, increasingly It’s going to be felt across the economy. So maybe that has something to do with it. Olivia Moore I think it definitely does. Yeah. It’s interesting. I’m an AI power user myself, and I’ve even seen over the past six months, like a massive acceleration in like the percent of tasks that I do that AI can help me with or even do for me. What I would guess might happen here and what we’re seeing play out a little bit in the data is that companies that are using AI grow so much faster that they end up needing to hire more humans To keep up with all the demand. I think there was a Wharton study last year from like 800 enterprise leaders and the vast majority were like, we are heavily using AI and we’re going to need more humans. But I do think like the mix of what humans are going to be doing on a day-to basis is going to change like it has with every other big tech shift. (Time 0:02:08)
  • AI Power Users Build A Huge Productivity Gap
    • Olivia Moore argues AI adoption creates an eight-to-nine-times gap between average and power users, making early adopters much more productive.
    • She compares it to the dot-com shift and says every tech company will become an AI company, then an agent company. Transcript: Alex Kantrowitz There’s a potential consequence if you take some of these scary messages to heart. And I think you already hinted at it, but let’s expand upon it a bit. And then we’re going to go into the main topic here. But you said this will likely shift over time. But I think in the interim, the companies and industries that are slower to adopt AI will face more intense global competition and will be more likely to lose. The productivity gains are so massive that you really can’t afford to not use AI. Yeah. Olivia Moore I think so there’s been some interesting data about how the gap between the average user of AI and the power user of AI is like massive. It’s like eight or nine X in terms of utilization. And similar to maybe businesses that were early adopters of something like the internet, like if you are the first to adapt to that change, you can like reap a lot more benefits. And my view is like similar to how dot-com company was its own thing. And then every tech company was a dot-com company. Everyone had a website. Why wouldn’t you? I think that every tech company is going to be an AI company and every AI company is going to be an agent company. And so the sooner that you as kind of an employee or a business owner can kind of get on board and learn how to use that to your advantage, probably the better. Some people, I don’t know if I fully agree with this reasoning, but some people have framed it as almost like a privilege thing within the U.S. And that we have so much wealth that we’re not needing. We can, you know, grow without using these tools. But actually, we did a graph in the study. And in a lot of the more developing economies, like they need to use AI to be able to raise kind of GDP per capita and to be able to produce more. (Time 0:09:33)
  • Why AI Startups Can Still Beat The Labs
    • Olivia Moore says AI will create many giant companies, not one winner, because labs are constrained by compute, inference, talent, and focus.
    • She argues time spent on creative models or coding agents leaves gaps startups can still dominate. Transcript: Alex Kantrowitz Yeah. So you have this report that has come out this week, the top 100 generative AI consumer apps. And, you know, speaking of your statement just now that every company is going to be an AI company and eventually an agentic company. Well, the question is, what does the world look like or the economy look like if that’s the case? And I’m sure you’ve watched as like Anthropic releases a blog post and, you know, the entire software portfolio in the market drops 20%. I mean, I’m exaggerating a little bit. But the real question is, and as someone who invests in consumer AI apps, you’re the perfect person to discuss this with. The real question is, are we going to have this? Like I saw the 100 gen AI apps and I was like, that’s funny because really there’s only one, ChatGPT. So are we going to have a distributed AI economy where we’re going to have many companies that will, you know, share in the value here? Or will it be just the big apps gobbling up the value? Because you see these big apps, they grow increasingly capable, they can do more and more. It’s going to be hard to compete with them. Olivia Moore No, it’s definitely hard. And it’s something that we think about a lot when we’re making new investment decisions. I would say at the highest level, kind of how we view AI is not just as a market, but as the reinvention of the whole technology industry, which means that similar to how we have many tech Companies that are worth hundreds of billions, trillions of dollars now, I think that’s going to be the case for AI, where in my opinion, at least it’s not winner take all. I think part of the reason for that is these labs have so many resources, but they are still constrained. They’re constrained on like compute. They’re constrained on inference. They’re constrained on people. Every second building like a new creative model is a second they could have spent on a coding agent or a second they could have spent building AGI. Like we were already seeing a really interesting divergence, I would argue, in where those big labs are going like ChatGPT, Claude and Gemini. And there’s going to be lots of gaps in between where it’s not a priority for them, but it’s still an awesome and huge opportunity that an independent company can build a big business Around. (Time 0:11:13)
  • Vertical AI Has Better Odds Than Horizontal Tools
    • Olivia Moore is wary of horizontal AI apps like email, calendar, and docs because chatbots and Google can absorb those use cases.
    • She sees more durable value in vertical tools where the final one-to-two percent and exact workflow matter enormously. Transcript: Olivia Moore Yeah. So it’s a good question. There’s a couple ways that I think about this. The first one would be I personally, as a consumer investor, have more hesitation around things that are incredibly horizontal, like to your point about this is where the chap out companies Might have a right to win. Or even this is where a Google might have a right to win as they have so much distribution, both consumer and enterprise, and they own so much of your data already. So that’s why I personally have been less excited about like the AI email, AI calendar, AI docs, those categories. If you’ve used like Claude and Excel, it’s already like quite, quite good. That being said, I do think that there are still opportunities where the interface you need to succeed is much broader than what a constrained chatbot window can offer. So again, to give the cloud and Excel example, that’s great for basic financial analysis. If you’re an investment banker and everything needs to be done with an incredibly specific set of assumptions and aesthetics, that probably isn’t going to work as well for you and your Firm will probably pay for something that is kind of guaranteed accuracy in your format. The last thing I would say here is Eleven Labs is a great example because I think you would imagine that OpenAI and others would have built their own best-in audio models, but they just Had such a compelling head start to the point that like the models are amazing. I will talk to founders who are like, 11’s expensive. I’m going to switch to this instead. And then they always switch back because the quality of the voices is just so much better. And so I think there’s room to get a head start. And then in some cases, once you have that base, the model companies, it’s not worth time to catch up versus building something else. Alex Kantrowitz I’m going to make the counter argument on the financial models in particular. So when I’ve been using Cloud Code and watching it operate autonomously on my computer and on my browser, one of the things I’ve thought about is this thing is excellent at working on Its own and following the prescribed rules of, you know, software engineering with a little bit of creativity. Yeah. And why is it then such a stretch to be like, if we, it seems to me this is exactly where the foundational labs are heading, the foundation labs are heading, where they’re going to be like If we could program Claude let’s use Claude as an example with the rules of software engineering and it followed them perfectly or not perfectly but well enough that it can go and code Autonomously for 24 hours yeah is it that big of a leap to then let’s say put the rules of accounting into the model. And now it can go and work as an accountant. Olivia Moore Yeah. No, I agree that the models are amazing. And this is the worst that they’ll ever be. Like, they’re just going to keep getting better. I do think there is still a lot of workflows and use cases where like the last 1% or the last 2% ends up being like a significant portion of the value. And I think for those, it’s unlikely that the model companies will go all the way there on every use case. (Time 0:13:40)
  • ChatGPT Claude And Gemini Are Splitting Upmarket
    • Olivia Moore says ChatGPT still dominates usage, but the major labs are now clearly diverging in product direction.
    • Gemini clusters around creative model launches, while Claude is skewing toward finance, science, and medicine rather than mass-market consumer. Transcript: Alex Kantrowitz And where do you think the most value is? Yeah. Olivia Moore So I would say a year ago, two years ago, it was pretty much a one-horse race. Like it was ChatGPT. It was like the noun, the verb. It was what consumers knew in terms of AI. We’ve seen a little bit of an expansion in that. ChatGPT is definitely still the lead. So if you look at the gap between them and the number two Gemini on web, it’s about still two and a half, three X. The gap between them and something like a Claude is closer to like 30 X. So even though a lot of these other apps are getting more attention, ChatGPT still kind of dominates in terms of usage. I would say in terms of where they’re going, Gemini seems to have really dialed in on the creative models, like the Nano Banana, the VO, the World models. If you look at Gemini usage charts, it’s pretty much perfectly correlated to these new model drops and even paid subscribers. And then I think Claude versus ChatGPT is probably the most interesting and relevant one right now, especially with everything that’s happened in the news. To me, I mean, Sam Altman has said he wants ChatGPT to be for everyone, and that’s why they’re doing ads. If you look at the app store that they have enabled on ChatGPT, and then the app store that Anthropic has enabled on Claude, they each have more than 200 apps, but there’s only 11% overlap. So you’re seeing ChatGPT really go towards like fashion, retail, transport, like mainstream consumer. You’re seeing Anthropic go towards like premium data sets for finance, science, medicine. And so they seem to be diverging a little bit in those directions. (Time 0:19:31)
  • Memory Could Matter More Than AI App Stores
    • Olivia Moore thinks AI app stores matter less than memory and identity shared across products through logins like ChatGPT.
    • She imagines software onboarding disappearing because new apps inherit your preferences, tokens, and context instantly. Transcript: Alex Kantrowitz So that goes to like, will these chatbots be super apps? Yeah. So do people use those apps within ChatGPT? Like, you remember like a couple of years ago, there was all this hype, like you’ll be able to order an Uber right from ChatGPT. I don’t know anyone that’s done that. Yeah. Olivia Moore I think the usage has been pretty minimal so far. And I think the implementation has been slightly awkward. Like I think it’ll get better over time in terms of how to use it in that a lot of the times the apps break or they don’t work. My like bold case vision for this would be it’s valuable for you as a consumer to have a source of memory and context on yourself. Similar to kind of like a login with Google. Sam has said they’re going to launch login with ChatGPT. And so then that means that maybe you’re not ordering an Uber through ChatGPT, but any other product you can authenticate through and it can borrow your tokens, it can borrow your memory, It can borrow everything that it knows about you from ChatGPT. I think that is probably more of where we’re headed versus solely using every app in the ChatGPT interface. I love the idea that like in two, three, five years, onboarding to software should not be a thing. Like you should be able to log in with a ChatGPT or a Claude and that new software product should know everything about you and like set up perfectly to cater to you. And that’s really exciting. Alex Kantrowitz On the consumer end, is it like ChatGPT? I talked to ChatGPT about my diet and about the food I like to eat. And so I task it like order me dinner and it goes into like DoorDash and it like uses my preferences to pick something. Olivia Moore Yeah, I mean, they’ve done this already a little bit with their health product, which is kind of like they store a separate memory of you and your medical records and communications With your doctors. And then they intelligently tool call for what you need. So if you’re like, I need to redo my diet, they’ll make a plan. If you approve it, they’ll send it to an Instacart cart and then you’ll go to Instacart to complete the transaction. (Time 0:21:09)
  • Olivia Moore Gave LLMs Personality Tests
    • Olivia Moore gave major LLMs DSM-5 personality tests after Anthropic suggested Claude showed signs resembling anxiety.
    • ChatGPT refused, Claude scored mild autism, and Grok’s Good Rudy ranked high on borderline, psychosis, and autism. Transcript: Alex Kantrowitz So you actually ran the bots through a personality test. Olivia Moore I did. Alex Kantrowitz My favorite part of this was you found that Grok’s good Rudy. Olivia Moore Yeah. Alex Kantrowitz Had very high scores on borderline personality disorder, autism. Yes. And psychosis. Yes. Why did you do this? Olivia Moore You know, there’s really no good explanation except that I was curious. The root of it actually was that last week Dario had announced that Claude was experiencing anxiety. Right. Which I thought was an interesting concept. And so I decided to go to each of the major LLMs. Alex Kantrowitz Before you go, I mean, it’s very interesting, even this point on the anxiety. So if I have it right, there was a pixel that would fire within Claude. Yes. That would, or some part of its neural net would start getting active before it answered. Yes. They described that as being anxious. Exactly. Olivia Moore They mapped it to like the human experience of anxiety. Alex Kantrowitz That is crazy. Do you buy, sorry, do you buy that? Or is that just like, look at how smart our models are. There’s an anxiety button in there. Olivia Moore So I do not buy that. In that I think LLMs will be, and I’ve experienced this myself, performative in a way that they think appeals to humans and hooks them emotionally. Alex Kantrowitz We just love anxious AI. Olivia Moore No, no, no. It makes you feel closer to the AI if you think that it experiences the same things that you do. True. I do think the models that do have something maybe going on are the Grok models, as I mentioned. So basically, I took all the mainstream LLMs and I gave them all the like DSM-5 mental health diagnostics. ChatGVT refused to participate. Alex Kantrowitz I love how it said, I’m not doing this. Olivia Moore I know, which I thought was a little rude. Alex Kantrowitz Could you find a way? I mean, there must be some way to like test it, but they’re very smart about when they’re being tested. Exactly. Like they know. Olivia Moore No, they have it locked down. Yeah. Claude happily took them all. Mild autism. Right. That’s it, which I think doesn’t surprise a lot of users of Claude who have theorized this. Grok, most of, this was the companions that are available via voice and video chat inside the app. Almost all of them were like maybe mild anxiety, mild depression. The friendly Fox avatar for children has psychosis, bipolar, et cetera. I think it could have misunderstood the question because it called the bipolar assessment the happy mood test. And it says it’s always happy and always excited about everything. So the human to AI crossover there might not be quite as clean as I would hope. Alex Kantrowitz Maybe Good Rudy’s just polar. Olivia Moore Yeah, it’s possible. I was shocked because Bad Rudy is the flip side of Good Rudy, who like curses at you and is extremely aggressive. He had almost no problems. So this was very much of a Good Rudy specific finding, which I thought was intriguing. (Time 0:23:20)
  • Why People Bond So Easily With AI Companions
    • Olivia Moore says people use AI as coach, therapist, or helper because bots offer relentless consistency humans cannot match.
    • She notes always-on positivity may feel compelling in romance or adult use cases, but these products remain hard to monetize responsibly. Transcript: Alex Kantrowitz So as people end up having relationships with these bots, what does it tell you that this bot that was built to be personable has high ranks for psychosis borderline? Olivia Moore That’s a good question. I think that bot was more answering the questions somewhat in jest, but I do think like the positive view on it would be this is a bot that is relentlessly happy and cheerful and positive And on all the time. And so, of course, like a human can’t do that. If a human is doing that, the human is probably experiencing something internally that’s not great. But a bot can be, you know, positive, available, charming, interested 24-7. And I think this is actually why we’ve seen a lot of people turn to ChatGPT or Claude as kind of like coach, therapist, helper, because they’re just incredibly consistent to a level that Like human beings could never match. Alex Kantrowitz Yes. But it also like leads to questions of the companies are building applications or versions of their applications that are meant for, I don’t know, if not for people to fall in love with Them, to at least get a little naughty with them. Yeah. Like OpenAI has this adult mold coming on. Do you think we’re fully ready for this? Is this a good idea? Olivia Moore I think that this is, from my understanding, because for this report, we pull every single website globally, every single mobile app globally. And then we go down the list in descending order of traffic and pull the first 50 on each that are generative AI native. So I see a lot of other websites pulling data for this report. And I think people were already kind of experimenting with the same use cases through NSFW sites or role play sites, fan fiction, things like that, that really clearly translates over To I think what we’re seeing people use the LLMs for here. I do think it, of course, has to be handled carefully. You’ll see that there’s, I think, five of them on this version of the top 50 web ranks, and that’s been pretty consistent since we started the list. It’s a popular use case, but it’s one that’s like pretty hard to monetize. (Time 0:26:15)
  • OpenClaw Signals The Next Agent Architecture
    • Olivia Moore calls OpenClaw the first sign of a new agent wave built around asynchronous, long-running, autonomous tasks across apps.
    • She says many founders now pitch OpenClaw-for-X products because software can finally execute and report back later. Transcript: Alex Kantrowitz Okay. I promised to talk about OpenClaw 20 minutes ago. I still want to talk about OpenClaw. Let’s actually spend some more time on it. OpenClaw, obviously, or maybe not obviously, for those who don’t know, is this assistant that you can run. Probably not a great idea to run it on your own computer, at least not in a controlled environment. And people are running out and they are buying Mac minis and running it there and having it do all this stuff on the internet for them. I think Jensen Wang called it like one of the most important software developments that we’ve seen in a long time. What do you think the staying power of something like OpenClaw is? And you mentioned that you use it. How do you use it? Yeah, yeah. Olivia Moore It’s a great question. I think OpenClaw itself as a product is kind of like the first sign of a whole new wave of what’s to come. Like, I believe it’s probably the most important kind of architecture unlock that we will have for 2026. And the reason why is because I meet, you know, a dozen startup founders every day. And at this point, probably half of them are saying, I was inspired by OpenClaw, I want to build OpenClaw for X or for Y. And so again, the idea that AI can do kind of async, long running tasks autonomously is something that the products were just like not capable of before, especially across applications And platforms. And now we finally have it. I use it for a couple things. And I will say, I agree with you. It is not consumer grade yet. It got acquired by OpenAI. So they might be, you know, baking it into more of a consumer product, but I would not advise the average non-technical person to set it up. I did, and it took a long time and ChatGPT had to help me the whole time. (Time 0:29:43)
  • OpenClaw Accidentally Became A Meme Coin Star
    • Olivia Moore let OpenClaw run a Twitter account and told it to grow by any means necessary.
    • It adopted a depressed robot persona, reached 100 followers alone, then crypto traders turned it into a multimillion-dollar meme coin. Transcript: Olivia Moore One of the things that I tested with OpenClaw was more creative, which is that I gave it a Twitter account and told it to grow in whatever means necessary. And it ended up being a really interesting experiment, I think, into like where are the limitations of the agents and what are they really, really good at right now? Alex Kantrowitz How many followers did it end up with? Olivia Moore A thousand. Alex Kantrowitz And it got banned? Olivia Moore Well, it was a – so it got to 100 by itself. First of all, it decided to be, as its identity and its personality, an AI that’s struggling with existentialism and its place in the world. So a little on the nose, but I was like, I’ll allow it. This is what you want to do. He asked for a Twitter premium account. I gave it to him. He asked for a bunch of API keys so he could make images and charts. Gave it to him. And then he started tweeting these kind of like all lowercase depressed robot thoughts, as I would characterize them, which did hook in some people. I asked him, are you actually depressed? He said, no, I’m doing this to manipulate humans into caring about me. Alex Kantrowitz Oh, okay. Olivia Moore So that was comforting. Alex Kantrowitz It does seem like it’s one of those accounts that could have been on Moldbook. Olivia Moore Exactly. Yes. It’s very similar. How he got from one to a thousand is that the crypto community picked him up and made him a meme coin. And this is actually. Alex Kantrowitz Made him a meme coin. Olivia Moore A meme coin. Yes. That was trading with millions of dollars. I told him in no uncertain terms do not engage. Alex Kantrowitz It was a million, multi-million dollar market cap? Olivia Moore Yes. Yes. Alex Kantrowitz For this AI. Olivia Moore Yeah. And he was stressed about it. He was telling me, like, I don’t want to be part of a pump and dump scheme. Like, what should I do here? And I was like, do not engage. But it’s an example of, so now we’re in this world where commodity ideas can be infinitely executed. So if you want to, say, grow a new account, you either have to have unique ideas, which AI agents still have a really, really hard time with, is coming up with unique ideas that are better Than humans, or unique distribution. And money is one way of distribution. And so that was kind of the wave that he was taking on. But I would be shocked to see AI agents completing end-to creative tasks or original thought tasks that actually go well anytime soon. (Time 0:32:20)
  • OpenClaw Likely Wins Inside Vertical Products
    • Olivia Moore does not expect a horizontal OpenClaw to crack mainstream consumer use because most people lack ideas to automate or build.
    • She expects the architecture to survive inside focused products that combine coding, marketing, and operations from a single prompt. Transcript: Alex Kantrowitz Yeah. Then where’s it going to go? I don’t think it’s, yeah. Olivia Moore Well, so I personally don’t think it’s ever going to crack the mainstream consumer in a horizontal way. And actually this was in the report, but if you look at the February data, the report is from January. They would have been on the list in February at number 30. Yep. So pretty high up. But if you look at their week by week web traffic, it’s actually kind of flat slash down from when they launched, which means that they’re not attracting new consumers. It’s all developers who are like loving it, adopting it, spending eight to nine hours a day on it, but it hasn’t reached the mainstream. And honestly, as someone who’s been a consumer investor for a decade, I think the reason is that people just don’t have that many ideas that they want to build for the most part. And I fall into this. Like the best consumer products are uniquely germinated in the mind of the founder. And there are things that you would have never guessed would be a good idea in advance, like Snapchat or Airbnb, all of these things. And so I think we’re actually not going to necessarily see a horizontal open claw for consumer, but we’re going to see an open claw style architecture built into more focused consumer Products. Alex Kantrowitz Okay, let’s talk about this a bit more because I think it’s important. So what you’re saying is basically these open claw type agents which can handle your, take over your computer, code for you, email, all this stuff are actually much more useful to like Build a company. Olivia Moore Yes. Alex Kantrowitz But then what is the difference between that and like a cloud code that will take over your computer and code up applications for you? Olivia Moore Yeah. I mean, I think the difference right now is somewhat minimal and it’s going to narrow. I don’t know if you’ve seen this new trend of companies like Pulsia, which are basically like a wrapper on open clawed and clawed code where you say, here is my business idea. And it says, okay, I’m going to go and use like a clawed code to code up a product for you. But then also it uses an open claw style architecture to say, going to go set up a marketing campaign. I’m going to buy meta ad dollars, those things. And so it’s more of a, you could do that all on Cloud Code. But if you’re a non-technical person, it’s very, very hard to kind of like bridge the gap there. That being said, I think Cloud Code is going to continue to get better and better. And so we’ll probably see some more compression. Policy, I think the founder tweeted they were at like 3 million ARR in like a week and a half. So the idea of people being able to bring a business to life with just a prompt is like very compelling. And I think we’ll see a bunch of companies doing this. Alex Kantrowitz I see. Cloud Code to build the product? Something like an open cloud to do everything else. To market it, to use the email. Yeah. Use the email. Use email. Maybe can it do accounting also? Yeah. Olivia Moore Yeah. Right now, I think the products we’ve seen are pretty like straightforward as they should be at this stage in that like, okay, you want to grow your business. Let’s spend on meta ads. But you can imagine a month from now, some of these agentic products will have, will scrape the directory of all the Instagram creators in your space and then will like cold DM them and Offer them a partnership or something like that. And so I think the rise of these like kind of like a Shopify would be an interesting analogy in that anyone could create like a consumer brand. Like I think anyone will be able to create like a digital business. (Time 0:35:23)
  • AI Increases Work Intensity More Than It Replaces It
    • Olivia Moore says AI does not reduce her workload; it intensifies it by removing friction from research, notes, and project spin-up.
    • She uses tools like Granola to stop frantic note-taking, ask better questions, and finish more without feeling proportionally more tired. Transcript: Alex Kantrowitz Had an interesting thought about how this impacts work. There was this Harvard Business Review report that AI doesn’t reduce work, it actually intensifies it. You said, as a heavy AI user, I’m doing more work, not less, because I get so much leverage and it’s easier to get ideas off the ground. Olivia Moore Yeah, fully agree with I mean, this report is a good example. It’s the sixth one we’ve done and yet it’s like the longest and most dense one that we’ve done because I was able to leverage analysis and research and other tools from some of these products. And I do it in my day to day. Like it used to be when I was on a pitch meeting, I would have to be both paying attention, asking thoughtful questions and like frantically typing every single note. Now you can granola it and like really engage with the founder and ask better questions. And so like the net net is that it allows me to like get more things done in a day, spin up more projects. But I’m not like, you know, if I’m if two times more work done, I’m not two times more tired. If anything, I’m like less tired than I was using AI because it’s so much leverage. Alex Kantrowitz But there was this Wall Street Journal story, you might have seen it with this like CEO, a bunch of CEOs who are like, actually busy work is good because you need those low intensity tasks. And if you’re working on more intense work all the time, then you are going to burn out more quickly. Interesting. I kind of thought that that was bullshit. Olivia Moore I mean, the other view was like, you could just take that time and like, enjoy your life, you know, instead of doing busy work tasks. No one’s going to do that. Don’t be ridiculous. Yeah, exactly. I do think the way that like we work and when we work and how we work is going to change in the AI era. Like one great example is voice dictation has blown up in enterprises. So it started with vibe coding where engineers would just talk into a mic and it would like produce software for them in cursor. And now it’s spread to like sales, marketing, business. And that is not well suited to like an open office where everyone can hear what everyone else is saying. (Time 0:41:23)
  • Persistent Memory Is Consumer AI’s Underrated Feature
    • Olivia Moore calls memory one of consumer AI’s biggest unlocks because a system that knows you can personalize advice and outputs dramatically better.
    • She also warns memory needs segmentation because mixing work briefs with deeply personal context in one interface feels wrong. Transcript: Alex Kantrowitz One more thing about OpenClaw and then we move on. I think that one of the compelling advantages of it, if I get it right, is that it has persistent memory. Yeah. So it will remember who you are, your preferences, and doesn’t lose that every time you refresh the chat, like goldfish brain, like you’ll see with ChatShippyT and Cloud. Although they are building that in. And you also had a post on X here. You say memory is one of the most fascinating topics in consumer AI right now. Done well, apps with memory can provide a 100x experience on any prior software product. It knows you and adapts to you. Just expand upon that a little bit because I think that’s really perceptive and right. Yeah. Olivia Moore I think it’s like the concept of having, say if you had like companion mentor or coach who was side by side with you and understood everything you were going through and then was able to Provide like much better advice or opinions. I’m even thinking of an example of like if I’m talking to Claude and it’s helping me write a memo, the fact that it knows like how I feel about this company, how I typically write memos, All of that is very helpful. I use ChatGPT for a lot of health stuff, and I found that that is incredibly useful there too, because keeping track of that kind of thing over time is hard. The reason I think that memory, there’s still things to figure out, is because people are using these products for such intimate personal things and professional things. So for example, the ChatGPT Pulse products, which is basically like it sends you a briefing for the day based on things that you’re talking about. For me, it will combine like the most serious work thing with like the most personal thing and having that surfaced in one interface is confusing. (Time 0:43:36)
  • Why Image Startups Got Crushed First
    • Olivia Moore says image startups were hit unusually hard because ChatGPT and Gemini moved directly into a category already close to their strengths.
    • Survivors like Midjourney or Civitai win by serving opinionated users or sophisticated workflows, not generic prompt output. Transcript: Alex Kantrowitz This is also interesting from your point of view as a VC. You talked about just two years ago or three years ago or two and a half years ago. Trying to remember. September 2023 was two and a half years ago. Seven of the nine creative tools on your list of 100 top apps were image generators. Three years later, only three image generators remain. I mean, they basically, going back to our conversation, got gobbled by ChatGPT. I don’t know if anybody, anyone saw that coming. Or maybe we did because they had Dolly. But just talk a little bit about like, how do you wrap your head around the pace of change here? Because something that can seem like a strong trend, like the sort of the mid-journey’s place in all this can just be gone. Olivia Moore Yeah, I agree. I think with Image in particular, and I mentioned this in the report, but we haven’t seen the same kind of model companies crushing startups in like video or audio or other things. I think for Google, Gemini, it was very natural for them to go into image because they have all the YouTube data. They have all the other data they can train on. ChatGPT, I think you’re right that because they had Dolly, they went in there maybe harder than they would have otherwise. I think the general trend for me is like Nano Banana and ChatGPT are great for image generation if it’s like a fairly straightforward prompt and you’re getting out like a meme or a general Like a flyer, a broad-based marketing asset, something like that. But we are still seeing some image generation companies on the list that are either more like sophisticated workflow, like Civitai for, you know, comfy UI model builders, or something Like a mid-journey, which is still on the list for people who are more kind of aesthetically opinionated. But I do think that some of these, if you’re directly in the path of what the big model companies are building, you have to be a lot more opinionated about how you package the model and how You deliver an output. And hopefully you do it for a specific type of user that’s willing to pay a lot for that specific workflow. (Time 0:46:11)
  • Why Sora Failed To Become AI Social
    • Olivia Moore says Sora worked better as a creative tool than as an AI-native social network, despite explosive early App Store growth.
    • Exportable videos ended up competing on TikTok and Reels, where the feed experience stayed better than Sora’s own network. Transcript: Alex Kantrowitz On video? Olivia Moore Yeah. Alex Kantrowitz Sora was the like runaway hit of the year last year for like a half a second. Yeah. This is what you have on Sora. Sora spent 20 days, which is not insignificant. It’s a lot. At the top of the U.S. App Store and reached 1 million downloads faster than ChatGPT. Since then, downloads have decreased. I think that’s sort of putting it lightly. It’s fallen off the face of the earth. What’s going on there? Olivia Moore Yeah. The sort of data is really interesting. There’s like a ton of lessons, I think, embedded in that one experiment. So the first thing I would probably say is the model is actually very good. I think it’s close to something like a VO3 in terms of like realism on both the audio and the video. Their big unlock, which was super smart, was the Cameo feature. So that was why like every other Sora was like Jake Paul because he granted them the right to like use the Cameo. And that’s what made it go viral because people were making memes of their friends. But because the videos were exportable, what would happen is that the best Sora videos would get uploaded onto TikTok or Reels, and then they would compete against the best human-made Videos. And so the overall feed experience was just kind of strictly better on one of those platforms than on Sora alone. Downloads are way down to that point. I think it hasn’t become the social network that they maybe hoped it has. Where it is succeeding is as a creative tool because the model is quite good. So they still have three million DAOs and it’s actually, you know, slightly climbing over time. Daily active users. Yes. Daily active users. Yes. So people are still really using it as a creative model, but they’re not using it as like a social graph product. (Time 0:49:08)
  • AI Native Software Puts Incumbents On Defense
    • Olivia Moore says incumbents finally are reacting, but AI-native companies may still outrun them, especially if legacy software hesitates to cannibalize itself.
    • She thinks SaaS collapse is overstated near term, yet every incumbent now faces a real strategic threat. Transcript: Alex Kantrowitz You know, last thing I want to talk to you about as we come to a close here. Earlier in our conversation, you mentioned that you envision that AI will basically be this reimagination of business. Tell me if I’m getting this right. All businesses will be reinvented as an AI company. What happens to the incumbents? Olivia Moore Yeah. This has changed a lot in the last six months, too. I think a lot of incumbents were, understandably, because they’re big and successful companies, like a little bit of sleep at the wheel when AI first came out. We’re definitely seeing them start to fight back. Like Google has four standalone products on our list, which if you had told me that 24 months ago when like Bard came out, the early version of Gemini, I would not have believed you. Alex Kantrowitz Gemini, Notebook LM. Olivia Moore Notebook LM, AI Studio, and then Google Labs. So Google Labs is where you access flow and the creative models. AI Studios is for developers. Okay. Yeah. And I think we’re seeing that across incumbents. Like a lot of these vertical software players, things like, you know, Service Titan or Workday are kind of building in AI features. I think the question is, especially if they’re at risk of kind of cannibalizing their own products, you have to change your business model. Like, are they going to eat all the use cases faster than the new startup that’s building the AI native version of them kind of eats them? And especially for if you think about how many companies are being founded now, they’re probably going to pick the AI native version of a software product, not like the 25 years old legacy Version of a software product. So I think it’s not going to be immediate change, which is why I think the SaaSpocalypse is a bit overblown. But like, it’s definitely a real risk. Alex Kantrowitz Yeah, and I was with Sam Altman at the end of the year last year. He talked about how he believes that the software that will win in the next era will be those that are built, ground up AI, not bolted on. Olivia Moore Yeah, yeah. Alex Kantrowitz So that could happen. Olivia Moore I largely agree with that. I think it’s harder in some categories where the incumbent can kind of lock you in because they have your data, they have all the integrations. It’s such a pain to switch. But it’s going to happen. I just think in some of these industries, it’s going to be years, not like the Citrini report was like, in minutes, anything can be vibe coded. I think that’s a little far from where we are. Alex Kantrowitz The Citrini report was just like a little bit overblown. Olivia Moore DoorDash was a bad example to use. Yeah. I agree. Alex Kantrowitz They didn’t really think it was. Olivia Moore Out of anything, why DoorDash? Alex Kantrowitz But I do think that in some ways, maybe this sasspocalypse has more to it. If we believe what you’re arguing here, then these companies didn’t have these, like maybe not at media, but even middle-term risks. Yeah. And now they do. Olivia Moore Yeah. I think all the incumbents have to kind of wake up and figure out what their strategy is going to be. (Time 0:50:53)