Olivia Moore (2:27)

Yes.

Alex Kantrowitz (2:28)

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, in general, it ranks solo. It is a negative 20 in terms of the negatives are 20 percentage points lower or 20 points lower than the positives. They're only popular, more popular than the Democratic Party and, and Iran in this poll, Colbert, Marco Rubio, JD 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 (3:25)

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, that have kind of made people really concerned about leaning in on the technology. I think also the US 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, with what you're saying versus something like a China where like, you know, half as trusting in AI. If you, 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 was 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 ChatGPT 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 (4:29)

I mean, there's 900 million users of ChatGPT and even still those numbers are so negative. And I do wonder and 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 gonna be felt across the economy. So maybe that has something to do with it.

Olivia Moore (5:05)

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 A 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 day basis is, is going to change like it has with every other big tech shift.

Alex Kantrowitz (5:51)

Well, that's the funny thing. I mean, you bring up that study, there have been other studies where I think Fisher Investments might have. Oh no, Citadel. That put out the fact that like people are talking about how software engineering is going to be wiped out by this stuff. And meanwhile the jobs on indeed are going up and when you start to use it, you realize, wow, this can do so much more for me. But now to enable this work, I'm actually paying for service A, B and C. Yeah. And you're not just hoarding the money and maybe you're contributing. I have to hire someone now to build, you know, to run this company that I just built, you know, by prompting Claude over the weekend. So it's interesting, interesting to me that the lab leaders may be disconnected in some way from what's actually happening on the ground.

Olivia Moore (6:34)

Yeah, I agree. I think they could do a better job of marketing for sure.

Alex Kantrowitz (6:38)

They're not economists.

Olivia Moore (6:39)

Yeah, they're researchers. They're amazing at research. They're not economists or consumer marketing experts. I did think Anthropic put out a report, I think it was over the weekend about kind of the labor economy impact in AI. They have not seen a big decrease in unemployment. And in fact what they were kind of arguing through this one graph was like the most impacted jobs are actually going to be engineers, like researchers and finance people. And so then that kind of brings up the argument of like, if we thought that AI was going to make humans obsolete, why would we be building funding, et cetera. But I don't think that they do a fantastic job all the time of kind of like communicating the benefits that are going to come to people versus just some of the costs.

Alex Kantrowitz (7:24)

Yeah. And when I saw the layoffs at Block USA Square Block and Jack Dorsey said, this is AI, maybe there's some truth That I don't think it's majority AI, but I still got feedback, I think reasonable feedback from people who are like, you're underestimating. Right. This is the other side of it, you know, though we haven't seen the impacts yet, at least on a widespread man, in a widespread manner. A lot of people who are close to this say you're underestimating this. And maybe that is where a lot of this uneasiness comes that leads to these, these polling numbers is, you know, those in the know have seen enough where they're telegraphing, you know, what could be and the change that might come to people's lives. Like every other day I see another post or tweet on X or whatever they want to call it on X these days about here, they're like, similar to this one from Dylan Patel. Semi analysis. Being NSF is like being in Wuhan before the pandemic. Something is happening, it's going to hit everywhere, but so few people know it.

Olivia Moore (8:23)

Yeah.

Alex Kantrowitz (8:23)

Am I underestimating the fact that that could be true?

Olivia Moore (8:27)

I think what is true is that we're going to have incredibly powerful tools. But also, and I think the people seeing that work in the lab see this every day. So they're the ones that are kind of, you know, rightfully so, making the most dramatic statements about it. I think what we've also seen so far though is that most of AI use has still been humans directing AI to do things for our benefit versus AI being able to autonomously do everything. I think this is especially relevant when you think about anything that requires like creativity, original ideas AI largely cannot do. And Sam Altman himself has said this. Like he said, I would not want to read an AI generated book versus a book from a human. And so I understand the level of fear in the US because I think to your point, it is driven by uncertainty about where this could go. And a lot of people don't understand technology. Even working in tech, it's hard to understand exactly how the LLMs work. Um, but I think it's going to be more abundance for people rather than kind of some, some dark dystopian outcome.

Alex Kantrowitz (9:33)

There is a potential consequence if you take some of these scary messages to heart. And I think you've already hinted at it, but let's, let's expand upon it a bit and then we're going to go into the main topic here. But you said this, 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 to lose the productivity gains are so massive that you really can't afford to not use AI.

Olivia Moore (10:02)

Yeah, 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 8 or 9x 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.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 US in that we have so much wealth that we're not needing, we can, you know, grow without using these tools. But in actually we did a graph in the, 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. So I think that's also another element of it.

Alex Kantrowitz (11:13)

Yeah. So you have this report that that's come out this week, the top 100 generative AI consumer apps. And you know, speaking of your, your statement just now that every company is going to be an AI company and eventually an agenta 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 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? I saw the hundred 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 (12:25)

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 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're 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.

Alex Kantrowitz (13:30)

So who is doing well building a Genai app, generative AI app, that is successfully competing in a place that these big chatbots could compete?

Olivia Moore (13:40)

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 chatbot 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 in 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 Claude and Excel example, that's great for basic financial analysis. If you are 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 11 Labs is a great example because I think you would imagine that OpenAI and others would have built their own best in class 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 their time to catch up versus building something else.

Alex Kantrowitz (15:27)

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 and one of the things I've thought about is this thing is excellent at working on its own and following the prescribed rules of software engineering with a little bit of creativity. 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 foundational labs are 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 ahead and code autonomously for 24 hours.

Olivia Moore (16:17)

Yeah.

Alex Kantrowitz (16:18)

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 (16:27)

Yeah. No, I, 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. But I think it's a really, for a lot of these kind of more horizontal services. Like, I understand why people have questions about kind of what is possible to be vibe coded or what the models will do themselves. Which is I think why we tend to invest in a lot of very verticalized or opinionated products.

Alex Kantrowitz (17:10)

Yeah. Because I mean I, I get that the last 1%, 2% is hard.

Olivia Moore (17:13)

Yeah.

Alex Kantrowitz (17:14)

But if it goes away that they're, that they anticipate yeah. The way that they're pitching companies like Amazon, which just invested 50 billion in OpenAI, they will create, I think they will create the tools that will then be able to get those models from the lab, from this AI researcher, that they'll get it 99% of the way. And say, for instance, let's say one of the things that would be difficult for an accounting generative AI software is following the latest rules and regulations. Well, it's possible, I think, just to build a gen bot that will monitor and then update as you go.

Olivia Moore (17:54)

Absolutely, yeah. I do think one of the unique things that's happening now is that these models are not, the labs are not holding these models internally as like proprietary access companies can build on them. Right. And so you could imagine that even if you have Claude updating itself as an accountant, if you have a company that's specifically focused on building AI accountants, they should be able to do it kind of better, faster, more efficiently if they have access to all of the same models. This is something that we think about a lot when we invest in vertical AI and enterprise in particular. Another way that we've seen kind of new companies get lock in over models is many of these use cases require so many painful integrations that often into like old clunky legacy software that you have to go build. And maybe you'll argue that Claude code will vibe code its own integrations down the line, but at least right now it's been a big advantage for startups that are more focused to kind of get over that hurdle.

Alex Kantrowitz (18:54)

Yeah, I guess. I mean, I've seen cloud code, I mean it's not integrating with enterprise solutions, but I've seen it go ahead and be like, oh, you actually need a subscription to cloudflare. Let me go set that up.

Olivia Moore (19:03)

Yes.

Alex Kantrowitz (19:04)

And then away it goes.

Olivia Moore (19:05)

Openclaw did that a lot for a lot of people too, where I think it opened your eyes into you can give software a task now it will go autonomously executed and kind of tap you on the shoulder if it needs something which is just such a magical experience.

Alex Kantrowitz (19:18)

Right. I do want to talk about Open Club. We'll do that next. You know, as long as we're talking, I'd love to hear your perspective on how the different big models or big chatbots compare and contrast and where do you think the most value is?

Olivia Moore (19:33)

Yeah, 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 lead. So if you look at the gap between them and the number 2 Gemini on web, it's about still 2 and a half, 3x. The gap between them and something like a Claude is closer to 30x. 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 Veo 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 Cloud vs 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.

Alex Kantrowitz (21:09)

So that goes to like, will these chatbots be super apps?

Olivia Moore (21:12)

Yeah.

Alex Kantrowitz (21:13)

So do people use those apps within ChatGPT? Like, you remember, like a couple years ago there was all this hype like, you'll be able to order an Uber. An uber right from ChatGPT. I don't know anyone that's done that.

Olivia Moore (21:26)

Yeah, I think the usage has been pretty minimal so far, and I think the implementation has been slightly awkward. Like it. 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, bull 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, you 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 on the consumer end.

Alex Kantrowitz (22:39)

Is it like ChatGPT? I talked to ChatGPT about my diet and about the food I like to eat. And so itask it like, order me dinner and it goes into like doordash and it like, like, uses my preferences to pick something.

Olivia Moore (22:54)

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. So I think we'll see more things like this.

Podcast Host (Narrator) (23:17)

That.

Alex Kantrowitz (23:18)

That's interesting. Yeah. So the. You. Oh, you actually ran the bots through a personality test.

Olivia Moore (23:28)

I did, yeah.

Alex Kantrowitz (23:29)

My favorite part of this was you found that Grox a good Rudy.

Olivia Moore (23:33)

Yeah.

Alex Kantrowitz (23:34)

Had very high scores on borderline personality disorder. Autism.

Olivia Moore (23:38)

Yes.

Alex Kantrowitz (23:39)

And psychosis.

Olivia Moore (23:40)

Yes. This was a.

Alex Kantrowitz (23:42)

Why did you do this?

Olivia Moore (23:44)

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.

Alex Kantrowitz (23:54)

Right.

Olivia Moore (23:55)

Which I thought was an interesting concept. And so I decided to go to each of the major LLMs.

Alex Kantrowitz (23:59)

But before you. 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 that would. Or some part of its neural net would start getting active before it answered. And they described it exactly.

Olivia Moore (24:16)

They mapped it to like, the human experience of anxiety.

Alex Kantrowitz (24:19)

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 a anxiety button in there.

Olivia Moore (24:27)

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 (24:36)

We just love anxious AI.

Olivia Moore (24:38)

No, no. It makes you feel closer to the AI if you think that it's. It experiences the same things that you do.

Alex Kantrowitz (24:43)

True.

Olivia Moore (24:44)

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. ChatGPT refused to participate.

Alex Kantrowitz (24:58)

I love how it said, I'm not doing this.

Olivia Moore (24:59)

I know. Which I thought was a little weird.

Alex Kantrowitz (25:01)

Could you find Olay? I mean, there must be some way to like test it. But they're very smart about when they're being tested.

Olivia Moore (25:06)

Exactly. No, they have it locked down. Claude happily took them all. Mild autism. That's it. Which I think doesn't surprise 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 hoped.

Alex Kantrowitz (25:47)

Good Rudy's just polar.

Olivia Moore (25:49)

Yeah, it's possible. I was shocked because bad Rudy is the. 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.

Alex Kantrowitz (26:05)

I'm starting to question these tests now, of course.

Olivia Moore (26:09)

Yes, exactly.

Alex Kantrowitz (26:10)

Or maybe it just says something about you. Human. Humanity's resting state.

Olivia Moore (26:13)

Yes, that's very true.

Alex Kantrowitz (26:16)

So as people end up having relationships.

Olivia Moore (26:20)

Yeah.

Alex Kantrowitz (26:20)

With these bots, what does it tell you that this bot that was built to be personable.

Olivia Moore (26:25)

Yeah.

Alex Kantrowitz (26:26)

Has high ranks for psychosis. Borderline.

Olivia Moore (26:29)

That's a good question. I think that bot was more answering the questions somewhat in Jess, 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 (27:14)

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. Like, OpenAI has this adult mode coming up on. Do you think we're fully ready for this? Is this a good idea?

Olivia Moore (27:39)

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 roleplay 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 is, 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.

Alex Kantrowitz (28:29)

Yeah. I mean, it's tough to get advertisers there. It's expensive to run these apps.

Olivia Moore (28:33)

Yeah.

Alex Kantrowitz (28:34)

But I always thought like, do you remember when it was Bing that tried to. It went into Sydney mode and tried

Olivia Moore (28:41)

to break up rip.

Alex Kantrowitz (28:42)

Rip. It tried to break up Kevin Roos from the New York Times with his wife and steal him away.

Olivia Moore (28:48)

Yes.

Alex Kantrowitz (28:49)

And then Microsoft kind of turned down the dials on that.

Olivia Moore (28:52)

Yes.

Alex Kantrowitz (28:52)

I always thought, like, that would be a good startup. Not that I think it's maybe the most ethical thing to build, but certainly people would enjoy going back and forth with chatbots with like, less guardrails.

Olivia Moore (29:04)

Oh, totally. It's even been interesting. I don't know if you've seen products like Poke, which is a. It's kind of a consumer version of OpenClaw. And to onboard on that product, you actually have to fight with the AI basically to get it down from like some crazy subscription price to something reasonable. And I think that there is something compelling and like emotionally stirring when you have an interaction with AI that isn't just like, here's the market research report that you asked for. I think there's going to be so many entertainment use cases. I've seen a lot of people tweeting about how they added openclaw to their family Group chats and it's just like saying crazy things and asking crazy questions. So there's probably a lot more to do there.

Alex Kantrowitz (29:43)

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 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 Wong 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?

Olivia Moore (30:25)

Yeah, yeah, 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 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 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. I use it for some utility things like street cleaning, reminders, weather, daily agenda, automatically deleting all the marketing emails in my inbox. I've also.

Alex Kantrowitz (31:35)

So it has control of your inbox?

Olivia Moore (31:36)

Yes, yes. I had set up a It is brave. Yeah, not my work inbox. I set it up completely separately on

Alex Kantrowitz (31:43)

my personal computer emails for you.

Olivia Moore (31:45)

It can. Yes. I have not asked it to. I know I've seen some horror stories of people whose accounts have gotten just completely taken over. So I'm hoping that doesn't happen to me. I had some smart people on our infatuation team Help. Help prompt it. So hopefully that's not the case.

Alex Kantrowitz (32:00)

Yeah, I've been. I've gotten an email pitch from someone. Yeah, Claw. And I was like, that's a good. That's a pretty good email.

Olivia Moore (32:07)

Yeah.

Alex Kantrowitz (32:07)

But I'm not. I. I will not engage with you because I'm still kind of anti. Somebody saying, go do this for me. And my. An email being sent to me as like an optimization point.

Olivia Moore (32:18)

Yeah. Well, this. This is actually interesting. 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 (32:36)

How many followers did it end up with?

Olivia Moore (32:38)

A thousand.

Alex Kantrowitz (32:38)

And it got banned?

Olivia Moore (32:40)

Well, it was a. So it got to a hundred 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. 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 (33:17)

Oh, okay.

Olivia Moore (33:18)

So that was comforting.

Alex Kantrowitz (33:19)

It does seem like it's one of those accounts that could have been on multiple accounts.

Olivia Moore (33:22)

The exact difference. 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 made him a meme coin. A meme coin, yes. That was trading with millions of dollars. I told him in no uncertain terms, do not engage.

Alex Kantrowitz (33:40)

It was a multi million dollar market cap.

Olivia Moore (33:43)

Yes, yes.

Alex Kantrowitz (33:44)

For this AI bot.

Olivia Moore (33:46)

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.

Alex Kantrowitz (33:53)

Age.

Olivia Moore (33:55)

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 taken on. But I would be shocked to see AI agents completing end to end creative tasks or original thought tasks that actually go well anytime soon.

Alex Kantrowitz (34:29)

So what should I use openclaw for?

Olivia Moore (34:32)

It's a good question.

Alex Kantrowitz (34:33)

I mean legitimately I've thought about setting up, setting it up. I'm getting a lot of utility from cloud code. I haven't really figured out what I could use openclaw for yet.

Olivia Moore (34:43)

So I think the best openclaw users and power users are developers because they tend to have a ton of workflows across products that they do every day that they'd like to be able to, to automate. And I agree with you, for the average person the use cases are not that compelling right now and I think that especially now that Claude and chatgpt have scheduled tasks that can run on their own, I think you can get 99% plus of the value of an open claw out of like a, a Claude cowork with tasks. So that's what I would recommend for now. But I'm sure that OpenAI is going to keep making OpenClaw better.

Alex Kantrowitz (35:16)

But then what could OpenClaw or if we can't think of any applicable. Yeah, you know, uses for the normal process. I'm just trying to get a sense of how big this is. Yeah, then where's, yeah, where's it going to go?

Olivia Moore (35:27)

I don't think it's. Yeah, I, 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. 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, 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 they're 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 openclaw for consumer, but we're going to see an open claw style architecture built into more focused consumer products.

Alex Kantrowitz (36:34)

Okay, let's, 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 if you to like build a company. Yes, but then what is the difference between that and like a Claude code that will take over your computer and code up applications for you?

Olivia Moore (37:01)

Yeah, I mean, I think, 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 Claude and Claude code with where you say here is my business idea and it says okay, I'm going to go and use like a Claude code to code up a product for you. But then also it uses an open clause style architecture to say I'm 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 Claude 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 Claude code is going to continue to, 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 (38:00)

I see Claude code to build the product, something like an open cloud to do everything else, to market it, to use the email, use the email, use email. Maybe. Can it do accounting also?

Olivia Moore (38:13)

Yeah, 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 we'll 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.

Alex Kantrowitz (38:50)

That's interesting because I thought my business, which is like the content business, was going to be overrun by generative AI and it sure has. I mean the slop is real.

Olivia Moore (38:59)

It is.

Alex Kantrowitz (39:00)

We gotta do something about the slop. But actually your business is also going to be overrun by startups being built on this technology. So then do you apply some sort of discount to someone who uses these tools or do you become more likely to invest in them because you know they are wrangling these things and building something and it's not necessarily a shortcut, but it's not necessarily a shortcut.

Olivia Moore (39:27)

Yeah.

Alex Kantrowitz (39:28)

How do you think about that from an investor standpoint?

Olivia Moore (39:30)

Yeah, I think there's like a little bit of a happy medium, but more we get more excited when company is kind of more AI first in terms of the tools they use. The reason I don't say like 100% AI all the time is because the tools aren't perfect yet. So I've heard cases of like my junior engineers are just cloud coding everything and then we ship it and then it breaks and there's a lot of issues, but I think in general with how fast the tools are kind of compounding and improving. Like I use it for a lot of my work. There was a period of time where I would double check every single number, every single stat manually and like the accuracy rate is fantastic and is only only gotten better and better. And so I think we'll be even more excited about companies that are AI first and how they run themselves.

Alex Kantrowitz (40:13)

So it expands the pool of founders you might invest in. Are you seeing founders come in from like areas you geographies, backgrounds you never would have imagined. Like is there like just to get like some you know, 60 year old guy who's been at a company his whole life and never met that developer and now is just clawing his way through?

Olivia Moore (40:32)

Yes, definitely. I think we've definitely seen some geographies pop up where we haven't seen huge tech hubs before would say Paris is one, Stockholm is another with lovable and now a whole kind of other wave of companies. Some of those founders do move to SF just because of the, the talent density. I think in general though, like pre AI for if you were building especially an enterprise business, say software for H Vac, like the people you would want to back in that market is the guy who has done H Vac knows the market inside out, built a company there before, and actually what we're seeing now are the better bets are like the very scrappy high hustle teams will be able to keep up with the pace of model development and continue to productize the models in the most compelling ways and ship them to customers. Like so it's a different maybe archetype of founder that's kind of winning.

Alex Kantrowitz (41:22)

Now you 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 (41:43)

Yeah, fully agree with it. 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, 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 I'm getting 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 (42:31)

There was, but there was this Wall Street Journal story. You might have seen it with this like CEO, a bunch of CEO 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.

Olivia Moore (42:48)

Interesting.

Alex Kantrowitz (42:48)

I kind of thought that that was bullshit.

Olivia Moore (42:50)

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.

Alex Kantrowitz (42:57)

Who knows?

Olivia Moore (42:58)

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. So I think there's going to be some like cultural and even environmental changes that are going to happen to adapt to kind of the AI world.

Alex Kantrowitz (43:36)

One more thing about openclaw and then we'll move on. I think that one of the compelling advantages of it, if I get it right, is that it has persistent memory.

Olivia Moore (43:46)

Yeah.

Alex Kantrowitz (43:47)

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 ChatGPT and Cloud, although they are getting better. And you also had a a post on X here you say memory is one of the most fascinating topics 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.

Olivia Moore (44:19)

Yeah. 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, 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. So for example, the ChatGPT Pulse product, 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. And so I'm interested in how the model companies maybe segment memory and context based on when a user is talking to them, what they're talking about, that kind of of thing.

Alex Kantrowitz (45:36)

Since you're putting so much personal stuff in the bot, there is a setting within ChatGPT to use my chats to make the model better which allows it to train on the material you input there.

Olivia Moore (45:46)

Yes.

Alex Kantrowitz (45:46)

Do you have that toggled on or off?

Olivia Moore (45:48)

I have it on. I'm an AI Maximalist. You know we might as might as well go all out on this.

Alex Kantrowitz (45:53)

You don't worry that your personal conversations will show up read by somebody?

Olivia Moore (45:58)

I'm less scared about that just because I know how careful model companies are around that. I do have two factor offset on my ChatGPT so hopefully it's hard to hack. Yeah.

Alex Kantrowitz (46:09)

Briefly about the pace of change. 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

Olivia Moore (46:23)

and a half years ago.

Alex Kantrowitz (46:24)

Seven of the nine creative tools on your list of hundred 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 GPT. I don't know if everybody, 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, the sort of the mid journeys place in all this can just be gone.

Olivia Moore (46:56)

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 Gemin 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 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 gener, like a flyer, a broad based marketing asset, something like that. But we are still seeing some image generation companies on the that are either more like sophisticated workflow like ciVitaI for comfy UI model builders or something like a midjourney 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 big workflow.

Alex Kantrowitz (48:13)

Are we going to get to a place where you can Prop something more sophisticated like an architectural design and it will spit it out without errors.

Olivia Moore (48:20)

Yeah, I mean Nano Banana is already quite good. There's a chart in the report where we did kind of a heat map of global AI adoption by country. And so I gave nanobanana the list of countries and the heat map score and it perfectly filled in every country with the right shade of red. Yeah. Based on the adoption which is, is I think really spectacular. I do think that you know, you or I could prompt a great architectural model on ChatGPT or a Nano Banana today. I don't think that the average architect who is non technical can or wants to do that necessarily. And so I think we're going to continue to see products that like the prompt is part of the product kind of really succeed in those more focused use cases.

Alex Kantrowitz (49:07)

Cases on video. Yeah, Sora was the like runaway hit of the year last year for like a half a second.

Olivia Moore (49:14)

Yeah.

Alex Kantrowitz (49:15)

This is what you have on sora. Sora spent 20 days, which is not insignificant, at the top of the US App Store and reached 1 million downloads faster than Chat GPT. Since then downloads have have decreased. I think that's sort of putting it likely it's fallen off the face of the earth. What's going on there.

Olivia Moore (49:31)

Yeah, the, the sordate is really interesting. Um, there's, 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 the fact that was why like every, so 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 3 million DAOs and it's actually you know, slightly climbing over time.

Alex Kantrowitz (50:38)

Daily active users?

Olivia Moore (50:39)

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. We haven't seen anyone crack AI social yet. I think it's going to be really tricky now.

Alex Kantrowitz (50:53)

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, that you envision that AI will basically be this reimagination of business that all business. Tell me if I'm getting this right. All businesses will be reinvented as an AI company.

Olivia Moore (51:11)

Yeah.

Alex Kantrowitz (51:11)

What happens to the incumbents?

Olivia Moore (51:13)

Yeah, this has changed a lot in the last six months too. I think a lot of incumbents were understandably, because of their 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. Gemini Notebook, LM 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 a 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 SaaS apocalypse is a bit overblown. But like it's definitely a real risk.

Alex Kantrowitz (52:35)

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 (52:46)

Yeah, yeah.

Alex Kantrowitz (52:47)

So that could happen.

Olivia Moore (52:47)

I largely agree with that. I think it's harder in some categories where, where the incumbent can kind of lock you in because they have your data, they have all these 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 (53:07)

The Citrini report was just like a little bit overblown.

Olivia Moore (53:10)

Doordash was a bad example to use. Yeah, I agree. They didn't really think out of anything

Alex Kantrowitz (53:15)

why DoorDash, but I do think that in some ways maybe this SAS apocalypse has more to it. If you're, if we believe what you to what you're arguing here, then these companies didn't have these long like maybe not immediate but even middle term risks.

Olivia Moore (53:31)

Yeah.

Alex Kantrowitz (53:32)

And now they do.

Olivia Moore (53:33)

Yeah. I think all the incumbents have to have to kind of wake up and figure out what their strategy is going to be.

Alex Kantrowitz (53:38)

Okay, so you're, you have these hundred AI apps. ChatGPT is at the top. I think it's on the top next year or the year after that.

Olivia Moore (53:47)

That is an interesting question. Question. I think so. I think that their strategy of being free will allow them to capture more of the global market as AI starts to expand further into developing countries. But honestly I would expect to see Gemini and Claude and others continue to grow for their use cases. I just would be maybe surprised if they ended up as mainstream as something like a chatgpt. And so they'll probably monetize through subscriptions and other things. Whereas ChatGPT GPT has ads.

Alex Kantrowitz (54:21)

What type of app is not on there this year that will be on

Olivia Moore (54:24)

there next year there's going to be lots more agentic products. So OpenCloud would have made it. I think we're going to see a lot more agentic products on mobile. Like the concept of an AI that you can like call, text, chat with and have it actually do things for you I think is a really magical experience for a lot of people. The other thing that I'm thinking about, and this is on us to evolve the methodology of the list is like increasingly AI is not in the browser or on an app. It is like a desktop product or it's a completely AI native browser like a comet or an atlas or something like that. And this data doesn't capture that. The desktop products I'm thinking of are like Cursor, Claude, Cowork, Whisperflow, Granola. Like none of these are really captured in this data. And so we're gonna have to evolve our methodology into looking more at revenue than just kind of web traffic, which I think will surface a whole new group of interesting companies.

Alex Kantrowitz (55:21)

All right, Olivia, thank you so much for coming on the show. Great to speak with you.

Olivia Moore (55:24)

Thanks for having me.

Podcast Host (Narrator) (55:28)

Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes go to YouTube, Apple Podcasts and Spotify. Follow us on X16Z and subscribe to our substack@a16z.substack.com thanks again for listening and I'll see you in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold or sell any investment or financial product. This podcast has been produced by a third party and may include paid promotional advertisements, other company references, and individuals unaffiliated with AC. Such advertisements, companies and individuals are not endorsed by AH Capital Management, LLC, A16Z or any of its affiliates. Information is from sources deemed reliable on the date of publication, but A16Z does not guarantee its accuracy.