# Reid Hoffman, LinkedIn Founder: 99% of People Are Using AI Wrong NEW ECONOMIES · 2026-07-19 Reid Hoffman, LinkedIn co-founder, argues most people underutilize AI by treating it as a search engine rather than an agentic workforce, predicting a shift where humans become managers of AI agent teams. He explains that Blitzscaling today means using AI to rapidly build and discard prototypes, while distribution remains a critical moat for startups. Hoffman warns that negative AI perception in the US and Europe risks ceding leadership to Asia, which embraces the cognitive Industrial Revolution. He highlights the importance of taste and judgment as skills that AI amplifies rather than replaces, and contrasts Anthropic's enterprise focus with OpenAI's consumer strength. Drawing from his decade on Microsoft's board, he shares Satya Nadella's lessons on rebuilding culture, corporate partnerships, and treating AI agents as employees that work for the company. Hoffman also spotlights applications in drug discovery (Manus AI) and personalized AI to maintain human connections. ## Questions this episode answers ### What does Reid Hoffman mean by 'agent managers'? Reid Hoffman predicts that within a few years, individual human contributors will be replaced by managers of groups of AI agents. Humans will orchestrate multiple agents, handing off tasks and troubleshooting, even letting agents work while they sleep. He expects this shift—already happening in coding—to spread across all knowledge work within about three years. [6:30](https://neweconomies.podhood.com/dc1af721-9556-4e5d-905c-a509838e6834?t=390000) ### How has Blitzscaling changed in the era of AI, according to Reid Hoffman? Hoffman explains that AI allows startups to build, test, and discard prototypes rapidly rather than simply scaling human organizations. Teams can now iterate with high uncertainty, and each person may manage thousands of AI agents. This shifts Blitzscaling from pure organizational growth to intense, agent‑powered experimentation and speed. [12:24](https://neweconomies.podhood.com/dc1af721-9556-4e5d-905c-a509838e6834?t=744000) ### Why does Reid Hoffman say AI has a negative PR perception in the US and Europe? Hoffman observes that in the US and Europe, people fear job loss and feel that tech companies are forcing AI on them, leading to resistance. In contrast, Asia, Africa, and South America see AI as the future and embrace it. He warns this could cause the US and Europe to lag in the cognitive Industrial Revolution—a ‘reverse revenge’ of the Industrial Revolution. [26:39](https://neweconomies.podhood.com/dc1af721-9556-4e5d-905c-a509838e6834?t=1599000) ## Key moments - **[0:00] Intro** - [0:00] Reid Hoffman: 'Most people are really underutilizing today's AI capabilities, blinding themselves with emotional reactions like "AI slop".' - **[1:55] AI Landscape** - [2:18] Reid Hoffman explains that the truly interesting AI use today is the agentic framework, where coding agents can work while you sleep. - [5:29] Q: How should people use AI in the next 12 months? - [6:30] Reid Hoffman predicts that within three years, there will be no individual human contributors—only human managers of groups of AI agents. - **[8:48] Taking AI Seriously** - [8:48] Q: Are we taking AI seriously? - [9:59] Reid Hoffman's hazard bet: humans will still fit into work for decades because AI has brittle weaknesses like repeating wrong prime number answers. - **[11:58] Blitzscaling 2.0** - [11:58] Q: What does Blitzscaling mean in the era of AI? - [12:24] Blitzscaling in the AI era shifts from pure organizational scaling to deploying AI that builds, discards, and rebuilds at high speed, says Reid Hoffman. - **[15:00] Silicon Valley Edge** - [15:00] Q: Is Silicon Valley still the best place to launch an AI company? - [16:29] Q: Should startups partner with AI model companies? - [18:50] Q: Is it healthy for tech when AI model companies replicate wrapper startups? - [21:59] AI changes which skills matter: visual thinking and taste become paramount while hand-eye coordination declines, says Reid Hoffman. - [23:14] Reid Hoffman: 'If you're not embarrassed by your first product release, you've released too late.' - [24:24] Q: Is distribution the new moat for AI startups? - **[26:20] Negative PR** - [26:20] Q: Does AI have a negative PR problem? - [27:59] Reid Hoffman fears the U.S. and Europe could face a 'reverse revenge of the Industrial Revolution' as Asia and other regions embrace AI more fervently. - [29:28] Q: How should governments promote AI in a positive light? - **[33:22] Winners & IPOs** - [33:22] Q: Who will dominate the AI market: OpenAI, Anthropic, or others? - [34:01] Reid Hoffman predicts 10 to 15 large tech companies will shape the future, with at least four frontier AI models competing. - [37:14] Public AI companies allow pension funds and everyday citizens to share in the upside and provide transparency against speculation, says Reid Hoffman. - **[38:33] Sam & Dario** - [38:33] Q: What are the most interesting characteristics of Dario Amodei and Sam Altman? - [39:18] Reid Hoffman shares that Dario Amodei predicts a 'white-collar bloodbath' in two years to push for societal dialogue on AI's job impacts. - [40:56] Sam Altman invested privately in universal basic income experiments to prepare for AI-driven job changes, notes Reid Hoffman. - **[42:33] Satya's Lesson** - [42:33] Q: What is the greatest lesson Reid Hoffman learned from Satya Nadella? - [45:36] The OpenAI-Microsoft deal will go down as one of the genius moves in tech history, says Reid Hoffman. - **[47:33] Reid's Week** - [47:33] Q: What does a week in Reid Hoffman's life look like? - **[49:47] Emerging Trends** - [49:47] Q: What two AI trends should founders get excited about? - [52:23] Reid Hoffman's second trend: use AI to amplify human connections by sending personalized AI-generated gifts to maintain relationships at scale. - [55:19] Q: Who is Reid Hoffman's favorite Masters of Scale guest? - **[55:33] Fire Round** - [56:30] Q: What has Reid Hoffman changed his mind about in the last 12 months? - [57:56] Q: What question does Reid Hoffman wish founders asked him more? - [58:46] Q: If Reid Hoffman were to start a new company today, what would it be? ## Speakers - **Ollie Forsyth** (host) - **Reid Hoffman** (guest) ## Topics AI ## Mentioned Anthropic (company), Inflection (company), LinkedIn (company), Manus AI (company), Microsoft (company), OpenAI (company), ChatGPT (product), Claude (product), Claude Code (product), Codex (product) ## Transcript ### Intro **Reid Hoffman** [0:00] Most people are really underutilizing today's AI capabilities, blinding themselves with emotional reactions like "AI slop" or other kinds of things. But the really interesting use is this agentic framework. There won't be individual human contributors anymore; there will be human managers of groups of agents. It can work while you're asleep. But here's the thing that's a little strange: AI has a negative PR perception in the U.S. and Europe, and a positive one everywhere else. And one of my greatest worries for the U.S. and Europe is they say, "No, it's really important we slow this down." And in Asia, you go to Japan, you go to China, they're all like, "Oh my god, this is the future, we want to be on it." Part of what made the U.S. and Europe so strong globally was the Industrial Revolution, embracing it early. And so it's kind of like the reverse revenge of the Industrial Revolution. Maybe the rest of the world is going to embrace AI and the cognitive Industrial Revolution earlier, and so it's a huge moment for this kind of wake-up call. If they don't reinvent themselves, then the dinosaur decay has started. Part of the reason why people have negative is because they say, "Oh, the tech companies are doing this to me, I'm going to lose my job," and that's the entire story. It's 99% of the human race, so I understand. But the question is, how do you get to the 99%? Show me benefit. Show me how I can be amplified in using it. So you go, "Okay, AI can be for me." And I think that's the way you persuade people. And it isn't by a story of words. Part of how you get trust is by seeing value. And so the unequivocal thing that I say to all people is, "It's super important to have—" **Ollie Forsyth** [1:38] Reid's, I have been a massive fan of you for the last 20 years, ever since I got into technology, and what a joy it is to have you here today. So thank you so much for your time. I'm super excited for today's chat. We have so much to cover, so big welcome. **Reid Hoffman** [1:52] Thank you very much, and a pleasure to be here. **Ollie Forsyth** [1:55] So we are at this incredible inflection point in technology. Everybody is talking about AI. It is moving so quickly. But I don't think many people realize just how far we have progressed in the last few years. What is the current state of AI today? ### AI Landscape **Ollie Forsyth** [2:12] Help the audience unpack where we are and where we are heading next over the next 12 months. **Reid Hoffman** [2:18] First, most people are really underutilizing today's AI capabilities. There's everything from the people who aren't doing it at all, for a whole variety of reasons: lack of curiosity, blinding themselves with emotional reactions like "AI slop" or other kinds of things. And so they're not really digging into the pretty amazing capabilities. Then there's a relatively not small group that are kind of using it as, kind of think of it as Google or Bing or search replacement, which is, "Hey, I get a more coherent answer." Like, "Is it okay for my dog to eat coconut?" Or other kinds of things, which kind of gives you a very precise and detailed kind of answer that you can follow up on in order to check, because these things always try to be pretty helpful, so therefore kind of hallucinate sometimes, although the hallucinations have obviously gone way down the last couple of years. And that's a bulk of use. But the really interesting use is for today, and capabilities which most people wonder, is this agentic framework of actually doing work. And because what all of the labs have been doing is, how do you get amplified in terms of how you operate? So for example, given coding has been the massive thing, all of the software developers who are using this actually have a large screen that they have multiple agents running on, and they're kind of doing more orchestration. They're like, "Okay, you're doing this, you're doing this, you're doing this." This is what the handoffs look like. "Oh, look, this one's got stuck on something. I'm doing, 'Oh, this one's finished, this one needs to get to the next one.'" You know, this kind of thing. Including, and this is obviously one of the things that has worked for the kind of economics generation in capitalism, is it can work while you're asleep. So one of the most classic ones these coding developers do is they have big problems that they set when they're going to go to sleep. So they get up in the morning and the thing has been working for eight hours, whatever the number is, and has something of a substantive piece of work left. Now, you'd say, because it's agents and coding, and it's only agents and coding, but actually coding is a lens into all knowledge work. It's like a form of reasoning. And any place where you can kind of close the digital loop, and that isn't just writing, that isn't just code, that isn't just images, that isn't just video, it's other things too. Part of the reason why there's startups and law and all the rest is a place that you can be amplified today, and you can actually, in fact, be doing that. And the underdeployment of that capability, like I can tell when people are starting to get into it, because it's like, "Oh gosh, I'm using Claude Code or Codex and I'm staying up till 2 in the morning getting stuff done." Or like, "I've been really diving into ceramics and now I have a ceramics app because I can do that." And it doesn't have to be like it's now doable as an amplification for the things I'm doing in ceramics. And that's the kind of thing that you're beginning to see, but that's still a very tiny percentage of the working people. And that's what today looks like. **Ollie Forsyth** [5:29] It's all changed so incredibly quickly. And I don't think many of us realize just how quickly this amazing technology was going to advance. Looking ahead in the next 12 months, how should we be using this incredible technology? **Reid Hoffman** [5:44] Well, not as a surprise. Part of that is the acceleration of capabilities and the digital closing loop. So not only will coding continue to get a lot better, but more and more people who are not coders will be deploying coding to do things, the ceramics app, a bunch of other things. And those coding capabilities will then go into all kinds of workflows, because you create agentic workflows. So what you'll begin seeing, which you see in a small number of people now, but as people going, like within, call it three years, and I think one year where you begin to see the broader-based adoption of this, there won't be individual human contributors anymore. There will be human managers of groups of agents. It doesn't mean that the people aren't contributing some pretty important things that are not just managing the agents, but also context awareness and everything else, but that that management of a group of agents will then become an understood developing pattern of work. And every place where you can do kind of the digital closing loop, that will be there. And that's part of what will be growing out. Now, in particular, I think you'll begin to see, because we've begun in the last year to really see takeoff in coding, I think you'll see the coding go to the next level, and then it bringing all the other knowledge workflows into the same kind of things that coding has been doing this year. **Ollie Forsyth** [7:18] You mentioned such a great point here around we're entering this new era around agent managers. Gone are perhaps the days where you used to go to work every day and code and try and create some cool designs. I've had a whole bunch of heads of AI at all the large AI models on the show, and the same thing keeps coming up. Agent managers are next. And a lot of people will think, "Well, what does that mean for the future of work?" And we see all of these headlines, but it simply just means,right, all of the legacy stuff we used to do, all the thing that, the mundane stuff, we can now hand that over to the agents. And then agent managers gets juicy. That's where the real excitement happens. **Reid Hoffman** [8:04] And by the way, it's more than just the kind of, as it were, the drudge work, the filling out of the digital forms for advertising and marketing. It is also a set of work, like for example, part of like if you're doing a marketing thing, agents normally kind of give you what is an expert median mean in terms of the thing, "How do I get distinguished alpha? And what am I doing in order to get there? And then how do I add that in to what I'm doing?" But it will be a partner in that kind of creativity, a partner in research, a partner in more detailed work that is not just kind of like the, "Oh, well, yeah, I had to type a bunch of different stuff, and now I don't have to type it anymore." It's going to be much more than that. **Ollie Forsyth** [8:48] Are we taking AI seriously? ### Taking AI Seriously **Reid Hoffman** [8:51] Well, I think people are both taking it not seriously enough and too seriously. The not seriously enough is a lot of people not actually engaging, realizing that we've created the best learning and amplification technology in human history, that we're entering into the cognitive Industrial Revolution, and this will be faster and larger impact than the Industrial Revolution. So that's the not seriously enough. And the too seriously tends to be a little bit of the science fiction thing. Like, "Oh my gosh, in two years, half of white-collar people will be out of work," or that kind of thing, as ways of not understanding human organizations and what humans can bring in and all the rest. I do think there will be a lot of workforce transition, but like what I actually think is that a lot of people's jobs will get replaced by people using, managing groups of AI. And so that transition is difficult, but it's not, "Oh, AIs are doing everything three years from now." **Ollie Forsyth** [9:57] Yet. **Reid Hoffman** [9:59] Yeah, there might be a three-year thing where that happens. But my hazard bet will be that we will actually have decades still of humans fitting in, because if I see the pattern of where AI is going is, we already have superintelligence. There's already things that ChatGPT, Claude, Copilot, Gemini can all do that we can't do. Speed, depth of access to the internet, kind of exhaustedness of research, a bunch of different things, including working on certain problems. Like for example, I haven't coded for decades, and I can create interesting things with code now, given AI. That's all kind of superpowers. On the other hand, what you discover is your ability to have context awareness, to understand when things are going off the rails or what real true excellence looks like and so forth, is still substantially better. And I think will likely be there for a while, because while these things are like to have this, what in the technical term is jagged edge of superintelligence capability, they also have weirdnesses. Like even the superintelligent, the great models today still screw up on like various kind of like prime number. **Ollie Forsyth** [11:14] So much. So much. Yeah. **Reid Hoffman** [11:16] And part of that screw up is that they, like you ask it a simple prime number problem, and it gives you an answer, and you say, "That's wrong, give me another one." And it goes, "Oh, oh, sorry, yeah, here's the answer." It'll keep doing that 20 times, 100 times. Whereas human beings, and this is part of what I mean, context awareness, the third time I give you the wrong answer, I'm go, "Look, I know I don't have this," and I stop. I know I need to change my game. And the models currently haven't really demonstrated any not super brittle, kludgy way of doing that. And that's just one instance where I think human capabilities may add in for quite a long time, and maybe for a very long time. ### Blitzscaling 2.0 **Ollie Forsyth** [11:58] I agree. The consensus also is the speed of technology and how fast it's evolving, all these incredible startups coming out of Silicon Valley, I think it's just incredible how fast they're growing. You famously coined this term, Blitzscaling, growing as quickly as possible, even amidst uncertainty. What does Blitzscaling mean today, and is it as relevant as it was when you published your first book? **Reid Hoffman** [12:24] Well, as I think, you know, it's even more relevant, although the pattern changes a little bit. So a lot of Blitzscaling was lessons from Silicon Valley about why within a 30-mile radius of, call it the peninsula of Silicon Valley, is over half of the Nasdaq market cap. And one of the things that I was told recently that I thought was interesting was that 91% of the non-Chinese AI market cap is in Silicon Valley. And actually, if you remove Anthropic and OpenAI, that only drops to 70%. And so it's a huge amount of kind of what's being created there. And it was kind of, Blitzscaling was, what's the lessons by which these technology companies of the future are built so that as many places in the world can learn, adapt, participate? I try to help the creation of Silicon Valley. Now, Silicon Valley is everywhere. So Blitzscaling was in part one of the things that was most uncomfortable was once you discover scale product market fit, how does it go like to the moon and to Mars and beyond in terms of how it's, Toy Story, to infinity and beyond, how does it go that way? And the answer was by really scaling the organization and taking a whole bunch of risks in product market fit, in scale of hiring, in business operations, in technology development, and so forth, in order to realize that scale opportunity at speed before others. Now, how Blitzscaling changes in the era of AI is that it goes from pure scaling of organization, by the way, it will still have some scaling of organization to the deployment of AI doing and redoing work at intensity. Because one of the many different things that AI brings to changing the game for how you build scale technology is you might build something for a couple of weeks and then throw it away and build something new. And that might be your way of doing it. Whereas previously, you really were trying to build on top of each new thing and then refactoring it. And you'll still be doing that with AI, but you'll be building at faster, higher uncertainty, higher risk, trying things, throwing it away, going again, and where you'll be still scaling a human organization, obviously the number of agents that you'll be scaling and how you'll be operating will be a multiple of the human beings, because each human being will be managing teams, potentially up to thousands or even tens of thousands of agents. ### Silicon Valley Edge **Ollie Forsyth** [15:00] Do you think Silicon Valley is still the best place to launch and scale an AI company today? **Reid Hoffman** [15:08] Well, it is just off generalizing the last 10 years. I do think the two places that get the scale technology story most correct are Silicon Valley and China. I'm trying to help Europe, Japan, other places, kind of build us out in various ways, because I think it's better for the whole world and better for obviously those regions. But basically, Silicon Valley continues to have the network, the information, the learning, the venture capital. It attracts talent from everywhere in terms of building these software technology scale-ups, and obviously that bleeds and other things. So there's also kind of biology and other kinds of things that are happening. But I think one of the things that's funny, if you look at the last 20 years, is there's always a new article about so-called peak Silicon Valley. **Ollie Forsyth** [16:03] Always. **Reid Hoffman** [16:03] And it's always proven to be wrong three to five years later. Like just like, "Oh, it's now the housing's too expensive," or, "The following taxation thing has killed it," or, "It's too woke, and so we're all moving to Miami." And then within a couple of years, it's like, "Nope, Silicon Valley has continued to massively grow, and Miami is still basically just crypto-ville." **Ollie Forsyth** [16:29] One of the interesting observations I've had also is a lot of these AI models now want to partner with a lot of these startups, which I think is great in some respects, but also potentially sometimes maybe a little bit damaging,right? When you have these AI models, trying to entice all these amazing startups to come and work alongside them and give them loads of free credits and maybe some equity, how should startups be thinking about partnering with these AI models, and should they? **Reid Hoffman** [16:55] Well, the normal thought will be, can we get an exclusive partnership or access by which we leverage that in return? And I don't think any of these AI models are really going to provide that. And what's more, partially because a lot of startups start with something that's thin, because that's part of the reason why software startups are so good, is like, look at the technology we started LinkedIn with. It was very thin. It's gotten deeper over time, but it's still mostly kind of a network effects business. So I think that the notion of partnering with them will broadly be beyond the scope and irrational for most startups. But partnering is different than building upon. It's a little bit like you might build upon the mobile app stores of iOS and Android and not partner with them, but still build something that's pretty effective. And so similarly, in terms of these models, and then you want to do what is kind of classic around, for example, the parallel of cloud services, which is you might start intensively with Azure or AWS or G Cloud or other, but you're ultimately going to want to have some diversity across them so that the pricing and dependency and your ability to do that. And so you'll want the same thing in terms of models, ultimately, not necessarily at the beginning, but that'll be part of your strategy. And then what you're going to be looking for is how do you build something that once it's built, that's very valuable, that the models can't just go, "Oh, we added it in as a feature," and your whole business goes away. And there's various techniques to try to do that. Some of them are network effects, some of them are like enterprise integration, but you're going to want to be doing that. So building on top of them can make a lot of sense, but you're going to have to build a substantive business that isn't just like a wrapper on the model. **Ollie Forsyth** [18:50] Let's talk about that, because a lot of these wrappers, a few weeks later, if it does really well, these AI models sometimes will build a very similar product. And I think we're going to see more of this. Is this a good thing for tech? And how does this actually end up working? **Reid Hoffman** [19:10] So I think it's a good thing for tech. It's part of the Schumpeter creative destruction, which is it isn't that once you've innovated or created a business, you're good for all time. It's part of the also S&P topple rate, which might be much quicker in this accelerated universe. And it's a thing to be smart about. Like entrepreneurs, 90-plus percent of entrepreneurial businesses fail and fail without really getting off the ground. And that's because you have a bad theory of the game, you're unlucky in your market timing, you're unlucky in your competition, all kinds of different things. You can't pull together the resources to execute against it. And that's fine. And so, for example, I saw this back in the day when like at GPT-3, hey, I'm building a copywriting ad business thing on top of it. And you're like, well, but its writing capability is very good. What are you doing beyond just like saying, I'm giving you a front end to GPT-3? And so when GPT-4 came out, kind of the whole business got disrupted. You have to be having an entrepreneurial theory of the game. That's why it is that, for example, the AI companies, the hyperscalers and AI companies themselves doing it, or like other people just go around you and use it directly. Like, for example, it's like, well, I built a great app with Claude Code, and now everyone's going to buy my Claude Code app. Well, could they just point Claude Code at it and say, build me that app? And the answer is yes. And in which case you're like, okay, so why would they pay you a lot of money for it? Because the token cost of Claude Code or Codex doing this is not going to be that high. So you have to have that more detailed theory. But by the way, I have continued to invest in various AI companies along with Graylock and others. And so there are scope of smart people doing this kind of thing, but you have to have that thought on the go-to-market, that thought on the predictability of it, the thought on network effects, the thought on enterprise integration, the thought on what kind of loops, like data loops and other things, are really something that creates unique value that then if you're one of the AI companies that say, I really need to get into this, they go, hey, we're going to come and offer to buy you for a huge premium because that's how we get into the market well, and that's how we compete with our competitors. And that's what you have to be having as an entrepreneur. **Ollie Forsyth** [21:39] I probably also say on top of that, personalized AI is probably something pretty relevant. How do they stay relevant? And also this whole thing around taste. We can have so many of these amazing AI models, but if they don't build amazing taste around the consumer, around the builder, it becomes harder to compete. Do you agree with that? **Reid Hoffman** [21:59] I do. And I think part of the thing that AI causes, it changes the landscape in which skills really matter. So for example, when you're doing graphic design, it used to be the, oh, I have a lot of hand-eye coordination. I'm being able to draw very well. And it's like, well, AI can draw very well. That AI coordination doesn't need to go down. But your visual thinking and what your bar is for what is really good goes up. So it changes the landscape of which skills are really important. And the landscape is now like, oh, it's super important to have the taste, to have the judgment about what excellence looks like, and not just in visual, but obviously in code and writing and da da da da. And then the hand-drawing skill, that goes down. And so if you went, I was just a hand-drawing skill person, you're like, okay, then you're going to have to figure out how to bring that into AI and have AI amplify and say, okay, I take these skills on and I still add something on top of AI. But like the taste, the orchestration, the judgment is another one in addition to context awareness that I think will persist for decades. **Ollie Forsyth** [23:08] How should builders be thinking about building beautiful products with taste front of mind? **Reid Hoffman** [23:14] Well, one of the things to understand about the internet is the internet on offering products through the internet is the other product is only a URL, a click away, an app download, et cetera. So that can be a small advantage that they found you versus others, but like the other thing is discoverable. So that's part of the reason why you want to have a very good sense of what a great product is for that problem solution. It's kind of like one, you have to ask theright questions. Two, you have to have a sense of kind of what does real quality look like? And by the way, one of my aphorisms that I'm famous for is if you're not embarrassed by your first product release you've released too late, that is still correct because it's the trajectory towards great. It doesn't necessarily need to say, oh, I wait for four years to have great coming out. It's like, no, no, no. You want to be learning and engaging to get scale product market fit and which things really work or not. But you want to have a fast learning curve towards that. And then, of course, one of the perennials for entrepreneurship is your go-to-market, your distribution. You have to have a differential theory of that. One of the most common failing of quality, tasteful knowing what theright problem is and theright great solution is, is understanding the go-to-market is as important as your product in order to succeed. **Ollie Forsyth** [24:30] Is distribution the new moat for a lot of these companies? It's similar to media companies today working with creators. We all have this amazing thing, distribution, audience, which we build over a long period of time. A lot of these AI companies that are emerging today, they may have amazing products, but they don't have the distribution. Some people say moats are dead and there's nothing really that is relevant anymore. But I actually think if you have distribution, it's a great moat to have, no? **Reid Hoffman** [24:59] Distribution is great, and it's extremely important. And it's one of the reasons why, by the way, in existing companies, it's not necessarily game over for them. If they don't reinvent themselves, then the dinosaur decay has started. And this is actually, for example, part of what has gotten the SaaSpocalypse wrong because it's which SaaS companies are embracing and doing AI will be most likely part of the future, at least on a risk coefficient. And those that are not are almost certainly not part of the future on an accelerating decay. And it's the similar thing in terms of distribution, which is you say, hey, I've got distribution. That allows me to use AI and to amplify and to do it. If you kind of go, oh, I'm not going to use any AI, then my guess is your distribution may persist for a while, but you will start arcing down some. And that's part of the reason why the AI reinvention, the unequivocal thing that I say to all people is start playing with it, start using it, and understand how it helps you get to better upside. Not just better cost savings, that's interesting too, but better upside. And that is, I think, key. And distribution helps you get into that loop much faster. **Ollie Forsyth** [26:20] You know, we all want to be part of this AI journey,right? We have this FOMO, this kind of fear of missing out when there is so much and just incredible paradigm shifts happening. But do you think AI has a negative PR perception today? ### Negative PR **Ollie Forsyth** [26:35] And if so, how do we change that as an ecosystem? **Reid Hoffman** [26:39] Here's the thing that's a little strange. AI has a negative PR perception in the US and Europe and a positive one everywhere else, including Asia and so forth. And one of my greatest worries for the US and Europe is they say, no, it's really important we slow this down. I mean, this gets to kind of the idiocies in the US of like, let's ban data centers. And it's like, look, there's nothing that says any particular region should adopt a data center if they don't want it. And I very much get the local community should ask for good things that help the local communities, economic upside and jobs and other kinds of things, and also noise pollution and kind of other things that are important to getright. But that's like part of the future. And in Asia, you go to Japan, you go to China, you go to other places. Like, how are we part of this future? But not just Asia. You go to Central and South America, you go to Africa, you go to the Middle East. They're all like, oh my God, this is the future. We want to be on it. And so you've got the, it's kind of like maybe it's the reverse revenge of the Industrial Revolution. Part of what made the US and Europe so strong globally was the Industrial Revolution and embracing it early. And maybe the rest of the world is going to embrace AI and the cognitive Industrial Revolution earlier. And then you'll have some kind of the pattern of modern reverse colonization from the US and Europe, from everywhere else adopting AI much more fervently. So there's a tale of two regions in AI perception. Part of the reason I state this as bluntly is, of course, I want the US and Europe to embrace and to be a leader in the cognitive Industrial Revolution. I think it's great societies, great sets of social and societal values. And we want those to be at the leading table in the world, if not leading the table. And so it's a huge moment for this kind of wake-up call. **Ollie Forsyth** [28:49] You would think, especially in the US, if they're leading the turbocharge and the storytelling and the big picture vision and making AI the most amazing technology, they would be very positive about it. Europe, where I'm originally from, I'm originally from the UK, sorry to the listeners listening to my British voice every single day. But they're having a few more positive signals around AI and what it can actually do. If you were to coach some people in government, controversial question, I know, but if you were to coach some people in government today, how should we be thinking about AI in the positive light, not a negative one? **Reid Hoffman** [29:28] So the ultimate thing is to engage and see value. Part of the reason why people have negative is because they say, oh, the tech companies are doing this to me. I'm going to lose my job and AI is going to be doing the job. And that's the entire story. And by the way, if that's the entire story, you don't tend to be broad-minded and say, hey, my society, my community needs to work. Most people tend to go, well, if it doesn't work for me, then it doesn't work for anyone else. Obviously, there's a certain amount of narcissism and egoism in that perspective that is 99% of the human race. So I understand. But the question is, how do you get to the 99%? Show me benefit. Show me how I can be amplified in using it. Show me that even if it's a job transition, which I don't really want to sign up for, it feels like a reduction in agency. This is part of the reason I wrote the book Superagency, because it's like how you can gain agency and lean into it and do that, however the tech companies are deploying their AI agents. But to you say, okay, even if I don't want to be doing this job changes and I'm now being forced into it and doing it, what are the benefits I get? Well, one benefit is obviously huge, like an exoskeleton of the mind and the capabilities, which is great. But also like part of the reason why what I would like to see deployed with speed and vigor is like a medical assistant that runs for free on every smartphone. Because you go, oh, I'm doing this job transition, but unlike where it used to be, only the 0.1% or 0.01% of humanity could have a doctor on call 24/7 to answer something for their kids, their parents, their partner, their pets, et cetera. That exists now and to deploy that effectively. And by the way, the same thing for a legal assistant in terms of like most people, they sign a lease, they don't know how to read the lease and deal with it. But AI agents can do that, can help with that today. Educational tutors and helping do jobs, all the rest of this stuff. So you go, okay, I get it. I can gain agency. AI can be amplification intelligence. AI can be for me. And I think that's the way you persuade people. And it isn't by a story of words. It isn't by a, hey, just trust me and I'm trustworthy, so you should just follow me. It's by getting them to engage and getting them to use it and seeing value for themselves. And that's part of the reason why it's like engage, engage, engage, engage is the short answer. And by the way, when you're a leader in a company or a society for doing this, it's get people to engage so they see the value. **Ollie Forsyth** [32:07] Exactly. And you mentioned the Middle East. I think one really interesting thing they did actually last year, they gave each member of the population ChatGPT for free for a couple of years or something,right? That's a great example in just getting people to engage in the new type of technology. What's happening in Southeast Asia, just spent some time in China for the last few weeks and what's happening there, I think it's really interesting. It's all about engagement and trust at the end of the day as well. **Reid Hoffman** [32:33] Yes. Well, and also part of how you engagement a thousand percent and part of how you get trust is by seeing value. Obviously, we live in very chaotic times. People tend to trust institutions, leaders a lot less across not just the political spectrum, but also the corporate spectrum and institutions. Even you see nutty groups of people not trusting doctors and so forth, which is insane. Like the anti-vax stuff and all the rest. But part of how trust is built is by, ah, this has been helpful. This has built useful things into my life, a medical assistant helping me with my work. And that's the kind of thing where people start going, oh, now trust is being rebuilt. ### Winners & IPOs **Ollie Forsyth** [33:22] You know, talking about who actually wins in this market, 12 months ago, this is a controversial question, and I know you'll conflict it, but I'm going to ask it anyway because this is our show. 12 months ago, I thought ChatGPT was going to win, OpenAI was going to win in general, you know, on the consumer and enterprise side. My thinking has now changed. Anthropic is going to win on the enterprise side. OpenAI is going to win on the consumer side alongside enterprise. But it's no longer just three or four companies. I actually think it's going to be 10 or 15 companies who are part of this ecosystem. Do you agree with that? And how do you see this planning out? **Reid Hoffman** [34:01] So this is precisely the thing that for eight plus years I've been telling antitrust folks, which is if we were five to seven large tech companies heading to three, I would have an antitrust concern. But literally I was like, we're five to seven heading to 10 to 15. This was from eight years ago. And they're like, well, which ones? And you're like, we don't necessarily know. Like I wouldn't necessarily predict Nvidia. Nvidia is one. I thought OpenAI was coming. I wouldn't necessarily picked Anthropic, but Anthropic is clearly there now too with a nearly trillion dollar valuation and a basis of coding. Now I do think enterprise, I think Anthropic will make a lot of progress in enterprise. By the way, I think Microsoft has a whole bunch of surfaces and everything else there. So we'll also be vigorous there. And I'm just, you know, I'm not saying this as a proponent. I'm just saying this as a, like I'm principally a venture capitalist, you know, kind of investing in these things. But I think there is going to be more. Like I think, like for example, you say, well, is it only OpenAI and Anthropic? Because you've got the consumer with OpenAI and you've got kind of coding amplification and a set of kind of enterprise amplifications. And the answer is I nearly am certain that three to four years from now we'll go, oh yeah, there was this third. And this is one of the things that's great about entrepreneurship. Now, what's good about that is it creates a lot of value for society and a lot of value for entrepreneurship. A lot of value for society because they're competing with each other. So they're offering a huge amount of productivity at low prices. It's one of the things where I think there's likely to be at least four frontier models, if not maybe five to eight, in which case, like, hey, as an entrepreneur or a society, you can play out between them. And so I think that's likely to play. Then there's a whole bunch of things on top of that that allow entrepreneurs to then compete with each other and so forth. Just as the scale companies are competing with each other, when I'm creating a new business, my new business, I either succeed myself and create a new star in the constellation, or if I've created something of value, I can sell to somebody. And when there's 10 to 15, I can sell to someone much more valuable. This creates a cycle of human and financial capital investing in more and more of these things going because if I go, hey, if I succeed at all, I get something of return. I don't have to create the new OpenAI, the new Anthropic. I can create something valuable that's smaller and it's still worth it for the team and for the capital. And that, I think, is the universe that we have clear sight into. **Ollie Forsyth** [36:38] And you know, what's super interesting, I think, as we enter the IPO Gold Rush is the opportunity for all of us to participate in the upside. And you made a great comment on a recent podcast show. And I'm going to paraphrase this a little bit. As we enter this IPO Gold Rush, there's a subtle feeling where if all these incredible AI companies are providing human value and society value, we can all participate in the upside. And the great thing about being a publicly listed company is all transparent. Everything's in black and white. **Reid Hoffman** [37:14] Exactly. And I think one of the good things about being public is pension funds can participate, every citizen with economics can participate, and we have the additional visibility of public companies to know what's going on, know where society may need to nudge it, one direction or other versus speculation. Like the classic, like there's all this kind of random speculation. Like a classic one is AI data centers are using lots of water. And that's just basically not true. They're actually not even using that much electricity yet today because the electricity prices are more of a function of under-invested in grids, fluctuations of energy supply costs, Iranian war, et cetera, et cetera. They will scale. And so electricity costs will go up, but also AI applied to it can make grids more efficient, can make data centers more efficient, can make home appliances more efficient. And so you're like, well, with AI applied to it, maybe it could actually, even with a massive scale of intelligence. So there's all of this speculation because it's private and then people just want to take a political position. Whereas when in public companies, you can go, what's true? And you can see it. And that's one of the virtues of more and more of these companies going public. ### Sam & Dario **Ollie Forsyth** [38:33] You know, you spend so much time with these incredible AI leaders, especially Dario and Sam, your investment in both the companies. What is the most interesting characteristic about both of the founders that people might not know about? **Reid Hoffman** [38:53] I'll say one characteristic that they might feel uncomfortable as in both of them that is useful is, and I can say a couple of characteristics, but they're both very principled. And part of that principle is the reason why they come out and say, oh my gosh, like for example, Dario, we're going to have a white-collar bloodbath in two years from now because it was three years from last year. And you're like, okay, Dario, people get panicked and say that and they don't hear it the way you mean it and so forth. But what he's meaning is it's very important in the construction of these technologies that it isn't just me doing this solo, but some broader-based inclusion of society in the dialogue about what's important to build, what's important not to build, how should this be kind of society accretive, et cetera. And it's like, hey, wake up. There's a big jobs thing coming and I want to engage people in the discussion. And by the way, similar thing for Sam. I haven't talked to him about the 5% kind of sovereign wealth fund idea for OpenAI, which I think sovereign wealth funds are a great idea. It's one of the things that we under-deliver in the US and I think is good in parts of Europe and good in parts of Asia because I think it's actually sovereign wealth funds part of how to put capital on the side of the people. And so I think sovereign wealth funds are good things to do. And so I think that's a good thing. And that's part of, again, the how do I engage society and be socially positive, have some authenticity across that and some commitment to that. And like for example, with Sam, who's obviously spent a couple of years being attacked by various quarters for untrustworthiness. Like part of what I point out to him is like, look, Sam put money in early into experimenting with universal basic income privately to see if this was going to be an important tool for society in an age of AI prosperity. Doesn't mean there isn't some complications around it, but he was investing in it. It isn't just words. It isn't just talking about it. He was actually putting money and effort behind it. And that's part of where I think both of them have this kind of principled both impact for society positively and legitimacy by engaging society in the dialogue, which I think is important recognitions of where they're very valuable and some other AI leaders are less good. **Ollie Forsyth** [41:28] Do you think those two individuals in particular, do they get too much flack in the media when the media respectively, they don't actually work at these companies and they don't always know what's actually going on? **Reid Hoffman** [41:41] The short answer is they get a lot of political and other flack that is ignorant, unwarranted, hostile, and uninformed. That doesn't mean, and then because of course classically how someone will attack my statement is they'll say, you're saying that they're perfect and they're angels. And like, no, I have not met a perfect person. Right? So myself included, nobody is perfect. And so the question is, net strongly positive and help them with amplifying the strengths and minimizing the weaknesses. And they're both really good people. They care about society. And so like, for example, unlike XAI, which is trying to engage the whole porn ecosystem to try to get some market share, like they actually care about the impact in humanity for what's going on. And so they are quality leaders. **Ollie Forsyth** [42:33] You also just stepped down after a decade to the board of Microsoft. ### Satya's Lesson **Reid Hoffman** [42:37] Well, actually, it's the end of this year. I'm just not standing for reelection, but yes. **Ollie Forsyth** [42:41] And end of this year, a decade is a long time working alongside incredible coworkers and Satya Nadella. What is the greatest lesson you have learned from Satya that we can pass on to fellow founders listening to this episode? **Reid Hoffman** [42:55] So that's a great question. Satya is, I think, an amazing, like I think I in my Masters of Scale podcast kind of really popularized the term refounder and has done a spectacular job with Microsoft. I mean, I think amongst the best of all the scale companies. And I think there's kind of a whole set of skills, but I think let's call three of them out. So one of them is he thinks in terms of who has theright natural platforms to do these scale problems. Like what is like the scale knowledge work look like across large companies, across societies, et cetera? What is the way that workflow happens and how is that provisioned to enable companies effectively? And part of his thing is, as opposed to replacing companies, is because they're all his customers, he is the most aligned to how do you amplify them and what is a set of things that they bring in as considerations? How do you help them move at speed, all the rest of that in terms of that? And sometimes he's slower because he's addressing like proprietary intellectual property within company, proprietary information. Like for example, one of the things I learned from Satya in bucket one was, hey, if AI is providing new employees, it's actually really important that these new employees actually work for the company. They don't work for a different company who takes all that IP and goes and do other things, but actually works for that company, even if the AI is built by a separate company. So, you know, that's one area. The second is making scale organizations play. And part of the scale organizations is, you know, part of what, you know, the rebuilding the jet engine as you're flying is continuing these just world-class businesses in enterprise productivity software and a whole bunch of other things, but also rebuilding as you're going. And how do you rebuild the organization? And it's part of the growth psychology. Like the very first kind of corporate executive offsite that I went to at Microsoft was kind of saying, hey, we really have to follow the Carol Dweck growth psychology. We have to earn ourright in this. We don't just take it as a natural given. And how do you rebuild that in the culture of the company? And then the third, which I think people have seen, but Satya has done a stunning job of kind of corporate partnerships and kind of not just acquisitions, Minecraft, LinkedIn, GitHub, et cetera, but also like the OpenAI deal. Like lots of people thought he was being a fool working with a nonprofit that had no business focus, no business acumen, no product development, et cetera, but he was going to go do that. And his first table stakes was a billion dollars in in order to do that and did that. And that will go down as one of the genius moves by both Sam and Satya in history. **Ollie Forsyth** [46:04] Before both of them committed to the investment, did they give you a call to get your wise words of wisdom on what it's potentially could look like? **Reid Hoffman** [46:13] Yes, but one of the tricks that I had to do is because I was on the board of both at the time, that my role was a trust building that I abstained in the votes of both boards. Everyone was very clear about kind of where my position was and being on both boards. But still, even in that circumstance, part of what you can do is say, well, when person one tells person two, statement X or statement Z, you can tell person two, yes, that's true. Right? Like you know me and I'm telling you it's true. And then vice versa and back and forth. So you can go, ah, you can establish trust much more quickly because you can go, okay, the opposed to normal thing of, hey, is there something I'm being taken advantage of here? Do I have to put in a bunch of warrants and representations, due diligence, the contract? I can rely upon that. It's true. And then you say, look, these are the set of things. And by the way, I will of course be abstaining because it's important not just to appear completely high integrity and trustworthy, but the substance of it too. And the substance needs to be that I'm just like, look, I'm not voting on this. And I'm not voting on it because the decision needs to be made independent of me because I'm in both organizations. ### Reid's Week **Ollie Forsyth** [47:33] If those of you have so much going on, I would love to join as your chief of staff for a week or two. What happens on your day-to-day for a week? What actually happens? **Reid Hoffman** [47:42] It's kind of insane because it ranges anything from giving world leaders advice on artificial intelligence strategy to working with a bunch of different venture funds, Graylock and others in terms of investments to some of the kind of AI companies that I've co-founded. So Manus AI, trying to cure cancer and drug discovery with AI and Inflection and what are those doing? To doing new investments. I've done some new investments in the last month. Usually, I don't get around to announcing specifics to generating content like the book Superagency, the podcast, possible Masters of Scale, et cetera, to doing things for fun. And also, by the way, being informative in AI. Like for example, I've made a 4th of July record for celebrating America's 250th anniversary of reinvention and invention because I think that's the important thing, one of the important things to understand about American culture. So I do all this up. And any particular week is a triage across these. Which things are most important? Is there an immediate time demand? Is there something afoot? Can I put more time into this, et cetera, et cetera? And that's the wildly ambitious scope across all of this. **Ollie Forsyth** [49:06] I love it. Are you working seven days a week? **Reid Hoffman** [49:10] Yes. And people say, well, you know, this is a holiday. I'm like, oh, yeah. I guess it's a holiday for most people. **Ollie Forsyth** [49:17] No holiday. **Reid Hoffman** [49:19] And no weekends. I mean, occasionally a day with friends or something, but yes. **Ollie Forsyth** [49:24] And you sleep pretty well? You're like eight hours? **Reid Hoffman** [49:28] Yeah. Minimum six with a target of eight. **Ollie Forsyth** [49:31] That's pretty good. You know, from a trends point of view also, there is so much happening. I love what you're doing with Inflection, Manus, around this whole healthcare space. I think what's happening in Voice is really interesting. The Definite Keyboards, is that kind of going away? ### Emerging Trends **Ollie Forsyth** [49:47] If you were to pick two trends in particular, what are you really excited about that founders can also get excited about? **Reid Hoffman** [49:54] Well, so maybe about 18, 24 months ago, I started doing the voice pilling stuff because obviously the voice, as you just mentioned, is super important and is a baseline. I still kind of give that to people's advice because in engaging with these AI agents, raw amount of pure amount of perspective and data is more important. And we type too slowly. Everyone speaks, even very, very fast typists. You speak much faster and you want to get into you're just giving out every piece of context you can think of and trust that it will assemble that in a way. So just as a plus one to your thing. Now, for two trends, I'd say one of them is people tend to think of the coding agents as building coding applications, mobile apps and coding applications. But actually, in fact, where I think this amplification is, think about it for any particular kind of work you're doing. Let's take a natural easy step, which is like, say, for example, my investing business doing financial analysis. So like one of the things that you do is you can stick in kind of a business plan, even a seed stage, early stage, and say, build me a financial model of this. And then, by the way, it might not do it at one shot. This is part of agentic and routes, but rotating through it. And that financial model will be actually using coding assistants. Not just coding assistants, the setup, the Excel, deep spreadsheet, which it can do, but iterating through the code variations of it, doing research and bringing in databases from the internet, looking for like what goes, hey, I need some data like this. Where can I get that? And you're like, oh, yeah, maybe if I call somebody, I can get some data that I could then ingest into this, you know, kind of as ways of doing it. So that coding amplification is kind of one. It's not just you now writing an app, you know, for, you know, your podcast or something else as ways of doing this, but also kind of various, like, you know, very focused micro areas of work and ways of doing reason and thinking. That's one. And I think we are, people are doing that, but it's a little bit like the quote that's ascribed to William Gibson, which is the future is already here, just unevenly distributed. You know, that, you know, dynamic is very thinly distributedright now. It needs to be much broader. The second is to think a little bit about, you know, like what's the way that you are present in the various networks that are the amplification of you. And so, and I'll give kind of a very Reid answer on this, but it's not to say it's different for different people and so forth. So like one of the things that, you know, I have a lot of people that I've met over decades of working that I really value. And a little bit classic to the Dunbar number is, well, you can only really maintain a relationship with a maximum of 150 people. That's actually been not true because of social networks for a while, but it's also now really not true because of AI. And as a micro thing, like for example, part of when I create a record of AI music to celebrate, you know, America's 250th birthday and the kind of 4th of July, I then also create using AI custom one-off printed versions that have the person's face on them and other kinds of things because, you know, people who get this know that like they are part of the group that I think of, the part of the group that I care about, that even though I may have been five years since I've talked to them because I'm busy, you know, building, trying to cure cancer and other things, you know, lots of things going on, that there's still someone I care about. There's still someone who, you know, I go through the effort to get included, make sure that it gets to them, gets to their address, has a brief touchpoint. This is among the kinds of things that AI enables. Obviously, people think about is, oh, it can answer my email for me. And yes, it can do that. And by the way, that's valuable on a number of different contexts. But by the way, you still want to maintain that human connection. And as part of that human connection, you want that to be reinforcing your human connection with them. So it's not like they didn't think I went and custom painted, you know, you know, Eric's face on it,right? You know, they understand that I was using an AI tool to do it, but I was thinking about Eric, and I sent that to Eric, you know, as a kind of a way of doing it. And they're like, ah, great. And then it becomes, by the way, an artifact that is part of the treasured presence in our interaction. And so whatever the version is for people, it's exploring this form of creativity and human connection, reinforcing way of doing it. Not talk to my agent, don't talk to me. You know, some kind of, we're very busy and all this, like you've got a bunch of people pitching you to be on your podcast. You don't know them. That's a good start. But also amplifying the connection you have with people that you know, value, trust, respect, want to go through life and work together. **Ollie Forsyth** [55:19] I love that so much. The human connection, but also the in-person connection, I think is next. And that's potentially the next big opportunity. We have covered so much. I have loved this so much, but we always love to finish with a sweet spot. And that is the quick fire round. So I say a quick question, you respond with your immediate thoughts. Masters of Scale, one of my favorite podcasts, turns 10 years old next year. Who is your favorite guest you've had? ### Fire Round **Ollie Forsyth** [55:46] And who is the guest you have not had on the show as of yet? **Reid Hoffman** [55:52] Truly, I don't really have a favorite guest. I have some more favorite and some somewhat less favorite, but it's been just spectacular and great. And, you know, for anyone who's not listened to it, Brian Chesky, who was my very first one, like was a great approach of how design to all of life and experience was spectacular. I still remember the, what happens when you, like if the Pope were arriving somewhere, what is the experience the Pope has and how do we replicate that for you,right? And it was like, wow, never thought of that,right? And like kind of great. So that would be Masters of Scale. **Ollie Forsyth** [56:30] I love that. And if you haven't listened to Masters of Scale, listeners, go and subscribe. We'll put it in the show notes. What is the one thing in the last 12 months that you have changed your mind on and why? **Reid Hoffman** [56:41] I changed my mind fairly constantly with updating both data and thinking. And I think, you know, it's a great question because I think it's important everyone do that. I guess what I would say is I think it's a story of slightly slower AI adoption than I'd like. One of the things that I'd been predicting from many years ago, I wrote for the MIT Tech Review, that we have AI agents that'd be listening to every meeting, giving analysis and following up. And I think because of the human-human thing, it will be slow, that adoption. My team, we record every meeting and we use AI and have a bunch of custom AI agents for research follow-ups, et cetera, to amplify us. But like I even see startups that are not doing that yet. And startups tend to be the boldest. And I think everyone needs to get there because it's a team amplifier as well. And I think I just was like, if you'd asked me, I would have thought this year would be the year that that would just, you know, blitzscale into being. And I think we'll grow, but maybe it's next year that it'll be blitzscaling. **Ollie Forsyth** [57:49] You know, so many founders, I'm sure, want to spend time with you. What is the one question you wish founders asked you more of? **Reid Hoffman** [57:56] I think one of the things that's probably most important is, where do you think my startup plan, my theory of the game, is most likely to fail? And what do you think about my proposed solution to it? And how might I stress test that solution more? And do you think there's something that I'm more like, that I should be paying more attention to? So focused on, as opposed to, it's going to work, it's going to work, it's going to work. It's, okay, it's good. It might work. What is the thing that's most likely to blow me up and how do I navigate that? **Ollie Forsyth** [58:30] You know, I love meeting VCs where they say how amazing things are, but actually behind closed doors, maybe it isn't always theright story,right? And I think to finish off this, you know, incredible episode, this last question fits in quite nicely. You sold eBay when you were 35 and one of your greatest friends said to you, Ned, you shouldn't wait a year to found and build LinkedIn. You should start now. If you weren't building everything you're building today, what is the one company you would start today and why is now the moment to be creating it? **Reid Hoffman** [59:09] Well, so I have created Manus AI for drug discovery. And thank you for referring to Ned and my Vanderbilt commencement speech. I would say there's a whole raft of different kinds of applications. One of the ones to really do is say, hey, look, there's going to be just a flood of digital AI applications. So, you know, whether it's, you know, productivity, coding assistance, so all this is cool, great, and some of those will work really well, but there'll be a lot of competition. One of the biggest issues in entrepreneurship is trying to pick thin competitions. Part of the reason why we went to, you know, drug molecules. So to think about like what's something that's a simple small step-off AI that can move with speed. Because like if you say, well, I'm going to build robots that are going to be doing manufacturing, it's like, well, does it take like building each new robot in each new manufacturing center? And is that going to move really slowly? Some people are going to do that successfully. But like what's the thing that is just that one step-off that you have a unique edge to? And that's the kind of thing that I would recommend people do. And that's part of the reason why Manus AI has been, you know, kind of the thing I've been doing most intensely over the last two years. **Ollie Forsyth** [1:00:22] This has been incredible. I'm so excited for the next 12 months. We should come back in 12 months and figure out like what does the next 12 months look like. But thank you so much for coming on this edition. It's been amazing. **Reid Hoffman** [1:00:32] My pleasure. That would be awesome. --- This library is powered by PodHood (https://podhood.com), the podcast website platform.