20VC: Reid Hoffman on Foundation Models: Who Wins & How Do Incumbents Respond | The Inflection AI Deal: How it Went Down | Why Trump is a Threat to Democracy | The Future of TikTok | Lessons from Sam Altman, Brian Chesky and the OpenAI Board

Reid Hoffman
The american electorate right now hasn't really fully remembered the corruption and incompetencies of Trump. I've had a two hour lunch with Biden. He was asking me questions about AI. He was explaining stuff that was going on in nuanced detail in Israel. He's good.

The real issue is AI is a human amplifier. I'm a lot less worried that the robots are coming than Putin is coming with his AI enablement. Artificial intelligence in an economic sense is it's a steam engine of the mind will have a cognitive industrial revolution. This is 20 vc with me, Harry stabbings and the show state is such a special one. We hosted the one and only Reid Hoffman live in the studio in London.

Harry Stebbings
Reed has been one of the most impactful people in technology over the last two decades. He's the co founder of LinkedIn and Inflection AI. As an investor, Reed has backed the likes of Facebook, Airbnb, Zynga and more. And Reed's also a board member at Microsoft and was on the board of OpenAI. But before we dive into the show, stay.

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Remote opportunity is wherever you are, you. Have now arrived at your destination. Reed, I am so excited for this. This is the first time that we've met in person, and it's been like. Six years, some number of years.

Reid Hoffman
It's that distant before pandemic, prehistory time. I was young then. Yeah, well, still young now relative to some of us. I'm not so sure about that. But I want to focus the first bit on the state of AI.

Harry Stebbings
I wanted to actually just ask a bit of a bold question, if it's okay. Can you be objective and impartial given your board membership with Microsoft? Essential answer is yes. By the way, what I have most wanted to aspire to be is a public intellectual, which is, how do you speak the truth about who we are and who we should be as individuals in a society? So I aspire to that in every aspect of my life.

Reid Hoffman
Now, that being said, I do, of course, have commitments to the board of Microsoft. So the things that I can't talk about, but as opposed to, like, objective, is, like, I just say I can't talk about it versus giving a false answer or a misleading answer. And then the second is, obviously, I learn a bunch from the world from that. Like, there's a perspective that I will learn from the intensity of Microsoft that may give me a blue colored lens as I'm looking at something, but I myself aspire to be a public intellectual, to speak truth so that we collectively become better. Why do you think you aspire to be a public intellectual?

Harry Stebbings
I didn't mean that rudely, but no, no. Well, that was the goal. I get great joy from discussion, where we are discovering truths together. Teaching is part of that, right? Some teaching is, we're in a seminar and we're talking, we go, ah, we now understand some important aspect of the world better, whether it's about ourselves, whether it's about the world.

Reid Hoffman
And that's what I think to some degree. One of the fundamental parts of the meaning of life is, which is how do we become wiser, more intelligent, more compassionate, et cetera. But that's because the discovery of truths about these things that we share on this journey that we call life together. Does AI make the discovery of truth harder or easier? Both.

On one sense, it's a great companion catalyst in these things. It's just like, for example, don't proxy your judgment of truth to what you happen to have found in a search engine. It can inform your perception of truth. Google told me Radwine was fantastic for me. Exactly.

In a similar. It could be bad in that regard, because you might say, well, the AI said X, and you're like, well, okay, maybe. Do you think more value accrues to existing incumbent brands, given the importance of verification in the new AI world? So the New York Times becomes more valuable because it is a validated source of truth versus content creator called Sarah on Twitter, who is not a validated source of truth? I would to some degree hope so.

I mean, one of the things that I think that the kind of the libertarian kickoff of the Internet has underplayed is that we need to have shared media be how we learn together. And so some of that is, you need to say it isn't just propositions in the wild that where a thing is said that you can, like, for example, get better from COVID by taking hydrochloroquine, it's like, no, no, no. Just because that proposition is said and said by the then president of the United States doesn't mean that it has any scientific validity and isn't actually, in fact, destructive to your health. We need to have better sources of how are we collectively learning. Like, for example, when we as human beings try to figure out how to get to truth, we use panels of human beings to do it.

It's like a scientific panel observing a study or deciding on a paper. It's a blue ribbon commission and trying to figure out what the facts are in a public circumstance. It's a jury in a criminal trial. We bring a group of people together, and that brings a set of balanced perspectives. We need to have that kind of thing, and we need to have the brands and institutions that reflect that kind of collective approach to discernment of truth so that we learn together.

Harry Stebbings
I guess we only have those validation boards of certifications for large decisions. Is reed guilty or guilty for all the mini micro decisions? We don't have those validatory sources of certification. And now we can, in various ways, like, we can amplify that way. So, for example, questions around what's someone's professional cv?

Reid Hoffman
Well, LinkedIn is working its way towards being a hire and higher source of. Yes, if it's there, it's got a very high likelihood of being accurate. Do you think so? It was Gustav at Spotify. I know we have this schedule.

Harry Stebbings
He said that the number one thing that he looks for when hiring today is the quality of someone's prompts. How do you think about and respond to that? It is classically for Gustav, it's a good lens into the future, because call it five years from now, there won't be a professional doing professional activity who, if they're not using AI to help them with it, is being fully competent at the profession they're doing. The speed and intensity which allows you to process information, find information, analyze information, make decisions, is only going up year by year. I do want to start.

We mentioned using the tools. Well, there. The thing that everyone says, and I think that I see is the commoditization of the tools in terms of, especially the foundation models. Do you think that foundation models will become commoditized, and what do you think will be the end state for the foundation model layer? The commoditization language is interesting language.

Reid Hoffman
I do think that it won't be that it's kind of like grain of wheat or a pound of copper. Foundation models will be different. They'll actually have somewhat different strengths and weaknesses. Like, some of the most interesting work that's being done right now is kind of comparing and contrasting Gemini with chat, GBT with copilot and Bing chat, and saying what? Because even between the open airlines, what are the differences?

How do they operate? What are they good for? Do you think teams can keep up. With the progression of the LMS? Because I speak to founders often, they're like, God, we almost need to hire someone full time to do an analysis of the different changes in LLM providers, just to keep up.

That's not necessarily a bad thing, but part of the thing is to be choiceful about what your analyses are relative to what's important that you solve and understand that everything is changing at a fast pace. So if you say, for example, like, what I've heard from some people who've done analysis, Gemini is better at producing fiction. OpenAI is better at the kind of Wikipedia like reports three months from now. That may be different that me as a user, that might say if I'm trying to solve a certain kind of thing, like if I'm trying to write a science fiction novel, maybe I'm going to go to Gemini and work on that mostly. But by the way, of course, one of the things for products, for individual users using multiple is good because that's where I was going with it.

Is it commoditized? Actually, in fact, I think there will still be differences, but I think our behavior both in creating products and as individuals will be almost more like kind of a conductor in an orchestra. It'll be like, well, a little bit louder on the bass, a little bit softer on the cello as a way of navigating. It won't be that they're all just vanilla each other now. I do think because we have multiple ones that are competing with each other, there will be an intensity of providing it at low price, fast response, et cetera.

Because if provider one isn't working that well, I'll just go to provider two. I think that we've all realized that actually cloud providers is the way to make money and the cloud providers will buy up the LLMs and actually just integrate them as amazing products to add to their product suite. What happens then? Because the only one that's too big to be acquired is OpenAI, given the price. But everyone else, even Mister OL at 5 billion that can still be acquired.

By Amazon, I do think that every cloud provider and frankly, every scale software company is going to need to have a serious provision within, like they'll want to have some internal teams and some internal talent doing things. It doesn't necessarily need to be everyone's doing frontier models, but because I think it's a blend of models that will be creating the quality of the highest tune cognitive services, the elevation of cognitive capability, I think that everyone's going to need to participate, whether it's acquisitions, whether it's developing and refining open source models, whether it's building your own, you'll see all of them in that range. Sam said compute will be the single most defining currency of the next decade in some version of the words. How do you think about that? What is certainly the case is that part of what's happening with AI is it isn't like we've discovered the algorithm.

It's that we've realized that applying scale, compute, turning these things into learning machines off a lot of data with scale teams is the thing that has generated all the magic. And so compute is obviously a very, very central part of that. And as yet, all J curves turn in s curves. But at the moment, we see each new level of scale, of compute bringing new serious capabilities to the table. And so, therefore, compute really matters.

And commute will matter in training, compute will matter in inference and providing we are going to be on a journey, maybe forever, as human beings, of massively increasing the amount of compute available to us in all aspects of our lives. For many years, people have seen the deceleration of Moore's law. Do you think we'll see the alternative of what we thought, which was that deceleration and actually exponential acceleration? Well, so Moore's law was specifically transistors, right? And so that deacceleration of Moore's law still happened.

But what people didn't realize is, well, I can just build much, much bigger data centers and I can tune a new set of chips to a much different set of functions where those functions, mathematical graphic processing units, can actually, in fact, do things that are extremely important to us. And so I think we're already in the equivalent of a resumption of the acceleration of Moore's law. And of course, if we want to be a little bit like advancing the ball in the future, what happens when quantum computing becomes very real and applied is there may be other areas where it's even much more accelerated. When we think about the business model of foundation models, as you said, that we've got this real race to the bottom in terms of pricing, how do we think about when the marginal revenue exceeds the marginal cost and when they actually become viable business businesses? And actually, are they viable businesses?

So I think that there is literally no doubt in my mind that there's viable businesses that will play out purely. In the foundation model, purely in the. Foundation model and also the others. But the foundation model as well, in part because, look, at some point it is the classic venture thing of you start investing and you may even have bad operating margins. Like for example, if you said the first x thousand stays at Airbnb, the operating margins were terrible.

It was kind of money losing. You have to get to a certain scale, you have to bring a certain amount into it to then make it into the amazing business that it is. Like the food delivery market most often. All of these things have various elements to say. The very first of it looks like very bad.

Now, why conviction on even the frontier models? And the answer is, because look, software ultimately that almost always has good operating margins. Software is cheap to execute, it's expensive to AI to develop it. Now if you just say, well, we're not getting as much value out of it. Five years from now, the development curve costs will get more slower and more amortized as we're turning into the make money from it side.

Harry Stebbings
The thing I find really interesting is actually the size of incumbents today. Some of the largest incumbents, you can probably tell me, and it might be a little bit off, but I think it's like Microsoft does about 300 million in free cash flow per day. We've never seen the size and might of incumbents. Everyone says Nokia. Nokia was not anywhere nearly as powerful as this.

Are they too big to use up? How do we think about the fear of the incumbents are too big? Mistral's new funding round 40 hours of Microsoft's free cash flow. Yes, exactly. If what we were was seven big tech companies heading to three, then I would be concerned because of the monopoly effect.

Reid Hoffman
But I actually think we're seven big tech companies heading like 15. And so yes, the big tech companies are becoming bigger. All of them are compounding. It's a function of globalization. It's a function of we're all in one big global network.

It's a function of the more and more importance of tech and AI. All of this stuff leads to massive size, but size is always relative. If you said, well, there is only one uber company and it's called Microsoft or it's called Google, well, that would be concerning. But the fact is Microsoft, Google, Amazon, Apple, they're all competing with each other ferociously. And part of the thing I think we'll see because people frequently say, well, but that's it.

It's like, well, but actually, look, Salesforce is coming along, there's a number of companies that are seeking to get into that set. What's more, if you don't take only a us perspective, you go, well, what about Bytedance? Bytedance is a huge company, right? You know, Alibaba, Tencent, etcetera. So we're heading towards globally more and more very large tech companies.

And that actually is a feature, not a bug. Part of the benefit you have is take this AI revolution we're in. It's because you have these large companies that can invest in multi year risky projects, that can create things that are massively valuable for society. When they started, there was no clarity that there was any valuable business in this whatsoever. Do you think it's a VC investable asset class though, because when you have irrational buyers or prices, any of the large incumbents, that's not a good business for purely rational buyers to be in.

Harry Stebbings
And when you look at the amount of money that they have and are able to inject, it is so asymmetric compared to VC capital injections. So look, VC's always are looking for the areas that not off the mainstream kind of major company already established. Like for example, if you came to me and said, I've got an idea for a new smartphone and I want you to fund my new smartphone to compete with the iPhone, you'd be like, okay, good luck, or I have a new kind of mobile or desktop search company that I want you to invest in. Okay. And so sure, there are things in these large tech companies like and with AI that you shouldn't be doing startups to try to compete with them on, right?

Reid Hoffman
Because that's where their dominant position and there's network effects and moats and enterprise integration and list of customers and all the rest of stuff, you go, no, no, you don't attack a fortress at the front door. That's what disruption is. It's like, what's the new territory or the diversion of the river or something else as kind of a way of doing that. And I think there's a lot of that available within venture. It's just not, oh, I'm going to go build a frontier model to take on Google search.

Harry Stebbings
Do you think a new frontier model will be created today? Do you think that wave has already gone and the incumbents and the hyperscalers have kind of escaped already? I think it's almost 0% the way a frontier model created in the way that frontier models exist today. I think that wave is gone. But on the other hand, to think that the only pattern for these scale learning systems happens to be these attention transformers together with a set of techniques like mixture of experts and other kinds of things, and say that's the only one true path.

Reid Hoffman
It's like, well, there might be other paths. And so therefore that may also get you alternative paths to building interesting frontier models, and those may still happen. Sam said on the show that the quality of the models was the biggest constraint. Do you agree with him? And how do you think about quality of model improvement and the trajectory of it?

I do think that part of the thing is to make sure, because a lot of people try to build these models and build them poorly, so it isn't just put in data, put in compute, press button, go away for six months, come back and go haha. I've got GBD four. There's a whole bunch of art and science. And what I mean by art is like, well, you train it this way first, then you train it that way second, as part of the kind of the evolution of this. And there's a bunch of stuff that isn't written down in the published papers and so forth about how to do this kind of thing.

So quality of model really does matter. And it's a small number of teams and a small number of folks who are doing it that well so far. It'll broaden, there'll be more. By the way, size of compute, as per the earlier question, is really going to matter. People frequently mistake what quality of data means because they think, oh, you have to train on the New York Times.

And actually, in fact, most of it is quantity of human data, not because you've had any particular journalist who's got a particularly nice way of writing with words that makes anything particularly useful. That's why I thought LinkedIn was such an interesting topic, though, because actually it's the most extensive structured data source probably on the planet. In terms of professional networks. Yeah, in terms of professional data, yes. But you know, there's lots and lots of very interesting piles of data.

For example, all of the academic publications, I mean, there's tons of things that are very interesting. There's GitHub with all of the code repositories. I'm just going for this every time I look at Nvidia and I'm like, no, I can't go higher, can't go higher. And then another quarter comes, I'm like, it went higher? Is that a good buy?

Look, I think Nvidia is a great company and Jensen's a great CEO. I don't actually myself trade in the public market that much. I'm a private market investor, so I don't actually really make those operative decisions. It might be, I think their chips are extremely valuable in this scale AI transformation that is happening. Without all of the Nvidia inventions and chips, we wouldn't be nearly as far along as we are now.

The real question is buy at this price. I don't know. That's the price question. That is the real question. We spoke about the different providers.

Harry Stebbings
I have to ask you, I had so many people suggest questions, and this one I really wanted to talk about, which was the inflection deal with Microsoft, how did that go down? I love the story as well. Does Satya call you and go, let's take this one. Satya and Mustafa had a conversation, and it was kind of funny because both of them called me afterwards and said, I had this really fascinating conversation about what is the kind of work we could do together. Do you think we should possibly think about this?

Reid Hoffman
And so I had separate conversations with both of them because obviously I'm on both boards. And then they said, well, should the next conversation be the three of us? And I was like, no, I think I have to keep my hat separate because I have to talk to Mustafa from a Greylock hat, from a inflection board hat. I have to talk to Satya from a Microsoft public board member hat. And I have to make sure that I'm playing each role effectively.

And if I'm in the room, it's like you can almost bring two baseball caps and go, okay, okay, okay. It just doesn't quite work that way, so it's better to do that. And so they, in a set of conversations, kind of got to the position of saying, well, Mustafa had already been worried that the notion of the massive increase of scale of frontier models was going to be beyond startup companies ability to monetize with an agent infrastructure is going to take a long time for agent infrastructure to monetize. He's like, look, we have this really great product. We have this really great agent, but if we're going to keep pace with that, we're going to be massively in the red for a long time.

And yet that's what we really want. We want to make sure this great agent that really helps everyone is going to continue and grow and thrive. And that was part of the, okay, well, maybe we could do that at Microsoft. While at inflection, part of it was we'd been thinking about like, well, maybe the real business is around AI studio, that you have a number of different models, some of which are custom trained, like inflection, other which are open source models. And you're kind of being a b two b AI studio model because that's what we had been thinking about doing with inflection anyway, given the economics of the business.

I was like, well, that business could then be funded by this transaction. The people who want to build agents can go do it at Microsoft, and the people who want to do b two B studio can stay with the company. Sorry for being naive. Why did Microsoft do it? Because the transients or the decay rate of models is so fast.

Harry Stebbings
It's not for the model. Is it for the team? Look, there's a decay rate to the model, but the model is still valuable because part of the idea with inflection and still inflection 2.5 is a unique GBD four class model that is the best one that prioritizes emotional intelligence along with analytic intelligence. So its EQ is as good as its iq and its iq is pretty good. And so yes that, and by the way that learning and so on.

Reid Hoffman
But part of it was of course that one of the things that Microsoft was looking for is year by year, how is copilot iterated into the kind of agent that is this new agentic universe, this new world that we all see coming and Mustafa and Karen and some of the key team at inflection, thats what they wanted to build. So I was like okay, let's build that. And we're starting. Their whole strategy is building on the OpenAI models that Microsoft and OpenAI are already working on together. Do you think that inflection could have been a standalone business?

Well, it is a standalone business as a B two B AI studio. But as an agent it was a very risky proposition. What does it mean like a B two B AI studio? So large enterprises can come in and. So someone comes in and says I have a customer base, I would like to provide AI to them in the following way.

Can you help provide the set of models through the APIs that I could then use to service my particular business need, whether it's a community, a customer service function, an application, et cetera. So when we think about that merging and actually going, actually there's a huge amount that we can gain from the distribution, the cash flow of Microsoft is this big partner. Do we think that AI favors more incumbents or favors startups more? The answer is both differently. And I'm not trying to weasel out of a question.

Look, if you're saying what really matters is like the driving function here will be the billion dollar compute run to make this model. It'll be very difficult for startups to do that. Even in this more modern global venture capital where startups can raise billions of dollars if it's a billion dollars per compute run before you've got your revenue really working in a way that you can predict where that becomes very valuable, that becomes very difficult to finance. So that's all large companies, that's Google, Microsoft, or kind of their partners, OpenAI, other folks. But that doesn't mean that there isn't a lot of room for startups.

Startups can do all kinds of things. They might build smaller models, they might build models in different ways. They also might use the frontier models through APIs. But they can do things, they can take on markets because, because any company can only take on like a couple of markets. Really?

In a serious way. Sure. So there's a lot of markets that Google, Microsoft, Amazon, et cetera, don't get to. And so it's like, okay, startups are opportunity there. And what if you were creating something, you took a risk in getting there where people thought you were crazy.

Like for example, think about early Airbnb, where people said, that's nuts. No one's going to ever rent a room from some other human being. And you say, no, no, we take a risk and we get there. And when you're right, you've created a very valuable business. It's interesting, you said there about the cash required and the speed required and the incumbents having that.

Harry Stebbings
I had so many people ask the question, if you were to rewrite blitzscaling today, knowing all you know now, what would you change? That's interesting. Blitzscaling is still applicable. Chris and I have written about this a little bit in blitz capital, but the blitzscaling creation of the future, it's like you're doing capital raises that literally. The general received wisdom is, that looks totally insane.

Reid Hoffman
And you have to have that in your toolset some. So that was, for example, what Sam Altman was doing with OpenAI, where you go, wait, you're gonna put billions of dollars into this 501 C three effort that doesn't really have a direct commercial goal in order to build this stuff, because this scale application of compute with this small focus team is going to create something that's going to be an archimedean leverage to change the world. Okay, sounds good. Yeah, sounds good. I mean, like for example, the very first OpenAI Microsoft deal was Satya and Kevin Scott brought to the Microsoft board.

We want to put a billion dollars into the investment in this vehicle from a 501 C three that doesn't really have any particular plans at making its equity worth anything, and we can't demonstrate any valuable product right now that's useful, but we have conviction that it should, and this is what we should be doing. That must be a tough board approval. It sure is. Fantastic. I love that.

Harry Stebbings
Can we do 2 billion? Are the best founders, the best fundraisers? You need to be able to fundraise as a founder, so you have to have that in your skillset. There are some fundraisers who are not particularly good founders, especially when they're quasi fraudulent. Are there many truly great founders who aren't great fundraisers?

Interesting. When you look across those, you don't need to name them, just intrigued. No, it's a little bit like what you were selling in blitzscaling. This is the thing that standard studies of business don't really track, which is when you think you might be successful at scale and you still have tons of risk, you go, generally speaking, within the software world, and maybe even the hardware and a bunch of others, raise a ton of capital and start spending it on the presumption you will be successful, even though your probability might be 20% or 30%. And to do that, you must be a great fundraiser.

Do you think competition is good for companies? We spoke about the foundation model earlier. Just intense competition, the incumbency. Intense. Is competition good?

Reid Hoffman
At least some competition is essential. I think very few companies pull their selves into a coherent shape and deliver in a focused way without some scope of competition. There's exceptions, but, like, for example, Google brain invents the kind of transformer and publishes it, and it's kind of bouncing around as kind of a research project. And it takes OpenAI developing it, scaling it, and releasing it as chat GBT. For Google to go on red alert and go, oh my God, we should be doing this too.

Harry Stebbings
I always, whenever I'm investing, I always love competition, but it has to be like shitty incumbents. I don't want it when there's 20 procurement companies all funded by Saqora and benchmark and great and everyone in between. The successful entrepreneurial things, generally speaking, is you outpace your competition. So when you have a lot of ferocious competition, that is challenging, but you've actually put your thumb on something that most entrepreneurs don't really fully recognize, which is to some degree, it's the most valuable market you can against bad competition. Yes.

I speak to LP's often, and they say to me, why are you in Europe? And I say, well, Warren Buffett once said, the secret to success in business is weak competition. Yes. And so I chose to be a european venture capitalist. Yes, exactly.

Reid Hoffman
I'm sure your european friends love to hear that. I don't have any, honestly, I lost some years ago. Okay, I do have to ask, when you think back to your time with OpenAI and on the board there, what are one or two of your biggest takeaways? How did it impact your mindset? Well, one of the things that was very interesting, and I think Sam doesn't get enough credit for this.

Sam was very, very much wanted to have a board that was separate governance from himself. Founders tend to set up is no, the board is my ribber stamp vehicle. I'm in control. I'm doing this stuff. And part of that, for example, was when Elon had announced to the company that he was leaving and not financing it anymore.

And Sam called me, and I said, look, I'll cover the salaries. And he asked me if you joined the board. And I said, yes, I'll join the board. And so then he said, well, will you come to a fireside chat? Because the company does only a few people here know you?

Will you do that? I was like, sure. Of course they should get to know me, and we should have mutual trust. And literally, one of the questions that Sam asked me that he hadn't prepared me for is we were sitting in this entire company meeting, and he says, so what happens if I'm not doing my job well? And I'm like, well, I would work with you to try to improve it.

He said, no, but what happens if I keep not doing my job well? I'm like, okay, well, then I would fire you. And he's like, okay, great. I'm like, you just asked me in front of the whole company, would I fire you? It's like, this is a little strange.

It's the only time I've ever been asked this question in any of my boards, in front of a company thing. But it's reflecting what Sam has always been trying to do with the OpenAI board, which is, it's a genuine, independent governance board. People don't realize, with all of what I thought was the set of mistakes around the November debacle, that one of the positive attributes of that that was because Sam had made an effort to say, this is a separate governance board. I think he was making too much of a AI safety. Who are the most AI safety people?

Make sure they're on the board. Some of those people should, of course, be on the board. But you also need to have good board knowledge, good knowledge about what are the kinds of things that a scaling company and a scaling organization. Because, by the way, it's a chaotic mess. That's part of what blitzcaling is about.

And what things do you kind of go, okay, that's fine. And what things you learn from and which things are important. You said that things go wrong, and it's blitz scaling. You've got Scarlett Johansson. Quite funny, actually.

Harry Stebbings
I know. It's hilarious. You've got the super alignment team leaving. You've got the equity problem. I mean, there's blitzcaling.

That's kind of like. Also, I hate people that throw tomatoes from the back. I cannot imagine the intense stress and workload. But there is just a question about that. In a week is a lot.

Reid Hoffman
Well, look, that in a week is a lot. But by the way, having done this at PayPal, having done this at LinkedIn, having done this at Airbnb, having done, like, all of this stuff, it's always a chaotic, hot mess. Is it? Yes. Sometimes a lot of it happens in one week, and sometimes it's different.

The real question is, how do you learn and adapt? Like, how do you go, okay, that was a screw up. Now let's fix it and let's be better. Who was the best at learning and adapting when you look at those hot messes, huh? Well, all of those are very good examples of ones that have done it very well, because look at the.

Look at where the companies have become and what they've done. I would say. I don't know if I could say best. There were different problems. I mean, we had at Paypal, we had ebay trying to shut us down, and that was where all our volume was.

We had at Airbnb. They had this very early, like, trust and safety thing where a person had stolen a credit card and literally totally trashed a place. Right? Like, had a kind of like a drug party, you know, binge leaving the place and not quite the equivalent of flaming ruins, but. But kind of physically totally trashed.

And so what do you do? Because you need trust in a marketplace. So each of these things had a different emergency that you were like, all hands on deck. We have to solve this, and we're dead if we don't. What do you do when shit hits the fan?

Harry Stebbings
You're a very calm, collected individual. Well, so for me at PayPal, that. Was my primary job, to be the calm, collected individual. As COO. Yes.

Reid Hoffman
I was like, the, go solve this problem. There was a lot of, go solve this problem. Go make sure eBay can't kick us off their platform. Okay, sure. I added to this.

Harry Stebbings
Do this for Tuesday. Yes. Tuesday morning should be done by Tuesday morning. Help us launch Japan was another PayPal one. The lawyers were coming back week by week with a longer list of.

Reid Hoffman
Here's all the criminal penalties and all the things that if we launch PayPal in Japan, no executives could land there because it'd get arrested. And so. And you're like, so literally, Peter came to me and said, the lawyers are screwing this up. Figure out if we can launch Japan and kill it if we can't, but otherwise, get us launched. And I was like, okay, we figured out and we launched four weeks later.

Harry Stebbings
What was Peter's biggest strength and his biggest weakness? Oh, look, super smart. I'd say his biggest strength is a willingness to be contrarian based on first principles and an absolute maximization of speed. Can we have this done by the end of the day? That kind of thing.

Reid Hoffman
And I think his biggest weakness is probably thinking that that's the only way you play the game often. The way. Yes. When we look at a lot of those, when you look at Airbnb, it was like, I cannot imagine someone being in my home. Ridiculous.

Harry Stebbings
Putting your credit card details on the Internet. I cannot imagine that ridiculous. What do you think we are saying today? I cannot imagine that ridiculous that in ten years time it's like, duh, I'm going to Barcelona, of course I'm going to Airbnb it. Or of course I'm going to put my credit card.

Reid Hoffman
Yes. Well, one of them is, I think, even shorter than that. Every single person who has a smartphone will have one or more personal agents, personal AI agents. That is their agent. It is like, there for them.

And on a whole range of things. Like, not just where should I go for a restaurant meal tonight? Or, hey, I had this odd conversation with this person at work. Can you help me talk about it to, hey, I'm writing an essay on this. Can you critique this and get me more information?

But just a whole range of things. Like, for example, I have this skin legion. Should I be concerned about this? Every person today will have an agent that they interact with and consult with every day, multiple times. Is integrations not the goldmine level for the future, which is like, you need the integration into apple fitness into your banking account.

Yes. And by the way, this is part of the whole realm of data, is that now when you tell people, oh, we're going to have to integrate all this data, they go, oh, my God. And they feel like it's a lack of control. Loss of control. That's frequently what they mean by loss of privacy, is a loss of control.

And actually, in fact, as you begin to realize of actually, in fact, like, if I had a bioscience monitor that would tell me and tell the doctor if I had some, like, for example, I would love to know if it's like, uh oh, you might be 15 minutes away from a heart attack, that would be very valuable knowledge to know. And I would like it to escalate to. The ambulance shows up. Like, it's almost like you think it was like a. A support version of minority report.

Like, the ambulance shows up and you're like, why are you. Oh, we're here for you. But we're about ten minutes early. We can wait. Okay, so everyone has a personal AI agent.

Harry Stebbings
I always think that we overestimate adoption in one year cycles and underestimate in ten. Exactly. Do you agree that's the case here? 1000%. Right.

Reid Hoffman
So people think, oh, it's all good. Some people say it's all going to be different this year, all going to be different next year. And it's like, next year, it's going to look a lot like this year. But as you compound year by year and as you get certain phase shift changes, then all of a sudden the world looks entirely different. I mean, for example, consider how just driving over here through London, I was reflecting on two thirds of the people I saw on the street were looking at their phone, doing something with it.

Think about what, like 20 years ago, if you had portrayed that, they said, oh, that's the Jetsons, that's the city of the future. It's like, no, it's right here. And what they're doing on that. Yes. It's more like, I look back at your grandfather or your grandparents and they were like, write a letter, wait two days for a response, and we message, and it's done in a second.

Exactly. A friend of mine said, we will in the future vote for algorithms to run countries. Not for people.

No. And part of that reason is because if you look at what the AI revolution is, it's a shift from, we program the computer and obviously we're still programming it, but as opposed to programming knowledge into it, we're giving it a learning algorithm. The learning algorithm then goes through a whole set of training sequences to become a cognitively sophisticated device. That particular quote presumes that the algorithm is something like that, as it were, is coherent, that you kind of look at the algorithm and actually, in fact, what we want is a really robust learning system that has learned a lot of really great things, has incorporated a lot of human feedback into that, and is making good actions and judgments based on that. And by the way, that's what we hope for from our leaders, whether they're leaders in politics, leaders in investing, leaders in entrepreneurship, leaders in academia, leaders in journalism, that kind of, we are learning machines that have learned good judgment.

In these questions, do you think we. Dramatically overestimate the concerns around AGI? Broadly, yes, for the following reason. The problem that I have with these critics is that the real issue is AI is a human amplifier. So it's part of the thesis that I've been going out and trying to get people to understand is actually, in fact, it's a human amplifier for a large number of years.

I don't know if a large number of years is ten or 500 or whatever, but it's a human amplifier. And amplifying bad people, too, is the question. So whether it's a terrorist, a criminal, a rogue state, and so we go, oh, the robots are coming. It's like, well, I'm a lot less worried that the robots are coming then Putin is coming with his AI enablement. Right?

So let's focus on the, on the bad humans and what's happening there, and then pay attention some to the science fiction side while we're on kind of. The world around us. I have many on the show and I ask them, because I'm a naive brit sitting in London and I say, us elections, how do you think this plays out? And every single person so far has said it's inevitable that Trump will win. So I'm glad to say that every single person so far is wrong.

I think part of the reason theyre saying that is the american electorate right now hasnt really fully remembered the corruption and incompetencies of Trump. Theyre like, oh, the world is kind of a fragile place. Im unhappy with how theres all this global conflict. Im unhappy with the tragedy thats going on in Gaza. A stack of things because of the huge stimulus thing from COVID prices have gone up.

And im unhappy that theres been an inflation of prices. I have some agitation and completely legitimately agitation. So they're like, well, I'm agitated. Biden's president. I'm agitated when people start remembering that Donald Trump agitated for an insurrection that killed police officers.

He was convicted by a jury that said not only did you do sexual assault, but you slandered about it in a jury thing. And they start like it's a jury. That's right. When they begin to remember that, they will begin to get much more negative. So it isn't that, it's, are you.

Harry Stebbings
Overestimating the knowledge of the american populace? I hope not. I think there's real work ahead of us to remind people about what a Chernobyl Trump is. But I think if we successfully remind them, and then also, by the way, you know, Biden has passed more bipartisan legislation than any president in decades. He has done stuff for the climate on inflation reduction.

Reid Hoffman
He has helped assemble the world on Ukraine. Do you concede, though, that essentially by voting for Biden, you just vote for a very good administration around him because of course. But by the way, vote for any president, you're voting for sure. But there's normally a leader, and Biden. Is what Biden selects his staff.

We have had a whole history of presidents where the staff is what does everything. And he is the person who's like, look, I've had a two hour lunch with Biden. Like, it's very popular to say, well, he's old. He's not cognitively with it. In a two hour conversation, he was asking me questions about AI.

He was explaining stuff that was going on in nuanced detail in Israel. He was kind of saying, look, this is what I care about your average worker, and this is what we need to be doing. And how can you technology industry be helping the average worker? Look, it was a two hour, robust conversation. He's good.

Harry Stebbings
That is not what I normally have on the show. So it's nice to have a different opinion. Do you think that actually, when we look at some of the problems that you mentioned, do we think that AI does more to harm or to help income inequality moving forwards? There's almost a little bit of implicature in the question that income equality is the most important feature. I think that AI will raise incomes both for working class people and for, you know, middle class people and for wealthier people.

Reid Hoffman
I think it'll raise incomes across all of them. And so therefore, I'm actually, in fact, quite positive on that. And I can make arguments for how AI provides productivity increases and is positive on each of these levels. Now, there's some jobs when we'll just want the AI only to be doing it versus the human. So, for example, driving.

We actually want AI's driving because they don't get drunk, they don't get tired. They have a lot more sensors to pay attention to the world around them. Like they can have lidar and infrared so they can see the kid who is running out from behind the parked car, or as a human can't. There's all kinds of reasons why we would want that. And each of these cases, like, for example, if you look at one of Greylock's portfolio companies, Cresta did a study of which people in the customer service were most benefited by early AI.

And it was the entry level people, it was the people coming in and learning the job much more quickly. And that's a pattern that you can see across this. I think it's beneficial across the entire thing. Now, the inequality question, I think a much more fraught question for the following reason, which is, I don't know, of any human society organization where we don't run on the basis of inequality, right? Like better investor, worst investor, better entrepreneur, worse entrepreneur, better business, worse getting into college, et cetera, et cetera.

We run. Our entire human society runs on inequality, even places ostensibly communist, who's in charge, who gives, give other people orders, etcetera. Like, human beings are tribal creatures. So we have inequality inherently in the system, and we try to orient it so that people can, through hard work and talents and everything else, rise up as much. And I think that equality of opportunity and equality of ability to make amazing things of themselves, like you with 20 BC, is a really, really good thing, but the end result is inequality.

Then you say, well, but how much inequality is too much? Well, obviously there's an answer to how much inequality is too much, when it's like, well, I now am the autocratic ruler. Like, say, I'm Putin, and I say, half of the country belongs. I own and belongs to me, and everyone has to do what I say or I kill them. Okay, that would be a problem.

And so there's problems, but it's like, for example, people say, well, but a CEO shouldn't make more than 20 times what the entry level. And it's like, where do you get your magic number? Well, it's also like, then it just breeds, like, the most ridiculous stock compensation, which led to the most extremely worst situations happen. I want equality of opportunity. I want massive economic opportunity.

I want ability to do your best work and express your talent. And I think AI can do all of that. Does it benefit more wealthy people or more working class people? I think we want it to benefit both massively. One of my biggest worries is actually regulation.

Harry Stebbings
And obviously, being in Europe, it's one of our biggest skills. I'm terrified, actually, that we're just going to regulate every element to the point of it not being able to progress in the way that it could. Is that a legitimate risk? Of definite risk. I mean, this is one of the reasons why the vast majority of stuff that I talk around technology and AI, is we will have much better tools to make much better things for human beings and society in the future.

Reid Hoffman
Let's make sure we get there to building those tools. So, for example, your average press person, your average government official will say, what's the most important thing in AI? We make sure that those big tech companies, you know, dominate with the AI. That's the most important thing. I was like, well, that's interesting.

I think your most. Your most important job is I have a line of sight to a medical tutor, a medical assistant, probably better than your average general practitioner, on every smartphone, don't you think? Your actual job is, how do you get that on everyone's smartphone? That every single person in your country, maybe in the world, has potential access to good medical advice. May not be perfect medical advice.

Wouldn't you think that's your top job? Or how about a tutor for any age of human being in any subject, wouldn't having access to all of that for every child that you have in your company, wouldn't that be your top job? So interesting. When you look at the balance sheet of a country, if you can actually impact the healthcare budget or the education budget by 5%. Oh my gosh, yes.

That's the orientation and that's the blind spot from the press and the blind spot from the dialogue. But do you think the political system is educated enough to be able to make regulatory decisions that will take that. Stance when you talk to the right smart people? The answer is yes. And so, for example, in Europe recently, have you seen some of it?

Macron, he's been doing a good job here. He has. And so the White House executive order, very good. The UK AI Safety institute, leading in the world, like, really, really good, helping the US, etcetera. So we have some glimmers of light.

Harry Stebbings
It was interesting, actually, speaking of the UK AI safety, Mister Clifford. Love Mister Clifford. And he said a brilliant question, which was, what should be the AI strategy of medium sized countries? Which non us country is doing it best? So I would say medium sized countries.

Reid Hoffman
The basic answer is, don't try to just replicate everything. Don't try to try to say, we are going to have our own GPD four model or whatever the current time slice of it. And that will be our own bangladeshi kind of version of this. Because just like, for example, say, well, you're going to have your own Os for your phone, or you're going to have your own Os for the computer. It's like, no, that doesn't make sense.

But it does make sense is to say, okay, given that these technology trends are happening and that there's an important, you know, the way that I describe artificial intelligence in an economic sense is it's a steam engine of the mind. It has, just as the steam engine gave us physical superpowers, the AI gives us mental superpowers, and we'll have a cognitive industrial revolution across this entire. It'll be much faster. This is one of the things that's like a little vertigo. Much faster than the industrial revolution because of the speed that it can spread throughout the world because we have the Internet and mobile and in a globally connected world.

So when you're a Indonesia or something else, you say, okay, well, we know that the tech companies are building these things. We know that these things are possible with open source models. How do I most help my citizens? How do I most help my industry and my people participate in this and then be making those moves? And so for example, you don't say, well, I'm going to build my own supercomputer.

It's like, well, how do I kind of get the right access from the hyperscalers to good compute that helps my industry and helps my citizens? How can I nudge them to say, I want you to provide systems and services that fit my cultural values in here and make that possibly work? So I think it's just like a startup developer, you say, well, I'm not necessarily going to build my own frontier model, but I'm going to build upon these platforms that are being constructed. And that was the reason I was using mobile platform and a PC platform. I'm going to build upon the platforms being constructed for things that help my.

Harry Stebbings
Society, two company specific ones. Then we're going to do a really cool read. AI, you mentioned bytedance earlier. I'm so sorry for the base question. Should it be banned?

Is it a threat to us democracy? Think that it is an unusual threat to us democracy? Although I do think the key question is China bans western social media and other companies with it. So I think it's not an unfair thing to say, hey look, if you're banning ours, we can ban yours. I think that's the baseline of the fairness side.

Reid Hoffman
Now that being said, part of the chinese approach to these things is they view that all of their companies essentially work for their governments. Now, they think that's true of the west too. They don't realize, no, actually, in fact, we operate differently. Like Google does not work for the us government, Microsoft does not work for the us government. There's ways that are accountable by law, but they have to go through a legal process for that kind of thing.

And so given that legal process doesn't exist within China, one worries about what security vulnerabilities and other things that happens because the companies don't have the kind of autonomy that our companies have, that they have where for example, they can sue and say, no, we're not going to respond to this subpoena or this request from government because we think that's an illegal order which you can't really do in China. So that kind of thing does present a possible concern and risk. I don't have any data that suggests that they're doing anything right now on it, but it's possible. And so you want to. So you want to close down that possibility.

Now, what the us government proposed was to say, get to a form of governance that is not the chinese form of governance, that is within the western sense. Divesting is a version of that. If us TikTok Bytedance became a public company government launched on the Nasdaq or something else, that would give it the kind of governance that would say, okay, great. We understand that the governance is by kind of public rule of law, not potentially corruptible by a government that doesn't have that public rule on. That's a good place to be.

Harry Stebbings
What do you think happens? Well, I think likely, and I have no inside information here. I think Bytedance waits for the election because they presume that Trump could get bought off by investors since he's a coin operated person in his entire life, not just in his presidency. He did a great Domino's pizza out there. Have you seen that one?

Reid Hoffman
No. It's from the nineties. It's brilliant. It's really very good. Yes, but he is completely coin operated.

And so self coin operated to some degree. It's like that Churchill line. It's not insulting that he's for sale, it's that he's for sale for so cheap. Have you met him? No.

And it'd be difficult, given the harm that I think he's doing to the country and the world is. I think he's amongst the greatest ills that has made a huge negative damage in the world. Final one. And then we're going to do Reed AI, obviously, you've known Facebook and Mark for a long time. I think he's probably one of the most underrated or underappreciated people in tech.

Harry Stebbings
When you look at his cornering of the h 100 market, it's just astonishing insight. And he got killed for it in public markets. How do you think about that when you look at it now and reflect on that? There's two different questions there. Zuckerberg is one of the best metastrategists.

Reid Hoffman
I deliberately pun on meta, but meta strategists? What is the game we're playing of any technology leader on the planet? I learned from him on this. He's super good. Matter of fact, one of the things I have to do is I have to send him the speech that I just did in Perugia, because I was referring to Carthago de lendest.

And I hadn't realized that was actually one of the things he put on his t shirt and all the rest until I saw a picture recently. But he's a really great metaphor, a strategist, and I think is seriously underappreciated for that. Now, in the question of public markets, I think part of what you have to do is you have to build communication and credibility over time with public markets, where they go, okay, you haven't surprised us. You may have made a new announcement, but you've been kind of building towards it. And so they tend to react when you say, well, look, we're doing really well, but our profitability is going to go down because we're going to invest in all this stuff.

They go, ah. Like we don't understand how the process. And so that the surprise response is a negative response. I think obviously the public market should have responded differently because I think he is a great metastrategist and his turn into AI who's going to matter fundamentally here is 100% correct. I also love his brand change.

Yes. Now we're going to do very different. So I'm going to get read AI and then how do you want to do this? Do you want me to ask you, you can answer it first and then watch, or do you want to watch first? Why don't we watch first?

Just because. Then I'll both put my answer and my commentary on the read AI answer together. Here we go. Yes. What have you changed your mind on most?

Harry Stebbings
I can hand it to you and you can hit play. Absolutely. I've changed my mind on how fast generative AI is advancing. I initially thought significant breakthroughs in creative fields would take longer, but AI tools have rapidly evolved in writing, art and music. So on this one, it's funny, it's almost like you could accuse read AI of being like the wise person with the elephant because it's an AI.

Reid Hoffman
It's like what I've most changed on my honor is AI and how it's accelerating and it's like, nope, actually I haven't changed my mind on AI stuff in the last twelve months, one year. I would say that my answer to this question would be that it's almost much more of the response to AI. And I think, I'm confident that this will still happen. But, like, trying to get people to see the positive sides, like, it's like, look, most people are like, oh my God, why are we building this AI stuff? It's dangerous.

Like risk discourse. Risk discourse. Like, look, we have amazing things in front of us, and that's why it's worth navigating the risk and the slowness by which persuading journalists, academics, other people to say, hey, look, by the way, your discourse around AI is like the discourse when the printing press was launched. People would say, this spreads misinformation. You're like, okay, by the way, the printing press was a good thing.

You might have noticed. So let's think about what could possibly go right and the slowness by which they're getting to what could possibly go right. I'm. I think we just have this kind of propensity to be negative in a lot of ways. Humanity.

Harry Stebbings
Okay, so we're gonna go for the biggest misconception over the next ten years. Here we go. The biggest misconception is that AI will completely replace human jobs. In reality, AI will augment human capabilities, transforming jobs and creating new opportunities we can't even imagine yet. So I broadly agree with this one, but I do think that what people kind of presume is that with a massive increase in cognitive capability, that that will just kind of create, you know, since we're in Britain, a bunch of people on the dole.

Reid Hoffman
And actually, in fact, I think what it's doing is transforming a lot of jobs. And just as we discussed, learning how to do prompts and learning how to do it, that will be an essential tool. Like, for example, if you ask people to say, most jobs require some facility to do with reading. And so, yes, you'll have to be able to use these tools in some useful way. But I think there will be lots of new and interesting human jobs.

Harry Stebbings
What job do we not have today that do you think we will have in ten years time? Well, I think we'll have a whole swath of jobs that are in the prompt. Engineering, AI research, assistant directors. Okay, let's go for biggest business influence on me. Yeah.

Reid Hoffman
Okay. My prediction will be we'll get this one wrong, but we'll see. Okay, let's see how this goes. Because, by the way, as I told you, I hadn't listened. Can you predict this?

Yeah, I don't know actually what it will say. I have a little of zero idea, and it's one of the reasons why I'm surprised. And so, part of what we decided in doing this fun thing is I literally have not listened to any of these answers before. Right here, right now, I'd say Satya. Nadella, his leadership at Microsoft, focusing on empathy, innovation, and a growth mindset.

Read AI
Has profoundly influenced my views on leadership and culture, especially as I've watched him successfully navigate rapid technological changes while fostering an inclusive and innovative environment. It's not bad actually. I'll give it pretty good points. It was much better than I was expecting. It's better than most VC's.

Reid Hoffman
I intervened, yes, to read AI. So points to that look, Satya has been probably the thing I most learned from Satya has been how do you do cultural transformation of massive scale organizations. And he has demonstrated that that is doable and possible in ways that I don't know if anyone ever has before. How does he do? Part of the benefit is he comes to Microsoft as an outsider insider.

His whole career was through Microsoft. But he was in charge of Bing, he was in charge of Azure. He was the one who was launching the new strange projects versus the person sitting on top of office. That gave him both this kind of outsider insider perspective, which was okay, I understand what is great about Microsoft and I also understand how Microsoft needs to grow and evolve. And those two things together have made him amazing in his transformation.

And he's willing to take these really bold risks. Like for example, it's like I'm going to go put a billion dollars into a 501 C three on a partnership thing with OpenAI. He does these bets that are super smart, even though I think the vast majority of public company CEO's would never make that bet. What's the boldest bet you've made that didn't pay off? Oh, what's immediately coming to mind are some investments that didn't work out, I think.

I'm not going to call them out because it seems ungentlemanly as a partner and as a VC. But there are a couple of investments that I've made that I thought, oh, this is going to be great and huge and was completely fumbled. What did you get wrong? They're different. In one case it was the people, in another case it was the difficulty of the market.

Part of the thing that you learn as you get more experience in VC's is that sometimes markets are different. If are just wrong, like difficult. Now here's one that I got wrong initially. That will be fun to share. We were talking about bad competition being the central thing.

So I think I was one of the first couple people that Elon Musk pitched SpaceX to and I literally kind of laughed at him thinking, because by the way, to my defense, his pitch was, I'm going to be the first person to send life to Mars because I'm going to send a turtle to Mars and you're like, that's not a business. That was the pitch, right? Good. Do you have a slide, too? Exactly.

And there was a fool in the room, but the fool wasn't Elon. The fool was me. The thing that I learned from watching Elon's rocket success, pun intended, was that if an industry has had decades of technological innovation that are not reflected in the market, because the structure of the market locks in this anti innovation kind of oligarchy, it's hard because there's something that's locking it in, but if you can break it, it, it's huge. Elon is one of those people who takes the whole concrete wall down with him when he's going through it. So if someone can do that, it can be really good.

And that was an instance of a mistake because I should have said, yes, I will invest in this. And now, of course, I've updated to when I think it's somebody who could take on the structural change of a market because the technology has already been built, then I will consider investing in things. So unfair to ask, but I'm going to ask anyway. Do you think David Sachs and Keith Raboy are underselling their potential by being full time venture investors? Look, I think they're both very smart.

There's a deep value in allocating capital to the kinds of products and services and companies that could be transformations of the world. Maybe there's other things that would better, like being entrepreneurs or being CEO's or other things, but I think it's a real contribution. Keith told me I had to ask you about Airbnb the night before you made the decision. Talk to me about that two hour conversation with Keith. And how did that go down?

So obviously, Keith, super smart. He's worked for me twice, once at PayPal, once at LinkedIn. I provided him his instrumental reference for working at square and a sack of other things. I called Keith because he had worked with the founders longer and earlier, and I just literally met them a couple days before and was kind of sorting through the questions of what are the questions that a smart person might have once they've sat with this project for more than a couple of days? And have you got answers to those questions?

How do you think about it? Which is the. What I do on every investment that I do. And, you know, Keith was quite helpful to my making my decision because, you know, he's like, look, I met them, I've talked to them. They're smart.

They're first principle thinkers. They're not hiding any skeletons in the closet, you know, helpful. Yes. That is, as, you know, as an investor, extremely helpful because you're like, oh, I, I met them three days ago. It seems very exciting and I want to offer them a term sheet right now.

And so all of that was quite good, which is the reason I invested and joined the board. And I was trying to persuade Keith to get a little bit more closely involved too. And I think he was a happy investor, but wasn't. He said, he said one line to you and you said, if that's true, I'm in. Maybe it's something along the lines of that it actually has, that the marketplace demonstrates the network effects that we expect to have.

Harry Stebbings
Okay, so we're going for biggest mistake. You see, first time founders make. Oh, back to read AI. Oh, here we go. Yes.

Read AI
First time founders often don't iterate quickly enough based on customer feedback. Rapid iteration and adaptability are key to finding product market fit and achieving sustainable growth. That's interesting. Not bad. Not bad.

Reid Hoffman
It is definitely one of the major failure points because the over belief that your vision is the one perfect vision versus getting data. Now part of the thing where that's a little limited is part of what I suggest the founders is that they should always be getting, trying to get disproving data to their investment thesis on their business and on their product. But even by going around and asking smart people, like saying, what do you think of my product service? What do you think will go wrong with my business? And aggregating, that doesn't mean that everyone who gives you something is right.

Maybe most of them are irrelevant, trivial, wrong. But when you begin to hear the pattern of it, that's the way you go, oh, I need to adjust. And you might even learn that you need to adjust before you've launched your product. The other thing I see biggest difference in first and second time founders is that second time founders bake distribution into everything that they do, the way they build the cap table, the way that they craft their ICP. Yes.

Harry Stebbings
Everything is distribution centric. Yes. That would be another classic one, is distribution, especially in mobile Internet software, is more important than quality of product. Yes. Do you think then, because my worry is incumbents in a world of AI win because they have distribution advantage.

And so even if their product is worse than specialty providers who are startups. Yes. It doesn't matter if you're a medical transcription company, bundle them with Microsoft product suite. That's just going to get the contracts. Yeah.

Reid Hoffman
So look, that's always the challenge in startups. And it's one of the reasons why the Internet has been much better for entrepreneurs than mobile ecosystems, because the mobile ecosystems are controlled by solitary providers in ways that the Internet is not. And that's why we've seen a lot more generativity on the Internet than mobile ecosystems. Read AI. So we've got here, where will you be in ten years?

Okay, interesting. This is going to be a talking to read AI. Sending read AI to these 20 vc. Why can't I just get him to do it? In ten years, I'll be leading an AI driven public health initiative to predict and combat pandemics and pioneering AI education systems to reduce global inequality.

Read AI
I'll be shaping international AI ethics regulations and involved in space exploration projects, using AI to support humanities and expansion to other planets. So read AI will certainly be doing that, because I'll be sending read AI, do all those things. We're gonna be very busy. Aren't you wonderful? Like space, income inequality, let down, climate change.

Harry Stebbings
It was just one week. That's exactly. So where will you be in ten minutes? So, are you happy now? Yes.

Reid Hoffman
Part of the earlier questions of, like, I'm a student of decision making, so I'm always looking back on decisions I. I have made, and it isn't that I would necessarily remake them, but how would I learn to make decisions better in the future in everything I'm doing? And so. And that's reason I wouldn't, like. I just don't know if I'd say, well, would I make that decision differently?

Would I end up in a different life path that would be better than the one I'm in? I thought it was interesting that when Elon was interviewed, they said, like, you know, are you happy? And he said, I think most people think they want to be me, but actually they wouldn't. I thought that was a. It was a kind of harrowing moment.

Yeah, no, I. Congratulations. I think he is driven, and by the way, anyone who achieves that much amazing success is driven. And by the way, that level of drivenness is very stressful. You have to go with that stress.

And Jensen said something similar. Would you advise people to be entrepreneurs? And he was like, oh, my God, it's so hard. Yeah, I didn't love that. And he also said, we should lower.

Harry Stebbings
Our expectations because it will make us more resilient. No, no, no, keep your expectations. And by the way, I think in retrospect, he said, no, no, I'd still do it again. I think after he thought about it more, he was like, okay, no, no, no. So where do you actually want to be in ten years?

Reid Hoffman
Well, I think the part of the read AI answer that's absolutely correct is, how do I help not just industry, but society and global ecosystem realize the human amplification benefits of AI? And some of that's public policy. But how can we have a new golden era of humanity? Just as the last chapter in my book, Impromptu, my speeches in Bologna and Perugia about homotechne, we evolve ourselves through technology. How do we have that, that grand step forward is humanity.

That is what I would like to be continuing to contribute. And in ten years, maybe I'm doing that more as a thinker, as an advisor, than as a board member, investor, inventor, although maybe it's all of the above. Can I ask you a final but slightly weird one? Is there a question that you don't get asked that you think you should be asked for? What are the things that I love and have learned about the Silicon Valley approach to building the next world, our future world, and what are the things that I think Silicon Valley still needs to learn?

Harry Stebbings
If you were to answer that question, how would you answer it? So, on the first, I have learned so much by, just by the fortuity of having gone to Stanford and learned about software entrepreneurship. I never would have gone and sought out Silicon Valley. It was literally, oops. I'm a student at Stanford, and a bunch of my friends have started doing this, and I've started paying attention and said, hey, that's cool, let me go do that.

Reid Hoffman
There's a ton one every scale problem that you think of, 30% to 80% of the solution is technology. So criminal justice, economic justice, medical climate change, that having an orientation of how do we deploy technology to help that scale problem, because technology changes the possibility curve, changes the cost curve, et cetera. So how do we do that? And Silicon Valley is one of the most intense places in the world of how do we organize corporations and organizations and startups to tackle new technological problems? How do we take risk, allocate initial early capital and a seed?

How do we evaluate it, where we grow it? How do we build networks and teams around it? How do we have an entire entrepreneurial network within Silicon Valley where the coopetition of it is very important? Because both competing and cooperating. The classic kind of theory is, oh, no, no, you should compete and you shouldn't talk to each other.

It's like, no, no, you should talk to each other all the time and you should compete intensely is kind of the angle on this. And that whole approach to how do we solve problems? And, you know, the classic aphorism is, to a hammer, everything looks like a nail, but it is amazing hammer. And it works on a lot of things. Not everything, but a lot of things.

So that's what I'd say, is the things that I've learned from Silicon Valley, and obviously there's a whole bunch of entrepreneurial lessons, like, your distribution strategy for a software thing is more important than your product. And then on the things that Silicon Valley needs to learn by nature, the whole, like, hey, we're pirates, we're disruptors is like, hey, we're building this new thing. Just trust us. It's like, look, now, technology is really centrally part of the fabric of human life. You can't just have your engagement with the world be, hey, I'm going to go build something that's going to totally change your life.

And just trust us. You'll like it when we give it to you. You need to be in conversation more. You need to be in conversation more. Whether it's through the press or through direct, whether it's with government and saying, here's our theory about how the world should be, here's how we're operating, here's our intent, here's the things that we're doing.

It doesn't have to be revealing your secret product plans, but an explicit kind of sense of here is how we're trying to be in the mix of society. And these are the things that we care about so that people can be in dialogue. When they say, well, actually back this part of it. Like, for example, whether you're a phone provider or a social network, we care about what you're doing with kids, and we don't think you're being smart yet about what you're doing with kids. And we'd like you to tell us more about how you're navigating mental health issues or peer pressure.

The fact that kids bullying at school can follow them home in these things. What are you doing to help with that? Right? Because that really matters to us as an example and being in dialogue about that. We're no longer just the pirates and disruptors.

We are part of the genetics of what happens in society. And we need to take. With power comes responsibility. We need to take responsibility to that. And the minimum beginning and responsibility is dialogue.

Harry Stebbings
You are the master of social networks, and you spotted a network effect before. 99.9% of everyone in the world, everyone thinks TikTok's a social network, a paid machine. In the early days, to what extent is TikTok a social network or actually a case of very effective paid marketing? Well, it was a genius invention that came about of necessity because the chinese government didn't want to have any social networks with more than 500 followers. So how do you drop out the whole following mechanism and still get a high scale?

Reid Hoffman
People are producing content, individuals and individuals are consuming content. And how do you make that happen? The way that social networks like LinkedIn and others made this happen is through I have a graph. I have a graph of LinkedIn connections. I have a graph of followers, etcetera.

And they couldn't do it that way. They couldn't do followers all on YouTube. So what they did is they paid for so much content to be created. But then that created a scale effect in the entire thing because TikTok watches you the moment that you launch the app. How many seconds did you spend on this?

Did you swipe on this, etcetera? And it's learning about you to the next thing because it's matching you to the flow of current content in this stuff. Now, it's a social network as much as there's individuals who are creating stuff that's being consumed by other individuals, but it's not a social network in that I'm connected to my friend Harry on LinkedIn. Reid, I've loved doing this. Thank you so much for doing it in person.

Harry Stebbings
This has been such a joy to do. It has been an absolute pleasure. And I look forward to the next. But before we leave you today, we're. All trying to grow our businesses here.

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20VC: Reid Hoffman on Foundation Models: Who Wins & How Do Incumbents Respond | The Inflection AI Deal: How it Went Down | Why Trump is a Threat to Democracy | The Future of TikTok | Lessons from Sam Altman, Brian Chesky and the OpenAI Board

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1. Introduction to Foundation Models

2. The Inflection AI Deal

3. Political Insights and the Threat of Trump

4. Lessons from Tech Leaders

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