Reid Hoffman says the AI race is not a cage match

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RANA EL KALIOUBY: Reid Hoffman is one of the leading tech investors of our time, and I’m lucky to call him a mentor and a friend. He’s co-founder of LinkedIn and has backed so many influential startups. Plus, he served on the board of Microsoft for a decade. He’s recently said he’s turning his focus to Manas AI, his AI drug discovery company. With Anthropic and OpenAI on the path to going public and SpaceX surpassing a $2 trillion valuation after its IPO, I needed a check-in with Reid. So we hopped on to talk about what’s signal and what’s noise in the AI race, and so much more.

I’m Rana el Kaliouby, and this is Pioneers of AI, a podcast taking you behind the scenes of the AI revolution.

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Hi, Reid. Welcome again to Pioneers of AI.

REID HOFFMAN: My absolute pleasure.

EL KALIOUBY: It is always so great to have you on the show. It’s been a while since we last chatted, and as with everything in the AI world, there are lots of updates. So I’m excited to catch up.

HOFFMAN: Likewise.

Copy LinkWhy Reid is leaving the Microsoft board

EL KALIOUBY: I want to start with some personal updates on your end. After a decade of serving on the Microsoft board, you departed from the board.

HOFFMAN: Actually, I just said I wouldn’t stand for reelection, which means I’m on it through the end of the year. But yes.

EL KALIOUBY: OK. But you largely did that because you are going back to founder mode and focusing on Manas. Tell us more about that. I’m actually really intrigued by it.

HOFFMAN: Well, when Ujjwal, Sid, and I had been doing the work over the last couple of months, we began to see some small-molecule proposals from our AI drug discovery engine that our computational chemists were looking at and saying, “Oh my God, that’s really interesting. That could work.” And I said, “OK, I’ve really got to make sure that this thing is navigating and building, because these things really matter.”

So I’ve got to focus on this. I talked with Satya and said, “Look, it’s been a long time. I’m always a friend and an ally. I’ll continue to help even afterward, but I’d really like to spend my time more on building, on being a founder, than essentially being a governance person.” And I can still help. As a matter of fact, Satya and I were just on the phone today talking about some piece of strategy.

EL KALIOUBY: Amazing. As you reflect on the Microsoft board, is there anything that stands out? Any takeaways, reflections, or insights?

HOFFMAN: There have been a couple of things. One is obviously the LinkedIn acquisition, which is one of the epic M&A deals in history in terms of growth and impact and revenue, with higher operating margin, et cetera.

EL KALIOUBY: Also continuing to be successful, right?

HOFFMAN: Yeah.

EL KALIOUBY: LinkedIn is still thriving, and that’s not to be taken for granted.

HOFFMAN: Exactly. And then helping navigate the organization through buying GitHub, which was bought at well over revenue in terms of comparable prices. But the strategic part of it, and how that plays into the whole coding revolution now, is really key.

EL KALIOUBY: Right.

HOFFMAN: Facilitating conversations of trust between OpenAI and Microsoft — those are some fun highlights.

Copy LinkHow SpaceX is trying to become an AI company

EL KALIOUBY: Incredible. OK, I want to spend a little time on the big news in AI. So the SpaceX IPO was on June 12. It was only in February that SpaceX and xAI merged. And a big part of SpaceX’s IPO story is actually an AI strategy and an AI narrative. It seems that they want to vertically own and integrate the AI supply chain, whether it’s compute, data centers, the model, Grok, and Cursor’s acquisition, which, as we record this, was announced just 48 hours ago. I would love your take on what that all means.

HOFFMAN: Well, in a sense, SpaceX talking about itself as an AI company is somewhat honest in the sense that, well, we bought xAI, and what we’re going to do is use our market cap to try to buy our way into being an AI company. That’s essentially what it’s trying to do. So it’s not surprising that, whatever it is, X days after the IPO, they’re using their market cap to buy Cursor. And I wouldn’t be surprised if there were others as well, because SpaceX isn’t an AI company.

xAI is. As Elon himself has described, it’s a complete train wreck in its building of foundational models and other kinds of things. All the founders have left. It’s on its third restart, et cetera. So if you look at the revenue in SpaceX, it’s the idea that, oh, we’re going to be charging Anthropic a lot for compute.

EL KALIOUBY: Right.

HOFFMAN: So you’re like, “Oh, you’re a premium-priced CoreWeave. I get it,” which is not an AI company. But the reason they’re saying they’re an AI company is because they’re going to go buy a bunch of things to try to become an AI company. I think what investors are buying into, or holding on to, is that they’re going to spend a lot of equity capital on buying a bunch of AI assets and seeing if they can be cobbled together. You could almost think of it as the IAC of AI in terms of how it’s playing. So I’d say it’s TBD — watch this space. But it’s use the market cap to buy AI companies and try to buy your way into relevance.

Copy LinkHow to think about AI IPO valuations

EL KALIOUBY: Anthropic and OpenAI have also both filed for IPOs with the SEC, and both are expected to be historically giant offerings. You’re an investor in both of these companies, so my first question for you is: Do you think the order and timing of these IPOs are important in relation to each other?

HOFFMAN: I’m sure the two companies do, right? There’s definitely a lot of rivalry between them, and there’s the theory of who gets out first and whether one absorbs the capital. I don’t think it matters. I actually think there’s a lot of room for both. I think they naturally have categories they’re very strong in. There’s obviously everything that’s going on with code and its applications, and Anthropic is clearly testing the waters on expanding into design and legal and whatnot.

And OpenAI, with ChatGPT, is clearly the front-end search-Google equivalent. It is also testing the waters on other things and coming on strong. Codex is actually insufficiently talked about as a really compelling coding product. As a matter of fact, it’s kind of stunning how much it’s Claude Code and Codex. One of the questions in the SpaceX acquisition of Cursor is that Cursor seemed to have its bright-star moment some number of months ago and now seems to be fading over the horizon. So the theory that it doesn’t completely fade over the horizon is an interesting one.

But we tend to want to tell these stories as cage matches: One of them is going to win and the other one isn’t. And you’re like, well, actually, there’s a lot of room for both of them to win in an incredible way.

EL KALIOUBY: Almost every dinner conversation I’m at, the big question is, how can you make sense of the valuation of these companies? So what should my answer be when I get asked this question?

HOFFMAN: Well, think of it as a little bit like internet valuations. Some of them will turn out to be insane and go to zero, and some of them will turn out to be way too low and go a lot higher. This is what happens when you have high-growth, fast-moving tech companies, of which AI is most of it. Look at what Google became from being an internet company. Other things bombed for being too early.

So I think a number of these valuations will be like, oh yeah, you paid a lot for that and it turned into zero. But I think there will be others. For example, when you think about OpenAI and Anthropic, why should they be valued in the same trillion-dollar-company range that these others are? And the answer is, well, if you believe that AI has the impact of applying intelligence with the scale and price of electricity across everything, and these are going to be two of the major providers of that. What’s more, you can already see some of the revenue really well, and frequently the revenue comes later. In the OpenAI category, that could be advertising.

For example, Google’s early theory of revenue was, we’re going to sell enterprise servers. That didn’t work. Then it was like, oh, AdWords. Thus far, the best business model invented in human history. So if you’re like, all the valuations are crazy, you’re wrong. If you say some of the valuations are crazy, you’re right. Then the trick is which ones?

EL KALIOUBY: Which ones? Yeah. I think the other question that comes up a lot is, do we care whether these companies are profitable or not? As venture, at the moment, and maybe eventually the public markets, are we subsidizing the cost of AI and the cost of tokens? How do you make sense of that?

HOFFMAN: Well, we’re definitely subsidizing growth. A modern exemplar, speaking of trillion-dollar companies, is Amazon, which was unprofitable or barely profitable for a very long time and yet has an amazing strategic position and continues to. So it doesn’t matter if they’re profitable at IPO. It does matter that companies become profitable and eventually become seriously profitable. But part of valuations, which most people don’t appreciate, is future expected terminal value.

So you go, well, this thing is so strategically important, it’s going to exist for a very, very long time and continue to grow and have an important market position. Even if its revenues are modest or its profitability is wobbly, that still makes it a very valuable company.

EL KALIOUBY: I guess the learning, too, is you’re not always able to predict what these revenue models or business models are going to look like anyway, right?

HOFFMAN: Yes.

EL KALIOUBY: It’s going to evolve. It is evolving.

HOFFMAN: Yeah. Part of the thing is there’s some possibility that if you said there’s a 3 percent possibility it becomes an AdWords, that’s huge.

EL KALIOUBY: Right.

I’ll be right back with more of my conversation with Reid Hoffman.

Copy LinkWhat real defensibility looks like for early stage AI start-ups

All right, so let’s talk about what this all means for early-stage AI startups. Back to these IPOs and where this is going, how does this change how we think about both how we evaluate defensibility in these AI innovation ecosystems and what we should be looking for?

HOFFMAN: The change is in defensibility and in what kinds of things lead to sustaining value. People tend to be overly dramatic and say it all goes out the window, and that is certainly not the case.

EL KALIOUBY: Right.

HOFFMAN: But on the other hand, a bunch of things that used to be strong defensive modes aren’t. Part of the reason people were talking about the SaaSpocalypse is that they went, well, the previous dynamic with SaaS companies was, ultimately it cost a billion dollars to build the baseline tech that everyone would use. You chip away and eventually get an ecosystem and customer base. And then it’s very expensive for challengers to come in, because you’re continuing to grow your customer base while they have to spend a billion dollars and then get their first couple of customers.

Then you go, well, if all of a sudden it doesn’t cost a billion dollars to make one of these things, the product feature set of what’s useful to them may change radically, because individual companies may want things deeply personalized in ways they can do with the coding agents themselves.

Therefore, the economic model, which was I could have a high operating margin because switching is very expensive, becomes, I don’t want to pay you that operating margin anymore, and competitors can come in. Hence, SaaSpocalypse. Now, the reason the SaaSpocalypse is overstated, and it kind of plays to the defensive-mode question you have, is the real question is not short all SaaS. The real question is short any SaaS that’s not aggressive and driven, committed to becoming AI-native, and buy the SaaS that is. That also gives you some code to what moats might be.

There’s a bunch of standard defenses that I think will continue in the current age. Now, the interesting question is which things will be added in, and I wouldn’t be surprised if there were new kinds of moats. People have speculated: Will there be data moats? Maybe.

EL KALIOUBY: Maybe.

HOFFMAN: Especially on things that are real-time oriented, or where you can only serve the product if you have this particular data, versus training-data moats, which I tend to be a little more skeptical of. How do network effects play in? How does that work? I think there’s a set of different questions there. In some senses, brand and trust matter a whole lot more. So if you’ve established a brand and trust and gotten through the noise, how does that matter?

So I think there’s a stack of things that matter there. I do think it’s one of the things that you and I love about both being founders and investors is that when you’re throwing all the cards in the air, it takes intelligent, probability-risk-adjusted bets, working with speed, and making it happen. That’s fun.

Copy LinkWhy vertical AI needs deeper moats than a thin model wrapper

EL KALIOUBY: Yeah, that is fun. But we still believe that there is a lot of potential in vertical AI startups. Startups that are coming in with deep domain expertise to solve and reimagine workflows in, I don’t know, antiquated industries. I think of, let’s take the legal industry, for example. Three or four years ago, we saw a whole bunch of legal AI companies, and they’ve been quite successful. But then recently Anthropic just released their legal agents, essentially, which is essentially what these companies were doing.

So I don’t know if I would invest in a legal AI startup today, right? And I think that applies to a lot of these vertical industries. So that is definitely kind of a question mark.

HOFFMAN: Well, I think you have to ask a couple of questions, because if your company is just a thin wrapper on a model, sorry.

EL KALIOUBY: Eek.

HOFFMAN: Yeah. You’re basically just waiting around until the model company decides to go first party. They may still allow you to run and all the rest, and maybe you’ll switch to, oh, I’ll be using a Chinese open-source Kimi as a way of doing this, which is kind of what Cursor ended up doing off Claude code. But it’s not as good. And by the way, part of the reason these startups are so valuable, whether it’s coding or legal, is because they’re dealing in very high economic value. So if you say, well, Kimi’s almost as good, it’s 85 percent as good, in high-economic-value things, 85 percent kind of rounds to zero. So it really has to be something that is not-

EL KALIOUBY: A non-obvious problem to be solved?

HOFFMAN: Well, it has to be something where the model company can’t just tell its model, “Go close the loop on this,” learn everything about it, and then offer the product.

EL KALIOUBY: Go do this.

HOFFMAN: And learn everything about this, then just offer the product.

EL KALIOUBY: Right.

HOFFMAN: It could be that you’re integrating data sources that fundamentally aren’t really available to anybody, including the model companies. So, for example, even if Anthropic decided, “I’m going to start doing Airbnb,” it couldn’t do that.

EL KALIOUBY: Right.

HOFFMAN: So take what Sid, Ujjwal, and I are doing with Manas. It’s like, no, you can’t just go, “Now Claude, tell us about biological molecules that might actually detect, prevent, and/or cure leukemia.” It doesn’t work that way.

EL KALIOUBY: Right. Actually, this is my thesis anyway, but I’d love your take. I’m very excited about world models because I don’t see Anthropic and OpenAI and the big LLMs going into that space. They could, with enough funding, but it’s such a different play, for now anyway, which is why we’re excited about the physical AI space and the world model space.

HOFFMAN: I think the good thing about the physical model space is that there’s a whole bunch of stuff that’s pretty unique and outside of the data sets OpenAI and Anthropic are using.

EL KALIOUBY: Including getting your own data for the physical AI world, right?

HOFFMAN: Exactly. The data for the physical world, what kind of actual compute fabric you need for that, what compute fabric works in the right kind of timeframe. LLMs are still pretty bad at quote-unquote real time, right? They try to hack it in various ways. So there may be a whole bunch of stuff there that creates something important. There’s a reason a lot of smart people are doing it. It’s a good bet because it’s a new area that’s different from LLMs and could be really interesting. It’s a risk-adjusted bet.

Copy LinkHow AI fortunes could reshape start-up investing

EL KALIOUBY: Yeah, absolutely. I want to talk about the huge influx of capital that will happen with all these IPOs. When the employees of these AI companies get a windfall from the IPOs, what does that mean for early-stage investing? What does it mean for funds like ours? Will we see a whole new slew of AI start-ups in the way that the PayPal Mafia kind of created? What do you think will happen as a ripple effect?

HOFFMAN: I don’t fully know what the ripple effect is. It does tend to be that when people make a pile of money, they go into some philanthropy and some investing. One of the things that hasn’t been said as loudly as it should be about how the ecosystem of Silicon Valley got both so broad and deep is that when you had successful people, they stayed there and then turned into angel investors and advisers for the next thing. Eventually, it compounds and compounds.

When my PayPal colleagues and I came out, we were talking to each other, investing in things, starting things, etc. So that will certainly happen because it’s not just the founders of each of these companies. All the executives and everyone else tend to make a bunch of money. The really interesting question is what happens when you’re getting pitched ideas and, just to be a little fanciful, AI is pitching you its business idea, and it’s going to execute this with a whole bunch of different compute fabric.

And either you, or you plus an AI, or an AI is making the capital-allocation decisions because, by the way, compute allocations will be capital-allocation decisions. My guess is that, in that universe, there are some deeply useful things about there being firms because the firms are running competent, specialized AI with data and everything else. This is all similar to the startup landscape becoming highly variable. We now, of course, have the investing landscape changing shape too.

EL KALIOUBY: Yeah. Well, you touched on this in your conversation with Satya Nadella, the CEO of Microsoft. You talk about this idea of a hybrid human-AI organization. One question I have is: How do we decide what work gets done by humans and what work gets done by AI? And also, in this hybrid organization, how do you build things like trust, culture, mission, and values that are so important to the success of any organization?

HOFFMAN: Part of what has made capitalism so essential and so successful to humanity, to all societies, has been that the allocation-of-resources decision tends to go to the things that drive quality up, price down, etc. So the answer to how work gets allocated is, well, where does the work get done at a certain amount of quality at a low price? That being said, humans will always be, I think, central participants in this. So the question is: How do we feel that we are in a collective market game that benefits enough of us that we will all hold ourselves to this game?

And so the notion that human beings will say, “Well, okay, we’re just less effective at everything. The AIs are more effective at everything. They should do everything,” is like, well, we still have to have roles and have to participate, and so we’ll be looking for those. But I think we will create the markets that enable that.

And you mentioned legal before. I think one of the funny things is, and I don’t think they should, but I think they will, lawyers will go, “Well, if it’s law without a lawyer, it’s not law.” So we have to be there, right?

EL KALIOUBY: Yeah. I spoke at a partner event for a law firm, and I was talking about AI, obviously, which is why they invited me. But I was intrigued because I think there are lawyers who are rethinking what a law firm looks like in the first place, and they’re building it with a whole bunch of AI agents. It’s very interesting, right? They’re rethinking it from the ground up.

HOFFMAN: Exactly. And by the way, that’s what I think should happen. The notion that we, a little bit like the great cyclical, should be focused on what humanity at the center means — it just doesn’t mean historic humanity at the center. It means a good role at the center in how the future is evolving.

EL KALIOUBY: I’ll be right back after this quick break.

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Copy LinkWhat a sovereign wealth fund for AI could get right or wrong

Okay, I want to switch focus here and talk about politics. And I will timestamp this to say we’re having this conversation on June 17 because politics is also moving fast these days, right?

HOFFMAN: Or at least chaotic.

EL KALIOUBY: Yeah, chaotic.

HOFFMAN: They seem to love volatility.

EL KALIOUBY: Yes. So I want to touch on this idea of a U.S. sovereign wealth fund for AI. Anytime Bernie Sanders and President Trump seem to be agreeing even a little, I’m like, okay, this must be interesting. So I would love your take on Bernie Sanders’ proposal, this idea of a sovereign wealth fund overseen by an independent source to tax some of the largest AI companies, and then Trump’s proposal, this idea of the United States taking a stake in some select number of AI businesses. What do you think? What do you make of this?

HOFFMAN: First, I think sovereign wealth funds are a good idea. I think they’ve been executed well in a number of places in the world, and it’s one of the things the U.S. is behind on. You could look at the Singapore fund, you could look at the Norwegian fund. There are tons of examples that are good. Then I think it gets down to: How do you get the sovereign wealth fund started? How does it work? What’s in it?

I think part of the question comes down to this. I’ll put this in kind of classic American, Wild West, libertarian terms: We’re going to go steal some property from some people in order to put it in. We’re just going to appropriate X percentage. That, I think, is very alarming and destructive to the entire system.

Now, if you said something in between the two and said, OK, look, this is going to have a huge amount of economic growth. We’re going to have civil disruption because of questions around how jobs and industry change. So we’re going to do something intermediate and say, hey, companies X, Y, and Z, you have to accept investment from us at the same price you were most recently priced by the market. We’re going to invest a bunch and own a bunch, and then you can use the capital to grow your business. That’s part of the benefit of being here. And if you had some relatively equitable way, I’d prefer it wasn’t forced, to incent that to happen, then that’s more like, OK, we’ll have some economic basis for this.

Part of it is, I think there’s been a bunch of investment in Anthropic and OpenAI from a number of funds that oversee pensions, 401(k)s, and all the rest, so there’s already a certain amount of public participation in it. So those are some early reflections. But I do think sovereign wealth funds are a good thing. I’m not sure anywhere in the world we’ve made state-owned enterprises kind of equivalent functional entities. I don’t know if I’ve ever seen that. I’ve seen sovereign wealth funds work amazingly well as venture firms. But the idea of, “Oh, it’s a state-owned enterprise” — for example, utility companies just about anywhere — is kind of a problem. Anyway.

Copy LinkWhy AI safety needs principled oversight

EL KALIOUBY: Right. OK. I want to talk about AI safety. Again, at the time we recorded this conversation, Anthropic was forced to pull its Fable and Mythos models off the market over U.S. security concerns, which, by the way, Anthropic had initially raised as well. I’ve always been an advocate for thoughtful regulation of AI, even back when I was running Affectiva, and I don’t know how to feel about this one.

HOFFMAN: Maybe it’s mixed news. I think it’s broadly bad news, but there are probably some good elements to it. The bad news part of it is that it doesn’t look like there’s anything particularly principled — here’s the way we’re navigating through things, applying a kind of rule of law and predictability. It’s more like, hey, we’ve had some contentious interactions with this company anyway, so we’re going to hit them with a stick. And we’re not justifying why we’re hitting them with a stick, but not OpenAI or others, and so forth.

There are ways of doing this. They say, well, those models aren’t the same. It’s like, OK, that’s not entirely uncredible relative to the particular cybersecurity issues, although I think Anthropic was putting real energy into making sure —

EL KALIOUBY: Fixing it.

HOFFMAN: — even in their general release, this thing didn’t create any problems for key industries. So it’s a little unclear, and this kind of autocratic, willy-nilly way of applying it is very suboptimal. Now, the good part of it is, look, I think we should be paying attention to major threats — cybersecurity, bio-terrorism, et cetera — and should intervene when we need to on that. At least that’s potentially a positive case of that.

EL KALIOUBY: OK. Last couple of questions. I’m curious, what category of AI do you think is most undervalued by the market right now, and what is maybe overvalued? And what are you tracking, even if you’re not invested yet? Again, asking for a friend.

HOFFMAN: Asking for a friend. Well, as an investor in your fund, I’d say some —

EL KALIOUBY: Yeah, don’t share all the secrets here.

HOFFMAN: Yes, exactly. Look, it’s obvious that I think the biopharma stuff is pretty important. I don’t think there’s going to be room for only one, with Manas, but one of the funny things about the Manas pitch deck is: We’re an AI drug discovery factory for creating monopolies. And you’re allowed to say monopolies in your pitch deck because that’s essentially what the IP is for drugs, right? We’re not making any antitrust violations or anything else, and it’s perfectly fine for it to be discoverable. Yes, yes, this was our pitch deck.

EL KALIOUBY: Yeah, that’s so interesting.

HOFFMAN: And so I think there’s a whole bunch of different stuff there. I think one of the maybe more uncomfortable areas, but one that will be huge, is a bunch of stuff going on in defense tech, because I think we are in a time of more war and conflict. I think that area will be another one. I think the question of where AI can be embedded in something else that has a really big moat is interesting. I’ll say one thing that’s not, I don’t think, per se economic: What does AI mean for the reinvention of universities? That’s been one of the things I’ve been paying attention to.

EL KALIOUBY: Right. Oh, that’s a good one. Yeah.

HOFFMAN: I don’t think it’s an economic thing, although I do know of one for-profit university in the U.K. that’s going heavily down that path.

EL KALIOUBY: Interesting.

HOFFMAN: Anyway, those are some random comments.

Copy LinkWhy human experiences may become more valuable in an AI saturated world

EL KALIOUBY: Cool. Do you have an anti-AI thesis where, as everybody doubles down on AI, we will be craving more and more human experiences and human connections, and what that could look like, and whether AI has a role in scaling these endeavors?

HOFFMAN: I think for sure. And it goes all the way back to John Naisbitt’s Megatrends from, I think, the ’70s, which is high tech, high touch. I think for sure as we get high tech, we want more human connection in a variety of things. The question really is: What does it mean for investing and so on?

EL KALIOUBY: Right.

HOFFMAN: For example, just a couple of weeks ago, I was in Japan, and the focus on tea ceremonies and human experiences — I think there’d be a lot of desire for those kinds of things. Which of those things are interesting economic opportunities at small scale or at large scale, I think is TBD. But I think the intense demand for the human will be very high. Where does the buy-side demand match up with the supply-side pricing? That’s part of the reason why, when people are trying to think about, well, what happens when we get to an AGI universe, they say live entertainment and hospitality and so forth.

You say, OK, well, what’s the particular way to bet on that in a way that gets amplified? I don’t know. But those kinds of things — I think it’s one of the reasons why a lot of people say, ah, sports teams. No one’s ever going to want to watch robots playing basketball.

EL KALIOUBY: Yeah. My daughter, as you know, Jana is a food anthropologist, so she’s definitely on that side of the spectrum and thinking about businesses in this area. And I look at what she’s thinking about, and I’m like, these are great for humans and humanity, but I don’t know if they’re venture-scale. So I’m trying to see if the two worlds can intersect. Anyway, I still don’t have the answer yet.

HOFFMAN: Work in progress.

Copy LinkHow young people can use AI to build superagency

EL KALIOUBY: Work in progress. OK. So, last question. My kids — so Jana is 23 and Adam is 17 — are actually very different users of AI. Jana does not really use much AI. Adam uses AI for everything. I am curious what your advice would be for the young generation, not specifically about the use of AI, but also broadly how to think about purpose and agency and possibility.

HOFFMAN: Well, as you know, this is part of the reason I wrote Superagency, which is that agency is, to some degree, a mindset. I think what’s really important is that you embrace AI as part of your agency. You say, “This is part of how I learn, how I work, how I live, how I do things,” and so forth. It isn’t that I sit back and do whatever the AI tells me to do. It’s that the AI is my tool, companion, car, et cetera, as I navigate things. I think it’s really important to start iterating and doing that.

And it’s a little bit of one of the things I’ve been thinking about writing an essay on: the kind of mistakes made by college graduates booing or otherwise dissing AI. You’re like, “Look, you guys have the opportunity to be Generation AI, where you come into the workforce saying, ‘I know this a lot better than all of you. You should be hiring me to help you become AI-native organizations,'” and so forth. It should be an opportunity, not a threat.

And they say, “Well, but the entry-level jobs market’s way down.” It’s like, yeah, at the moment, it’s not really because of AI. There may be some of that, but it’s actually because of global turbulence and businesses being unable to figure out how to invest and plan. It’s because of overhiring in the pandemic and the idea that, hey, maybe remote work really does work. Then: Oh, right, remote work is pretty hard to make work.

EL KALIOUBY: Lots of AI washing.

HOFFMAN: And so it’s AI washing and all that stuff. But the point is: Embrace it for your agency. AI can do a whole bunch of amazing things by itself, but it’s not complete, and humans can add a lot of significant and important things.

EL KALIOUBY: Correct. Okay, so the advice is not just for young people, but I love this advice to have an agency mindset.

HOFFMAN: Yes.

EL KALIOUBY: Love that. That’s a great way to end our conversation, Reid. As always, such a pleasure.

HOFFMAN: Yeah, always awesome.

EL KALIOUBY: Thank you for joining us.

I always get so much out of my conversations with Reid. When there’s so much happening in the world, it’s great to have a friend and a trusted voice to help unpack it all. Thank you so much for listening. We’ll be back next week with a new episode.