Why AI will dwarf every tech revolution before it: robots, manufacturing, AR glasses from CES 2026

0:28I'm going all in. times. I think everything we've seen over the last 30 years of technology from the PC revolution to cloud computing, to the internet, mobile, all of that is going to be dwarfed in comparison to the impact that AI is going to have on society. If you're here at CES, you know that you're here for that reason. And we've got two amazing guests who are going to join us to have this debate. And additionally, I've brought my box, a box filled with all the ghosts and gadgets of Christmas past. And we're going to go through those at the end of our discussion. But here's a quick video of our guests who will be joining me today.

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1:43Our next guest leads venture capital firm General Catalyst. with$40 billion in assets in our management as of mid-year. Our aspiration as venture capital is to be the best seed firm in the world. The decisions we're making, the companies we're building, are going to impact the world for centuries to come. Ladies and gentlemen, please welcome Bob Sternfels and Hamant Taneja.

2:09All right. Gentlemen, welcome. All right, team. Let's do it. Let's do it. So we're here at CES 2026. It's really interesting to watch this conference get this new life breathed into it. We had this period during COVID when CES obviously had to take a pause. And we were wondering in Silicon Valley, hey, is anybody going to show up at CES? Is it still relevant? Do people care? And now look at this. This is one of the largest ones ever. And everybody's here. I saw Lisa from AMD, Jensen from NVIDIA, Uber, Neuro, Waymo. The change is amazing. I think maybe to start, you spent a career at McKinsey trying to accelerate change.

3:00And in venture capital, you know, literally building these businesses from the seed stage on. How do you look at the pace of innovation and change? in this past two years since ChatGPT was launched, compared to the first 30 years of our careers, we're all of a certain Gen X age. Compare the last two or three years to the 30 before it. Yeah, well, first, Jason, thanks. And it's great to be up here with you guys. And yeah, I would just say this week is amazing. I think there's over 150 ,000 folks here this week. And you talk about CES being back. I think CES is back. And that's great. And with all of these things happening, I think there's such a premium on folks from different perspectives getting together, because that's where new ideas are created.

3:53And my big hope and why we're here is when you mix and mingle with different folks, you come up with new things and the world needs new things. And what I love is you mentioned a lot of the tech leaders. What's exciting for this is I think everybody sees tech as part of the equation. And so when I look at the folks here in CES, you see not only the technology leaders, the investors, but you see folks from almost every industry vertical that are here now because they know that technology doesn't sit on the side. It's central to everything we do. And I get to your question. Look, I think we're moving at literally warp speed now.

4:29It's just night and day different. It's almost a, you know, DC, AD type of thing when you can see the change of pace. And I haven't met a CEO yet that isn't talking about how do I get my organization moving faster? It's quite frankly, less about strategy. It's more about organizational speed. Hey, Matt, how does this feel compared to our first, you know, couple of decades where companies would take two or three years to release a product? And now companies are releasing products in two or three weeks, two or three months. Yeah. So look, the world has completely changed, right? We've often said this is peak ambiguity.

5:08You have massive geopolitical change. You have an incredible amount of change around every country trying to drive strategic autonomy in different industries. And all those dynamics keep changing. Alliances, the new world order, everything. And underneath that, our tool of implementation is technology. That keeps changing, right? And so what the technologies can build today versus what the LLMs could do, let's say, two years ago, or November 22, let's say, when ChatGPT came about, is fundamentally different. So what are you building towards as to what the world's going to look like so you can have enduring value?

5:40And then what are you building with where the technologies you're using aren't going to obsolesce and destroy your value proposition over time? It's just all kinds of change. And so it's a really dynamic time. And the other thing you will see is, you know, we invested in Stripe in 2010. It became a, you know, a hundred billion dollar company, let's say 12, 13 years later. You look at Anthropic, which we're also investors in, that goes from$60 billion last year to, you know, a couple hundred billion dollars. And by the way, with good economic progress, these are not pine-the-sky valuations. They're based on actual growth of the business.

6:17Well, that goes back to your point, which is the compression of how fast value can create when code self-writes and access to distributions change. So fundamentally, it's just really exciting. And I think it's going to accelerate from here. This was one of the statistics we would look at in venture capital. Hey, how long does it take this company to get to$100 million in revenue? How long does it take to get to$1 billion in revenue? Unpack Anthropic and that journey, because this company's revenue, and you have OpenAI, Obviously, they're contemporary, trending towards$20 billion in revenue a year.

6:49Where's Anthropic at? And what's the revenue mix? Where does the revenue come from? Well, look, so Anthropic builds language models. It's got one of some of the best models out there. There's a couple of companies that are doing a good job of that. And then they've got Cloud on Top, which is, to me, the essence of transforming the engineering department of enterprise, right? And that's a killer application where everybody is now using these tools. So that business, when we invested, was doing about$880 million, which was a 10x growth from the year before. 10x year over year. 10x growth the year before.

7:21And then last year they announced it. They're growing another 10x or more. And so when you look at that, and we invested at the$60 billion valuation, assuming it's going to be like a 3x growth from there because those are staggering numbers. And it does 10x. Can't predict it. But to see adoption is so fast. And so you look at that and say, so we ended up investing at, you know, a eight, nine, $10 billion kind of run rate business at 60 billion. That's the cheapest deal that got done last year in venture capital on a financial basis. So we just have to get our head around what does scale really mean?

7:56And what, you know, are we in the business of creating what we used to think of? Like, can we create a deck of coins? Now we're talking about can we create trillion dollar companies, right? I mean, that's not a pie-in-the-sky idea with Anthropic and OpenAI and a couple others. Games changed. Scale of technology is fundamentally different in what it can do. Bob, what's behind this massive revenue ramp? Because you get to see all the incumbent businesses. You get to see the elite businesses that are growing two or three times X each year. You also get to see the ones that are struggling. and then you see these large numbers and 10x year growth, what's driving this in your mind?

8:36And is it sustainable? I mean, that's the other question. I hate to give you the classic consultant answer, but I do think it depends. And I think we're at a tipping point this year. And I'll tell you why. I think what's underpinning this 10x and 10x, you know, we work with most of the large enterprise in the world across all industry verticals. And And what we have seen is a huge uptake of leveraging these technologies, like Anthropic. We're leveraging Anthropic. And so large enterprise is using technology at a scale and rate that they haven't before. And if you look at IT spend as a percent of revenue, et cetera, all of this stuff has gone up.

9:14And I think that is propelling the 10x to 10x. The conundrum is, and it's been widely written about, realizing enterprise at scale value in non-technology companies is proving harder than people think. Got it. So in plain English, that means, hey, you've got a travel company. There's somebody deploying AI and you're watching what's happening at Tesla or Google and they're getting these phenomenal results. But maybe that legacy business is having a harder time achieving those results. I'll make it even simpler. Typical non-tech CEO might say, hey, Bob, do I listen to my CFO or my CIO right now?

9:55CFO is saying, we spent all this money. Why do we need to be the fast adopter? I'm not seeing the ROI yet. Can we pause? CIO is saying, are you freaking crazy? This is the moment that if we don't, we'll be disrupted. We think now, I will say the shining part is I think there's a path where you bring those two together as allies. And you say, yeah, but let's rethink this. Get out of pilot purgatory, really think the reorganization, all this stuff. There is a path. But I think right now, most CEOs are getting torn a bit between, do I listen to my CFO or do I listen to my CIO? And I think this is a really good jump off point, Hamant, of your strategy at General Catalyst.

10:34You and I have known each other for a long time, really a long time, decades. And you always prided yourself on being the great seed fund. We're going to get to these companies when they're $10 million in 10 people and put that first check in. But then I saw this news item go by a month ago that you raised$9 billion. And then I see you're buying companies. So are you out of the seed business and now doing random acts of private equity? What's going on here? Explain to me the strategy and general catalysts. How much time do we have? It's going to take some time. So look, I would say we very much view ourselves as a venture capital for AmeriCorps and a seed venture capital of the firm market core, because our true north for the 25 years we've been around has been meeting founders where they are.

11:20And what that means is essentially help them navigate ambiguity in the past when they're sort of beginning and the business isn't clear, all the way to figuring out how to scale in the complex markets that they go into. So everything we've done has been in that context of creating these catalysts, the flexible capital they need, the policy capabilities they need, the market access they need, and those sort of relationships globally to actually build a nearing company. So that hasn't changed. So why did we go, you know, acquire a health system in Ohio? It was a nonprofit. We worked with the attorney general, converted it.

11:57And I say this, by the way, with a great sense of responsibility, because that's a community in Akron, Ohio that we take care of. So that hospital has to continue operations in all the dimensions it takes care of with people. But we bought it to actually have a place where we can work with our founders and transform with AI, create abundance and resilience for this health system so it can take care of the people a lot better. And if we did that, then we can go do that for the other hundreds of systems across the country and be able to do that. So some of it is, that's market access. It's very hard for healthcare startups to go deploy successfully at scale in these systems.

12:34We are gonna go show how. We're gonna actually go on the ground, we'll do with them and show the world how so it can transform the health system. Your other point about sort of buying companies, we look at that as there's a lot of workforce transformation. I think Bob and I talk a lot about this. I think work fundamentally in these companies has been a change. So if you're a call center in an emerging country today, it's a declining asset value because you know it's going to be displaced with AI. So we look at that and say, well, but those are customers on the other side. If we bought that as a piece of the puzzle to work with an early stage founder to learn how to quickly accelerate adoption of AI into the call center space and serve these customers and scale a lot faster, the compressed value creation we're talking about, that is a new playbook.

13:22So this is not about trying to be PE. This is about acquiring businesses in PE that actually have declining value but have important customers that need to be served and help them get to that AI transformation that Bob's talking about faster by getting our founders in there. This is extraordinary, Bob, when you think about it, just so the audience can put their head around this. Venture capitalists used to back founders to then be the barbarians at the gate to try to take on these big industries. Now these big industries, in some cases, are in significant decline, struggling, and the venture capitalists are coming in and saying, we'll just buy the castle, open the drawbridge.

14:02We're going to buy it so that we can take our startups and accelerate, whether it's healthcare, financial services, or customer support and outsourcing, business process outsourcing. And essentially, we don't care about that business economically necessarily as much as we care about it for access to that customer base. Running McKinsey, this is a playbook that is like coming out of the future in a time capsule and saying, we're going to just upend the entire ecosystem. Yeah? Yeah. I mean, I just gave a talk at a university and was talking to some potential folks to join us. And I said, look, I'm jealous.

14:46I'm jealous of all of you because you have a lot more time to do what we do than I do. And you're doing it at a time where it's going to be a lot more exciting. Because if you just link this and hang out what I love is, and effectively, you're creating a new asset class. This is not private equity. This is about how do you transform incumbent entities into something different? Private equity typically optimizes an existing asset class at a certain scale. This is about transformation. So you think of large existing enterprise, and I think you have a choice. You have a choice of transform or die.

15:26And so there's this wonderful moment. But because of some of the incumbent advantages, I wouldn't say that it's predetermined which way you're going to go. Right. You can actually do this quite quickly. And I think you're showing the power of private capital can actually do this. So we've talked a lot about this, right? So one of the things we think about transforming a large enterprise, what do you really need? You need a few pieces. One is you need data infrastructure that can ready you for the enterprise. You need the models adapted to you. And then you actually need a new model for how the workforce is going to function because you have agents and humans.

15:58And there is a massive change management exercise. So a lot of our partnership has been about figuring out, okay, what is that new model going to be to transform these businesses? And what does that mean when you get on the ground? You look at department by department. Take HR. How do you drive transformation of healthcare and how you take care of your people? That process is horrible today. And we have a business called Transparent that goes and essentially creates abundance in that regard. It uses AI. So you have direct access agentically to all kinds of healthcare services. take yourself and then be able to be routed, whether you need a surgery or you need to have cancer therapy or mental health, and do it in a way that is seamless, cost effective, and helps enterprises take control of your cost structure.

16:41You need coding to fundamentally transform. That's what Anthropic does. There are companies working on transforming the call centers. There are companies working on transforming their sales and marketing. But then when you have these technologies in there, how are the actual people going to do their work in concert with these agentic capabilities. That is a whole new model. And, you know, you guys are inventing a talk about that because there's a lot of innovation that needs to happen in that whole sort of workforce transformation. That thing is ultimately where Rubber's going to meet the road on how quickly teams embrace it, customers embrace it, and we can actually diffuse AI into these businesses.

17:15And Bob, you've had to deal with this internally at your organization. What's the right size? And what happens when a piece of technology takes a career and takes out the first five years. What happens to an organization when you just basically gut the first five years of development? And this is why some people in the economy are looking at AI and they're scared. And they're looking at AI and saying, is this going to benefit me, my family, my kids who are graduating from school? This technology, and I think management consulting is the perfect place to look at it. tell me honestly, the first couple of years you're training up one of these really smart kids to write up reports and do analysis, that can be done with AI today perfectly, close to perfectly?

18:07Yeah. So I'll give you a couple stats first on us, then more general. 25 squared and 40 ,000 and 25 ,000. What do I mean by that? So let's look at McKinsey as a bit of an incubator. The 25 squared is we're simultaneously doing two things at the same time. So we have client-facing folks, which most of you in the audience would know and think about when you think about a McKinsey consultant. We're growing that body at 25 % next year, 25%. Unprecedented number of new hires because the work is changing. They're not doing the stuff that you talked about. We saved, we looked at it, we saved 1.5 million hours in search and synthesis last year.

18:55But we're dividending that to solve more complicated problems and do different things. You guys are probably sick of McKinsey charts out there. You know, we have agents that do this. They just gave you 2.5 million of them in the last six months. I want to get rid of charts. But the consultants are doing different things. We're adding 25 % to that body. So they're moving up the stack. They're moving up the stack and doing these more complicated problems. At the same time, though, about half our firm are non-client facing folks. We're down 25 % in that group with 10 % increase in output. And so simultaneously, and I know this is hard also particularly for folks to get, we're going to be adding and shrinking simultaneously with the two halves.

19:37And this has never happened in the history of the firm. Our model has always been synonymous that growth only occurs with total headcount growth. Now it's actually splitting. We can grow in this part, the client-facing side, and we can shrink in this part and have aggregate growth in total. And that's a new paradigm and a new dynamic. We're seeing this in venture. You and I were around for the days where you'd give a team$3 million and they would come back in 18 months, having spent it on data centers and building a team of 20 people, 30 people. Then we'd see the first version of the product 18 months later.

20:13And then now it's the 3 billion now. Yeah, it's but it's insane just how much more is getting done with less. And so do we worry about society and our industry's ability to communicate to society this change? Because if you were to tell an average business executive 10 years ago, prepare to hire 25 % more people on this side of the business and cut 25 % on this side of the business in the same 18-month period, their head would explode. What? Why? How come? It doesn't make any sense. And then young people are graduating and they're sending out 100, 200 resumes, getting no job offers. We were sitting here 10 years ago.

20:58Every graduate from a decent school was like, I have an Uber, a Coinbase, and a Google offer, which one should I take for$150K? And those offers just aren't there. So how do we communicate better as an industry? And then what's the advice to young people coming into the workforce? Yeah, look, every company, I would say Silicon Valley, but broadly in the tech industry, in the startup industry, what was it? Essentially, it looks like a C-corp with a bunch of engineers. But in a world where code self-rights, what is that next level innovation? What are these companies actually going to do? I think that's ultimately the transition we're going through in what does innovation actually mean.

21:35It's going to be less about being able to write code for that. It's much more going to be about systemically how to adopt this into the world. And capabilities, to your point about ambiguity in the opening, because we don't know about the capabilities of these technologies or how the world's shaping up, there's a lot of ambiguity. So to me, the companies that do really well and the way we guide the founders, a lot of it is become iterative. Constantly change, constantly move forward as opposed to what used to be before was become precise. Find this narrow edge, create your growth loop and go build a company.

22:07Now it's like constantly iterate. And in order to have the customers give you the license to iterate, it comes down to trust and relationships. So founders that are very good at engaging with customers, building trusting relationships, and say, hey, we're going to go figure this out together. We know how to leverage this technology, but we don't really know where it leads and what the possibilities are. But we co-create. And so the advice I always give is all about radical collaboration in this next phase. We've got to figure this out together. We're different stakeholders that all touch a system are figuring out what this means to them and then what it means in terms of the overall optimization and the transformation that we can do with it.

22:46You know, one maybe exciting part to this, because I think you framed it as you're a graduate and how do you get into the workforce and is it getting tougher? We did a little bit of work that said, what kind of skills are folks going to need in an AI-infused world from an employer's point of view? Less the startup, but you're more an at-scale enterprise. What can the models not do? And so therefore, what skills will humans play? And the work isn't done, but came back with kind of three key ideas. What can the models not do? Aspire. Set the right aspiration. Do you go to low Earth orbit? Do you go to the moon?

23:26Do you go to Mars? That's a uniquely human capability. So how do you look for the skills about aspiring and getting others to believe in the aspiration? So leadership and goal setting. Human. Human. judgment. And we've seen a lot around in this room evals, but there's no right and wrong in these models. And so how do you set the right parameters, the architecture based on firm values, based on societal norms, whatever? How do you build the skills to set what the right parameters are? And then finally, true creativity. The models are inference models. The next most likely step, How do you think about orthogonal stuff?

24:07And so some of the work we've been doing with large enterprises, if you believe in some of that, it can take you back to challenging some of your assumptions on where you look for talent. It actually means that where you went to school matters a lot less. And so do you start looking for raw intrinsics? Can you widen the base? Can you actually look at, let's take a tech background, not which university you graduated from, but what does your GitHub profile look like? Let's actually get to the content. And could that actually start meaning that a wider set of people can enter the workforce with different pathways?

24:40One of the things you said that really resonates is around creativity, because what, you know, we were going to college, it was all about learning how to solve problems really well. Right? And now in a world where we have this technology that can solve problems for us, it really is about asking the right questions. It's like going back to the Socratic dialogue, It is about creativity and who can imagine best what the world is going to look like and then leverage these technologies to go shape the world towards that, to your point about vision. And teaching our kids, you know, I get this question a lot about what do you want, how do you want your kids growing up?

25:12It's like learning how to ask the right questions versus solving how to, you know, work on hard problems. It's a very different mindset. And it is about curiosity and kind of back to being kids when you're growing up. It is about channeling your curiosity. Can we actually rethink our pedagogy in a way that we can develop this next generation to be more that than it's 8 o 'clock on Wednesday morning and I'm going to factor polynomials because I'm in seventh grade, which is what our system looks like today. Yeah, the advice I've been giving to young people is there's nobody coming for you. There is no training program.

25:46You have to make that for yourself. And do not go in through the front door with a resume. Just email the CEO of the company. and redesign their landing page and say, these are the three things that I think could be better. And I saw you speak on this podcast. I think your company's incredible. I would love to come work there. And I did this spec work. Now, people are like, why should I do free work to get a job, to prove you actually have a skill that is meaningful? You're not going to be able to get into a training program. So many folks now in corporate America, especially the people who are onboarding, people are just like, hiring somebody and training them is going to take longer than building an agent.