The AI Data Every Founder and Investor Needs Right Now (Q2 2026)

89% of all global venture capital in Q1 went to AI companies. Not 30, not 50, but 89%. Q1 alone matched the entire prior 5 quarters of AI deal value combined. On top of that, SpaceX just went public on Friday and we have quite the lineup. In addition to SpaceX shattering all IPO records, we have OpenAI and Anthropic behind it targeting trillion-dollar-plus evaluations at IPOs. We're 3 years away from a billion autonomous agents doing real economic work and about a decade away from a billion robots doing the same. Welcome back to the Agentic Podcast. I'm your host, George Bandarian, general partner at Untapped Ventures. And today's episode's a little different. I'm sharing the full State of AI and AE, autonomous economy, presentation I gave live at Boston, Toronto, and New York Tech Weeks. Recently to a virtual room of over 1,000 participants, founders, investors, all trying to make sense of where things stand right now, and more importantly, what's next? Where are things headed? And maybe what's not so obvious? So I covered the venture data on funding rounds, valuations, exits, IPOs, and then really went deep into the autonomous economy. Whether you're a founder of just figuring out what to build or an investor, figuring out where to allocate, this one's definitely for you. So let's go. So let me kick us off here. Hello and welcome everybody to our event titled The State of AI and AE, the Autonomous Economy Venture Landscape and Investment Opportunities. My name is George Bandarian. I'm the founding general partner of Untapped Ventures, and I'm so glad you're here today. And I want to welcome our entire New York Tech Week community of founders and investors. Hope you're enjoying all the great events this week. I also want to welcome our untapped community of LPs, portfolio companies, and friends from A360 and other groups. And for those of you that have been to our events before, you know that we bring all the data and stats and education along with the demos and entertainment. So what we're going to cover is quickly touch on what's happening in AI today. Some of it you'll probably be familiar with. And then I'm gonna really dive into the state of AI venture landscape here in Q2. My job is to hopefully show you what you don't know and what's coming next, which is really the autonomous economy. Once we have a shared understanding of that, I could provide some advice to founders and suggest some themes and thoughts for investors around investment opportunities. Now we have different audiences in the room today. We have founders from all stages, ideation, formation, to pre-seed, seed, Series A, and beyond.. We have all kinds of investors from angels to institutional LPs and VCs, CVCs, corporates, and many others. So I'm going to do my best to talk to and provide value to each of the different groups across this presentation. So let's dive in and talk about what's happening in AI, right? So just stating the obvious for a moment, something we all know, AI is a massive platform shift that's affecting and gonna continue to affect every aspect of our personal and professional lives. I feel like this slide doesn't do the platform shift justice because I don't think we can compare it to the platform shifts before it. Obviously this one's much bigger. Anyway, don't take my word for it. Let's hear what Jeff Bezos had to say about it recently.

AI is real and it is going to change every industry. In fact, it's a very unusual technology in that regard and that it's a horizontal enabling layer. Today we talk about AI-first companies like OpenAI and Anthropic and Mistral and so on and so on. There are so many startup companies that are AI companies of various kinds, and that's normal for this phase, but that is not the biggest impact that AI is gonna have. The biggest impact that AI is gonna have Is it is going to affect every company in the world. It is gonna make their quality go up and their productivity go up. It, it's by every company, I literally mean every company, every manufacturing company, every hotel, every consumer products company, et cetera, et cetera, et cetera. And so that is hard to fathom, but it's real. There is no doubt. We don't know how long it will take exactly. We don't know how quickly that transition will occur. It'll probably occur at different rates. In different industries, but that is very real.

Yeah, I think it's really powerful the way he puts it, right? It's gonna affect every industry. We don't know how long, but it's gonna happen. Back to what Jeff is saying, ultimately as an investor, it's a really exciting time. As a human, it's a very exciting time. If you look at how AI is being used in drug discovery and design, in material sciences to create new materials that don't exist in our natural world, in neurotech and understanding the brain and getting more out of the brain, if you will, robotics, quantum. And so let's dive into some of these areas. Just as an example, let's look at the proliferation of robots at CES this year.

The age of the humanoid robot is upon us. They are everywhere here at CES. There is one here. This booth over here has humanoids. Unitree behind us, which is known for their robot dogs, has humanoids. Engine AI has humanoids down there.

Sharpa has a ping pong playing robot over here. They are everywhere. It seems—

It's not just 1, 2, or 3 companies that add it. It's truly coming to maturity. We're gonna see them in a lot of places soon.

I love the ping pong playing robot, right? All right. So with that, let's just dive into the data, right? Let's look at the data across the AI venture landscape from funding rounds, valuations, M&As, IPOs, and take a look and see what's happening. In 2024, AI captured 36% of all global venture funding. Last year in 2025, 48%, higher by other counts. This is CV Insights counts. And then already in 2026, what we see in Q1 is that number jumped to 89%. We've never seen anything like this in venture. Or 50 years of venture, 90% of global venture funding went into AI. And that total was more effectively than the 5 prior quarters combined. So Q1 was monster. And if you look at it, obviously we know that mega rounds used to be $100 million rounds, but I guess now we need a new word, like double mega, not even double mega, it's like super mega rounds, right? where the deal sizes are in the billions and you have a number of companies raising a ton of money. So obviously it is concentrated in a few companies, but there's a lot of money pouring into this. And April was more of the same. Amazon doubled down on Anthropic with another $5 billion. X Energy rang the bell at a $9 billion valuation selling AI data center power. OpenAI made its 7th acquisition of the year, and basically half of every new unicorn since 2024 has been in AI. This thesis or this focus, the sector isn't slowing, it's just compounding. And obviously the May data, we don't have it incorporated yet, but we saw Anthropic raise their $50 billion round at close to a trillion-dollar valuation and a number of other big wins in May, including Cerebras going public. The Cerebras CEO was there at the Liquidity Summit, so I got to hear him speak and kind of talk about the journey from how they started and the unique approach they took with their chip design and architecture all the way from the early days to going public at $56 billion. And we'll talk more about public. So April, it was more of the same. May, more of the same. It's really definitely heating up. And all of the investors from the top-tier funds are betting all their chips on AI, right? And what's happening is AI startups command higher valuations at later stages, not as much at seed where we invest, it's kind of similar, but as you get into A and beyond, there's definitely a valuation premium for AI startups, which is good for many of you founders and certainly for us investing at the early stage. So that's like a little bit on funding rounds and valuations. If we look at acquisitions, again, record acquisitions. So Q1, we had 266 AI M&A deals. That's up 90% year over year and nearly double the prior quarterly record. This chart is a little deceiving. This is just Q1. So you could see that just in Q1, we've done almost as much as the prior years. And so we're on pace to have a record M&A year. And part of the reason for this is, frankly, the incumbents are scared, right? And they're striking back And buying their way into the AI era because they realize they can't compete, right? They don't have the skills, they don't have the capabilities, they don't have the products, they don't have the talent and the teams. And so they're needing to buy AI startups to be able to fill and plug holes in their portfolio and be able to compete. And so what's fascinating is this isn't just 1 or 2 or 3 buyer lanes, but we have 7 or more active buyer lanes that are creating multiple exit opportunities, right? From big tech to enterprise tech to data centers to non-tech incumbents to SaaS giants to AI labs to AI startups, everybody's buying what they need and what they can. So if we look at some of the notable acquisitions, you'll notice here Google shows up a few times, Amazon, Microsoft show up a few times. And what's interesting is that whole longer timeframe to exit is being compressed down to 2 to 7 years in many of these examples. So the exits are looking really great, and the one weak spot in all of this in venture compared to other asset classes was liquidity, right? Especially from an LP's perspective and GP's perspective was that the IPO window has been kind of closed for the last few years effectively. Last year I predicted it would open this year around this time, and once it did, it was just the floodgates would open, and we're starting to see that. We had put this chart together a couple months ago. We added the 2026. The thing to pay attention to is not the count, but the volume, and the volume is now gonna be much bigger than $2 trillion. So let's take a look at the data behind it. It's easily gonna be in excess of, it looks like $4 trillion at this point of IPO value. So if we look at it, here is Cerebras right down here. So they just went public at $56 billion a few weeks ago. Next up is SpaceX. Oh man, that's gonna be great. SpaceX was a client of mine in my prior company. We had invested in xAI that obviously got acquired by SpaceX. So they're looking to go public at around $1.75 trillion. That's gonna shatter all IPO records. And create a new kind of ceiling, if you will. And then a few months later, we have OpenAI and Anthropic set to go public for a trillion each. We'll see where they land. So we're gonna have our first kind of $3 trillion IPOs. That's $4 trillion right there of IPO value. And then of course you have not too shabby $10 to $200 billion lined up for the next 12 months. And there's probably a longer list, but these are more like the AI or AI-related. ones that I have on this slide. So that's gonna be great for liquidity, for LPs and GPs, but it's also gonna be great for then all that liquidity is gonna be able to come back into the market, whether that's LPs reinvesting in GPs like us, whether that's GPs raising new funds. That somebody was saying yesterday at the event, like in Texas or Austin alone, SpaceX, you're gonna have I forget the number. I'm gonna probably misquote it, but I think he was saying something like 100 millionaires, centimillionaires, maybe a couple billionaires as far as early SpaceX employees, early SpaceX investors. So there's gonna be a lot of new money entering and a kind of an, I think, a new dawn of company building, formation, and investment that's gonna happen. In the next 12 to 18 months as the liquidity enters the system. So it's really exciting. And so key takeaways before we move on to the next section: record funding with majority of global VC dollars going into AI, record M&A activity with AI startups being acquired in record numbers and more quickly, and we're going to see record IPOs. So checking on the stats. Okay, great. Some people were able to help me out here. 400, 400 millionaires? No, 400 centi-millionaires, 4,000 millionaires. Wow. That's amazing, right? 400 centi-millionaires and 4,000 millionaires will come out of the SpaceX IPO alone. So that's gonna be great. All right, and so moving on, let's now talk about, let's move from the data talking about really what's happened in the past and maybe what's on the near term, and let's really pan out and look at where this is all going and what the future is. And so from our vantage point, what we're seeing is that we're entering the autonomous economy. So what does that mean, AE, autonomous economy? Where we're gonna have billions of agents, right? These are the digital workers that do the work on the computer, and we're gonna have billions of robots. These are the physical workers that do work in the natural environment, and they're gonna be able to execute full work end-to-end, not assisting humans, but actually doing the work instead of the humans. And they're gonna be able to transact, right? There's a value for what they create, and they're gonna be able to have transaction securely within defined policy. So it feels like we're moving from AI to AE in many ways. And so if we drill down and define this a little bit better, for centuries, humans, we've been used to this idea that economic output, the way we measure GDP and a lot of other metrics, has been tied to human labor, right? It's been constrained by biology, our human biology, time, and headcount. This is how, if you wanted to get more done, that's what you needed. And now we're entering the autonomous economy where the primary engine of value shifts from human effort to autonomous intelligent systems. And where the biggest constraint is no longer how many people you can hire, but how much compute you have, how much compute energy and data you can access. This isn't just some efficiency upgrade, it's a fundamental, fundamental rearchitecture of the global economy. And it wasn't possible up until 6 months ago at the most, right? And this is a massive shift. I think this is a massive civilization shift that we're in the middle of. And so let's dive into it. We see 4 pillars. In blue, you have the autonomous intelligent agents, like we talked about. These are the knowledge workers. And in green, you have the robots, and when I say robots, I mean that generically. I don't mean just humanoid robots, any kind of autonomous robotic, it could be autonomous cars, drones, boats, submarines, it could be a robotic arm, it could be humanoid, any and all of that in the green. And then you have the, in purple, the secure economic infrastructure. So these are the new payment rails, could be on-chain, off-chain, but everything for identity, permissions, audit, It's really the trust layer, right? And then you, in orange, you have then the vertical and horizontal solutions bringing the blue, green, and purple to the enterprise. So the enterprise could adopt a vertical solution for healthcare or a horizontal solution for accounting or HR, for example. I don't think I really need to make the case for this. It's pretty obvious why Enterprises will adopt it going from, say, on top of a manual human process with multiple bottlenecks to a completely digital autonomous process that could work 24/7, doesn't take days off, and doesn't call in sick. So another way to think about this is this evolution of going from where we started with generative AI, which was like— me sitting in front of a chatbot and talking to the AI and the AI is there to help me, right? Human in the loop. And now where we're at is human on the loop where I could sit there with my Claude code. Let's just take a coding example, right? I could sit there with my Claude code and I could tell it what I want and then it could go run and I could have multiple agents building stuff for me. And where we're going to, we're not quite there yet, but where we're going to is human off the loop. Right, where the autonomous agent doesn't need me as the CEO or the product manager or the engineer to tell it. It's already monitoring user behavior in our app and it's seeing that there's a new cohort of users that's behaving differently. It hypothesizes that maybe this new feature is needed. It does a little test, it builds it, it does a test, it works, it rolls it into production and updates the PM and, hey, I just rolled out this new feature. Not quite there yet, but that's just one example. And you can think about that. There's a few different examples here and how that could show up as these tools and systems get better. And as we build the infrastructure layers that are missing, we'll talk about in a second, that are going to enable this autonomous future. So why is this happening now? If we look at the data that validates the timing, on the left you have the growth in the data center power. On the right, you have the growth in the agents, a 43% CAGR that we're in the middle of. Robotics, if we just look at robotics alone, it's having its record fundraising last year, and that's continuing into this year. So let me play a video that maybe helps put some of this together, especially on the more robotic side of things. So Let me start this one. This one doesn't have audio. I turned the volume down a little bit, so hopefully you can hear me okay. Yeah, so I mean, what we just saw was different kinds of robots in the warehouse. Now we're looking at different kinds of autonomous cars from tractors here doing the farming, autonomous actual farms, 3D printing. So here we have a 3D-printed house in 24 hours, which is pretty unbelievable. Of course, Elon's bringing us the Robotaxi, and now, you know, we already have Waymo, but we're gonna have autonomous trucks, automated stores with no employees. And again, half the stuff I'm showing is already out there, right? Like, this is the Amazon Go store. That already exists. Drone deliveries, automated kiosks instead of cashiers, robotic surgery, more precise than even the most skilled doctors. I think the real question here is how fast will things change, right? And I love this where in 1900, there was all horses and one car. And then in a short 13 years later, just one horse and the rest all cars. And again, that was when things moved slowly, right? In 1900, things moved really slowly, and we're at a time where things move a lot more quickly now. And so all of these things are happening, and they're happening all at once. And so I think the future is gonna be truly amazing with the advent of AI and robotics. And so hopefully that helps, because picture tells a thousand words. I think a video tells a thousand pictures. And so that gives us a little bit of a peek across different industries, what's happening and what this is going to look like at scale. But what— the way we think about the AE value stack is similar to your typical AI stack, but a little different. And this is really more around the AE stack where you have the intelligence and compute substrate at the bottom. This is kind of the enabling infrastructure, the models, the robots, the compute, the data centers. It's the macro enabler providing all the tailwinds. And then on top of that, you have the agent runtime and orchestration, planning, tool calling, memory, workflow graphs, sandboxes, right? You have on top of that autonomy control plane. This is the brains that manages swarms of agents and robots, identity, permissions, policy, evals, audit, rollback, kill switch. And then you have the machine workforce layer, right? Referring to both agents and robots as machines. I think of that like our new HR directory. We used to have— we used to just manage people, but now we need to manage agents and robots, and we need to know what tasks they can do and have task marketplaces and workflows, workforce scheduling to know what robots are scheduling and out there, and a fleet management and a skills registry. And on top of that, you have the autonomous experiences, the value capture layer at the enterprise, automating back office, front office. every vertical and horizontal use case like we talked about. To recap, the primary labor force is moving from humans to agents and robots. The value metric is moving from time to outcomes, and the scaling constraint is changing from hiring people to hiring energy and compute. And so we're all in on this. We've repositioned ourselves that we don't invest in AI-native startups anymore. We invest in AE-native startups. And so I think the way to think about this is, okay, what does it look like if we have a billion agents and a billion robots? And the example that I give is this, right? So let's just say I'm a company, I have some retail operations, and an agent is monitoring and it notices there's some issue in one of our stores or one of our facilities somewhere. There's some supply chain breakage or issue. It puts a post out, whatever that might look like, and there's some robots nearby. The robots pick it up, apply for the job, apply for the gig, if you will. The agent picks a robot, I don't know, based on reviews, proximity, price, whatever. The robot goes, fixes the issue. Obviously the robot has a camera on its head, takes a photo, provides the proof to the agent. The agent validates it and settles the payment. And all of that was done without a human involved on either side of those two companies, right? So there's two companies involved in that transaction, and the work was done and the payment was made without a human involved. And so I don't think that's science fiction. I think this is an inevitable conclusion of the technology that we see and the direction we're going. And so the trillion-dollar question becomes when, right? Especially as an investor. And the reality is it's not too far away. The billion agents, we're going to get there by 2028. So that's only in a couple of years. And then obviously with the robots, atoms are heavy, manufacturing supply chains take a little while. So it's just going to take a while to literally have a billion robotic machines. 2040s is probably the conservative forecast. If we look at some of the data behind that chart I was just showing, certainly sometime before there. If you ask Elon, we're going to get there way sooner than that. So I think the idea is focus, at least for us, focusing on the brains, the agents today, and the bodies, the robots tomorrow. Now one thing that happens when I give this presentation is the highly empathetic people in the audience start to get nervous and concerned about all the people, right? Because it is a concern based on a lot of estimates of 50 to 80% of the current labor workforce is going to be automated, what happens? And so I think it deserves a real answer and not hand-waving. So I just want to spend a couple of minutes on it. Some of you may know me. For those of you that don't, my personal kind of MTP, massively transformative purpose, which is also the firm's MTP, is really around this concept of fostering these innovations in AI that help us reach our untapped human potential. That's where the name Untapped Ventures comes from. People think it's untapped founders, markets, technologies. It's all of that. It's a multi-entrendre, but the original, the origin story is really around, I was always fascinated that we only use 13% of our brain and the idea that like from a self-development, personal development standpoint, how do we help people live 100% of their capabilities and the best life that they can possibly. So anyway, that's our MTP and we have some moonshots around raising a bunch of funds and helping impact the lives and uplifting the lives of a billion people across the planet and in the process building a great enduring legacy venture brand. But anyway, I bring all that up because the human question is a very important one and very near and dear to my heart. And so we spend a lot of time thinking about this. And so I, A, I'm gonna answer this on multiple levels. So answer A is we're gonna create new categories, right? As these agents and robots come, we're gonna have new titles and new roles and have a new kind of jobs that require like agent supervisors and robot field techs. Although you could argue robots should fix robots and I'm sure they will, but for some period of time, we're gonna need humans fixing robots as well. Second answer is we don't know all the answers, but we have been through this before. We've seen this movie before as we went from 97% agricultural kind of population civilization to industrial to services and now going to autonomous. Every time we figured it out, and I believe in America and I believe in our innovation mindset, and I believe we'll figure it out. Now, one thing that is gonna be different this time is that it's gonna happen a lot quicker. So there in the other transitions, there was decades to figure this out. This is gonna happen a lot quicker. And so there is gonna be some years of hurt, pain in there. And I think the other thing is that the governments have a responsibility too, right? And so whether it's something like UBI, universal basic income, the government's gonna have some responsibility in playing an active role and helping smooth this out. I have a lot of VC role models that I look up to. Vinod is one of them. So let's hear what Vinod had to say about this.

I think each country will do things differently. Starting in about 2030, 80%—

4 years.

4 years away. 80% of all jobs, so 2/3 of all jobs will be capable of being done by an AI. But what happens when all labor is free? The abundance of goods and services will be very large. Prices will be very low. So I would suspect by 2040, $30,000 will buy, and maybe $10,000 will buy much more than you can buy if you have a $100,000 income today. So the level of income you need in a deflationary economy will be very different. Interesting.

So you think it'll cost less for just lifestyle?

Look, all education should be free. All—

Which means colleges, goodbye?

It's a real question. It'll take longer because people like institutions and the notion of institutions. But you won't need a college to get an engineering degree. You won't even need the engineering degree except if your passion is learning. All healthcare, healthcare except interventional procedures like heart surgery will be near-free. Labor, whether you're talking about farm workers or assembly line workers or retail workers or accountants, that'll be all free.

Wow. Really profound predictions there by Vinod and this idea of the deflationary trend of as this intelligence pervades and exponentially increases everything becoming free or near free. So definitely something to keep in mind there. Now in closing, a good friend of mine, Peter Diamandis, has this great quote that I love. The best way to help a billion— the best way to become a billionaire is to help a billion people. And so now I've come up with my own version of this, and I'm now quoting, the best way to become a billionaire is to help a billion agents and robots, right? As we wrap up this section, what I want you to consider is how can you embrace the autonomous economy to, depending on what your role is, if you're a founder or an investor, but to increase your margins, disrupt your market, make great investments. So that's the core content here today. We went through the stats and then we talked about the autonomous economy. So I just want to end with some advice to founders and then some advice to investors, and then we'll open it up to Q&A. We should have a good 10, 15 minutes for Q&A. So if you haven't dropped a— if you have a question, feel free to drop it. Take a look at what's on there. If you see anything really interesting you want me to answer, feel free to upvote and I'll start with the ones that have the most upvotes. But my advice to founders is, and again, this should be obvious for any good AI founders, you should already be on cloud and using it to the maximum. And I think Anthropic is winning the race now, beating OpenAI and others for a good reason. And it's been a good part of that is that they focused on enterprise and business and they've built the most complete kind of for-business AI product suite where one subscription kind of gets you more or less everything you see here and you could really do a lot with it. And so then again, as a founder, you want to move to an org chart that looks something like this where you might have your two co-founders and then you have your chief agent. And you have a bunch of agents, managers, and agents in other areas. I'm not suggesting you shouldn't hire. The one-person unicorn idea sounds nice, but I think in reality, if you're gonna build anything meaningful, you're gonna need lots of humans. But the idea that you should certainly have over time 10 to 1 or more agents to human ratio, right? And ultimately you have to understand what we VCs are looking for. And so, As we discussed, we're entering the autonomous economy, so please no more copilots, that phase is done. What agents and robots are you building that could actually do the work, right? We want to invest in startups that have durable defensibility and moats, like not just another me too, and also not something that, you know, as cloud and ChatGPT, as OpenAI and Anthropic go wider and deeper with their solutions, like they did recently, announcing that they're going into health and announcing the legal, right? They're— it's like the internet and what we saw with Facebook and Google, where one new product announcement puts dozens of startups out of business. And we've talked about this thin layer, right? It can't be just a thin veneer layer on top of a model. There's got to be some real defensibility and moats there. What's your path to $100 million and even $1 billion of ARR? Do you have a clear line of sight of that you're going after a very large TAM, something that is something that everybody needs and that it could become a really great generational company with winner takes all or winner takes most kind of dynamics. And that $1 billion used to be a big outcome in VC, right? We used to underwrite to $1 billion, but that's not the case for a lot of VCs anymore. It's billion dollars is like a minimum kind of scenario. We're looking for 10 to 100 billion. And now with these trillion-dollar outcomes, how can this be a T, not a B, right? We're looking for a trillion-dollar company. In real estate, it's all about location, but in VC, it's all about team, right? So why you? Why your team? Why do you have the right to win? What's the unfair advantage? All right, shifting gears now. We're talking to the founders in the room. Now let's talk to the investors in the room. So let's talk about like investment opportunities and This is not financial advice, disclaimer, not a financial advisor, but when I talk to LP groups, I talk about as you're looking to invest in AI, you have to cover the 3-layer stack, right? So you have to have the public markets angle and having a good idea there. And we've seen obviously NVIDIA's done great the last few years. We've had the Micron kind of run up recently. And so obviously you want to be betting in the public market stocks that are related to AI and capturing the AI tailwinds or driving them. Then there's been a lot of money to be made the last few years with the late-stage pre-IPO companies, right? So if you were buying those secondaries of SpaceX, OpenAI, Anthropic lately, Databricks, Cerebras, and others as they're gonna go public, those are good. Those are opportunity to buy $10 million and 2 to 3x that in a matter of a short window. And then you have the early stage, right? That's where the real asymmetry has migrated. And the late stage stuff has gotten really competitive, but anyone looking for not just 10x, but 100x to 1,000x outcomes, obviously that's in the beginning, coming in as early as formation, seed, and that's where we play, right? But in that case, the selection and access is what decides everything. And so unless you have unique access and some sort of a sourcing flywheel and a process to diligence hundreds of deals, then a smart LP move has been proven out to be to back specialized AI funds and then use co-invest rights to concentrate and co-invest on the breakouts, right? So that's like a strategy to think about all 3 layers. And so if we think about venture fund math at the seed stage, the power law is in effect here. So in a, for example, in a $50 million fund, and again, I have a bunch of assumptions. I won't go into all the details, but the idea here is, and this is what we were talking about, a billion-dollar outcome is nice. That's going to 1x on, on, on kind of a fund return. A $10 billion is a 6x and a $50 billion is a 30x, right? So as an LP, If you invest in a fund, you put $1 million in, you're looking at, can I get $6 million to $30 million back as they make diversified investments, right? As you might guess, this is similar to how our kind of fund 2 model is shaped. And then you want to build your sourcing strategy, right? So how can you be present at all the AI events, the AI groups, the accelerator demo days, and all of that? And so again, I won't spend a lot of time. This is our sourcing flywheel, which is all based on our inbound, right? We have our podcast, our thought leadership, our content, or this today, right? Events like this, educating the market. And then we have our outbound and we have our partners. And so just to wrap up this section on LPs, like I said, if you're looking to invest in early stage, you don't have all the deal flow, a really good idea is to invest in an AI fund, find a manager, you like and that you believe in, that has a community that you could actually be part— participate and learn, not just get quarterly and annual financial statements, get access to their deal flow and be able to co-invest. And all of that is available with us. In Fund 1, we did, I think, 7 co-invests so far, and we plan to do another 10 in Fund 2. And we have a thriving community. That's probably one of our big differentiators. And I know some of our LPs are on the line here today. We have over 100 happy LPs representing all kinds of communities, all kinds of businesses, I should say, and some very prestigious communities like the logos on top. And we get together every month. We have a 90-minute investor mastermind where we connect on networking and we talk about— I update on sourcing and diligence and really circulate and surface asks to our LPs, and every time I do, 3 to 5 hands go up about how they could help us and our portfolio companies by becoming customers, by, by becoming subject matter experts or advisors. And we do a lot of cool, fun events in person. We just had our annual general meeting in LA with 100 people. You could see that photo there. So anyway, a little bit about us and what we're up to at The Fund as We're bringing Fund 2 to market this year. Okay, so I'm done with the core content. So key takeaways and next steps. So hopefully I've inspired you to do as Neo did in The Matrix and take the red pill, go all in, no matter if you're an investor, if you're a founder, even if you're an AI founder, just take the red pill, go all in. One of my favorite shows growing up was The A-Team. So you want to build your AI team here., right, of experts, whether again as a founder or an investor. And obviously there's a gold rush happening in AI. Not everything will turn into gold. There's gonna be plenty of losers, but get in the game. And if I can help in any way, let me know. So like I said, we take pride in our Untapped community and we have so many different members of the different ecosystems or the different parts of the ecosystem today. So let me just kind of do some callouts, right? So If you're a founder raising a pre-seed or seed round and you feel like, hey, I'm building an autonomous economy, or even if it's not exactly that, but you think you have something great and you're raising a round, pitch us, please. We'd love to hear from you. If you're an angel or an LP and you're interested in learning more about Fund 2, I would love to chat with you personally. If you're a fellow VC and you want to partner and share deal flow, you could chat with Tripp. He's based in SF. If you like our vibe and you like what we're doing and you want to intern with us for the summer or after, we have an amazing 4-month internship program and you could apply to that and Shanth runs that program. And then finally, like I said, I'm incubating one AI company this year in the autonomous economy. So I'm looking for one strong technical founder, or it could be two of you already, but with a sharp idea, I'll help build it and scale it and exit it. And my role can range anything from co-founder and executive chairman or whatever, down to advisor or whatever, but I want to find the right opportunity to help incubate one company. This is not an accelerator, it's not an incubator, it's not a cohort. I'm looking at one thing to do in my excess time, which there isn't a lot of, but I've carved out enough time because I think it is important to do that. Okay, so Cassandra asks, for early-stage companies building that verified trust and identity layer, the one AI agents will have to route through before they can act on someone's behalf, what does a fundable thesis look like to you right now? I think what you're asking is, so obviously given what I presented, that fits, the thesis fits. So then what makes that fundable? I think what makes it fundable is you having validated that you've built the right thing for the right person and it's something that they want to buy, right? And so I think the early customer traction is what's important on that one, right? Building the product, getting a couple design partners, obviously, or hopefully getting a few of those design partners to convert into paying customers and be early referenceable clients. that would really be strong support for why this is a really fundable startup. Okay, so Philip asks, can AI make humans more valuable instead of replacing them? My bet is that the more we automate, the more human connection becomes the scarce premium thing. Do you see room in the autonomous economy for companies where the human is the whole point? Okay, awesome. Thank you so much for bringing that up. Again, I did the important human part, And I forgot the key kicker there. And I, I just think I need to add a slide there 'cause every time I do this presentation, I forget the center, which is yes, absolutely exactly what you said, which is that as this happens, the, in addition to all the things that I said, I think that there's gonna be some winners, some Bs or Ts, right? Billion-dollar or trillion-dollar outcomes that are gonna be focused on What do we do with this 50 to 80% of people that have now lost their job? And it's not gonna be the old upskilling, reskilling answer in prior HR tech kind of mentality. This is not a upskilling, reskilling answer, right? This is now gonna give rise to, again, as civilization changes, as the economy and civilization changes, this concept of Monday through Friday, work 9 to 5 or whatever is gonna change if the cost of things have come down, if agents and robots are doing work. And so that concept was relatively new, right? Like that was the industrial era for the most part, not necessarily prior to that. As humans, we've had different forms of living and surviving and enjoying and happiness. And it always hasn't been this structure of Monday through Friday, 9 to 5 work. So I think that's one of the things that could change, but I think that startups that are focused on solving that issue and figuring out, I personally have a thesis, maybe a hope around something around purpose and passion, right? It's not just helping the truck drivers that lost their jobs because now all the trucks are automated in an autonomous auto grid. It's not just about reskilling that truck driver, it's really Hey, what's helping people discover their purpose and why are they on this planet and what are their passions and how they could live that? And for a cohort of these truck drivers, one could be that he loves hiking and he starts taking people on nature hikes and that's what he's doing every day. And he loves his life. He hated driving the truck. He loves doing these nature trails. Every time he takes 10 to 15 people with him every day. And he makes good money and he's very happy doing that, much more fulfilled being in nature and showing people around whatever the local national park is by his house that he takes people to, right? So to me, that would be a great example of this actually being better. And if somebody could figure out how to do that at scale for everybody, I think that's gonna be interesting. So I do think there's gonna be some winners that come out of that. Sorry, I kind of spent a lot of time on that question because like I said, it's one that I'm very passionate about and I forgot to hit it early on. So thank you for that question. Andrew says, where do you stand on companies, founders building for new categories that don't exist yet? Yeah, so that was a, that was a nice alley-oop question to me. That, that's exactly what we're looking for, right? We're not looking, what we don't want is for you to be in a category that is already has a startup map. And already has a bunch of logos in that box, right? Ideally, there isn't a box yet, and ideally, there isn't even a startup map for what you're doing. The more new and different it is, the more interesting it is to us. The argument there is obviously that if you're, if there already is a map, then you're already a little late. There's already well-funded startups ahead of you. Your chance of winning goes down.. And in that case, if you're going to come from way behind or even materially behind, again, what is your advantage? What do you know that nobody else knows? What data do you have access to that they don't? What— why are you going to come and be able to beat people that are ahead of you, theoretically have stronger teams than you, and things of that nature? All right. And there you have it, the full Q2 2026 state of AI and AE, autonomous economy. The data is clear, the window is open. The question is whether you move now or watch it happen. So if this episode resonated with you, just make sure to subscribe to the Agentic Podcast so you don't miss future conversations. And if you're a founder building the autonomous economy, especially at pre-seed or seed, we'd love to hear from you. We back AE-native founders with million-dollar first checks and work closely to help you build toward this future. You can learn more about Untapped Ventures and explore our thesis and pitch us at untapped.ventures. And if you found this episode valuable, share it with the founder, investor, or operator who needs to hear about the data right now. That's it for now. Thanks so much for listening, and we'll catch you in the next episode.