At HumanX 2025, Ryan sat down with HumanX CEO Stefan Weitz and Crunchbase CEO Jager McConnell to talk about where the money is in the AI space, where most enterprise AI strategies fall short, how companies can build business models when AI tech is evolving so quickly, and why this is AI’s microservices moment.
2024 was a defining year for AI investment. Read the HumanX/Crunchbase report.
You can learn more about HumanX or register for next year’s event, April 7-9, 2026 in San Francisco.
Follow Stefan on LinkedIn.
Follow Jager on LinkedIn.
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Ryan Donovan Welcome, everyone, to the Stack Overflow Podcast, a place to talk all things software and technology. Today, I am here at the HumanX Conference with some very special guests to talk about the AI landscape, who's succeeding, who's going to be acquired, where the money is. My guests today are Stefan Weitz, CEO of the HumanX Conference, and Jager McConnell, CEO of Crunchbase. So welcome to the show, gentlemen.
Jager McConnell Great to be here.
Stefan Weitz Thank you, thank you.
RD So you all were kind enough to share a report that you put together before this about where the money is, who's funding who in the AI space. Can you talk about what drove that report and what you're sort of most interested about?
SW Sure, I'll start at least. We at HumanX have really focused on trying to provide actionable information to our attendees, to our sponsors, to our speakers, and that was the whole initial idea, was how do you help enterprises navigate their way through this AI forest and do it in a way with confidence and conviction, and that's missing right now for most of the enterprises we've spoken with. They don't have a great AI strategy, they've got maybe an idea or 25. I've talked to one company that had 230 pilot projects running at the same time. Not kidding– 230. I'm like, “How much are you spending?” You don’t want to know. So part of that mission is to get data that can drive decision making. And we did some work with Harris, the polling company, great company, and that was all about the kind of enterprise AI landscape, but really with Crunchbase and the technology they debuted I guess a few weeks ago now or a few months ago. When we heard, we got the inside scoop on this that this was coming out, we said, “Holy smokes. That's actually really interesting,” because now– well, I'll let you talk about it– but basically you're able to, in some ways, predict the future. It's almost precogs, if you're a big sci-fi fan, for companies, and so that could be a really useful signal for a lot of these enterprises who are looking at vendors and looking at companies and saying, “Who's one I should partner with?” So we’re very excited about it.
JM And the only thing I would add is, we have about 80 million people coming to Crunchbase. Why they come to us is usually trying to ask a question– who's going to get funding next? Do they have money? Are they growing? Are they going to get acquired? And rather than just giving them the historical data, we thought we have more data than anyone, so let's go and take all that data and help predict the future, what's going to happen next. And then when you layer that on to a conference like HumanX and say, “Look, which of these companies are going to get acquired? What companies are going to raise funding?” it changes the dynamic a little bit. It is like, “Well, if I'm an investor, maybe I should start with my time at the companies that are going to be raising money soon, rather than just using a single point of data like how long has it been since the last funding round.”
RD And that was the sort of marques stat for me, was that 30% of the companies here are merger and acquisition targets. It's an eye-opening stat, but we've seen a lot of mergers and acquisitions in the past couple years, some big ones with Salesforce buying Slack, Splunk getting purchased.
SW Well, even in the AI space. It wasn't an acquisition, but Inflection and Microsoft. That wasn't an acquisition, but it was some structure like that. Even in the AI space, you're seeing rollups happening already. There's a lot of great ideas, incredible talent, and probably too many companies right now out there chasing, and many in some flavor of the same thing. And so consolidation's natural in an early market. We've seen it over and over again in the internet and early internet days, so not surprising, but I think what's probably surprising is just the time compression. So AI's been around for a long time obviously, in different flavors, but the current cycle is two and a half, three years old maybe. And so I think that's the thing that surprised me the most, was that number of companies that could be rolled up within a year, a year and a half of instantiation, and that's what's really surprising to me.
JM And then we see a lot of these large corp dev departments at these large companies hunting desperately on Crunchbase trying to figure out which are the ones that they should acquire or not. And I think it gets back to something that was said earlier, that these companies are desperate to figure out what innovation they should have internally. And they're just too big, it's not on their roadmap. They've got roadmaps that are out three years, and that's just too slow. So they see this little point of ingenuity, this amazing little piece, and they want to bring it right in. And that's why this M&A is happening in sort of increasing volume.
RD And startups are very good at focusing on that one thing, just solving this one problem really well, and some big company says, “Oh, that could help me. I'll get that. Plug that in. We're good to go.”
SW It's funny, and we don't have to go down this rabbit hole, but that is both a blessing and a curse. So I can tell you a number of enterprises I've spoken with. They took that approach of, “Well, that's interesting. Maybe we should try that,” which is counter to how any MBA or even Business 101 student takes in undergrad. You always begin with your business case. What actually moves my business? Where can I save money? Where can I increase my revenue? Those are the things that matter. And then after you define your business case and define the use cases that'll move your business forward, then you go find a technology. I think what's happening right now is because of just the somewhat frothy nature of the industry, it's almost going backwards. It's like, “I saw this cool tool for HR management, and I'm going to go do that,” when that may be important to your business, but it could also be the 15th thing in your list if you're being honest with yourself. So it's a fascinating dynamic we're seeing right now.
RD And AI is the new hotness and it's the place that's getting all the VC money, and as somebody who's been through a couple bubbles, anytime there's increasing–
SW I think all of us have, haven't we? We all look the same age and we've all been through this a few times. UniFi WiFi anyone? That was me. That was 18 months of the rocketship of my life.
RD So anytime I see increasing VC money in a place I'm like, “Oh, is that a bubble or is this going to be something that pans out?”
SW Well, I mean, I'll give you my personal, I'd love to hear from you too, but I gave a talk opening morning on this– is it a bubble or is it a revolution? And I think the answer is yes, it's both. It is a bubble to a certain extent, but even the most popular bubbles of the past several hundred years, whether it's tulips or even the automotive industry or the internet itself, even though they were bubbles– this is a great stat that I got from primary ventures– in the turn of the 1900’s, there were 2,000 car companies and over 3,000 unique car models. So as an investor, if you're there in 1904 and you're looking at this, would you have picked Ford and Mercedes? Maybe. But most likely you didn't. Most likely you picked Edsel and something else. And so it doesn't change the fact that because of all that investment, and think of railways as the same way, because of all that investment, it created long-lasting financial, societal impacts. And so I think that's the wrong question in some cases– we're in a bubble or not. We probably are, but all that means is you have so much capital flowing in, which will leave long-term tracks for the industry to grow and prosper. That's my opinion.
JM I agree with that logic. The only thing I might add, and I don't know if you agree with this, is that AI is positioned to continuously disrupt itself. It's going to be a constant disruption. And if that's true, then all of the dollars that are going to companies today are at risk because those companies may be disrupted by some new technology that's just around the corner. And I don't think that's been true as clear as it is now. With SaaS as an example, it's hard to make the better CRM at some point. But in AI, you saw DeepSeek kind of go and disrupt things pretty quickly. With the startups that are here, what is the proprietary thing? What is the thing that's going to differentiate them in perpetuity? And I think that's a big question mark, and that leads me to think it's a bubble, because the dollars that you're investing in often may be in companies that may have a lot of trouble in the future. And in the end state, if we're in a place where, let's say, 10 years from now you can just ask an AI to go and just build this thing and build it better than we can imagine and it just does it, how do you stay relevant?
RD How do you compete with that?
JM Exactly. How do you build a business model that wins in that?
RD It is interesting, I think AI is a greenfield market so everybody's like, “How do I get the one that rises out of it?” I talked to somebody in VC yesterday who said, “I don't think it's a bubble. This is just the model for VC. You throw money and you see who bubbles up.” Do you think the sort of merger and acquisition is a good sign for the market? Is it a sign of maturing or is it a sign of people getting soft exits?
JM I'm in soft exit camp myself.
SW I think you're probably right.
JM I think it's like, “Let's take the money when we can because we don't know what tomorrow's going to bring.” And there's obviously great exits that are happening. I think investors are saying, “I'm happy to take that win,” especially after many years of losses. Many investors didn't see an exit, didn't see the return in 2022-2021. I mean, they were making investments then, but they weren't seeing the exits, especially 2022 into 2023. So now they see a 80x return, “I'll just take that, thank you.” That's my impression.
SW Well, an 80x, I would take that all that long too. As an investor, yes, I'll take that. I don't care what kind of company it is. I think that's probably right. I'm trying to think if I have any counterfactuals on that one. It’s probably right. It probably is. I mean, there's certainly ones that are doing it for strategic reasons and that makes a ton of sense. And I was talking to one company, I won’t name that company, but they just got acquired recently and I said, “Are you excited about this acquisition?” And he is like, “It's a good outcome, but really,” and this may be just talking points from his PR person, but he was really excited for what this new company who acquired him, what distribution and expansion opportunities it can provide. So that's the one thing. I think you are in, to a certain extent, a sea of sameness. Not that these companies are the same, but it's so noisy. I don't know how many, there's 300 newsletters I think out there for AI or something like that. I'm sure it's more than that, honestly, and most of them are just linkmalls to someone else's content. So I don't know how any normal human being without being an AI could actually figure out which companies could solve their needs. So I think there is this just cacophony out there, and so to break through and grab attention is difficult and in most cases will not happen. And so going and partnering up with somebody, whether it's a soft exit or not, hopefully would allow you to kind of create longer, bigger value because you can be seen by more people at that point. But you're probably right though, most soft exit.
RD There's a lot of pieces to the AI stack. I talked to somebody a year ago or so that said things like the inference stack is going to commoditize pretty quickly. Do you think there's things like that, foundation models, inference stack, whatever, that's there's going to be the sort of default choice that bubbles up?
JM I feel like what's going to drive at least the next five years of customer action is going to be who do I trust, and that's especially at those foundational layers. So I think that's what stickiness looks like in this world. And even if there is a new disruption, do I trust it? That's immediately what happened around DeepSeek. It was like, “Oh, well, it's disrupted. It's cheaper. It's so much better. Oh, but I don't trust it. So now I'm going to go back and I'll pay more for the other model.” I think that's going to be a repeatable thing.
SW It's funny, I agree and I think it's a relatively western viewpoint. So for example, the reason I'm so fascinated by things like DeepSeek or Monos and everything else is not so much for J.P. Morgan using it. They're not going to, to your point, there's no chance. Even if it's open source, not happening. I mean, maybe they will, Terah Lyons is here somewhere, but I think she'll probably say no. What's going to happen though, I think, is those models, just like payments in the early 2000s, late ‘90s, Africa jumped so far ahead of the western world in payments because of necessity. They didn't have high speed networks, they didn't have reasonably priced smartphones to use and that kind of thing, and so they adapted and created those incredible EnPay systems to pay using your SMS, your Nokia 8800, and then it made the western world look pretty behind. We were still doing ACHs and EFTs and all this kind of crap and PayPal was our big thing. And so I think that's what has me most interested about these new types of models, is I can see a company in Africa with users in Africa, maybe rural Africa, I can see them being really excited because they can run the models locally. It's free. And they can serve their constituents at a far lower cost. Is it going to be as flashy and great as a reasoning model from OpenAI? Probably not.
RD It doesn't have to be.
SW But for certain, depending on the function you're operating against, if you can shrink that down to an on-device model, for example, within your application and your cost literally is zero, if you have to on-prem it at your place or do it yourself, your cost is there but it's tiny. And I just don't think a lot of those companies are going to have the resources to go to OpenAI or to Anthropic or to anybody else and pay the API fees. I don't think that'll work. So that's what I'm excited about. I think just the democratization of this because of those innovations, that's what I get really excited about.
RD And I think the open source angle is another interesting one because there's a lot of those open source pieces in the stack that came from necessity. Some big company, Netflix is doing this that never has been done on this scale and they're like, “Well, we'll release this open source,” and it becomes a default. And there's a lot of tools that are like that now and I wonder how you think about the AI stack having that same sort of disruption from open source?
JM I mean, yes, I think it's going to happen. Again, it gets back to trust in a lot of ways. If you're going back to J.P. Morgan maybe we should say that, but the bigger the company, the more that trust matters and the more if you can do it yourself and have complete control of this situation, I think that very tempting, especially if you really have any question about where that data is flowing to and how can you truly trust it. And so yes, I think open source solves some of that.
SW It is interesting to think about open source in the previous era, if you will. It did take a long time for enterprises, and once everyone used the same libraries and everyone used the trusted libraries, then okay, great, now I can pop them in and go. But even that, I remember back in the day I was at Microsoft, we obviously couldn't use any open source at the time. They've changed their tune since then, but no open source then, and it was partially because we didn't want to deal with the license, but also because, do you really trust this library? Do you understand what it's doing? And of course you can look at it and everything else, but I know I was a developer for a long time. I miss stuff all the time when I'm doing code reviews. I wasn't a very good developer. Sorry for IE4. That was after a few too many beers one night.
RD That was you?
SW No, not all me, but there was definitely part of me in there. But so I think you are right, trust is going to kind of gate a lot of this stuff in the AI stack.
RD And I think it's also interesting, with the open source model there are a lot of companies building businesses on top of open source software, that as it matures, the software isn't necessarily the thing that differentiates.
SW That’s right. It's like Red Hat and Linux. That was a service company, and we're seeing a lot of those. People always ask me, “Why would anyone do open source?” Well, because you're not selling the software, you're selling the services, or you're selling a wrapper or a hosted version, or all the different things that make sense for a company, making it easy to use. Because back in the day, Linux, if you are not a computer-savvy person, no one's doing a Linux install on your device, but you get Red Hat and suddenly you have a Distral and I can do it.
RD So I want to talk about the conference a little bit. This is your first year.
SW It is.
RD It's very impressive. Everyone I talk to is just like, “This is their first year?”
SW I'm not sure that's good, because everything else in first year is terrible or we did a good job? I'm not sure. Probably a bit of both. It's the tyranny of low expectations.
RD So can you talk a little bit about the origin story, how this came about?
SW Sure. I'm a nerd, been a nerd since I was a kid. I've been writing code since I was eight on the old Apple IIs way back when, and I've always wanted C-3PO. I've always wanted my Knight Rider KITT car. I really wanted KITT, I was just so enamored, and so I worked in the space for a long time and maybe five years ago I resigned myself with the fact that we're probably not going to get C-3PO in my lifetime when all I'm using Alexa for is to set timers, it can do a lot more obviously, but that's what I was using it for. And then of course we saw Transformers pop, and we saw the first paper back in ‘17 and we saw the more commercialization of that, and I looked at it as a guy who's been in AI for a while, not as AI per se, but really a new human computer interaction model. That was really exciting. I thought this could open up opportunities for enterprises everywhere. So we started calling basically all of our friends who run these big companies and said, “What are you doing for AI strategy?” It was about 18 months ago, and a lot of them said they don't have one, a lot of them said they do have one but they're clearly lying. Anyway, I realized they just didn't have a strategy, and I said, “Oh my goodness. If we're relying on enterprises to figure out an AI path forward on their own, we are going to radically underdeliver on the promise of AI or we're going to make a ton of messes because people will deploy it in inappropriate ways.” And so we said, “Well, what can we do here?” My business partner is Jon Weiner, he's founded Money20/20 and Shoptalk and Health and all these industry-leading events like this, and we said, “Let's put something together which feels like that for AI,” bringing enterprise and mid-market companies together with the best innovators in the world who we have on stage behind us here and help them get clarity and conviction in their AI journey. So that was the thesis of the whole thing.
RD Jager, I'm sure you've been to a bunch of conferences. What's your take? I know you're next to the CEO here, so what's your take on the conference?
SW Be very careful.
JM I know. It is the best conference I've ever been to my entire life, actually. And to be fair, I can't think of the last time I went to a conference that is so relevant about what's happening now. I do go to a lot of conferences. This is so relevant. Every vendor, every desk I can go to, every booth is an interesting company doing really innovative stuff and you don't usually see that, actually. Usually you hunt around for the innovation, and this one, it's everywhere I look. So that's exciting for me as Crunchbase, to see these companies that somewhere in this room are going to be the next Decacorn or some crazy thing, so it's fun for me. This gets my brain kind of popping. So it is a great conference and I'm happy to be here.
SW And the startup area right to the right of us here has been mobbed all three days. And it's actually surprising, not surprising, but we have all these companies over here too, which are also busy, but really that's where you're getting the mobs. And so that just shows that there is, for you especially at Crunchbase, and larger too, but it just shows the reason they're here in the front of the expo hall is because they bring so much good energy and there is this curiosity of people here at HumanX to go and talk to them and explore. And they do that, then they go over to Google Cloud and see their stuff, which is really cool, so they can kind of see everything. They can see big, established companies and they can see literally startups that probably have raised– oh, I see Jim Currier there of NFX talking to them. All right, get the money! Go get the money, buddy! He's a good investor. You want him on your cap table. But that was the idea.
RD I know talking to some of the folks at Stack Overflow, we got in pretty early because we were like, “Oh, it's the human part of it.” That's been a big thing for us, maintaining that human, not cutting folks out, although I do see some companies here.
SW I saw that too. One says ‘stop hiring humans’ I think was one of the taglines on the booth I saw. I walked by and said, “Guys, come on. It's called HumanX.” The whole idea of HumanX is humans are exponentially more powerful with technology. That's the idea of a HumanX. So guys, don't do that. It's a good attention grabbing headline, I'm not faulting you for that.
RD So you talk about the companies differentiating themselves. What do you think will be the differentiator? If you look around today, what's the thing that'll bubble up a company?
JM Well, I'm very biased, as you might imagine here. I do think a lot of the workflow tools, it's always going to be hard to differentiate. I just don't know how you do it, especially with AI tomorrow doing it better. And we were kind of talking about this before, as a data company, I feel really good, because if you've got proprietary data that no one else has access to, it's very hard to beat me at the game. And so my challenge is how do I differentiate the stuff that I have even more? So that's where we went to predictions and insights and was like, “Let's go and have something that no one else can do because they don't have our 80 million users using it that uses data, that 17 years of edit data.” All that stuff let us go in a differentiated path. As you look around the room, that's always what I'm thinking. It's like, “Well, can someone else do this better if they come up with a better prompt in a couple years?” And that's going to be the challenge. But for me, data and differentiation in that data that no one else has access to is the holy grail I think in the long run because, no, AI can't make it up, and that feels like a winner.
SW Unfortunately I would agree. I don’t know why I keep saying J.P. Morgan as an example, but Jamie Dimon was talking about how, I can't think of the exact ratio, but in essence, all the data that AI's been trained on to date, they have– I'm missing the number– but five times, ten times the amount of data behind the firewall at J.P. Morgan over all their history. And so I agree, the real exciting piece to me is these foundation models and frontier models are absolutely incredible, they're absolutely incredible pieces of applied stats in most cases. But when you look at what the enterprises can do with their own data, I mean, that's where I think we're going to see the kind of, May Habib from Writer talks about you're 10x-ing your employees. So literally you're not cutting employees, you're actually making them far more capable. She said in essence, just this ability for someone else I was talking to has employees that are salespeople that are also now basically doing all their own contracts and all their own, so that just shows it's not shrinking jobs per se, but it is this ability to kind of make the people who are in those jobs be able to do more stuff and hopefully have more fulfillment and stuff they can do. I'm not sure how I got onto that topic from what you asked, but there you go.
JM And maybe I'll try to bring it back together.
SW Yeah, please. Thank you. Save me here. I'm like, “Where am I going with this?”
JM But if you think about how much data is locked behind the firewalls, behind the closed doors, the AI companies that figure out how to tap into that and extract value for their customers out of that, where essentially every customer has unique proprietary data that now they can utilize in their own business flows, that's where things get interesting.
SW I totally agree with that.
RD You obviously keep mentioning a specific large company.
SW I don't know why. I honestly don't know why.
RD Do you think AI is ready for the enterprise?
SW Oh, yeah. I mean, not wholesale, but absolutely. There are absolutely applications that we've seen in companies that are absolutely cutting costs or making people more efficient. I mean, again, I think we have to kind of disentangle AI and Gen AI and this kind of nebulous concept in general which is probably a little hypey, with practical applications. I mean, I'm just thinking USC for example. This isn’t an enterprise per se, but USC has their new model which they built to track and predict the course of wildfires in the city so they can warn residents ahead of that. I think of things like in drug dev, there's a particular protein that these scientists have been working on for 12 years to figure out a method of action and Google's new co-scientist product did it in 48 hours. I was listening to Thomas Wolf from Hugging Face, I read his piece a couple of days ago and he says really he doesn't think, and he's smarter than I am so he's probably right, but he doesn't think that AI necessarily will ever be creative. And I thought to myself, I'm paraphrasing, but I thought to myself, “Really?” Because I was at TED last year and I can't think of the company, but basically they said they had this realization that so many hospitalizations were caused by infection. It's very obvious, but catheters in particular were a huge problem. And so they gave that problem to an AI and said, “What would you do to fix this?” and it created a catheter with basically a bunch of teeth on the inside– don’t worry, on the inside. When they first told me that, I'm like, “No, no, no, no, no. I don't care how much it hurts to have an infection,” but it created basically this catheter with teeth inside that would prevent the bacteria from making it all the way up the urethra and everything else, and no human had ever thought of this. So sure you could argue, and he argued that orthogonal thinking is where we get a lot of innovation, but there's probably a lot of things to be mined from even our historical acts. And there's so many examples of that that are saving lives and doing real work. It's real.
RD It seems like a synthesis thinking. You haven't put those together, but AI will find it.
SW Exactly.
JM And the only thing I might add is, so I worked at Salesforce for a very long time in the early days, for 11 years, and I heard a lot of customer requests and it was always an AI question that they were asking. Just none of us knew it back then. It was like, “Can you help me find my next customer?” That's what every Salesforce customer asks Salesforce. And those are enterprises that are ready for AI, because as a Salesforce product, if I could say, “I understand who you sell to. I'm going to go and find customers like that and give you new customers that look like that,” that is AI ready for the enterprise if you could come up with that tomorrow. So it's how do you package it and how do you distribute it out to the end users in a way that’s differentiated.
RD And I think that's a good qualification, the AI versus Gen AI. Gen AI, you kind of want it to be unpredictable and dream about new things, but the Salesforce one is interesting because we worked with them on one of the first things I did here was work with them on how they built Einstein AI, which is pre-Gen AI. And now they have Agentforce. Do you think these AI agents, that's the thing everybody's talking about? Somebody described it as sort of the microservices moment for AI, that now everything's kind of composable. You have every SaaS product is an API now. Do you think we'll just have a front end to everything on the internet?
JM So I've played around with this idea a little bit of what if I could just go and it just creates the UI that I need for the thing that I'm trying to do? And so then it does just become a services based model, all APIs everywhere, and the AI just reaches out when it needs to. I do think that's a place it could go. The only question I have though is can the AI just make, there's that one AI interface, can it just make the thing that, so it doesn't need to make the call, it just creates it itself, and that's where you have disruption on those business models. But if it can't, then I think it's viable. But I love the idea of, using Salesforce as an example, the UI doesn't matter because the AI will make something that's perfect for what you're trying to do regardless of how many services you're using simultaneously. And that's where operating from is a little teeny step in that direction where it's trying to treat every other service like an API, but eventually you won't even see all that happening and you're just going to be presented with the perfect way to see it. And I'm excited about that future, honestly.
SW And at the end of the day, UIs are simply abstractions between human clumsiness or our way of thinking and silicon. And so they're there only because we had no other model that would work. And so when I think about what AI can do, and this of course gets a little bit futuristic and probably sounds like science fiction, but it should be one canvas to rule them all. And literally you shouldn't have to think about, “I'm going to open this app to send an email.” You should be thinking about, “I need to contact, I need to talk to Ryan Donovan today.”
RD Sure, of course you do.
SW Every day. And your assistant, your AI will figure out the best way. They'll know, “Okay. Ryan actually usually responds faster on WhatsApp than on email,” or whatever it might be and it can broker the appropriate connection to the appropriate service. So I think you're dead right. This is the microservice moment for AI, but I think that what's cool, and to Jager's point, what's cool is, unlike the 90’s and 2000’s or later obviously for microservices, where basically you still had to have APIs and things talk to each other, I think now what's going to be really interesting is that you can create, AI themselves can talk to each other sans-APIs. So the machines themselves can actually have these conversations independent of our, again, kind of clumsy, “Here's the schema, here's the API, here's what you have to go do to make this work.” AI will hopefully take a lot of that complexity away.
RD Well is there anything y'all wanted to talk about before we head to the outro?
SW Well, I think one thing I'll just say is part of the reason we have so many disciplines– this is not a pitch for us necessarily, but it is– we have so many disciplines here at HumanX. We have entertainment, we have Michael Ellenberg who's the head of media at a huge entertainment organization. We have Draper from VC, we've got everybody. We have healthcare, we have Roberta Schwartz from Methodist Health. We have literally some of the best people in the world that aren't necessarily what you would consider some AI-forward organization. And the reason I wanted all these people to come is because, and this is the message, because I have found some of the best thinking that I've seen in AI has come from interdisciplinary and cross-disciplinary conversations. And so literally it's the person who's in real estate who was talking to me this morning, sees something in finance and they go, “Oh, that's applicable to me.” So I think that’s what I want to leave everyone with. My perspective, at least, and really seeing it at this conference come to life, is don't be afraid to look outside of your industry, and that can be applicable for developers and everything else, to look at innovations that are happening, even if you think, “That doesn't apply to me.” Because with AI, it's bigger than siloed applications that we've grown up with for the last 40 years.
RD Love it.
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RD Thank you very much, everyone, for listening. We are at the end of the show. I have been Ryan Donovan. I edit the blog, host the podcast here at Stack Overflow. If you liked what you heard or didn't like what you heard, have comments, suggestions, email us at podcast@stackoverflow.com. And if you want to reach out to me directly, you can find me on LinkedIn.
JM And my name is Jager McConnell, CEO of Crunchbase. You can find it at crunchbase.com. Hopefully you all know that. If you want to check out some of the AI prediction stuff, you can go to crunchbase.ai where you sort of will see all the new innovation we're doing there. And you can always find me on LinkedIn as well.
SW My name is Stefan Weitz. I'm the CEO and Co-founder of HumanX. You can find us at humanx.co. Our next event is in April in San Francisco, next April in San Francisco, Moscone Center. And you can find me in all those same kind of places.
RD All right. Well, thank you very much for listening, and we'll talk to you next time.
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