B (2:48)

Yeah, yeah. I'll do the midstream question first and get to leadership. No question. It's just a fascinating topic. In fact, just heard Ben Horowitz 2 minutes ago Talk about this in person. So interesting to see his viewpoint. But midstreams focus entirely on financial operations. It's so interesting, Scott, I think for the longest time, I think when we think about technology, new solutions, technology, even 10 years ago at Kiventis, you think about technology budgets. Now you really think about, hey, what's the workforce that we're applying here? And are there budgets that, you know, sort of, when you think about top of license, there's bottom license, where people just don't want to do this work or it's getting outsourced. You know, a lot of what we do at midstream is really focused on thinking about, hey, there's financial decisions. If you think about rocks, pebbles and sand, there's a lot of the pebbles and sand that either just people don't get to it because it's not important enough, or they get consultants to do it, which is very expensive. If you have software agents tackle that, not only can you give the fish, you can actually teach the person how to fish all the time. And it's much more sustainable, it's much more cost effective. We've done that on the cost side and supply chain where we're going to manage care in pharmacy and other areas. In terms of leadership, Scott, it's funny, 10 seconds ago, before this, Ben Horowitz was asked in this small group I was part of, you know, hey, what do you think of the leaders today? He was like, you know, I think leaders are always evolving. You know, entrepreneurs are always evolving. But I don't know, Thomas Edison, Steve Jobs are pretty good too. So there's some, there's some, you know, things about leadership that never changes because we're human beings. But I tell you, Scott, I think the mental model I had 10 years ago to what's today, which is dramatically different, is I think a lot of times we'd look for entrepreneurs who were, hey, you've been there, done that. You've done this for 15 years, 20 years, and therefore now you earn the right to go build this new company. What's really fascinating Scott, in this next round are people with 2, 3, 4, 5 years of experience are running circles around the so called experts. And it's a very different wave. It doesn't mean they have not partnered or surrounded themselves with domain experts who've been in the industry for 30 years. In fact, all the top performing entrepreneurs I know now have those domain experts. But it's just super impressive to see that this generation of entrepreneurs in technology run circles around people who've been in the industry for 20, 30 years.

A (5:24)

And there's a lot of that because they're just so much more almost computer native. They came up early in technology and so forth. So they're just like, their minds are just so much further ahead of people that are, you know, I asked it to say like my age, but they're just in a different, they're playing a different game because they just understand and connect dots so much easier. Is that part of why that's, the why that's happening?

B (5:45)

Yeah. I don't, I don't want to inflate Bobby's ego too much, but, but I do think that, that when I, when I was, I was in college when the iPhone came out, right. To date myself and you know, when I look at my, my niece who like grew up on all the sort of devices, she's sort of Native in the iOS and I think that people who are native to your point with ChatGPT or anthropic or any of these platforms, you know, you kind of see this now even in the production of code. Right. Engineers who use Cursor or Windsor for any of these tools are just 30, 40, 50% more productive than engineers that don't use it. And for them it's like using the iPhone. For me like 10 years ago. Right. And so I do think that the other, the other thing I'll sort of say, Scott, is it used to be about 10 years ago, you know, when we were building these companies, we'd say, hey, you know, Bobby, you studied computer science, therefore you're an engineer. And we'll give you all the technical stuff, but really the business stuff, that's like up to us. You know, we're the, you know, sales, marketing strategy, whatever you want to say. What's really different in today's era is it's all the one person, this same person who studied cs, like Bobby, has learned the health system go to market, has learned marketing, has learned strategy, has learned the domain expertise and they're really a triple threat. And so they just go faster. They are able to Iterate faster. And I think the last thing I'll sort of say is when you're young, you're unafraid to get on a plane and go see the customer and not only do you listen to their problems, but you observe what they're doing and then you say, hey, you know what, I know you asked for this. What you actually want is this, this and this. And Palantir is a company that kind of showed that you needed a forward deployed motion for that. And now every entrepreneur does that. They're forward deployed in their nature. So so much of the way we're building companies, the entrepreneurs, everything's changed. And so you're seeing these companies go from zero to tens, if not hundreds of millions of dollars. Anthropic went from 0 to 1 billion to 10 billion in two years. And that's sort of just in revenue run rate. That's, that's just, you don't see that often.

A (8:04)

That's an incredible, incredible growth story. Bobby, can you take a second to introduce yourself and talk about what you do and so forth?

C (8:15)

Hi, yes, huge pleasure to be here. Obviously I'm the son of a very bright and successful entrepreneur, but I recently got my master's in computer science and since June have been part of a very small, very young, very lean, and I'd say very talented, very driven team of applying AI in the EdTech industry. So what we do specifically is we provide different tools for teachers to create different types of resources for students. And on the product side, the idea is we make the process as easy as possible for teachers to create a learning material, whether it's a test or homework about any subject for any grade level and share it directly to students. And then kind of on a deeper side, we're trying to use the best techniques, engage with the resource, the research to try to align these materials to be the most effective so that students actually learn from them. So I'd say that I've been, you know, I've been part of the startup for like four or five months now, but definitely a lot of what has Venkat has just been saying has I. My vision is definitely aligned from what I've seen. So I think something that. So yeah, gone.

A (9:39)

We'll talk about that for a second because you talk about that often. How the engineering leadership, the people that founded the company are also so very, very forward deployed and very involved in touching customers and how important is that to making sure that you guys get product market fit. Right. Talk about that for a moment. It's something that can mention something that you mentioned to be regularly, you know, how closely tied these people with great engineering backgrounds are, are also to being customer centric. Can you take a moment there?

C (10:04)

Yeah. So first I want to speak. So for myself I have been focusing mostly on the AI side but kind of the term AI engineer today probably means something very, very different five years ago where before it was very math heavy, very machine learning training models yourself and it took years and years of experience to get good at that. Whereas now in this new domain of AI in the application layer, which is what I consider companies like us, it's a lot more of a well rounded skill set of both, you know, it and it's open to a lot of young people because both on the technical side there's a lot of interesting new innovative ways to apply them and then it's also a lot about engaging with some sort of problem or product market fit. But yes, both the it's definitely very much in the DNA of the founders and company culture to be talking to customers, talking to, you know, the main people who we who are main customer face are teachers who, you know, designing systems to save them time and really be a painkiller to them. And then also on the other side of being a product for districts, making sure that we're aligned with different curriculum standards and learning techniques and then also making sure that in selling to them we're not forgetting about the, the people who will actually be the end users of our product, which will be students who will receive the resources that were created by the teachers.

A (11:40)

So I mean fascinating. What a fascinating journey and what you. It's so interesting to hear both your perspectives because Venkates at this now for 10 years plus in this area, but 20 years in healthcare and some of those with Mudit and Juventus and some of those with Andreessen Venkat talk a little bit about how important it is to sort of, you know, usability for your systems. Like you're working with large systems like I mean common spirits, a 30, $40 billion system, but they've got so many different solutions to work with. You know, how do they choose what solution to work with and how do you make it so easy for them to work with you that they could see these bending the cost curve on supplies, on management, on other things. How do you sort of.

B (12:29)

Yeah, I think it's an incredibly important question because I think that health systems and obviously the very largest ones already have platforms like EPIC or ERP systems, et cetera. And the famous quote is the race is always between the incumbent who can innovate or the innovator who can distribute. And I think for us in any area, Scott, whatever you choose as a startup, you have to be 10 times better than the status quo for you even to get a chance to be in the door.

A (12:57)

Right?

B (12:57)

Like otherwise, like it's, it's, you're not going to, it's not. The ticket is not worth it, I think.

A (13:01)

But talk about that for a second because people would rather use the existing platform for sure. If you're developing a point solution or something else, you got to be so much better than the existing platform because they don't want to bother to make a change or invest the time, the energy, the staff. So I love that concept. Bob, we'll come back in one second. Yeah, go ahead.

B (13:18)

You, you, you have to be 10 times better number one. Number two is you have to have a speed to value. So these platforms that can do everything, EPIC and ERP systems, et cetera, they are so they can, you could check the box on any particular area and say, you know what, I have that particular feature. But what you don't have is someone who's concentrated to say, you know what, if I don't deliver value to you in the next 12 months in this area, I'll walk away. And you don't have to, you know, it's a no brainer thing, right? So it's like, so you have to make it such a no brainer value prop for them to engage. And the speed to the roi, not just hey, I have an ROI in five years, but the speed in which you can give money back to the organization to say, hey, these guys are or and gals are very legitimate in the way they can work with us. And they are, time is money and they are actually delivering points on the board for us. Not some hypothetical prototype that they show in a demo or something like that. It does, it doesn't work. So I think the stakes are very high.

A (14:11)

Yeah, but I love that concept of speed to value. Bobby, you were going to add something in. Go right ahead.

C (14:15)

Build off Venkates point real quick. Of he talked about different coding tools earlier like cursor and surf and that was definitely a case of the race between the, the innovators or the incumbents who have to innovate or the innovators who have to distribute because you know, they integrated basically AI into the workflow of coding faster than the traditional platforms to code. And then at this point the traditional platforms to code have caught up. They've tried to Integrate AI in a lot of ways. But the first to market because you know their product was really, really good, they were able to capture a bunch of distribution. So and I've seen that in a lot, a lot of cases just in again AI in the application layer of applying LLM specifically to different domains.

A (15:04)

Yeah, that's interesting. And talk a bit more when you're talking to. I'm going to ask Bobby a question. When you're talking to teachers and teachers are excited about what you're doing and I know you're both distributing both the teachers but more so to the systems, to the districts and so forth, what is the value propositions they have to see and what are some things you hear from customers when they're using the AI and technology that you're working with.

C (15:32)

So I think something that I have learned has been a huge learning curve is building a software is not the same as maintaining it. So you know, we have people who are using legacy parts of our platform and like if we, when we update our data sometimes we were just dealing with a huge issue with that. But just over time there's definitely always the need to provide a lot of support to them. Even we find that our AI tool makes their overall makes. I think the main selling point to most people businesses are either a painkiller or vitamin but the painkiller is what draws people in. So really saving them time, making the process as seamless as possible for them to create any resource for any and then like directly to share it, directly grade it on one platform.

A (16:26)

And then talk about the company's commitment to constant improvement because that's a key issue, constantly improving the software. How focus is teacher on that?

C (16:34)

Yes, so very so again and this is, you know, regarding the new techniques and new ways to apply AI. As you know, companies like us, we pay the big providers, OpenAI Anthropic, Google kind of a little bit of money to make calls to their server basically to use their technology, their large language models for our specific products. And there's a huge, you know, just like how the main providers is a huge race to make their models as good as possible. There's also a race in the application layer of finding the most, you know, being creative and finding the most effective ways to apply them. So I think we actually have a fairly interesting and innovative tech stack now and then constantly working to keep up with the latest innovations because this specific industry is growing, you know, this specific domain of research is growing so fast.

B (17:30)

Yeah, I think this is a, this is, this is a great Point if I can write off of that, which is that, Scott, I think 10 years ago, when we're building software and selling it to organizations, you know, could be pharma, could be payers, could be providers, I think the thing was you'd build this software, you'd work on it for a year, you'd build it and you'd say, hey, these are three things I can do. And then you do a RFP processing, compare it to all these other tools that you have build by, et cetera, and you make a decision. But today what's happening is there's this concept of neuroplasticity in a person. How fast can you learn and grow? This is applying to companies today. And the reason why I mentioned people with a couple years experience are running laps around people with 20 years experience is that you did three things today as a company, this week you can do 30 more by the end of the month in production. Right? So the speed at which you have to figure out, hey, you know, Bobby mentioned, you know, OpenAI, anthropic, Gemini, et cetera, hey, maybe there's the new GPT5 came out. Okay, shoot. Let's just figure out, let's how to use this latest model and fine tune it and get the data right to work for this particular use case. And so the speed at which people are able to iterate is the competition. So the kind of very provocative thing to think about as an investor is what is the moat? It just might be execution, it might just be just speed to execution. That's it. And so for a executive who's at one of these large organizations making a purchasing decision, you have to say is this the pirate crew, that's going to work 10 times faster. And the concept in San Francisco now is996, 9am to 9pm Six days a week. That's the speed at which people are in the office working hard to build these software solutions to go execute for the customer. So it's just the most fascinating time that I've ever been in the last 20 years in technology.

A (19:12)

Talk about venkit. Because so much of this is so much work. You talk about 9, 9, 6, but it's all about, I mean the thing that Steve Jobs is genius was making it easy for us to use. I mean tremendous amount of trillions of hours put into making it simple for us to use the iPhone. And that seems very similar when you're working with a health system. And there's not enough brilliant technical people internally to be able to, to do stuff unless you make it easy for them. So there's so much work done in the AI side to make it easy for your customer to use. Is that, is that a fair statement?

B (19:53)

Absolutely. Yeah. I think that, I mean, I think the interface is nlp, right? It's natural language. I think it's like the thing that's so crazy to me is, you know, when I was an analyst, like way back in the day, if you learned Excel, it's one thing, if you learned SQL, it's another thing. You know, our agents today run the SQL query. They show which SQL queries they're running. You know, they, they do very complicated scenario planning. And so this is like, frankly, we're automating the role of an analyst or a senior analyst. We can, A lot of companies are doing this today. It's not just, you know, us. A lot of companies have those capabilities to augment, you know, analytical capabilities. So I think that the interfaces become so easy to use. It's way easier than using excel, but it's 10 times more potent. And so what, what, like that's the, that's the, the difference is anybody can use AI tools tomorrow in regards of age, background, et cetera. It's just really your willingness to type.

A (20:46)

Things in English and, and how well you could use it to access it.

C (20:51)

Want to add one small thing to that, which is I, well, I do largely agree, but I do think there is some spectrum in terms of, you know, you always want to make something easy, inviting to use. But then some platforms are more built for depth for people who are more technical. So you know, when it comes to the huge area of using AI to help coding, there are some platforms like Netflix and Lovable that are built for non engineers. And then there are some other platforms that have a little bit more of barrier for entry, you know, more for people who have like three, you know, two, three years of experience of coding. So. But yeah, no, 100.

A (21:34)

I mean, I mean some of the tech is built for tech people, some of it's built for lay people and.

C (21:38)

And there's a full spectrum on that.

A (21:41)

But yeah, 100. And then when you're working though, when you're working to develop, teach here for a specific teacher, you've got to make it tech easy for them in some way. Take it with school districts and systems.

C (21:55)

Yes. So I guess the couple. Well, yes, we do make it easy to them, but also we have a lot of things built in our platform to both make it easy, but give them the ability to customize and improve. And iterate if they choose to do that. Which we've actually found that making it easy draws people in but then you know, giving a little bit more depth is what is why a lot of teachers have spent a lot of time using our platform for more and more and you know, really retaining them.

B (22:25)

Right.

A (22:25)

And that's a really good point and Venkate talk about that because in any system you have users and super users and we talk about that in almost any business set you've got people that are really, really users and talk about that at midstream. What does it take to push people to become or not a push pull almost to want them to be. Because I love Bobby's point. I mean it's that 10%, 20% that really dig deeper and want to be super users that, that make the product really stable for the long run. I love that point. What do you see in that in terms of users versus super users of what you're doing in AI tools?

B (23:00)

Yeah, I think, I think you know, in this is why I mean enterprise software is more complicated. And you know my observation when I was in venture was that the younger founders tend to build consumer products and the older person used to build B2B companies. You know, but, but you know, the thing that's really, you know, important is I believe that first of all, you know, every person who believes their own, you know, you built your own app or whatever, believes they'll be using it all the time. And I think you have to just recognize that most people don't even want to use your application. Like that's just, let's just start there. Like sometimes the best kind of UX decision is no ux. In fact, you know, I believe in sending, you know, if you're a busy leader, send them an email, send them a text that just assume actually that they don't have the time to go interact with it. And then I think Scott, these relationships that you build, what not just doing the deal at the high level but with the people who are these analysts or whoever who are going to be your power users is all that's why those forward deployed motion is so important. Because I think what you have to do is observe. Not only is it hey, I have X problem today, but observe their entire workflow and say I'm going to do this. And then by the way I'm going to do two more things on top of that to make your life way easier. I noticed that you have 50 tabs on your Excel and you all tab through the entire day because you Read three portals and you go through this Excel sheet and let me just make one click for you. And so that sort of iterative journey and I think what's very addictive for this, and I'll end with this for the user, is that, hey, on Friday you push this out, the next Friday you did something new for them that is actually relevant to their workflow. And then it becomes addictive. This person is listening to me, they're responding to me and they're building iterative software that's way faster than any other software I've used. Right. Because this is moving literally week to week. But that user mapping is like very important. And you can't be sort of so thinking in your own world that, oh, everyone's going to be using your app all the time. The reality might be most people don't use your app and they don't care.

A (24:58)

About it, but the users that use it, that, that, that the sort of really mapping what they do and what you do, this has become so a part of software development, of code development and so forth. How intrusive does the user feel about that? How does that feel? How does that look like to a user when you're following every one of their keystrokes and stuff like that? I mean, how does it. Because that's become so common. But it seems to me so, so in some ways. So privacy intrusive. How do people feel about that? Or how does that look, Bobby?

B (25:29)

How do you guys do it on the, on the teacher side? I'm happy to answer that.

A (25:33)

We're.

C (25:33)

That's definitely something, the, the privacy end of it. Definitely something we're dealing with because that seems to be not something that is in the front of mind for teachers who are, you know, we're sort of a kind of. Our strategy is bottom up. So teachers oftentimes subscribe and then once we have enough teachers in a school, then we try to make a sale for the school and enough schools, we have a district. So I'd say more the higher upside. That's where the data and privacy becomes more important.

B (26:08)

I think for us, I would say, Scott, I mean, privacy in healthcare is the game. It's the ball game. It's like the one thing that will basically end your company. So we take security and privacy incredibly seriously. And I think we sort of say to a user, you know, this starts with the little things like you know, every now basically everybody has some version of a note taker. AI note taker these days on calls. And I think the first thing you do on any call you're on is like, hey, I have an AI note taker. Is that okay? And you ask for permission every single step, right? And so I think it's very much. That's a small example I'm giving. But every step of the way you're sort of asking for people permission. But the truth is every single person in their job, you know, people are always asking. I'm so worried, you know, are you so worried about replacing jobs as AI companies, etc. I think every. The reality is that health care, the demand far outstrips the supply and we don't have enough people to hire for these jobs. That's the state of truth. And 100% in higher ed, I'm assuming health care. But I think that even more dark, deep, dark truth is there's a big part of or a small part of your job that you just don't like to do and it just goes down in your pajama time or whatever. And it's one of those things like cleaning the house and those chores that if you had a Roomba going around, you would do it. And so what are these agentic roombas equivalent to your job as an analyst or a director or a cfo? I don't care who you are. Everybody has a list of things that they just don't want to do that I think they should just give it up to the agents to do. And that I think is actually a very interesting value.

A (27:37)

I absolutely love that. I've got a couple audience questions I want to tee you both up on. I know we just got a few minutes left on the AI discussion. I'll start with one that's more general. General question I'll get to more specific one about around the pet business and pet services. But the first question is somebody asked a question about line of sight into the promise of vibe coding is coined by Andres Karpathi. Do you guys. What is vibe coding? Do any want to take a quick shot at that? What is this? Why should we care? Bob, you want to take a quick shot of what is vibe coding? Do you. Are you familiar with the term?

C (28:06)

I'd love to go first but would love to hit here venture thoughts as well. But Andre Kaparthy has been a very big thought leader in my subsection of engineering, which is, you know, the. The new wave of AI engineering of applying AI to products. And the idea is the. The workflow for coders were using AI more and more. And this was a term he actually just, you know, he didn't write A paper about it, he just made a small tweet about it and it ended up coming viral. But the idea is people with less and less experience, if you use it can be as simple as like asking Chachi BT to write a Python script to automate something in your job, which I have many friends without a computer science degree who are finding ways to do that. So the. And so over time, if you think of the development of software, it has become easier and easier to use and it has become less training or has continued to require less training, less background because all these different tools and frameworks, you know, not. I don't want to get too deep in the tech. Before people are coding assembly, now they're coding in Python. And this is another layer where it allows you to build software faster, more quickly. And you know, again, there's a huge spectrum of this because, you know, it does take a little bit over time of actual coding as well as the Vibe coding to do things right and to do things securely. But I think especially for early stage startups where speed is the priority, the, the new AI tools to work faster has become a very big and very important thing.

B (29:49)

I think everybody should Vibe code. I think it's phenomenal. I think it's like, I think Vibe code is a very fancy way of saying making things, you know, using the new tools. And I think that I view it as an extension of if you use PowerPoint slides, if you use Excel is just another tool. But what's really powerful is before you had to ask an engineer or a designer, you know, to say, hey, can you, I have this idea. What do you think? You know, can you come up with something? And then they would take a week or two or two months or whatever time frame and you'd be amazed. You could do that in 30 seconds yourself. And that's a very powerful change thing. You could be a poet and you can Vibe code an enterprise financial tool, obviously to baby's production. You know, Vibe coding something in a demo to actually putting something in production in a safe way is, you know, the difference between nursery and PhD. That's, that's, that's a big difference. But actually getting there to capture people's imagination, selling things, etc. It's just a phenomenal tool. Everybody should Vibe code.

A (30:47)

So we've got a question from an audience member that's domain specific and Venkat. I'll try you on this first and I'm not sure either one of you guys will have great thoughts on this, but would love your thoughts so we've got somebody who's built a pet business and they're asking, and I need you to put your thoughts, your hats on outside of your own businesses. Any thoughts on how to incorporate AI in a pet related business where services are the core business? And this is someone I know. The person is asking the question because they were featured on Marcus Lemonis show. Brilliant people. But where do you think about AI? The founders of this are brilliant, but what do you think about AI in a pet services business? Venkat, any thoughts there?

B (31:25)

I think it has massive implications. I think like I think that any services business has massive implications. I would just sort of, I think the sort of starting point is I would just observe the workflows that you have for, hey, for onboarding a customer, right from the reception desk perspective, from registration. Think about all the workflows a customer has to go through to get to know you, to market to that person to once they walk in that door for the service, for the billing, there's all these aspects, there's buckets of workflows that you can have AI applications doing and you can have a much more profitable business. I think you can have a much better 10x patient experience. So I think a pet business and the fastest way I would do it is if I could convince a guy like Bobby Becker, you know, to come, someone of his ilk to say, hey, you're going to this startup, but actually come to my company, work for me as a CEO of a pet business, observe those workflows. I guarantee you someone like, like Bobby, his background can go automate or augment a big portion and make the experience a lot better. So I think there's like a massive amount of implications of pet business.

A (32:30)

No. Fascinating. Let me give you guys each 30 seconds more. Best advice for users of AI and not so much technical users, but end users of AI. Best advice for an end user of AI, you know, someone who's a business trying to use it, that's not a tech forward person or tech forward company to begin with. I guess they might have to become a tech forward company. Nine of the top 10 companies, my market, tech companies. Does everybody have to be a tech company but Bobby, Any advice for users?

C (32:54)

Okay, well I want to say one last thing. Beyond learning to use AI, and it depends where you are, a lot of people should learn, you know, just try out the new AI tools, see if you like them. But also don't forget to not use AI as well because I think there are, you know, there are many cases and I Think I see this a lot in academia where beyond using AI to help you write, to help augment your abilities, to help you code, it's also useful to take a break and a detox into work sometimes without AI, because I think they really are something that can enhance and expand our abilities. Though there are many places where I'm sure they can automate workflows, there are many other places where they really do. They're as strong as the user. So keeping your mind sharp and not being to relying on it. Get your news from places other than ChatGPT, you know, read some books, write yourself.

A (33:58)

But I think your point is so well taken. There's whole, there's whole thought today on the difference in the world with people that can go back to deep work as well, which has been discussed a lot recently. Not people that could just, you know, tweet back and forth and do things back and forth, but actually spend time devoted to deeper projects as well and be able to connect dots. I think your point is so right on that and I just love that point actually. So thank you for that. Venkat, any final advice to users?

B (34:20)

Yeah, I think, I mean I'll take the counter to that because Bobby lives and breathes into stuff so I like the refreshing. But I think like look, I think whether it's Replit or Figma make or Anthropic or chatgpt or any of these, I think just using some of these tools it just seems so daunting on the outside and people use buzzwords and all this. But I guarantee you once you open up some of these apps, even the current apps you might be using Canva or Figma to like, you know, just make like, you know, my, I'm getting married soon and my fiance who's a GI fellow made this incredible animation using like Canva. And these are not, these are very simple tools to use. Not to discount her work, but I think the first step is just opening these things up. And so my thing is just like poke around. There's, there's no, you know, obviously there's different stakes at work but in your personal lives, like just if it's little things that you want to do, whether it's planning a trip for a loved one or planning a wedding, in my case, you know, there's, there's so many of these tools, it just requires exposure and comfort like everything else in life and they're just really easy and user friendly. So just take the first step. That's my only advice, I guess.

A (35:35)

Frank and I'll ask you the more challenging question. Was it hard to find a spouse that's so much brighter than yourself? Was that very challenging? And how did you manage to do that?

B (35:44)

Well, it's relatively easy, Scott. If you're me, it's relatively easy. No, Yeah, I think I'm married up. I got some good advice from people like my mentors like Scott Becker. But, no, there's a lot of luck in life, and that was definitely one where I got lucky.

A (36:01)

Well, congratulations. Bobby Venkat. I want to thank you so much for joining us on this segment on AI for the Becker Business podcast, the Becker Private Equity Podcast. Thank you folks so much for joining. Just fantastic, both of you. Thank you very, very.