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We back a lot of founders, and one of the questions we ask is, are they open to advice? And in a environment like right now, where capital feels like the commodity of commodities, how do you assess it? How do you build that trust up front? So that they know this is not just a transaction, there is more that comes with it.

What is the biggest mistake you've made as an investor?

Um, I love all my companies, and anything you know about investing tells you that you need to focus on the winners. It goes counter to how I'm wired. That is a constant struggle. I've gotten better at it, but I do not do what I do.

What is the one that got away?

Depending on the day that you ask me, is perplexity because we saw it many, many times and passed on it because it was really a thin layer wrapper and we were looking for more of a moat.

And that's why you said, depending on the day you Because ask me, because

there are the there are days where you're like, Yep, I called it okay, great, I don't feel so bad, and there are days where you go, Oh my god,

that was Rudina. Seseri, founder and managing partner of Glasswing Ventures, an early stage venture capital firm investing in AI powered companies. From AI automating prescription fulfillment to AI that's reinventing cybersecurity, Rudina has always been ahead of the curve. Today, I'm talking to Rudina about the AI investing landscape, where she sees the real value in AI and what she looks for in founders before she writes that first check. I'm Rana El Kaliouby, and this is Pioneers of AI, a podcast taking you behind the scenes of the AI revolution.

Rudina, welcome to Pioneers of AI.

thank you for having me, Rana.

I am so excited for our conversation. Uh, 1st of all, congratulations, because you and Glasswing Ventures were named as one of America's top venture capital firms of 2026 by Time and Statista.

Thank you.

Oh, that's great.

Lots of hard work, but, you know, backing the right founders, dollars in returns out, but it's along the way, it's nice to see this.

Yeah, that's awesome. So I wanna start with a personal story, right? This is about six years ago. Now it was the fall of 2020, so it was during Covid. I took a walk by a river that's close to where I live, and I was really thinking about. It had been ten years since I was running Affectiva. You I know where remember, right?

this is going.

And I was like, I just need some advice. Who can I call? And I texted you on my walk and I was like, Rudina, do you have a few minutes? And you were like, on the spot, sure, call me. At the time, I was contemplating whether to raise an additional round of funding for the company or explore exits. We hopped on a call and I asked for your advice on what to do. Do you remember that?

I remember I know exactly where I was sitting as well.

Yeah, what, what, what were you?

I turned one of the bedrooms into an office, so I was literally in front of the computer, sitting at a desk.

do you remember what you told me?

I did. I said at some point, make a call, you know, you can keep going and going, but in so many words, make the tough decision and get it done.

Yeah, that's exactly that's about right. You were very. I think the thing that struck me is the clarity of your answer. Sometimes when people give advice, it's like, wishy washy, and and you were like, very Regina style, because I've got to know know you fairly well since then. And, um, yeah, you just said you've been doing this for ten years. It's time for a new chapter. Just get it done. It really helped clarify what I wanted to do next.

and I think it was particularly sort of l evident to me at the time because you had done all the hard work. It was just, you know, a question of had you taken it far enough? And and you know, it's your baby. I know a thing about starting a firm, right? With Glasswing, and it's very, very hard to let go, but you hit the success time to call it.

so do you get a lot of these calls from founders?

I do. I usually get them in the context of my own founders or founders that I've backed previously that are trying to figure out what to do next. It's funny because, you know, we back a lot of founders, and one of the questions we ask is, are they open to advice? And in a environment like right now, where capital feels like the commodity of commodities, where, you know, oftentimes, especially with younger founders, is a one time negotiation valuation.

Being able to sort of, how do you assess it? How do you build that trust up front? I talk about paying it forward so that they know this is not just a transaction, there is more that comes with it. And invariably, you see that more pronounced in a positive way with founders who have gone through that journey 1st and then know that who you partner with in terms of a backer is not just around valuation. And not even just the brand of the firm is actually a lot more nuanced, is the person you pick and how, and what will they do when the going gets tough?

Will that VC be there for you?

Yeah, absolutely okay. You've been investing for a long time. I am now an investor. I took your advice and now we're both investors, um, and I believe we're actually co-investors in one company. Um, yes,

and then some of us have a a little bit of a stake in some of you.

exactly. You are an LP in my fund. Thank you for the support. I really appreciate it. I would love your take on what it's like to be an investor in today's AI landscape. My sense is like every company is an AI company and every investor is an AI investor.

I mean, it's it's an incredible environment. The the closest sort of sentiment to what I'm experiencing and we're all experiencing right now. It was in 2000, but even then, I think it wasn't as pronounced as it is today. There is a lot of innovation that's going on. So with AI, building is no longer the challenge, building is not the mode we can all build. I sat down two weeks ago, wanted to create an app or an artifact, or, you know, whatever we wanna call it these days, an agent where whereby, you know, I could see all the audition opportunities that would come in Boston.

I wanted an entire format. Bum, bum, done, Done you know, that's not the advantage. So when you had talent that was building, you had a different type of mode. Today, I think the advantage is more around the data and the access, the totality of building systems. Um, because I think models and building in and of their own can be commoditized. If we've seen anything, is that you swap one model out and, you know, you place the the next.

But it's the data and architecture combo, and to what purpose and how deep can you go in that space? So tying it back to the founders, a lot of demand now for the infrastructure layer, particularly around GPUs, and, you know, and what sits on top of that. You see tons and tons and tons of those companies, and they're able to raise a lot of money. You have to decide, am I in for the journey or not?

With very little data, and but also you don't have the 18 months from now. We will be able to call it one way or another, because raises are fifty and 100 million, and everything is sort of a goal of setting up a lab. And I'm being a little euphemistic. I don't think everything is a goal, but many, many labs that are being funded. So the time for the winners and the losers to sort of emerge is going to take longer.

So it's a very different model. It's also very different from what you and I do, liking to be the 1st check in. How do you become the 1st check in? Roll your sleeves, help build the company. When their 1st raise is 30 million, the economics don't work. So we're thinking very carefully how we tackle that, and I don't think anyone has a good answer right this very 2nd. But I think we have ideas on how we go very early and make it so easy and bespoke for founders to build the business faster than they otherwise would that we might be able to get into that incubation stage.

you know, this is interesting, cause I was doing kind of a look at our portfolio, and it's almost like bifurcated into two like buckets. One is typical pre-seed and seed stage, so the valuations are under 15 million. We come in early, the companies are early, and then we've made a decision to also invest in these like horizontal AI, bigger physical AI infrastructure. Their early rounds are like, you know, $100 million, a billion dollar valuations, and we're a small check, but we still decided to do these because I think there's a lot of upside.

How do you think about valuations and how do you evaluate?

they're important, they're not everything. It's not really how I think about valuations. You want to be part of the bigger journey. So the way that I think of it almost like different products. We have this access check where we've gone into some of the biggest robotics companies around town and beyond. So in the physical AI space, we've invested in unconventional AI and recursive AI and a bunch of other sort of 100 million, 200 million type raises of 500 in some instances.

Where we want to have a seat at the table because for access, not just to the deal and potentially follow on capital with our LPs, but also the ecosystems that spin out. It's the whole community, the whole machine, so that's one piece. The other piece is the redefinition of seed, pre-seed, incubation, formation, whatever you know, flavor of the day label one wants to give it. I'm finding that I'm pretty convinced that the seed round now represents the old A.

The old A was eight to 10 million. Many, many, many of the seed rounds are in that range, maybe six to eight, but and many others are just raising 30 and 50 right off the bat, right? So, too early stage, it hasn't come to where the seed is, and the seed has gotten later stage, and no founder wants to take capital in between. This is a very interesting sort of dichotomy. And so by design, you try to tap into both, knowing that you better be investing in a company that's de-risked enough if you're writing a bigger check, and then in the smaller ones.

That you will do a lot of sweat, blood and tears, heavy lifting alongside founders, and those are fun. It's just that you have to do a lot more of those because the failure rates will be higher.

I don't know if you saw this program, Tech Trek that came out of, um, John Warner, Yeah, Yeah, exactly, I'll just give a kind of a summary of what it is. They basically selected a number of students from MIT, Harvard and Princeton and sent them to the West Coast to spend the summer there. They all lived in a house together and and kind of built their startups, and they came back, did a demo day, and some of them were really interesting.

And we were starting to meet with them to see if we want to invest in them. I would love your thoughts on this, because most of them are undergraduates or just like freshly out of school, so very little business experience. And part of me is excited to back these young, kind of super ambitious talent, but I have question marks on their commitment to the project or the startup. Because some of them are kind of still kind of maybe taking a leave of absence from school, but they might want to go back.

As a parent, I'm a little biased. I would love for them to finish school. Have you backed kind of

oh yeah. I mean, on my way here, I was talking to two nice. His name from Provenance, and I think he's a junior. And he's dropping out, and he, he had, like, a full merit scholarship. And they're basically trying to become the platform for analytical financial models presentation. So a really interesting take with their AI. It's funny you say that because the 1st thing I will say is, Oh my gosh, your poor parents. So it's just a notion, but so

Or not? I mean, if they do great, amazing,

not everybody's motivated by money, though. Some, you know, like I grew up in a culture I'm Albanian, where education was your most precious, same, yeah, you know, gift, because no one could take it from you, especially in a country like mine, where, you know, they had communism, wealth was taken, what was private became government owned. So some of us are wired in a way where education is closer to religion.

see, I'm getting goosebumps, cause I have the same wiring. Clearly, yeah,

Um, so, so I put that aside. So I have a fundamental view that twofold. One, um, there are some people who are special, that even if they don't have the answers, no matter the age, they will somehow figure their voice and figure it out. There is also a mentality that we've worked very strongly, uh, to overcome. 1015 years ago, Boston-based VCs, I would say, they back professors, and the West Coast was backing students. And if you think about mobile and a lot of the application ecosystem, really, the innovation, the transformation was driven by the students rather than the professors.

And I think that has something to do with naivete. So I always sort of go back to the Uber example, you know, the kids, I'm in Paris, it's raining. Why in the world can I not call, you know, a car or a cab, which became Uber on my phone? As basic as that, and the barriers that came about that they had to overcome that tackled along the way. So there is something about that naivete of I don't know too much to know that it's done this way.

That has to be balanced, of course, with driving adoption and the hustle, and we go in and out of waves as backers. The downside is I hope that they know how to quickly get adopters to embrace them because there is value in the relationship. In fact, domain expertise, especially when you're talking about a vertical domain, domain expertise and depth of trust and depth of understanding of workflows could be one of the few modes that remains in AI-started companies.

I'll be right back with more of my conversation with Rudina, but 1st, a quick break. The companies winning right now aren't just building great AI, they're building the infrastructure to actually run a business on top of it, which is where Stripe comes in. Stripe is built for whatever comes next, with planetary scale financial infrastructure to help you power any business model. As a matter of fact, 86 of the Forbes AI 50 run on Stripe, along with industry leaders like Salesforce and Pepsi.

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The business world is moving faster than ever, and when change hits, we need to learn in real time. On rapid response, you'll hear candid conversations with CEOs and leaders making tough calls about AI, human talent, responsibility, and the bottom line. How they navigate uncertainty, pressure and high stakes moments. I'm Bob Safian, former editor in chief of Fast Company, and I'll be your host. As each episode breaks down what you need to know right now, you can find rapid response wherever you get your podcasts.

I know a big focus of your investment thesis is vertical AI. My definition of vertical AI is basically AI ifying legacy industries like supply chain, manufacturing, financial services, insurance, construction, all these like unsexy industries. But where there is an opportunity to reimagine how work is being done, where do you see AI creating value in these industries? And maybe the best way to do this is if you can give us some examples of companies from your portfolio.

So I will give you a one two punch answer. I think as I contemplate it, 1st is there is a low hanging fruit opportunity set across these verticals, and that is to drive productivity orders of magnitude higher by way of understanding workflows. I think the easiest, and I'll do that in air quotes, path to creating value is to go in and saying, hey, pharmacy fulfillment is being done in this manner. There are five different systems that have been stitched together, different software providers.

Human touches the prescription, for example, in every step of the way. It gets digitally faxed, they have to take it, you know, type it up in the other system, et cetera, et cetera. So that, to me, feels like low hanging fruit. But the key is going to be to have access to the actually, the deeply vertical data that takes place to get the performance, and perhaps even more importantly, understanding the workflows. A lot of the challenges that we have in different industries is not that it can't be done, is that the workflow is in the mind of somebody, or in a 600 page, you know, binder that collected dust.

And there have been hundreds of deviations from it. So, but if you understand it, I think that's a low hanging fruit to drive quick productivity, enrich an experience, be able to actually deliver the technology in a different way than what it has previously been delivered, and make the ROI quite obvious. So I've just described a company called Assafi in my portfolio, whereby that's literally what they do, and they give visibility. Also on the you know how effectively prescriptions are being filled, because little known fact 30 of prescriptions do not get picked up.

So you've gone to the doctor, you've bothered, they've given you a diagnosis, they've given you at a minimum a treatment, if not a cure, and you don't go to pick it up. So there's a whole process and a lot of ways for them that are important,

One of the concerns I generally have, and that's like, kind of materialized even stronger in the last six months in the vertical AI space, is the frontier labs are moving so fast, but they're also adding capabilities really fast. And so you can imagine how a supply chain company they can build their own cloud agent to do a lot of this work, and then these companies become obsolete.

become obsolete. So I think there are two schools of thought competing right now. One is you go deep and specialize, the other school of thought is what a lot of the agent sort of large language models and players like Microsoft with Fabric and OpenAI and Anthropic. Whereby they're saying, you can just buy us as the layer and then build the agents on top of us, and therefore you don't need specialized tools. I think the reality will be hybrid, as is always the case in this world, so we will be if everybody's coding internally and building their own agents.

I have a lot of questions around the long term sustainability of those agents, the quality, performance, compliance.

That's why there's still opportunity in vertical AI, right?

And not only that, but it also begs the question, how else do these companies that are vertically continue to move up and down the stack? Whereby the advantage is not that the foundation model has seen it all, the advantage is the depth, is trust, is governance. There are all these other facets that are very, very important.

You know, the other thought I had, and I'll use the legal industry as an example. Companies like Harvey AI, right, have developed AI solutions for law firms, and they have seen success. But I'm also seeing this idea of reimagining what a law firm like an AI native law firm, right? Where do you see the opportunities? And it's an and, or is it an or?

I can make both arguments with the same level of conviction and be an opposing views because we really truly don't know. I'm increasingly believing, and this is the 2nd part, I said, it's a 12 punch. I'm increasingly believing that the company of the future should really start with a clean slate. So coming back to the law firm of the future, it could look completely different. So as you look forward and you look to the future, why can't I have my legal agent be there and the lawyer just provides the judgment?

I'm really focused on this judgment piece because think about agents. A model, whoever's model you pick, has been trained on all web data, and we can use that as the best, at least digital proxy for society's humanity's data. If a human had that kind of data, they would have been sort of a super overlord of sorts, right? We would have been way smarter. The models are not so, and I think it's this notion of, you know, their neural nets, so they're really dealing with the brain, not with the mind.

While we humans, as limited as we are, relative to the speed and processing and other capabilities that agents and models have, we humans actually can draw a lot of decisions with very imperfect and limited data. Yeah, and that Models are dumb

that, yeah, and that judgment, I, and so it's I, it still

a judgment.

is human.

Yeah, I think I think for for the safety of our species, I think we need to retain the judgment.

I'll be right back, but 1st, a quick break. So I want to move us towards, like, more of the horizontal AI and AI infrastructure, but I will start with the governance and safety part. I believe that that is a very important area to invest in, but we haven't made any investments in that space. Because I don't know if that's something that the labs need to take on. Like, is there space for companies that sit on top of the frontier models to ensure governance?

And so I'd love to hear your point of view.

so we invest actively in cybersecurity, and I would say the security plus safety, plus governance, and honestly, not just digital, but physical security are kind of coming together under one umbrella. Um, so I do think that there's high demand for governance. Every enterprise is trying to figure it out. Do they go to their established security partners because they are offering a new module or a new, you know, governance agent? You know, what do you do? So, for example, for my own AI usage, I get so many mails.

Actually, no, exactly, I get 45 to 63 mails per hour. It's incredible. And so I need some sorting and prioritizing, and in some instances, pre filling, pre drafting, and then I go and sort of change it and press send. But that means that the agent gets to look at all of my content, all of my emails. So we have a company called D2 that's basically providing that MCP security, and we couldn't be in compliance if we didn't have that capability applied.

So it's both regulation and safety and security. So I actually think that that's one of the areas that will get a lot of funding and the demand for purchasing it, whether it's delivered as AI service or as software plus service, it's almost sort of, um, indifferent to price, almost, because, you know, you must have it. This is an existential question, so it's actually a nice area to look into.

Yeah, okay, great. So you have invested in Liquid AI, which is a frontier lab, um, based in Boston, which is awesome. Tell us more about that and and your thesis around, like, where is the opportunity in horizontal AI?

so Ramin, Hassani and the amazing Daniela Rus, um, founded that business out of MIT. Unlike the other frontier models, what Liquid AI and Ramin is doing is actually computing at the edge, so that, in and of its own, sort of has different ramifications for compute efficiency. On the positive, they also, um, do something really interesting. So when you think about the pipe of any sort of agentic action that gets taken, how you use the models, the pipe is hungry the same, whether they need that full compute or not.

So the layperson's analogy that I give is it's a concrete pipe and it doesn't change, and you're flowing, you know, data and compute, and it's calculating and giving you outcomes, whether it needed to do the whole thing or not. That's how it's set up. What's amazing about liquid is that it's flexible, sort of the notion of liquid, so it shrinks if it doesn't need all that compute and it expands as it needs it. So, by default, those two facets really stand out to me because effectively it makes it a lot more efficient.

And, oh, by the way, for some of the kids of ours who are into AI, you know, environmentally friendly and all sorts of other ramifications. So there, I think there is a real advantage, not just in performance, but what it takes to deliver that performance. So I think there is a wave of opportunity with these big models, recursive AI again, with self learning, that are pushing into the next paradigm. Because at some point, I do think that we will run out of sort of improvements we can make to the large language models.

And the next big breakthrough will be a paradigm shift, and I think these frontier labs represent the potential for that next paradigm shift.

We've made an investment in a company called Odyssey, which is a world models Models, Yeah, company. And then we're also investing in several like physical AI, and also like, yeah, AI native interfaces, too, is an area that is so interesting.

So I'm actually quite excited about our local ecosystem and what we're doing with physical AI.

I was gonna ask you about that because obviously we're both Boston based, we invest all around the US. I think it's the same for you we as well.

have. We've always had more of a tendency to stick to the East Coast, and we do West Coast investments, but more selectively.

Yeah, so what is your point of view? Because there's a kind of a narrative that a lot of AI is happening in the Bay Area, but what's your view on what's happening on the East So I think Coast?

we need to acknowledge, and then we need to own our strengths. We need to acknowledge that the ecosystem in San Francisco, in particular, even the Bay Area, is extremely well developed. The, you know, having the big technologies be there just by sheer density, there is a lot of blessed density, and let's just not bother like it is. Where I think we have the capability is we have the highest quality students, professors, we have that kind of density.

And, you know, with initiatives like what Ryan Durkin has done with Mass AI, we're finally waking up and taking pride in what has been built. I mean, look at how many robotics companies there are, look at all that is happening across industries. Let's just not sort of worry about what we are not. I want to speak to what we are. A lot of founders, big ideas. It's speaking of students and undergrads. Merc Mercor came out of where Cursor came out of where.

Where I think we need to be sure is to capture and support these teams before they move to the West Coast to build out. I also think, and you know, you're an MIT person through and through, but MIT has not been as picked over as some of the West Coast schools. So there's also this moment in time where not only do we have density, not only do we have the drive, not only is Anantha and Sally, so the provost and president, driving this, you know, renewed energy around entrepreneurship.

But actually, we have the talent that's still here and now can do both, and the desire, so I think we should capitalize on that again. You want to create multi generations of students who contribute to industry and vice versa. Also, research funding has dried up, so partnering with industry becomes a lot more important than it used to. And we are all asking a lot of questions, at least from outside in. This is my take around the future of education.

What do you if Livy, if your daughter said,

Oh, please don't do this to me. But

yeah, if she said, You know what, mom, I have a billion multi billion dollar idea, I would rather go build, what would you say?

1st of all, I would support it, but it cannot be at the expense of an education. So she does it before, she does it after, she does it along. Whatever form education takes six years from now, right? We might look very, very differently. I want my. So, an education, maybe, you know, higher ed form again, maybe something else emerges that we don't even know about. But what I do not want my daughter to be is rich and ignorant.

I'd rather she be happy, well adjusted, well, worldly, like worldly

your daughter is very like, informed multidisciplinary, and she has a lot of interests.

is. I want her to be a full human in her fullest capacity, and I want her to embrace AI to know more, to discover more than she otherwise would not be able to. For many, many generations, higher ed has been that path. So if it continues to be, that will be very important to me. We'll see if she listens or not, if it's another form, in whatever form. But otherwise, we become so narrow, so focused, and with algorithms that are reinforcing in their nature.

In terms of what information we get fed, we confuse knowledge with information, and sort of we lose that worldly point of view that brings us together rather than points fingers separates us.

what is the biggest mistake you've made as an investor?

Um, I love all my companies, and anything you know about investing tells you that you need to focus on the winners and getting sort of the middle performers to move up. It goes counter to how I'm wired, like, I wanna save, so that is a constant struggle. I've gotten better at it, but I do not do what I do. You've got to put your effort truly, and I mean this, I mean it for myself, I'm saying it to you, but I'm saying it to myself.

You got to put the effort where you can generate the biggest returns because I wanna support my founders. That's why I'm in the journey, that's why I love it, I wanna see transformation. But we're also managing money for endowments, for pension funds. Everybody's mind goes, Oh, yeah, it's the rich guy's money that you have, and you're just making them richer. No, no, no. It's also the scholarships that need to be funded for families that can't afford them out of these endowments.

And they give us a piece of, you know, that endowment for us to create, you know, multifold returns. Or is the teacher's pension funds, or, you know, or firefighters pension funds? This is their livelihood. So it's very easy to say I'm founder friendly and lose that perspective, so you got to balance both. But yeah, I feel so vested.

what is the one that got away?

Depending on the day that you ask me, is perplexity because we saw it many, many times and passed on it. My partner, Clayda, saw it many times, got a material and passed on it because it was really a thin layer wrapper and we were looking for more of a moat.

And that's why you said, depending on the day you ask Because me, because

there are the there are days where you're like, Yep, I called it okay, great, I don't feel so bad, and there are days where you go, Oh my god. But it also speaks, in full candor, to that execution piece of how can you reach the market, getting adoption? Because at some point, like, you know, thinking, the year of mobile apps, it wasn't that your app was so much better than mine, or vice versa. Is that you caught that virality?

However, it got in the hands of consumers. It was very hard for a 2nd player or a 3rd player to replicate. So, you know, there's more to the moat.

yeah, absolutely. How are you using AI within Glasswing? I know you're using it in all sorts of ways.

We have, gosh, like eight AI engineers, full time.

that's amazing.

So over the last few years, we've actually built out what I call the brain diligence platform. Not only is it multi agent, they all interact with each other. There is a, you know, supervisory agent that understands a meta task, but is wonderfully trained on huge amounts of data, and yet probably very little data when all considered. But it's an incredible tool that maintains the depth of diligence, but helps us move much faster. So what we have done around the AI platform has really, really made a difference, where basically I would estimate about two, two and a half weeks worth of work in half a day.

Amazing That does two things. In environments like this, we can ramp up quickly, especially because we invest within certain theses, so we live deeply in those theses. But also sort of be able to line up the human experts to augment the customers. Why are you buying it? Et cetera, so that piece is quite interesting. We also have done we have, you know, the sourcing mechanism, which now we've pulled from, like archives and all sorts of different sources.

to predict who could be a

Who's starting?

who's the certain.

So, you know, and last week it was about 104 zero founders, this week was over 105 zero, and they get ratings. And this is an attempt to basically go discover them before they tell the world. Work in progress, I love that. Yeah, yeah, but really sort of unique, and also it helps you look at the founders in the last three, four years that have made it big. And you go, what are the characteristics? And

what are the characteristics?

I know it's been interesting. So Unisquare Ventures always used to say when it comes to it, it's founders that have known each other since childhood.

Yeah, that is so interesting.

I mean, that's one data point. I think it's probably a much more complex formula.

If you're listening and you're thinking of starting your company, who's your bestie? Start it with your bestie.

Started with your bestie that you know you've seen and

Yeah, trust.

trust, but also if you've managed to stay friends through the years of, you know, college separation, all that. There's some bond there that when the going gets tough, that bond can carry you through. So that has been important. But back to your question, so there's a lot around that, there's a lot around automation of tools. Again, you know, my email bit has been just life changing, and I think it's only the beginning.

Yeah, so exciting. What do you think the job of a VC will look like in the next few years? How will AI Judgment, change it? Judgment at the end? Yeah,

hm, hm. At the end, I think speed of research and due diligence and all that will happen. It's about how we weigh the analysis. Again, I think analysis will be automated. It's about the judgment and the patterns that may not be captured in the numbers that are hard to quantify.

yeah. What are you most excited about in the kind of near future?

I mean, we're changing the world. We are I hope we're doing I love it for good, and I hope it's human centric, but I know we are in our own immediate sort of worlds. But yeah, I mean, I think this is bigger than the industrial revolution. What will the social norms be in the future? Will we need to work in the same manner? I mean, it's an incredible idea to contemplate, and it's not far fetched. What do we do in new spaces, outer space?

What new avenues do we open? What does exploration look like? It's a whole new world.

whole new world. I love it. Rudina, thank you so much for joining us on the show. This was great.

Thank you for having me. Always fun.

Always fun. That was such a fun conversation with Rudina. Three things stuck with me. 1st, I can so relate to her biggest mistake as an investor, which is she loves all her founders just the same. And you're supposed to really focus on the winning companies. I feel like that's a lesson I'm learning as an investor myself. So it was great to hear her share her experience there. Two, we spent a lot of time talking about human judgment and the importance of human centric AI, which is, of course, something I care deeply about and I'm very passionate about.

So it was great to see that that is something she thinks about, too. And then 3rd, what she looks for in founders. I thought it was really cool how she looks for founders that are coachable, especially when we are investing kind of super early in their journey. And you want to be able to be a helpful partner on the journey for these founders. Thank you for being here. I'll be back next week with a new episode.

Pioneers of AI is a Wait What original. Our executive producer is Eve Trow. This episode was produced by Megan Tan. Video editing by Eric Purcell. Our senior talent executive is Stephanie Stern. Mixing and mastering by Brian Pugh. Original music by Ryan Holiday. You can join the conversation on LinkedIn, Instagram, TikTok, YouTube and X. Just search for at Pioneers of AI.