Amit Patel Managing Director Owl Ventures and Rishi Taparia Pre-Seed Investor Garuda Ventures: AI B2B and Education

Amit Patel Managing Director Owl Ventures

Rishi Taparia Pre-seed Investing Garuda Ventures

Investment Focus

Rishi: So here at Garuda Ventures, we are a pre-seed focused fund investing into founders at the various earliest stages. ‘Deck in a Dream’ is what we call it. Our focus here is largely on B2B focused businesses across software, across fintech, and across cybersecurity. All categories where my CoFounder Arpen and I have built companies before, as operators, and where I have also previously invested. And so we’re sticking to our knitting in big categories that are being disrupted now and backing founders as they’re getting going, as their first true believer.

Amit: Yeah, absolutely. Happy to, and thanks for having us on today. At Owl Ventures, we’re an education technology-focused venture capital fund. In fact, we’re the world’s largest EdTech-focused VC fund. We invest across the education spectrum, so it’s everything from early learning to K-12 to higher education to Lifelong learning, corporate learning, adult learning, upskilling, reskilling, however you want to refer to that fourth category. We also invest in what we call the EdTech Plus category. So that’s EdTech Plus other major sectors like FinTech or HealthTech. And we’re Sage Agnostics! We’re doing everything from early to growth. And the majority of our investments are here in the US, but we’re also investing internationally and have made investments across Latin America, Europe, Africa, and in various parts of Asia.

I’d say AI has certainly been a big topic of discussion. I think you’ve also heard from a lot of the mainstream AI companies on the potential impact that it could have on education. Some of the use cases are the kind that listeners may have seen like Khan Academy demonstrating a personalized tutor. You’ve heard Sam from OpenAI talk about the kind of data and analytics applications that could be there in education. And this whole real vision of delivering a personalized journey for students based on their previous learning history and really keeping them there. Research has shown this is the best zone for them to learn, which is this proximal zone of development. There’s been a lot of attempts at doing this historically, when it comes to education technology. But the really exciting piece about generative AI is that it has the potential to deliver and create a truly unique learning journey for each individual learner and keep them within that proximal zone of development.

Will teachers still be required with AI?

Amit: We are 100% aligned on that fact at OWL! We believe that, you know having the teacher in the loop or the human in the loop is the best way to actually utilize this technology. Because the impact that the educator can actually have on your life is immense. And I recall, that my Principal from my elementary school or my third grade English language teacher and all of these folks who showed belief in my potential, who I still remember and have driven confidence in me today. And so for us the way that we look at this technology is the demand on educators is going up and up every year, like the number of students they’re expected to teach and the number of things that they’re expected to do. And there’s only so much time that they actually have in a school day to get that done! And the hope is that this technology can take some of those routine or repetitive tasks off their plate and then actually allow for more time to have either one-on-one or small group interactions with students. Then they can actually have much more meaningful and impactful interactions. This has been shown in research to have the greatest impact on learning outcomes. So we are very much aligned on the fact that having the teachers still continue to be the center of the educational experience. It is something that we’re big believers here in Owl Ventures.

Amit: Let’s take generative AI, not just in isolation. As the economy itself has become more global in nature, as we move more into a digital economy ourselves as well, this whole idea of you are going to be done with education by the time you’re 18, if you graduate from high school or 22 in college or maybe somewhere in your 30s, if you’re going to grad school! And that’s all the education that you need to have a successful career? That is not the world that we live in anymore. First of all, advancements such as Generative AI are coming at such a rapid pace.

Amit: And secondly you have this global economy that’s happening! So you’re not just competing with employees in your domestic country, but on an international basis, either as an individual or as a company. And third, people are thinking about having, not just 20-year careers, but 30, 40, maybe even 50-year careers. And so somebody that is working in a field today or thinking about working in a field once they graduate. Actually that field might not exist by the time they’re thinking about retirement or in their last decade of their career.

Amit: And so again, this concept of lifelong learning or upskilling or reskilling is the reality of what individuals and companies need to think about if they want really have that successful career for 30, 40, or 50 years. And so we are also investing in companies that are helping adult learners think about this, as they are considering what is the next career that I want to take on? And one stat that I would also share is, here in the US, the majority of higher education students are now non-traditional students. It’s not the 18 year old that just graduated from college! It’s an adult that is thinking about his or her second or third career. They have a family, they have kids, they might have a job already. And so thinking about how to serve those individuals in a way that is actually convenient and allows the education to fit into their other life obligations is hugely important. And so these are the types of companies that we are continuing to invest in here at Owl.

AI is changing Everything

Rishi: I think in a short sentence, AI is changing everything, but it’s not unlike the technology evolutions that we’ve seen in the past. When I first got into tech investing in the early 2010s, we were just experiencing the transition from the way of building software to the cloud and then cloud to mobile. And so obviously, what that did was change the modality for everybody and the expectations of what technology could do? And how plugged in one could be with what access to information they could get? And we had companies that reoriented in order to adapt to the changing technology. We had new companies emerge as a result of the new technology and capabilities. If you think about The concept of Uber, as an example, it is now ubiquitous. Everyone talks about it. The idea of getting into a stranger’s car and going from point A to point B, you don’t give it a second thought. But it was not too long ago when that would have been unheard of and unthinkable. And that’s an example of a mobile native company that could only exist because of the new technology in the iPhone and effectively a computer in your pocket that started it all.

Rishi: And so for us, as we think about AI and how that impacts the portfolio, ultimately, every company is going to be leveraging AI capabilities, generative AI capabilities in their suite of products, whether it’s a new product that they roll out, whether it’s in working on inefficiencies that are driving that are not within their own capacity. Companies, whether they’re AI native businesses that are taking advantage of problems that now exist because you couldn’t previously solve before. And so they’re using the technology to solve it. For the sake of AI isn’t interesting to me. Ultimately, it just comes back to how are you solving the customer’s problem? What’s the value proposition? And how does the new technology capability make that better, easier, faster, cheaper, more efficient to deliver?

Humans have the Ability to Put all the Pieces Together to Solve a Problem, But AI Doesn’t Yet?

Rishi: I think that that is very true. And I think one of the biggest challenges right now is the capabilities in AI are not evenly distributed. And so as a result, the expectations versus reality for most experiences are not being met. And I fundamentally think we have an AI onboarding problem, quite frankly.  that needs to get addressed, because as you alluded is this the time to trust AI? It is a very important thing. and for people to have trust in the solution and that it’s going to deliver the expectation they have is critical. I think this is where we’re still in the very earliest of innings and I think there is a lot of talk in The Valley of are we kind of at the AI peak? or are we at the top? What does that look like? I actually think we’re just getting started because if you can look back to the mobile era, the first few companies in the first few years after the mobile era unveiled itself didn’t lead to the best companies! It was only after you had people who came up thinking you could build not any other way than for mobile and mobile native, then you got companies like Uber. And I think we don’t yet have the kind of engineering talent and founder talent that has only ever been AI native and couldn’t even think about building a company any other way.

Rishi: I think the capabilities, what’s possible, what’s going to be unleashed and unveiled in three, four, five years from now is actually going to be far more interesting, even than it already is today. Because there’s going to be an entire new squad of people that have come up with AI only. And I think that’s where you’re really going to start to see the acceleration of AI capabilities. And I believe some of the meeting of expectations, as far as the customer experience and what the technology can deliver.

Amit: Yeah. I echo a lot of what Rishi said and I think he put it nicely when he effectively said we’re in this first pitch of the first inning when it comes to AI! And I think there’s a couple of things that I would add to what he said, which is first of all, we get this question, not only from our portfolio companies! We get this question whenever we’re talking to universities as well as the K-12 system in terms of how do I actually use this technology? What’s the best way for me to find the value that I’m going to get from AI? I think one thing to remember is at the point that we’re at with this technology, it’s messy, right? It’s not clear. It’s new, and so I think step one is just to start to use it. And you’re probably kind of not going to really land on a great user case when you first start to use this stuff, like maybe I’m just using it for a Google replacement? I think, as you start to use this over time, you start to discover more meaningful interactions, the way that this technology can actually deliver value in a way that maybe had not been the first instinct that you had on how to use this type of technology?

Amit: That’s point number one that I’ll make. And then point number two is, I also think right now we also have these large scale general kinds of AI models that are trying to serve a lot of different user cases. I think as this ecosystem starts to mature and in the education sector, there are the EdTech companies that are coming in and building on top of these LLMs or utilizing them and then kind of verticalizing them for certain use cases, contextualizing it with data. That makes the interaction just much more informative, personalized, and relevant. I think that’s where you get much more satisfaction from the end user because it’s a response or an output that doesn’t seem generic but is really taking into consideration all the contextual data that it needs to make it a really meaningful interaction or response. Oh, 100% and I think as you’ve seen this iteration that’s happened with these LLMs with each version that is coming out, there’s just a much more meaningful improvement compared to the last version.
And so the speed at which this is happening is also increasing as well. And so where we are today, I think you probably are like most folks and will say, hey maybe i have an idea of where we’re going to be in six months or or maybe 12 months which is stretching it. But I think a lot of people are going to say quickly, I don’t know what’s actually going to be possible within 24 or 36 months, because the technology is improving at such a rapid pace. And then it’s really amazing, what might be possible in 24 or 36 months?

How will Education be if the US shuts down the Education Department?

Amit: Yeah I think this is a good question. This is something that may go ahead? Yeah I think this is a good question. I would say a couple of things. One is we’re continuing to monitor exactly what developments are happening and things are continuing to develop on an ongoing basis. A couple of things that I would say is a lot of the funding that actually happens is happening, especially in the U.S., at the local level, which actually is the right way a lot of these decisions should actually be made. And so that’s one thing that I would say is important to keep in mind and given all of the changes that are actually happening. I think the second piece that i would say is, there’s been some discussion about education and labor actually coming closer together. And one of the things that could be really interesting is having a closer connection between the education that’s happening and then the employment that’s actually results. Right. And especially when you’re thinking about higher education and adults spending on reskilling or upscaling, this educational experience actually has the ROI that I was hoping that it would. That is something that happens because you are seeing greater collaboration actually happen between education and labor. I think that that’s something that would be great because, again, having these things live in silos doesn’t really allow you to have the data that you need to have that iterative improvement cycle. That would be quite helpful.