EP 484: The Next Frontier of Startups: Domain Experts in the Age of AI
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This is the everyday AI show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. So quickly, uh,

I mean, with everything that's happening in generative AI, you know, if you listen to this show, things are changing, not even by the week, by the day, almost hourly, right? So not only are the tools and the capabilities changing so quickly that startups have access to, but it also changes things on the venture capital side as well. All of these groups that are investing in these startups that so many of us use, right? So even if you're not in the startup ecosystem, uh,

or in venture capital, I think today's conversation is going to be especially relevant because what's happening in the startup and what's happening here at NVIDIA GTC is going to be changing how we all work in the near future. All right.

All right.

We definitely see that we are live here at the NVIDIA GTC conference. The eyes of not just the AI world and the tech world, but I think the eyes of the business world are on what's happening here at GTC. And we're very happy and excited to be partnering with NVIDIA to bring you a lot of exclusive insights

in interviews from industry experts. So let's just get straight into it. Speaking of industry experts and startups, that's what we're talking about today. So please help me welcome to the show Alia Bahbool, who is the platform manager for the NVIDIA VC Alliance. Thank you so much for joining the show. - Yeah, I'm glad to be here. - All right, so tell me a little bit about what you do. What do you do as the NVIDIA, or sorry, the platform manager for the VC Alliance?

Yeah, so NVIDIA's VC Alliance is really our program to support VCs that are investing in the AI ecosystem. So we work with VCs on kind of the two aspects that VCs work on, so investment and portfolio support. So on the investment side, we are really working with VCs to bring them cool startups that we see that they're excited about and potentially want to invest in.

And on the platform support side, we're kind of working with VCs to support their portfolio companies on AI optimization, AI implementation, really helping them figure out how we can help their startups scale more quickly.

So I think when most people hear NVIDIA, they think GPU. They think of the company that's powering AI, but they don't necessarily, unless you're in the space, I think a lot of people don't know everything that NVIDIA does on the VC side, on the startup side. So let's maybe start there. NVIDIA is supporting thousands of startups. How does this all work, right? Because, yeah, people just think, oh, GPU chips. NVIDIA is more than that. Yeah.

That is definitely true. And we do have GPUs. That is part of what we do. But other than that, we also have a lot of software that startups can use to, again, work on their AI. We have access to a lot of models. We provide access to a lot of open source models, which can be really useful for startups.

So really there's a lot on the software side that we're doing that startups get discounts and computing credits. So a lot of other things aside from GPUs that a startup needs to kind of run their AIs. Yeah, and if you've listened to the show before, we featured...

some of the startups in the Inception program at NVIDIA. So how does the VC alliance in the Inception program, how do those two kind of entities work together? Yeah, so the VC alliance kind of fits, I would say, sort of like inside the Inception program in the sense that we specifically work with portfolio companies of VCs.

So Inception, you know, as you might know, is really a program for startups in general. They get a lot of access to support on kind of

um you know software and hardware and things like that um but we are specifically working with the portfolio companies of bc's on you know a similar type of thing um again support um and figuring out how they can you know better build their ais um so it's kind of just like a subsect of consumption and you know where does that kind of um handoff take place right because you know uh

I know there's tens of thousands, right, of startups in the NVIDIA Inception Program. You know, how do the startups in there, right, because I know we have a lot of, you know, startup founders listening to the show, where does it get to the point where they start working more on your side, right, versus just being this big umbrella of support that is the NVIDIA Inception Program? Yeah, so I would say for a lot of startups, what can happen is their VCs will actually recommend

them to us. So through us and we're able to kind of direct them to the support that they need. So I would say if you're a startup that wants a little bit more support from inception, what I would recommend is if you have a VC backer to get them to email us or kind of reach out to us on the VC Alliance team and we can kind of work with that startup on a more personalized level.

Okay, so it's almost like a bring your own VC, right? Like a startup, if they're in the inception program, they can bring their funder, their VC, under the VC lines. Exactly, yes, they can do that as well. Okay, cool. So before we get into kind of how venture capital and startups are changing so much right now in this concept of domain expertise, right?

Share a little bit about your background because I think that's going to be especially helpful for our viewers and listeners to know because you have a PhD in AI. Yeah. So I started off doing my PhD. I actually did it in astrophysics and AI. So basically looking at astrophysics with a lot of large data, how can we use AI to process that more quickly?

So that was where I started. And then I left and I kind of joined the investment side. So I joined Morgan Stanley first, building AI models to predict the stock market. And then I left for the kind of private investment side and joined the VC space.

Yeah, now I'm here. Yeah, and this is such a great combination of your background and your current role. It's pretty cool. But let's maybe hit rewind first because I think the startup ecosystem has changed so much, right? Especially over the last year or three, but even before that.

You know, can you maybe bring us up to date? Because, you know, as an example, yeah, five, 10 years ago, there were still startups working in AI. Artificial intelligence isn't new. But now it seems like, I don't know, maybe every startup is AI powered or AI infused, AI something. You know, where are we at just in terms of kind of the current landscape of the startup ecosystem when it comes to AI integration? Yeah.

Yeah, I think that's definitely true. I remember back when I was doing my PhD, you would see almost no startups advertising that they were using AI. And I think that maybe partly was because less people had heard of AI, so it wasn't as exciting as it is today. But yeah, now I think AI is a lot more exciting.

Even just if you look at like models, like LLMs, they're a lot easier to use. You can kind of plug in your own data and get a lot of outputs that are very customized. So definitely I think a lot more accessible than they were maybe five years ago. So yeah, I think you're seeing a lot more startups starting to use it and a lot more startups that are starting to, I think, really use it in some really interesting ways.

can startups really thrive if they're not, you know, if, if AI isn't an integral part of their operations, like, are there still like, you know, the equivalent of like offline startups? I mean, I think there definitely are. Um, and I think I, I sometimes see some of them and we kind of have these conversations about like where they can use AI to like optimize what they're doing. So, you know, for example, um,

there was a company that I was talking to that was in the fashion space and they were like, AI is not really applicable to us. And I was like, well, you can actually use AI to optimize on the back end of what you're doing to find customers or grow your presence or even just optimize your supply chain, for example. So I think there's a lot of things that companies can do on the AI side that even if they're not necessarily in the AI space, they can leverage it to kind of...

scale a lot faster than they would have maybe five years ago. Yeah. So I want to get to kind of a little bit how I opened the show in talking about this idea of domain experts and how AI is really changing the startup landscape. What the heck is a domain expert and what is their current and evolving role when it comes to working in startups?

Yeah. So I like to think of a domain expert as someone who really understands a problem. I don't think there has to be, you know, a specific type of expertise. Like they don't have to necessarily be a product manager or, you know, an AI expert, but just someone who has really kind of worked in this space and tried to understand the problem that they're trying to solve. So, you know, they could be someone who's worked in sales for, you know, 10 or 15 years and has really seen kind of

the space evolve, understands the problems, the pain points, all of those kinds of things. I would say, you know, they're probably a domain expert. They understand, you know, what's going on and kind of what needs to be done to make the space, you know, sort of run more smoothly. Yeah, I think, you know, I've always had this thought when you talk about startups, it's

you know, some, you know, fresh college grad, you know, in a hoodie, just, you know, coding in their bedroom, you know, coding in their dorm room, right? Going back to, you know, kind of Facebook, right? Like, I think that's what a lot of people think of.

Have you seen this in your role so far? Have you seen this change, right? This concept of, you know, now domain experts are maybe more important than, you know, the recent, you know, Harvard CS. Like how many, you know, CS students from Harvard and Stanford do you have on your team? Yeah. I mean, I think you probably still need those, but I,

But I have seen from a lot of conversations with VCs more recently that they are looking for people who really, truly, deeply understand the problems that they're trying to solve. And I think that is because, as I said, AI is becoming more accessible. And I think that's really great. But that means that in order to differentiate yourself, you need to be doing something. And that means that if you know a problem better than anyone else on the earth, you're probably going to be able to solve it maybe slightly better.

So that's kind of what I hear from a lot of these things these days. Yeah. Are you seeing or hearing from conversations that you're having a shift toward an emphasis on having maybe kind of quote unquote mid-career professionals powering or being a big part of a startup team? Are you seeing this shift happen? Yeah.

Yeah, definitely. I think even a year ago or eight months ago, everyone was just like, "Let's invest in AI." And then you were seeing a lot of those young grads getting a lot of investment. And I think now what I'm seeing is that VCs want to be a little bit more picky about what they're investing in, a little bit more careful. I think we've seen AI change really quickly in the last year.

Now I am seeing that they really want to be investing in people, I think, who understand the problems that they're solving. How much of it, and maybe I'm wrong here, but how much of it could be attributed to

large-language models just becoming more capable, right? I mean, these models now, when we talk about the commoditization of knowledge, right? Does that have anything to do with why domain expertise now is maybe more important than it was a year ago, three years ago, just because knowledge is more and more accessible to anyone that can sit behind a chat GPT or a cloud or something like that?

Yeah. I mean, I think that's definitely true. Um, you know, I was, I was actually just recently talking to a VC that's attached to a consulting firm and they were saying that, you know, for example, they are more and more leveraging LLMs in instead of analysts. Um,

But that wasn't the case for their senior managers, that they still really needed those people because they knew the problem. They knew how to solve them. They knew how to work with clients, all those skills. And so they were able to actually replace those people who really had a deeper knowledge of the space that they were working in. So I think it's exactly that.

Yeah, and you bring up a point which I have a lot of hot takes on, but even this concept of deep research. You see all the AI labs coming out with these deep research, OpenAI and XAI with Grok and Google, all of these. A lot of NVIDIA partners coming out with these tools that just research really at the level that an entry-level management consultant might be operating at. Exactly.

Right. So, you know, when it comes to domain expertise, um,

How those people, right? Like if you look at these reports that these, you know, LLMs can generate in, you know, two to 30 minutes and, you know, a domain expert looks and they're like, wow, you know, that would take me many hours or multiple days. And they're wondering like, okay, I know that I have talents. I have backgrounds, right? In, you know, sales and marketing or whatever it is. How can domain experts still find their way in the startup ecosystem when the tools available are becoming exponentially more powerful, right?

Yeah, I mean, I think this kind of starts to go into like the esoteric, you know, AI. But what I would say is that, you know, even if like, you know, a deep research report comes out that AI has generated, I think it still takes someone who understands that domain to kind of go back to what we were talking about to actually be able to say, look, what do I do with this information? How do I put it into action? Or how do I put it into, you know, to create a startup with it that is actually able to do something useful?

So I think there's still a lot of space around how do we use information that still requires, I think, people who have had a lot of expertise, like turning what their experiences have been or what research they've collected into actionable insights. One thing that I love about NVIDIA and learning from experts at NVIDIA, such as yourself, is the collaborative environment at

at NVIDIA, right? You know, if you're at one of the AI labs, you know, I think it's so super competitive, right? But NVIDIA, you know, your partners were just about everyone because everyone uses your technology to build their AI. So with that in mind, right, I'm sure that you're working with, you know, venture capitalists and startups, you know, working, uh,

across many different fields and sectors. What are you seeing like common trends, right? You know, whether it's on the VC side or the startup side, when it comes to AI, what are some common trends that you're starting to see right now?

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Yeah, I mean, I think, you know, as you said, we kind of are sort of this node in like the ecosystem of startups and VCs. So I think we work across like a lot of sectors. We work across like a lot of different kinds of companies, whether they're more on the application side or, you know, on the deeper kind of AI side.

But I would say, again, I think one of the trends that I've really seen is sort of this idea that you're starting to see startups that I think are a lot smaller and a lot more laser-focused on, I would say, more narrow problems, and then they're trying to solve them more deeply. What does that mean? How can startups focus?

find that, that narrow application for, you know, their app or, or their SAS. Like how can they find that? Cause I think that's so important. Yeah. Move so fast. It doesn't move really fast. Um, I would say though, I think, again, I think if you've kind of worked in a space and you know what the pain points are, uh,

you probably know what pain points can be easily solved by an AI that might come out tomorrow, or that ChatGPT might build on top of or build something that's easily kind of replaceable versus problems that I think are harder and maybe more complex to solve that require your intimate knowledge to actually go about making change. Yeah. And that's a great point that you bring up.

because all of the big AI labs are continually putting out new and easy to use infrastructure. As an example, OpenAI just released their agents SDK. I've

I believe last week. Yeah. It's hard when I do this every day. I'm like, was that last week or was that like three months ago? But I mean, how can startups even begin to deal with the pace of innovation at the big AI labs, right? Because you could spend six months, a year, 18 months building something, and then all of a sudden, one of the big AI labs comes out and releases something, and you're like, that's what we've been working on. Yeah. I mean, I think...

like competition is going to exist. I think it's part of the world that we live in now. So I would say probably for a startup, again, you know, I think this is, this is more on like my personal opinion. I think it's a matter of, uh,

getting customers and making sure that you're really solving the problems in a unique way. Because I think that's really what's going to allow you to thrive in a world where everyone is trying to come up with the same ideas in some sense. Yeah. What advice, because I'm sure that you hear both from on the venture capital side and the startup side, is it getting increasing on? I'm observing from the outside.

Do you think it's getting increasingly harder for these companies not just to find product market fit, but to actually get the users, get the paying users, get the traction because of everything that's happening at the big AI labs and just the sheer breakneck pace of large language models?

Yeah, I mean, I would argue, you know, to disagree slightly, I would argue that product market has probably always been difficult. I don't know that I would necessarily say it's more difficult today than it was five years ago. And in fact, you know, I might say that it might actually be slightly easier because I think, you know, companies are more open to the idea of using like innovative startups or, you know, technology to, you

you know, do what they're doing faster and quicker and better and all those kinds of things. But I would say definitely on the investment side, I do think, you know, it is becoming more difficult than it was three years ago when every VC wanted to invest in AI. And now, you know, you're not seeing that as much. So I think, you know, there's definitely maybe like a rebalancing of the ecosystem that's happening right now.

Yeah, and it won't be through on the VC side because I can only imagine, you know, maybe if you were, you know, 2020, 2021, you know, investing in some early AI startups, there's probably a decent level of confidence there, right? Is it harder to feel confidence in large investments?

you know, now in 2025 when the pace is so fast? And, you know, maybe walk us through, you know, what a lot of, you know, these VC groups are maybe not struggling with, but what are the challenges of being able to keep up? Yeah, I mean, I think it's definitely hard now because we've seen

As you said, you know, startups that they've invested in that we're doing really well. And then, you know, a big kind of AI company comes out and says, OK, we've actually done exactly what you're doing. And, you know, people are going to more likely to use their products over a startup's product. So I think, you know, definitely VCs, I think, are becoming a little bit more commonplace.

cautious from what I've seen, which is not to say that they're less enthusiastic about AI, because I think everyone knows that there's a lot of really, really exciting applications in AI, but just more cautious around which investments they make. And so I think VCs from what I've heard are starting to think a little bit more about how do we think about how AI is changing business models? How do we think about

you know, innovation and AI. How do we predict what the next, you know, thing that a big AI company is going to come out with so that we can make sure that our startups are sort of like well positioned for, you know, the next five years?

Yeah. And, you know, I'm curious, what are you doing right now to, you know, ensure that outcome as best as possible? Right. I mean, they're going to predict the future. But, you know, what are you all doing to ensure that both the VCs and the startups, right, the inception program or ones that you're working more directly with? What are those common steps that you're taking to make sure that they're as set up for success as possible?

Yeah. So, you know, tomorrow we have the AI day for VCs, which I think is, you know, one of the ways that we are trying to equip VCs to sort of have an understanding of what is happening in the AI landscape and how does it affect their investment decision making. So I think that's one thing, you know, VCs in the Alliance also get access to our industry insights, which again is meant to sort of be a,

a more year-round information on how should they be thinking about AI, what are the trends, what are the challenges, what are the exciting areas that maybe are open spaces for investment. So that's kind of, I would say, on the VC side. And on the startup side, again, we work with a lot of startups. I would say even startups that are not necessarily humanized.

using AI right now, but maybe could be. And that could help them scale, that could help them get customers, increase their customer reach. So I think those are some of the things that we're doing to kind of equip startups to succeed. And of course, when those startups succeed and we're working with them, we also succeed.

So we're very motivated to make sure that they do well. - Yeah, getting back to this concept of domain experts, right? I always have people that I picture in my mind who are maybe in their 40s. And I know now, unfortunately, there's also huge layoffs going around in the tech industry.

And one thing I always point out is like what better time, right, for someone with 20 years of experience in sales or, you know, 20 years of experience in telco, right, to be able to come in and, you know, build something from scratch. It seems like there's no better time. You know, what's your kind of advice to those domain experts who are maybe now looking at being an entrepreneur for the first time?

I mean, I would say a hundred percent, like if they have a really cool idea, this is, I mean, it's definitely a great time to be kind of acting on it. Um, again, as I said, you know, I think a lot of VCs are really looking for that. So, um,

You know, it's almost better to be that domain expert building a company now, maybe than it was like two years ago, where VCs were definitely more excited about, I would say, like any of the novel AI applications. And now they're sort of shifting a little bit. So I think you may have even a better chance of kind of getting

funded. Yeah. And speaking about what VCs are excited about, you know, I feel, you know, maybe five to ten years ago, startups were very proud of their, like, headcount, right? They're like, oh, we've raised this much money and, you know, we have, you know, 500 employees or,

80 employees, right? It doesn't, I don't know, from the outside, that doesn't seem super impressive to me anymore. You know, especially with, you know, now you can go in and, you know, in the weekend and via code, you know, MVP, right? And get something up and running and working. What do you think, you know, or maybe talk a little bit, have you seen a similar shift where people were maybe more concerned about the number of people and now maybe what are they concerned or focused on, you know,

more with all the recent advancements? Yeah. So I think I mentioned this. I think kind of the VC ecosystem is sort of going through this like rebalancing. And I think as a result of that, VCs are trying to be a little bit more cautious, a little bit more prudent. Yeah.

And so I think you're seeing VCs that, you know, want to see that companies have customers or they have some, you know, tractions becoming, I think, a lot more important than it was, again, you know, a few years ago. You could definitely have a company that got funded that had no customers. And I think you're seeing that a lot less often.

often now. So I think it's important to kind of make sure that, you know, you have a product that's working, that you have customers that are using it. Those kinds of things are becoming a lot more important as metrics, which, you know, they were as well, you know, seven, 10 years ago. So I think we're kind of, you know, seeing that sort of rebalance. Yeah. What's, what's still, you know, and I'm sure the rebalancing process is evergreen, right? It's continually like rebalancing, but what would you say right now in this kind of, you

venture capital, startup ecosystem, what are the things that kind of need the most rebalancing? Is it people that are still working as if it was five years ago and there's no AI? Is it people that aren't maybe talking to customers enough? What is the, in this day and age of AI everywhere, what's the biggest part of that relationship that needs rebalancing?

I think it's probably trying to fuse the two things. How does AI work with a model where we now want to have customers, we now want to see more traction than we did maybe three years ago? I think it's a question of that balance between building a product, building something that's unique and interesting, probably that uses AI in some way.

But at the same time, still kind of taking that maybe, you know, quote unquote, like old school approach and actually going out and finding customers. Yeah. What's, you know, I'm sure there's very few, few people, you know, and few companies that can, you know, sit in the position that you're in. Right. Because you have relationships with with all of these, you know, the big companies, the small startups, right.

But if you were sitting across the table from someone who's launching an exciting startup today, what's the advice that you're giving them? So I would say probably two things.

I think one, as I sort of said, I think really understanding the problem that you're solving. And I think that is on two sides. So there's the technology side, right? Understanding kind of how you're building technology. And then I think there's the customer side. So understanding the customers that that technology is then serving.

And I would say those probably are the two really important things that I'm seeing. And so I would say you definitely want to make sure you have both. No one wants to see as often the AI applications that are going to be obsolete in six months. But at the same time, a really interesting AI company that doesn't know what its customer is is also not interesting. So I think definitely having both of those is important.

Yeah. Uh, similarly on the venture capital side, because I know we have a lot of people in the VC industry listening to the show. What would you tell them? Right. Because, you know, I can only imagine how much more difficult their jobs are getting because it's like every day there's like a thousand new startups that do, you know, ABC and, you know, five years ago there were none. So what would you say to someone on the VC side? Uh,

So I would actually say to leverage AI as much as possible to kind of try to do some of that deeper research so that you can really stay abreast of all of the kind of AI innovations and developments that are happening. And I know there's so much information out there, which is why I say, you know, leverage AI to some extent. But I think it just kind of helps to kind of know sort of where AI is going and sort of what the challenges are and what the innovations are to be able to kind of

figure out what the white space is and kind of where you want to be investing. So I'm sure there's going to be a lot of news coming out in the next couple of days. We probably can't talk about all of it yet at this moment. But, you know, for, you know, startups, startups,

VCs that are looking at what's happening here at GTC because there's a lot you mentioned, you know, the AI day tomorrow, but what do you think they should be looking at that's happening here at GTC? I mean, I think, you know, definitely AI day for VCs is always, you know, something that I think is going to be super useful for startups and for VCs, but I would say Jensen's keynote is probably, and I'm sure everyone says this, but I think, you know,

It's going to be sort of a good kind of overarching sort of like summary and highlight of where AI is going and also what are some of the new things that are coming out. And I think everything in that speech will be useful for both startups who are thinking about where they should be building and VCs who are thinking about where they should be investing. Yeah.

It's always good, right? Like I always re-listen to his keynotes and I'm like, wait, this changes how I think about business, right? It changes how I think about work. So it should be, it should be exciting. But so we've covered a lot in today's conversation, right? Talking about things on the venture capital side, the startup side, you know, the ever evolving role of domain experts. But maybe as we wrap up, you know,

let's just double down on that what is your biggest takeaway from those domain experts right when it comes to uh you know maybe companies that should be looking at them to hire them whether it's looking at you know domain experts that are trying to build something on their own what's your biggest takeaway for domain experts uh today yeah i mean i think you know in the age of ai um

you know, everyone is a little bit worried that, you know, the information that they provide is not as good as what an AI would provide. So I would say, you know, to those domain experts that I think they really have something that's kind of unique in the sense that, you know, they have a lot more, I would say, practice almost processing the information from their specific domains and kind of knowing what to do with it. And I think that

Is a skill that is super useful whether they are working at a company or building their own and so I would definitely encourage them to leverage that All right, great advice all around. So Alia, thank you so much for joining the everyday AI show. We really appreciate it Yeah, it was great to be here. Thank you. All right We're gonna have a lot more for you this week and next week. Like I said the entire business

business world, tech world, AI world is just looking at what's happening this week at the NVIDIA GTC conference. And we're going to be here bringing it to you live from great experts like we just heard today. So if this was helpful, I hope it was. Make sure you go to youreverydayai.com. Sign up for that free daily newsletter. We're going to be reading

recapping today's conversation as well as speaking of the keynote, right? As soon as that drops, we're going to have all of the information out there for you. So thank you for tuning in. We hope to see you back tomorrow and every day for more Everyday AI. Thanks, y'all.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.