Venture with Grace
00:48:18 · Grace Gong, Vitaly Gordon
[00:48:18] S0: Selfishly, I personally felt like it could be really useful for, like, people who are nontechnical. So, like, you know, I feel like our AI spending may be even, like, larger than, like, the technical person because the technical person only spend on code. We have to spend on marketing, other stuff. So when you're looking and then sometimes there's also the comparison between like you use AI to do certain things and versus you actually hire like a person. Sometimes hiring a person may be even cheaper for really random tasks. And if you're building this dashboard for your non technical friends, what would you suggest them to do to actually... What what should they be like even evaluating on? [00:49:00] S1: Yeah. Sorry. We we spend a little time talking actually about mostly, you know, engineering, but but actually today, what we found in many organizations, 50% of the spend is actually not in engineering. And so we're also now helping, there as well. But but actually everything I I said still holds. You know, whether you're in marketing, whether you're sales, whether you're in finance, whether you're in HR, there's still outcomes that you can think about, like, about using AI. And you still wanna achieve more outcomes and you wanna spend less money to do so. Right? So all of it is actually still refined and you can still use our platform to actually, like, optimize all all of these things. So it's not just about engineering. [00:49:38] S0: I... Do we have a hard stop by eleven, or we can go over, like, five minutes
00:49:38 · Grace Gong, Vitaly Gordon
[00:49:38] S0: I... Do we have a hard stop by eleven, or we can go over, like, five minutes [00:49:42] S1: or something? Yeah. Also, it's it's fine. [00:49:45] S0: Yeah. Okay. So it's fine. Okay. So I wanna talk about the jobs category of things. So obviously I feel like nowadays people have a major concern of the junior engineer are gone. And apparently because of the token maxing, reverse token maxing, the junior engineer are back. So what exactly is gonna happen to the career of, like, a engineer? And so obviously, people always say, oh, you know, like, all the white collar jobs are gone because AI is doing everything. But clearly, it's not necessarily the case. And what's your kind of, like, opinion on, like, where the engineering jobs are gonna be going based off, like, what you have seen currently in the... With the with the data on your platform?
00:50:29 · Vitaly Gordon
[00:50:29] S1: Yeah. So I was actually at the dinner last night and, like, I went into, like, this argument, with someone. So I'm, like, very much into... Look. Like, OpenAI and Anthropic are two of the most efficient companies in the world. Like, literally, you know, Anthropic makes $6,600,000, you know, per employee, and they're still hiring a lot of employees. Why? Because when you have so much excess profits, like, why not invest them in order to grow even more? Like, you don't have to... Like, if Anthropic goes down to, like, $3,000,000 per employee, is that a better result? No. It's amazing. It's, 10 times better than, like, every, you know, other public company. So I... For me, I'm saying, like, there is... Like like, I don't see, like, a way in the future that, like, companies will generate such massive profit and will not reinvest them in in order to do more. So, like, you know, so as long as they're gonna reinvest in... Now, there's still kind of a thing where, you know, like, how junior engineers do become senior engineers. It's not like, you know, every single job will be saved. Some, you know, some might be disappeared. But, like, I I just... Like, I I I completely disagree with, like, all these AI doers because, like, if you see OpenAI and Anthropic in every single successful company, like, try to hire today an engineer, a product manager, a designer in the Bay Area. It's just, like, impossible even though, like, all... You know, everyone predicted. And if we can't make engineering job disappears, which is, like, where, like, 50% of, like, all the trillion dollar spend goes into, you know, removing, then, like, I don't think, like, you know, everything else will just, you know, will just disappear because we, you know, we cannot even eliminate engineering.
00:52:07 · Grace Gong, Vitaly Gordon
[00:52:07] S0: Since you mentioned about the data, which is like 50% of the current cloud or average, like, model spending is going to the non technical people. Where do people spend the most amount of money? And is this cheaper if you just hire a human? [00:52:25] S1: So probably, again, it might be sometimes cheaper because we do see some... One of our customers had a security person who's like... Who spent like $170 in one month. So obviously, yeah, like, it's way way cheaper to like, you know, our person. But like, in most cases, I would say that AI is still such a small percentage of total total labor spend that I think, like, you know, adding those aside, like, you know, we should be using kinda more AI. And I think we should be still using humans for... You know, there will be a lot of human related tasks about, like, taste and direction and, you know, other things. But I think this, you know, cheaper to hire a human. I think it will be you... We should hire humans to get much more out of our AI spend. But like it's... I don't think it will be cheaper on on a task basis. [00:53:21] S0: For the subsector that you guys have worked with, is there any particular subsector that you are very excited about? So for example, from my observation, I feel like a lot of money are actually going to the healthcare AI space. And do you feel like their spending is bigger than, let's say, quantum computing versus any subsector that you guys actively look at to tapping into?
00:53:21 · Grace Gong, Vitaly Gordon
[00:53:21] S0: For the subsector that you guys have worked with, is there any particular subsector that you are very excited about? So for example, from my observation, I feel like a lot of money are actually going to the healthcare AI space. And do you feel like their spending is bigger than, let's say, quantum computing versus any subsector that you guys actively look at to tapping into? [00:53:49] S1: Yeah. So currently, we're trying to focus on, I'll say, on tasks that are somewhat repeatable and are kind of like maybe like a little bit easier to find. The problem with, I would say with healthcare is that the fastest pre binary is either you get a drug discovery or not. And so it's very hard to, like, kind of like, operationalize. And, like, it's... You know, there's no, like, amount of AI that we can guarantee that you will discover, like, a life changing drug. Right? So so those are sectors that we're, at least, for now, focusing less on and, you know, like, look, there's a probably trillion dollars even in the ongoing, you know, tech, finance, you know, whatever ecommerce, retail sectors that, that's kinda, you know, where we focus.
00:53:49 · Vitaly Gordon, Grace Gong
[00:53:49] S1: Yeah. So currently, we're trying to focus on, I'll say, on tasks that are somewhat repeatable and are kind of like maybe like a little bit easier to find. The problem with, I would say with healthcare is that the fastest pre binary is either you get a drug discovery or not. And so it's very hard to, like, kind of like, operationalize. And, like, it's... You know, there's no, like, amount of AI that we can guarantee that you will discover, like, a life changing drug. Right? So so those are sectors that we're, at least, for now, focusing less on and, you know, like, look, there's a probably trillion dollars even in the ongoing, you know, tech, finance, you know, whatever ecommerce, retail sectors that, that's kinda, you know, where we focus. [00:54:39] S0: Speaking of retail, what is the current landscape of people building an AI in the traditional compared to AI native companies? Do you feel like AI native companies are actually spending more AI budget? Or who is actually owning the AI budget in these groups? Do they typically have a chief AI officer? And how is the budget allocated? Is that each department has an AI budget then you go after the department versus, like, that there's, AI guy at every company right now.