Venture with Grace
00:43:42 · Vitaly Gordon
[00:43:42] S1: Yeah, look, are definitely companies who kind of maybe figure out and there's, like, you know, they're very, very specific way of working. Let's say, you know, ramp just released their harness that is, like, highly, highly optimized for the way that ramp works. And by the way, there's, like, a significant number of people that are... Their sole job is to focus on, you know, this thing, and that's that's what they're doing. And so for, you know, those companies, I would say, you know, we less focus on because, obviously, they, you know, they already figure a lot of things out. So we should focus on the companies that need more of our help and not kind of like the companies that very large teams that are, you know, solely focused on solving the problem. Right? So that's kind of like to your question now. Now... But in terms of like what is the what is the competitive advantage is like, look, we've been doing it for quite some time. So we... And the... You know, our argument is is like, look, there is, like, endless advice on the Internet on how to use AI. Like, the problem is not like the... Like, there is not enough advice. Right? There is like... The problem is, like, knowing kind of out of all of that, like, I would argue 95% of at least is complete nonsense. It's completely useless. It's actually, like, more, you know, like, more harmful than useful. Right? And so knowing that what are the, like, the 5% that actually, like, can improve yours and given that, you know, if you actually know it and you don't wanna spend the time, like, sure, you can go and try every single one of these things Or you can, you know, part of a organization like ours that, you know, just we not already tested a lot of these things. Like I said, we like literally run an organization that tests like so many different variants and test every single thing that, you know, is coming in. The other thing is also we are automatically can know how to apply, you know, all of our kind of learnings into your specific organizations. And so I would say probably, you know, you will save a lot of money on, like, focusing on your core business and not trying to, like, focus on, you know, kind of like, what is our core business. And so we're very... We think we're the best at what we do.
00:46:00 · Vitaly Gordon, Grace Gong
And so, you know, like, usually, it will be hard for an, you know, an organization that, like, has a completely different, you know, mission that... To become better than than us at that. Yeah. [00:46:12] S0: Is there a particular, like, kind of, like, data that you would demonstrate to the client that, like, oh, with us, you will save x amount of dollar or like, is there any kind of like standard metrics that you guys typically like kind of like demonstrate? [00:46:27] S1: Yeah, we're like, literally, it's just like we we show them that we're, you know, we... I think there's actually something that is coming up. And there was a case study that is just, coming up on it, but that we, work with an organization. And I think if I recall correctly, their the, you know, their outcomes increased two and a half, x, while their AI, budget actually went down by, like, 20% or something like that. So, like, in terms of, like, actually, again, price per outcome was, like, massively, massively different result, just by, kind of, like, you know, using our system. [00:47:05] S0: Speaking of using your system, so who actually use the platform the most? Would it be the CTO, CIO or CFO? Because I could also see the use case of CFO looking at what's happening here. Yeah. And like kind of cut down the causes and something then.
00:47:05 · Grace Gong, Vitaly Gordon
[00:47:05] S0: Speaking of using your system, so who actually use the platform the most? Would it be the CTO, CIO or CFO? Because I could also see the use case of CFO looking at what's happening here. Yeah. And like kind of cut down the causes and something then. [00:47:24] S1: Yeah. So it's all the above that you mentioned as the CTO, CFOs and other like it's also like developer productivity teams or the people who you know, the AI budget. Like, think about there's like, in every organization, there's someone who's like goes and, you know, closes a large contract with like, whether it's Anthropic or, you know, OpenAI or Cognition or Cursor. And at the end of the day, like, they they wanna see and they wanna show to the CFO the results of that investment. Right? It's like... At the end of the day, all of these kind of kind of contracts are investment in order to achieve a certain goal. Right? There's like... You know, they're not buying those contracts out of the goodness of their heart. And if they can show that, you know, that investment made a large difference, that's not good. And so... By the way, that's not good not for the company, not for the vendor, and that's thing that we help with.
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.