The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:32:22 · Harry Stebbings, Alex Mashrabov
[00:32:22] S1: Okay. So the internal spend, 4,000,000, about 10,000 per head. What will that be in twelve months' time, do you reckon? [00:32:29] S0: So across the top engineers and across top creatives, it's going to keep growing. And I do believe we are gonna get to spend close to 50 k and 100 k a month for those who can call 10x engineers, 10x creatives. Unfortunately, I also expect that these people will ask for comparable salary raise as well. So I think that is just gonna correlate at some points. But also for a lot of other jobs, let's say we take legal, finance, and so on, it really stabilizes around like $500,000 a month very, very quickly. [00:33:03] S1: With those 10x engineers, the idea is they have thousands of agents running below them doing a lot of the difficult execution work that took time. Do we just have dramatically smaller teams with those 10x engineers, 10x designers, 10x finance leaders?
00:33:03 · Harry Stebbings, Alex Mashrabov
[00:33:03] S1: With those 10x engineers, the idea is they have thousands of agents running below them doing a lot of the difficult execution work that took time. Do we just have dramatically smaller teams with those 10x engineers, 10x designers, 10x finance leaders? [00:33:20] S0: I can definitely say that I had sort of a feeling that legal customer support is going to be mostly replaced. And that's obviously one of the main mistakes, operationally, which we have done in the company, that we didn't ramp these teams quickly. What we're seeing today is that, let's say our legal team is over 10 people, our customer success team is over 40 people. All of them use AI heavily. At these professions where I stay quite close today, I definitely can say that I don't see any elimination. It's true that probably over 60% of customer support requests, especially the first line of defense, can be handled with AI. But when it especially comes to B2B, like, AI just doesn't work. [00:34:02] S1: Revolut has now over 92% resolution rate on customer support for consumers. Pretty good. [00:34:09] S0: It's it's it's pretty good, but obviously, they did invest a lot into that. A shit ton. And and... But also very important, the way how Nick thinks about that is in terms of the playbooks. We launch products, new products pretty much every week. We have to keep up that agents with all the information and so on. And just due due to the high velocity, having extremely smart coordinated team is is very important.
00:34:09 · Alex Mashrabov, Harry Stebbings
[00:34:09] S0: It's it's it's pretty good, but obviously, they did invest a lot into that. A shit ton. And and... But also very important, the way how Nick thinks about that is in terms of the playbooks. We launch products, new products pretty much every week. We have to keep up that agents with all the information and so on. And just due due to the high velocity, having extremely smart coordinated team is is very important. [00:34:32] S1: That's really interesting how product velocity increases leads to harder customer support for agents. [00:34:38] S0: Of course. Because the agents are as good as contacts and the rules which they have. And if contacts and the rules change pretty much twice a week, it gets a little difficult. [00:34:47] S1: When you look at your engineering team today, what are they on? Are they on cursor? Are they on codex? Are they on core code? [00:34:55] S0: So from a period from March to June, everyone really moved to Claude, including the creative team. And that's where we actually started to see creative team vibe coding functionality, which we don't have in production. But then we started to see that all the coders quickly moved from CLOUD to Codex as of mid June. Over the time creative, especially 10x creatives, moves to Codex as well. But look, I do believe that it's cyclical. So
00:34:55 · Alex Mashrabov, Harry Stebbings
[00:34:55] S0: So from a period from March to June, everyone really moved to Claude, including the creative team. And that's where we actually started to see creative team vibe coding functionality, which we don't have in production. But then we started to see that all the coders quickly moved from CLOUD to Codex as of mid June. Over the time creative, especially 10x creatives, moves to Codex as well. But look, I do believe that it's cyclical. So [00:35:27] S1: It's so cyclical. My question to you is, will we continue to see the velocity of model release that we're seeing now? In three years' time, will it be like, oh, Gemini this week, oh, Anthropic this week, OpenAI this week, or will we see a a reduction in model release rate? [00:35:46] S0: I don't think that's gonna happen anytime soon. I believe, like, for example, recently, OpenAI announced that they basically built OpenAI for law, but that's only v zero. So over the time, they also are going to try to print smaller specialized models for... Not exactly smaller, but really specialized model for certain use cases. Clearly, like Astra excels in long term horizon.
00:35:46 · Alex Mashrabov, Harry Stebbings
[00:35:46] S0: I don't think that's gonna happen anytime soon. I believe, like, for example, recently, OpenAI announced that they basically built OpenAI for law, but that's only v zero. So over the time, they also are going to try to print smaller specialized models for... Not exactly smaller, but really specialized model for certain use cases. Clearly, like Astra excels in long term horizon. [00:36:08] S1: Do you buy that? I look at that GPT for law from Astra, and I'm like, I'm sorry, I think it's complete bullshit. With the greatest of respect, it is a very deep functionality required to serve some of the biggest law firms in the world. They're very, very deep and specific functionality. It's very specific according to the different types of law as well. Plus, if you wanna sell into these law firms, it's a multiyear sales cycle with some of the stodgy old lawyers and partnerships. You can't just say I'm OpenAI. Yep. We've just hacked into the Australian government, by the way, but we're here to serve your law firm.
00:36:44 · Alex Mashrabov
[00:36:44] S0: Okay. First of all, I think definitely the ability to switch internal use just for internal teams outside of law firms. I think that's definitely happening. Oh, I think we both invest... There is some company called Solve Intelligence. Love it. Yeah. Very specific. Very specific. And let me try to maybe bring a couple examples why, like, solve intelligence is so special and, like, where... Like, for example, how we learn from this. What can happen very often is that a company wanna just control the patent workflow even if they outsource the work. And that's very valuable just to have one system of record. So whoever can create AI native system of records is gonna win. And but going back to Higgs, why it seems so important for Higgs Field? There are so many systems today which are used for just to store assets. Like, some people use Dropbox, Some people use Google Drive. Some people are gonna try to use Miro. Some people are gonna try to use frame.io. Like, there are many solutions. But let's think about what people need. What people need, they wanna be able to search contents, and marketers especially wanna make sure that content is on brands in terms of the visual identity, but also if that sort of adheres to certain brand guidelines. And that's where semantic understanding and semantic controls become finally possible. It never existed before. So in our space, there are definitely other companies like Adobe and Canva who builds the best software for the Pixel for Serra, where everything was defined with pixels. But that's clearly not how the world is gonna work in the future. What we're envisioning, and that's what everyone wants, they wanna just be able to search and really work through the library of assets and all the knowledge through natural interfaces. So being able to own this interface and build the analytics, like this system of records, is important. That's why at Higgs Field, we invested so much in harness so that it improves over the time. And this harness also allows... It it basically learns visual style over the time, which, let's say, Claude and OpenAI cannot necessarily do.