The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:29:52 · Harry Stebbings, George Sivulka
[00:29:52] S1: He's my neighbor, so he's literally next door. So we can arrange that. But he said that we consistently underestimate how long it takes for enterprises to adopt new technologies, to get comfortable with data security, to get comfortable with processes. Is that right, or do you think actually we are past the tipping point? [00:30:11] S0: It's a good point if you're cutting cost, which I think Daniel and UiPath are are one of the best examples of of using AI to to make companies more efficient. Like, if you look at finance and how fast Excel went to 90% market penetration in finance, 1985 to 1986, literally eighteen months to twenty four months, Excel took over all of finance. Everyone switched from using a calculator, the HP 12 c, to to using Excel. And if you look at how fast, finance actually ended up, you know, using credit card data to value public companies ahead of their earnings, That was, again, a two year period more recently. And so finance is the slowest moving, most lethargic, you know, leviath. It's the worst possible customer base to go after unless you're providing outsized alpha or real value. In which case, the minute that there's something real, finance moves faster than any other industry. And so I'm actually making a bit of a bet by going into finance and and starting to take a go out and try to get to my own.
00:30:11 · George Sivulka, Harry Stebbings
[00:30:11] S0: It's a good point if you're cutting cost, which I think Daniel and UiPath are are one of the best examples of of using AI to to make companies more efficient. Like, if you look at finance and how fast Excel went to 90% market penetration in finance, 1985 to 1986, literally eighteen months to twenty four months, Excel took over all of finance. Everyone switched from using a calculator, the HP 12 c, to to using Excel. And if you look at how fast, finance actually ended up, you know, using credit card data to value public companies ahead of their earnings, That was, again, a two year period more recently. And so finance is the slowest moving, most lethargic, you know, leviath. It's the worst possible customer base to go after unless you're providing outsized alpha or real value. In which case, the minute that there's something real, finance moves faster than any other industry. And so I'm actually making a bit of a bet by going into finance and and starting to take a go out and try to get to my own. [00:31:06] S1: Do you know what I worry about? I worry that we lose the education process. What I mean by that is, like, a lot of, like, GPs or managing partners or you name the title in it, senior firm, they've been through the shit of analyzing companies, staying late, understanding what makes a great business, all of these things. Yeah. And then we'll just say, well, don't worry about that shit. Happy will do it. And so we have this no graduation pathway for the next generation, and so we have decision makers who don't have that graduation.
00:31:33 · George Sivulka, Harry Stebbings
[00:31:33] S0: Yeah. I'm less worried about that. I think, ultimately, one of the best things about being, you know, having the years of experience is is actually having the depth of knowledge about investing. So for example, if I'm a junior trying to price an asset, I haven't seen that many other companies that look like this company. And so I might say, hey. I think it should be priced at x, y, or z. And then someone in the IC IC meeting will be like, hey. No. I've seen 20 other companies in my forty years of career that look exactly like this, and they all went nowhere. And I'm I'm leaning on my prior experience. With Hebia, now juniors, who are really smart themselves, can say, okay. You might have remembered 20 deals, but I'm looking through every deal in our company's history in a giant matrix that anyone has ever seen. And and I actually can tell you quantifiably that when a company is performing here, it's it's ninetieth percentile across all this investing criteria. We should actually pay 90% premium to market. And I'm actually using more deals than you've ever seen because I know your name is on this many IC memos. And that type of structured thinking or that type of of additional information that you can now give juniors in their career actually think makes better investors. I I I don't I don't think that that takes away [00:32:44] S1: Do you really think it will be a tool for usage, not a tool for replacement? [00:32:48] S0: I genuinely believe it makes humans better. I genuinely believe [00:32:53] S1: years' time, do you not think that is a different story?
00:32:53 · Harry Stebbings, George Sivulka
[00:32:53] S1: years' time, do you not think that is a different story? [00:32:55] S0: I think that it will change the way that people do work, but I genuinely believe that it'll actually increase the AUM of the firms that use it. I think it'll actually drive more employment. I I think there will be some jobs that change. Hey. There's no more bookkeepers that do, you know, tabulations in in spreadsheets on two sheets of paper. [00:33:13] S1: But What changes most and what stays the same? [00:33:15] S0: The cognitive tasks that are lower in cognition, like more back office, kind of middle office, maybe even some of the more junior front office tasks, I think will start to be... Start to move into, okay. How can we manage AI juniors rather than, you know, actually do this ourselves by hand? But I don't think that, you know, just as Excel didn't end up taking away jobs from people or just change people, you know, to having to learn Excel, the exact same thing will happen with AI. [00:33:45] S1: So you don't think that we will see team sizes reduce as a result of agent integration into enterprise?
00:33:45 · Harry Stebbings, George Sivulka
[00:33:45] S1: So you don't think that we will see team sizes reduce as a result of agent integration into enterprise? [00:33:51] S0: You know, there's there's all these stories and, you know, you have, like, Klarna that's positioning for investors that they're firing half their staff, and and and no one really wants... And I think a lot BS. I think it's BS. Yeah. There might be some reality to it, but I think that it's it's an amazing marketing story. And so anytime that I ever hear something that's put out as a marketing story, I almost negate it in my head to actually think about, like, what the implications are. When you're saying something and screaming it from the rooftops, that almost always means that inter... Internally you're freaking out about something. I think I look at that really loud behavior, and I think that behavior itself really negates the content. That's maybe my my positioning on on this sort of stuff. [00:34:27] S1: How do you feel about competition? What are your lessons on competition? There are several players now in the heavier slipstream. How do you feel about that?
00:34:27 · Harry Stebbings, George Sivulka
[00:34:27] S1: How do you feel about competition? What are your lessons on competition? There are several players now in the heavier slipstream. How do you feel about that? [00:34:35] S0: I think that if a $100,000,000,000,000 of economic value will be created by AI and agentic applications, that there will be so much room and so much opportunity for a ton of different players. I don't think that when Excel came out and then Mark released Salesforce and then, you know, people created TurboTax, you know, all these unravelings of Excel actually were were produced later, but that made Excel any less valuable. I actually think it made Excel more valuable. I view Hebia as this platform as something that will actually get better the more people get inspired by it and build increasingly verticalized applications. What models do [00:35:10] S1: you use? You sit on top of what? [00:35:12] S0: We are completely model agnostic. We use all of the major model providers, some of our own models. But ultimately, the foundational difference that Hebia is capitalizing on right now is fundamentally new and and very important difference, which is I actually think on the order of creating RAG and and creating agents and decomposition, is this idea of us in the last year or so having pioneered scaling at inference. [00:35:35] S1: Talk to me about this.