How I Invest with David Weisburd
00:25:21 · David Weisburd, Joseph Coyne
[00:25:21] S0: Sitting where you're sitting, couple weeks ago, had David Breach, the Vista Equity president. They've deployed over a $100,000,000,000 in software. So they certainly thought long and hard on on this issue, and he believes that the future of software is not just selling software, but selling solutions. It's kind of do it yourself versus done for you model. Do you see that as the evolution in software itself? [00:25:42] S1: In the early days, we're seeing a lot of that. Consultative selling. I think we've seen portfolio companies with very powerful technology enter Fortune 500 companies, take the covers back, or open the hood and be surprised by how disparate and unruly the data is. And that very quickly turns into a data consulting project. For a VC, that's not what I love to hear. Right? We wanna hear [00:26:07] S0: like doesn't sound scalable.
00:26:07 · David Weisburd, Joseph Coyne
[00:26:07] S0: like doesn't sound scalable. [00:26:08] S1: This this will work out of the box. Right? And so I think you have to have your customers have to continue to deploy best practices in in data management, fidelity infrastructure in order to unlock, right, the plug and play value that a lot of portfolio companies and software companies will will ultimately bring. But the on ramp in the early days can be consultative. That that can be a positive to the startup in our world because they learn a tremendous amount about the problems that the enterprise is feeling. Once they've felt that and solved that, they can then replicate it and even create agentic workflows to replicate it across other use cases so that the next Fortune 500 they go into takes 10... Is 10 times faster for the implementation. But these are baby steps, I think, in the process of really unlocking the true enterprise value that will will come in in years.
00:26:57 · David Weisburd, Joseph Coyne
[00:26:57] S0: Reminds me of the Paul Graham advice, which is do the unscalable. If you wanna build a bill... Great business, do the unscalable, figure out where the problem is, and then automate. Same with the Elon algorithm. A lot of people think the Elon algorithm starts with automation, actually ends with automation. It's the number one problem you could have in engineering is that you automate something that doesn't actually add value. So have to figure out Yeah. Make sure that it adds value, run it, kinda make sure that that ROI is done. And then and only after then, then you automate. People have this, especially venture capitalists have this bias. Oh, I want something scalable. I want something automatable from day one, but sometimes it could be counterproductive even to the to the design of the product itself. [00:27:33] S1: Yeah. Potentially. And and I think, like, when you think about funding startups, you know, we always enter at seed. I think you need to create some realistic benchmarking and understanding that that will happen. And that leads to things like, you know, how much cash flow do you need to achieve a particular thing... A particular outcome. So what does it take to reach a series a, series b? I think on one hand, from a product standpoint, you can reach product maturity faster than ever. So, like, the dollars that we're putting into companies are being used with an efficiency that has been never seen before. [00:28:06] S0: Double click on that. Why why are companies able to scale so much quicker with so much less capital?
00:28:06 · David Weisburd, Joseph Coyne
[00:28:06] S0: Double click on that. Why why are companies able to scale so much quicker with so much less capital? [00:28:11] S1: I mean, I think it starts when you're thinking about product and code. I think agentic coding has been massively impactful, especially to people who know how to wield it. So early stage founders that are technical, that have engineering backgrounds themselves, are the people that we've seen in sort of the data research we've done that are benefiting the most. The most efficiency right now is being accrued to the engineers. You know, I think next on the list is something like customer service, which is just a great dataset, great use case that you can augment quickly. It's digestible. But when you think about, like, the biggest delta in efficiency, it's at engineer. And so, talking to large enterprises, you know, we have a number of advisors, technical advisors on our team that work at places like Meta, Amazon, Oscar Health. And when we talk to them, we say, what does your job look like now as an engineering or AI manager? And they say, I can accomplish four times as much in half the time. So when [00:29:03] S0: we do...... Improvement.
00:29:03 · David Weisburd, Joseph Coyne
[00:29:03] S0: we do...... Improvement. [00:29:04] S1: Yeah. And so when you when you hear that, you start to think about... And we see this just in practice. Right? It's like the founders that we're backing are being way more cash efficient to get to product maturity in a shorter period of time. And so that's part of the reason why we spend our time at seed. I think the delta, the alpha creation opportunity from seed to a is... That delta is greater than ever right now. And so when we think about risk allocation and investment portfolio decisions, we think in sort of sharp ratios. Right? We're allocators and buyers of risk. And for every unit of risk, we need to pay the appropriate price. As things go from non obvious pre product to post product and obvious, meaning some product market fit, customer references, revenue, during that curve, that curve is happening shorter and faster than it's ever happened. And as a result, you see series a's and series b's being priced where series d's and e's were prior. And so I wouldn't like to play that game as much as I'd like to capture the alpha going from non obvious seed to relatively mature product in a matter of year... Short short number of years. [00:30:09] S0: I don't think I've heard a single intelligent investor take the counter on AI. Disruptive AI has intrinsic value. I've... I haven't found anyone to say, oh, it's all BS. It's all hype. That being said, AI being valuable and all is reported that precede rounds today on average $100,000,000 valuation. How do you underwrite that?
00:30:09 · David Weisburd, Joseph Coyne
[00:30:09] S0: I don't think I've heard a single intelligent investor take the counter on AI. Disruptive AI has intrinsic value. I've... I haven't found anyone to say, oh, it's all BS. It's all hype. That being said, AI being valuable and all is reported that precede rounds today on average $100,000,000 valuation. How do you underwrite that? [00:30:32] S1: I think, again, you're buying risk. You're allocating dollars behind some level of risk. At early stage venture, these businesses are inherently risky. So if that's true, it's very hard for my team to pay that kind of price. Because even though if they're sophisticated, if they have the world's best team, you are still betting on an outcome that is extremely low probability.