How I Invest with David Weisburd
00:45:09 · Joseph Coyne, David Weisburd
[00:45:09] S1: Yeah. And I would argue that's all true. That may go away a little bit as you automate sales process, and that's fine. But what still remains is understanding customer needs. People who deeply understand their customer, some of them were formerly the customer they're targeting. Right? They bring back unique insights and problem sets that the best engineers thrive with. Okay? Generally, best engineers, unless they're the founder of a company, are not going out and talking to the customer or or have lived inside the customer for twenty years. And so the salesperson can also be sort of a customer solutioning specialist that brings back unique insight or understanding to the engineers that informs product road map, solutioning, and making sure that whatever we're building within a startup has extremely high value day one to the customers because it came from them. [00:45:59] S0: Do you know the story of how GoDaddy massively increased their revenue? I don't. They put salespeople into their customer service calls. Mhmm. So they realize that the best time to actually upsell somebody and figure out what people need is at the time that they have issues. And it goes back to this kind of paradox in customer services. When you have a problem and a company solves it for you, you may end up actually building affinity with with the company more so than if you didn't have that problem. So they actually [00:46:25] S1: turn de facto design partners with you. And
00:46:25 · Joseph Coyne, David Weisburd
[00:46:25] S1: turn de facto design partners with you. And [00:46:28] S0: So they they figured this out a decade ago, and now we're kinda seeing this straight emerge again in AI.
00:46:32 · Joseph Coyne
[00:46:32] S1: Fascinating. We invested into another AI company that was doing post sales data gathering for service delivery companies. So sales makes a sale. Right? They capture some data in their CRM about how that process went, and everybody has a steak dinner and high fives and says, great job everyone. And that's usually the... It's like the day of your wedding. Right? It's like the happiest day of everyone's life is the day that you consummate the deal. And then after that, you start actually delivering the service. You could be an investment banker. You could be a consultant. You could be a lawyer. You're delivering service over a long time series. Monitoring those interactions is what our company Knownwell does. And what it's pulling back is unique insights for the management to say, it's great that you sold this customer. We're gonna monitor minute by minute, interaction by interaction, a, how happy they are, but we're also gonna distill down everything the customer's telling you about what they need. You can take those insights and immediately put them back into those enterprises, to probabilistically and sort of stochastically lay out what should we build next. Because you have a time series, multiple customers, and frequency graph of what your customer is telling you. When you digitize that and digest that with AI, it creates unique insights for the service delivery partner, which says, you know, it could say, wow, we just really don't like this team that we're working with or so and so was not really great to work with or you weren't very timely. But it could also say, hey, the software you sold me does x y z, but we were really looking for, you know, tau. And that can be unique insight that can then recursively get pulled back into the product roadmap.
00:48:06 · David Weisburd
[00:48:06] S0: When I talk to engineers at Anthropic, I also have some friends at OpenAI. They're telling me that average engineers are getting a four or five x efficiencies and that the 10 x engineers are getting actually a 100 x. So the the 10 x engineers, which oftentimes are twice as expensive, end up being even better or returns on investment. Are you seeing the same phenomenon on the sales side where the top salespeople are actually getting these major efficiencies from AI?
00:48:30 · Joseph Coyne
[00:48:30] S1: I think it's still pretty early innings innings on that. The best salespeople generally are still the best salespeople. I think sales is probably slightly slower to adopt or at least, you know, just like a lot of enterprise that we discussed earlier, is only starting to scratch the surface of the true scalability. I think if you're an AI native, you're a founder and not just like an enterprise salesperson. A founder doing sales can do things that they never could have done at a scale they've never done. Even in like my own side projects, my agents are running, you know, business development workflows and analysis, you know, while I'm sleeping. Right? And so that's me being sort of like a hacky founder mind that just running those in the side. Similarly for fundraising at Studio VC, you know, lots of agents involved in identifying LPs, you know, drafting initial emails, keeping us in the loop in terms of follow-up, all these things. Right? So it's almost like we have a chief of staff there. But that's us as AI native, AI, you know, early adopters. When you think about traditional sales, there's some defensibility. There's a... Well, how do I matter in a world where AI is doing a part of my job? And so the willingness to adopt some of those technologies is a little slower. And again, that comes back to my point earlier where it's like, if the CEO is native and understands the impact that they could have on sales, that will start to trickle down quicker. But if you're asking that head of sales, right, they're gonna try to protect their fiefdom potentially.
00:49:50 · David Weisburd, Joseph Coyne
[00:49:50] S0: Yeah. It makes me think about this alignment issue where salespeople within startups where they have equity may be faster to adopt than ones in traditional kind of Fortune 500 companies. [00:49:59] S1: Yeah. It's a great alignment question. Yeah. [00:50:00] S0: If you could go back to 2009 when you first started working in venture and you could give yourself one timeless piece of advice, what would that be? [00:50:09] S1: Wow. [00:50:10] S0: That... This one, people take a long time to think about.