00:42:32 · Shensi Ding, Molly O'Shea, Gil Feig
[00:42:32] S2: Also, I think like consumer expectations are higher now. Like you just expect significantly more automation. And so the SaaS platform cannot keep up with the expected automation. It's [00:42:41] S1: just [00:42:41] S2: hard to compete. Like you don't want to have to buy a platform and then build your agents on top. You just want it to come out of the box. [00:42:46] S1: Does that make you nervous? [00:42:48] S0: I mean, I think we're, we're good at this motion. You know, and we also have a sort of like, in some ways forward deployed team. And the idea is, you know, a sort of if you can take off the shelf software that does most of what you need and then have someone customize it to exactly what you need at a relatively low cost, which is what AI facilitates, then I think there's still a lot of value in, in sort of platforms powering or buying, you know, sort of ready made software off the shelf, because there's still a lot of nuance and a lot of detail that you avoid having to figure out that that falls outside the time it takes to code in general.
00:43:18 · Molly O'Shea
[00:43:18] S1: Today's episode is sponsored by VCX by Fundrise, the public ticker for private tech, allowing investors of all sizes to invest in venture capital. Learn more at getvcx.com. Some of you may not have heard this yet, but our sponsor Public just launched something called generated assets, and it brings AI into investing in a way I've honestly never seen before. Here's how it works. You type in an idea like AI powered supply chain companies with positive free cash flow or defense tech companies growing revenue over 25% year over year. Publix AI then dispatches a swarm of agents that scan every single US stock, evaluates them, and instantly builds a custom index around your thesis. What really stands out is how clearly it explains why each stock is included. And before you invest, you can even backtest your idea against the S and P 500, so you're making decisions with real context, not just guessing. And beyond generated assets, Public lets you invest in stocks, bonds, options, crypto, all in one place. They'll even give you an uncapped 1% match when you transfer your investments over from another platform. If you want to build a portfolio that actually reflects your thesis, visit public.com/sorcery, paid for by Public Investing. Full disclosure is in the description. Enterprise AI runs on Merge, the AI infra platform for integrations, agent tooling, and model orchestration, so your teams ship product, not plumbing. Mistral, Dropbox, and Drata already trust Merge in production. Start building at merge.dev. Founders scale faster on Deal. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit deal.com/sorcery. That's deel.com/sorcery. I think we've become like a little desensitized to the valuations for AI companies or AI enabled companies. Yep. Do you think they're rational? What do you what do you see with Silicon Valley and maybe even the broader market could be upper market?
00:45:18 · Shensi Ding
[00:45:18] S2: Yeah. I I think it's it's it's crazy because the public markets are has just such a different story versus the private markets, obviously. So I think it'll be interesting to see when, like, opening up in Anthropic could go public because then it'll become, like, kind of, like, merging of the two. Yeah, I don't, yeah, I don't really want to like talk shit, get hit. Oh my god. But yeah, like, mean, obviously I have like a lot of like private thoughts on it.
00:45:42 · Gil Feig, Molly O'Shea
[00:45:42] S0: Yeah, to not name any companies. Like I remember when we first started Merge, we were like, candidly, was really frustrating to see some companies where we knew what their revenue was and we knew they were raising it like a 3,000 X multiple on that revenue. We were seeing insane valuations and like, can't help but be a little jealous or a little just like, Come on, like, why is this happening? And you have VCs telling you, You don't want that. That's not the thing. But in the moment you do it, of course you want that. And we're really glad we didn't because obviously a lot of those companies ended up falling some of them ended up doing really well, but most didn't. And we're seeing it now. A lot of the numbers that are coming out, some of them are really, really successful companies and are obviously going to continue to grow. But we know specifically, like we know the numbers, we know sales figures for some of these companies raising at hundreds of millions to billions. And again, we're looking at 1000x to, you know, 100000x multipliers, like a lot of these companies are going to fail, or they're going be doing well, but just not be able to raise their next round. They're going to be forced to massively lay off and slow down. [00:46:43] S1: How do you stay focused through all of that? There's just so much noise.
00:46:43 · Molly O'Shea, Shensi Ding
[00:46:43] S1: How do you stay focused through all of that? There's just so much noise. [00:46:47] S2: Yeah, we just have to think long term. And also, I think we just have, you just have to focus on like your wins for like your customers and the type of customers you're onboarding and like what your actual business metrics are. But yeah, obviously it's a competitive market when it comes to recruiting talent. It definitely makes it a lot harder, especially for people who are optimizing just for what has the biggest valuation, what has the flashiest numbers. So that's where you really filter for missionary versus mercenaries. [00:47:10] S1: Mhmm. So I think you guys have been a little bit humble. I know, and I think these are some of your customers. So some of your customers are names like OpenAI, Perplexity, Netflix, Uber, Mistral, Dropbox, Freshworks, and more. So how did that happen?
00:47:10 · Molly O'Shea, Shensi Ding, Gil Feig
[00:47:10] S1: Mhmm. So I think you guys have been a little bit humble. I know, and I think these are some of your customers. So some of your customers are names like OpenAI, Perplexity, Netflix, Uber, Mistral, Dropbox, Freshworks, and more. So how did that happen? [00:47:27] S2: Yeah, a lot of work. Like it was very a lot of work. Yeah. When we first got started, especially because we were infrastructure, a lot of startups like were very scared to use us. I remember talking to Ramp and they were, I think like a 100 employees at the time. And we were really scared to onboard them because our product was so, like, early. And, yeah, it's it's we've obviously gone, like, a long way since then. Obviously, they've grown a lot on us as well. And, yeah, we just we've had to adapt the company a lot. Like, I think after our series b, we made a really concerted effort to move upmarket, segment our team, have a more mature sales motion, and also just make sure our product was really enterprise ready. And that was really hard. But last year was really when it all started kicking in. [00:48:06] S0: Yeah, it really took climbing a logo ladder, riding off the reputations of each successive company size growth to be able to close that next level and prove that we could handle that. [00:48:16] S2: Yeah. And then once you like close-up, fucking up. [00:48:19] S0: Oh yeah. Yeah. [00:48:20] S1: Yeah. Was it intimidating getting bigger and bigger logos? [00:48:23] S2: Oh my god. Yeah.