Venture with Grace
00:40:08 · Austin Spiegel, Grace Gong
And if you can make that loop really, really, really good, then you're always going to stay one step ahead of the rest of the industry. [00:40:17] S0: What would you think is like the common mistakes that hardware companies typically make when they're building their own data infrastructure? And obviously you mentioned, it's not like technically everybody's strong suit to build something in house, but I guess what makes it so hard for other people to navigate this?
00:40:45 · Austin Spiegel
[00:40:45] S1: Yeah, good question. I mean, I think the biggest challenge is just underestimating scale, right? So if you start, I mean, is for more startups I'd say, but if you kind of start, early and you have a time series database you've deployed and you've got a visualization tool and maybe you've built kind of some wrapper software around that, it's hard to understand that when you're creating megabytes or gigabytes of telemetry that if your business is successful, which you're betting on your business being successful, then you're going to have multiple orders of magnitude for telemetry than that and it's quickly going to become this quagmire. So, I think that is one challenge. The second challenge I've seen is that a lot of, you know, just some businesses don't think about software as this living, breathing investment, an ongoing investment. They think about software like hardware where, I mean, obviously now businesses are iterating on hardware more quickly and changing it all the time. Like, each Falcon rocket that launches is different from the previous Falcon rocket that launches. But I think historically, is basically really long requirements phase, really long design phase, really long validation phase, and then let's go build several or hundreds or thousands or millions of this device. And if you take that same thought process and you apply it to software, you're not going to be able to... It's not going to scale, right? So inevitably your software is going to fall out of date, whether that's just security compliance. Maybe you want to make one change to the software you can't deploy it anymore because the deployment environment is no longer existing. Maybe you scale beyond what the platform is capable of doing, but none of the people that built the platform initially are there anymore, so they don't understand the intricacies of it. So I think that's also part of the problem, which is people don't take into consideration that this is actually an ongoing investment and it's not just, Okay, we built it and now we're done with it. We actually have to keep investing and I think people underestimate that.
00:43:06 · Grace Gong
[00:43:06] S0: Since I guess you described machines where 50% of the bill of materials is software. And so basically, assuming what you meant is for the hardware company, they're spending 50% of their budget onto software. And what would you say, as a software company yourself in the hardware space, how much would you say is you're spending on, I want to say software, but yeah, software or like, you know, I live in an AI land, everybody's spending like a majority amount, you know, GPUs and something like that. So like, how do you kind of like allocate your budget as a CEO for the company?
00:43:50 · Austin Spiegel
[00:43:50] S1: Yeah, I mean, I think we're fortunate in being a software business in that most of our expenditure is people, right? So that's definitely the most important and most expensive part of the business. And thinking about, okay, well, do we achieve our goals and working back from achieving our goals to figure out what headcount needs to be and who are the people we need to have a seat? That's a majority, I'd say, of the planning. Of course, there's also software spend, right? So, we use AWS for hosting. Obviously we use other providers as well, but AWS is our primary provider. We also use LLMs. That's another large expense and then like your kind of long tail of SaaS products. I think the big thing for me that I watch out for is certainly LLM spend. I'm still not... Want people... People use AI all the time. We have like 100% uptake in AI usage. We've got engineers using multiple agents. Something that I find kind of fascinating about this is it's always been really challenging to measure outcomes that engineers create and the engineering productivity, right? There's like how many different frameworks that try to figure out how to measure engineering productivity. And now we've just kind of turbocharged like the amount of work that engineers can do. And And we're also spending much more money per head because of that. And I still don't think we have a great way of actually measuring, like, is this meaningfully... What is the difference it's making? Like I 100% believe that AI is making a difference, but I think being able to measure that difference against the cost is still something that is really challenging and something that I'm definitely keeping a close eye on as we kind continue to consume these tools.
00:45:50 · Grace Gong
[00:45:50] S0: Let's say since you guys recently opened the asset department, so I'm sure it's for attracting a lot of top engineers. And if someone getting offers from SpaceX and like getting offer from you guys, like what would be your like pitch to them to like join you guys?
00:46:10 · Austin Spiegel
[00:46:10] S1: Yeah, yeah. I mean, it's a good question. I mean, I think there's a couple of things here, right? Like one is just like, what type of environment do you want? I mean, I think SpaceX is still an incredible company, but the fact is there's probably, like, what, 25,000 employees or something. I don't actually know the number at this point, but it's it's pretty high. So, if you want to work in a startup and you want to be really close to your customers, then that's where Sift really fits in. And you want to work on novel problems. Not everyone is trying to solve what eventually is agentic hardware development. There's actually very few companies trying to do that and we have an incredible install base of the leading companies in the industry that are ready to adopt these tools eventually. So I think that's kind of what's very unique about our business. I think the second thing is like, I don't know. I mean, this is all speculation, but are we at the top? Like, how much more juice is there to squeeze? I mean, obviously, I'm a huge believer in SpaceX, so I think I think that one is, is special, and I I believe it will go to the moon and beyond. But I do think, like, you know, how how much more, you know, like, what can you expect your return to be on joining a really late stage business where the earnings maybe does not quite match the valuation? But that's how I would think about it.