A Product Market Fit Show | Startup Podcast for Founders
00:08:42 · Pablo Srugo, Steve Tuck
[00:08:42] S1: Pain is relative. And I found myself many times when like things are, you know, hard or whatever. And you hear a story about somebody who, you know, grew up really poor, had this trouble, that struggle, and it just puts things in perspective. And so I'll say this, like if you're out there raising for your AI startup and you need like $2 million to turn your half a million in revenue to $5 million in revenue, there are hardware people out there raising $20 million to like build MVP one in, you know, three years from now and then maybe ship it, you know, two years after that. And so it's, pain is very relative. And raising for hardware is tough. [00:09:14] S0: If you're raising like, you know, like launching an AI startup right now is hard. It's so noisy. And there's so many difficult nuances to that particular business, whatever that is. And I think the thing that I would say is work to find the right set of investors, even if it looks fraught getting through that first phase or two. It is so important that you find folks that are curious, that have a real long view of what the business could become. And it is worth not lurching at that first offer that comes in from an investor that may not be the right fit.
00:09:14 · Steve Tuck, Pablo Srugo
[00:09:14] S0: If you're raising like, you know, like launching an AI startup right now is hard. It's so noisy. And there's so many difficult nuances to that particular business, whatever that is. And I think the thing that I would say is work to find the right set of investors, even if it looks fraught getting through that first phase or two. It is so important that you find folks that are curious, that have a real long view of what the business could become. And it is worth not lurching at that first offer that comes in from an investor that may not be the right fit. [00:09:51] S1: So we're going to talk at the end of this about two kind of specific things that you did, two tactics, which was building in public, which is not normal for a company like yours that has to build, you know, something for a long time, usually the operating style, you do the exact opposite. And the second thing that you do, which I find insane, which is you pay everyone the same salary. So we're going to go deep on why you do that, how you do that, how that all plays out. But let's start kind of at the beginning. Now that we understand a little bit better what you do, what was your background before you started Oxide in 2019? What were you doing? And what was the kind of idea? Where did the origin kind of come from for this company?
00:10:25 · Steve Tuck
[00:10:25] S0: Sure. So going all the way back was at Dell, joined Dell in October 1999, right at the absolute height. So Dell was the highest performing stock on any index in the 90s. It was just this insane run. And when we got there, our class came into this auditorium and they dropped like fake stock options from the ceiling while playing. We are Dellionaires to the like, we are Dellionaires. You have people dancing on cubicles. It was a wild time. And then, of course, everyone that was in industry at that time would watch, you know, one of the greatest economic collapses on the back of that technology bubble popping. And then had the real privilege of being at Dell through some really interesting times. The emergence of virtualization with VMware as every enterprise adopted this new technology that would allow much greater efficiency. And through the sort of storage and networking wars where HP and Dell and everyone were kind of competing on acquiring companies, but I was on the sales side through all of this and working with customers starting out from consumer into small business into enterprise. And eventually I started working with this emergent set of companies on the West Coast that at the time, to date myself even further, we would call Web 2.0 companies. And these were folks like, you know, MySpace and Facebook. What today we would call hyperscalers. And what they needed was something a little different than what Dell off the shelf kind of provided. And they would describe, you know, not deploying 100 machines, but 100,000 machines. And to be able to do that, they needed capabilities that the platform didn't have. And they also wanted some things that it came with kind of removed. And this was a difficult contemplation for Dell. And they had viewed this space as not really major server buyers. You know, those are colleges and the federal government and insurance companies and Wall Street. But I had started working closely with some of these companies, including this emergent startup joint that was a pioneer in the cloud computing space. And fortunately, they made quite a pitch. And I came over there early on in that company. And that, you know, six months later, my co-founder at Oxide, Bryan Cantrill, would come over there from Sun Microsystems.
00:12:56 · Pablo Srugo
[00:12:56] S1: This is like what timeline at this point?
00:12:58 · Steve Tuck
[00:12:58] S0: This is 2009. Okay. So cloud computing is super nascent. If you were running an AWS in 2009, 2010, it was kind of wild that there was this new mechanism where you could hit an API and kind of throw code at it and run applications. And like everything else just kind of worked. Also, sometimes things didn't work and you would have an outage that would be like three days long. And so the first era of cloud computing were all of these gaming startups and apps and fintech companies. They were the ones that were willing to go launch in the public cloud and operate there. And it would be a couple of years until the mainstream enterprise was like, wait a minute, we actually could use this, should use this and began to adopt it in scale. And then obviously the last chapter, most recent chapter of cloud computing has been AI. This is where all of the major labs grew up. This is where all of kind of the AI building has occurred is in cloud computing. And the thing that we learned over the 10 years at Joyent was sort of threefold. Number one, the way that Joyent was doing this was writing all the software portion, the cloud control plane and the update engine to be able to deliver cloud services, but buying off the shelf hardware. And short version, it turns out when you take software and try and pack it onto off the shelf PCs and rack form, things don't go well. All the problems around performance, stability, availability, they kind of stem from that hardware software interface. And, you know, like Apple pioneered and learned and like Tesla pioneered and learned the hyperscalers, Amazon, Microsoft, and Google realized we've got to blow this up. We have to redesign the modern computer from the ground up and co-design software in here for the cloud era. And so the machines that power the world's biggest cloud computing hyperscalers look nothing like what you can buy off the shelf from Dell, HP, Lenovo's, micro, you know, storage providers, network providers. And when we were kind of evolving at Joyent, we then got acquired by Samsung. And that's when I moved into kind of an operating role and then eventually would run the entirety of that operation. At the scale we were running, which was powering the Samsung cloud globally, that hardware software disparity just completely broke down.
00:15:16 · Steve Tuck, Pablo Srugo
And it was at one of our lowest moments where I was at OCP Summit, which is a place where all the big hyperscalers come to show off their wares, that we would first witness these incredible rack scale machines that Facebook had for themselves that were transformative. They were so much more dense and energy efficient and operable than anything that you could kind of compile off the shelf in hardware. And I was desperate. You know, I had my checkbook out from Samsung, like, how do I buy these? And, you know, how fast can you ship them? And the Facebook team kind of looked at each other and like, sorry, do you work for Facebook? [00:15:55] S1: These are not for sale, right?