Ben Horowitz and Ali Ghodsi: How to Run a Billion-Dollar Business

23:34I have my weekly one-on-ones. I have my weekly staff meeting. I have my weekly this. And then I do this. And then we follow the rules. And we do all of this. And then that's like just like the top part of the T. And then there's nothing that goes deep. And that's the issue, I think. Yeah, over-systematizing. Or making it, like, symmetrical. You don't even, you don't have to have one-on-ones with the same frequency of all your staff. Or like some of them, you know, like you can meet very seldom. Well, like everything is different. Every part of the company is different. You may need to meet with somebody every day.

24:07And then other people, you know, you can meet once a quarter for now because it's just not that serious. And you can't get caught up in making everything fair and symmetric. Particularly, like your staff, they got to be able to deal. And this is actually the biggest conversation that I had with Ali early on. It's like, if they can't do it, they can't do it. That's it. It's a wrap. Yeah, yeah, yeah. Don't try and fix them. They can't be fixed. It's not going to happen. And, yeah, it's a sad lesson, but important lesson. I actually, I want to turn the conversation to an area that Ben was saying you had to catch up on, at least in the beginning, which is the BD deal-making stuff, which is interesting to me just because I think of you as like a consummate deal-maker now.

24:58I feel like you're playing chess, everyone else is playing checkers. I want to go back to 2017 with maybe one of the first game-changing deals that you guys did, and that was the deal with Microsoft. Can you guys talk a little bit more about how that deal came about, anything you'd do differently? And by the way, founders still to this day ask us about it because it's sort of a model for how they'd like to do deals. Yeah. Maybe I should start by saying that, you know, we had tried to get close to Microsoft for a long while. I think Ben had told us you need to, that's an important partner because they have the biggest distribution channel.

25:30You know, today they have 60 ,000 sellers. If you can unlock that in any small way, it's going to be a game changer for you. And I had been CEO for a year. So I'd been trying hard to get in there. And many, many people offered me, you know, hey, so here's, I actually know Satya, so I'm going to get you introduced. And I got multiple introductions to Satya. He just like, I don't ever responded or just CC'd his EA and it went into an EA loop. You know, like we're still trying to find time. He's been so busy this last six months, you know. So, but then, then he had a meeting with Ben and I think he was here actually at A16Z and and they actually just talked and I was not actually in the loop.

26:10And then he called me up and said, hey, I talked to Satya and I think this is, he's excited. He wants to do this. And I saved the email. So Ben introduced me to Satya and this was, I think, 3 or 4 a.m. I was like in New York and the email went to Satya and then Satya added like four or five people to the email thread and then they added four or five people. So like within an hour, I had like 25 emails in my inbox. And suddenly all these people that were not responding to my emails from Microsoft, right after Satya CC'd them and CC'd the next person, they were all like, hey, I'm clearing my calendar.

26:40Would love to meet you. Do you have any time in the next two days or three days or, you know. But really kind of the original pitch of what's the give and get was Ben and Satya. at the A16Z, and they kind of figured it out, and I was not actually even there. So we had some luck, and then Ali did a couple of things that were, or quite a few things that were very, very effective. So the luck was, at the time, deal with big companies, there's always a timing element. And there was a company called Hortonworks that had a deal with Microsoft to provide some similar kind of functionality. And they were basically putting a gun to Microsoft's head, saying, like, you pay us more money or we're going to pull our product.

27:28And they were on-prem and they were in cloud. So it was like a big mismatch also. Yeah, so it was a real, so Microsoft was like super pissed at them and wanted to stick it to them. And so that was, you know, so you have Satya going, like, I think this company's interesting. and then this ground-level thing going like, we want to fuck these guys. And that kind of opened enough of a door to get it going. But there were, so like one of the most important things in the deal was, which, you know, and John O 'Farrell really emphasized this for both of us, was, look, you got to get them to put enough, They're such a big company that they're going to lose interest many times.

28:17So if you don't have them write you such a big check that somebody in there is going to get fired if it doesn't go well, it doesn't matter if you get the deal. You're going to lose the deal. And so what we did is we're like, and the technique that we had was, okay, give us a fork out. Like, we're a little company. We can't afford to do this deal. we can only afford to have one partner so give us a forecast of what you'll do. Yeah, because our engineers are busy. They're going to do this integration. That wipes out 12 months of our roadmap. We don't have anything else. You guys have like many thousands of engineers.

28:53So we only have one of these. Yeah, so whoever can sell them. We think you can sell the most, but we don't know. So, you know, like kind of challenge their kind of manhood a little bit. And so they come out with this big ass forecast and we're like, okay, great, just give us a little portion of that. It was a huge deal. It was a lot of money. Yeah, yeah. And then Ali said, like, you know, when we got all the way down to the deal, he was like, if I don't get this number, Ben's going to fire me. And so can you help me out? It was a very interesting dynamic. It was a very interesting dynamic. So, you know, John O 'Farrell had to strategize with us and told us that, you know, they have to do a big pre-commit because then they have skin in the game.

29:36Otherwise, they're just going to forget. They'll do like the PR, but then they'll forget about you. But then when we were trying to get that from Microsoft, I remember I was talking to Takeshi Numoto, who is one of the main brains at Microsoft, one of the key strategists there. And his thing was, I don't want to give you a big commit because you're such a small company. I'm worried you take this money and you get drunk off of it and you're not going to do anything afterwards. And so I had to really convince him that, no, I'm extremely hungry. I was like, there's no way. I will continue to have crazy appetites.

30:01Don't worry about it. So both sides were kind of worried about different things. But yeah, the give and get was important that you said in the beginning, which was they had a gap in the product portfolio, right? They were competing with AWS. They had a gap at the time. And we had a great product. They have an amazing distribution channel. So like in these BD deals, there always has to be a give and get that actually is kind of commensurate. And this is why most of these deals fall apart and they don't work. There has to be something that you as a small player can give that they don't have. And usually you don't have anything to give them.

30:35Usually I find all these small companies show up and they come, for instance, to Databricks now and say, oh, we'd love for you to partner with us. But what am I getting out of it, right? You don't report to me. I don't report to you. So the moment we've closed the deal, if it's not good for me, neither of us will just do our side of the bargain. So there has to be something in the deal dynamics, in the construct, that inherently is extremely beneficial both sides. There has to be a trade that makes sense. Microsoft really wanted that product. We really wanted their distribution channel. And then the other thing that I think a lot of entrepreneurs don't understand is, any big deal of that size, you lose at least three times before you win it.

31:12And we lost that deal. Ten times. Ten times. And like, including like the day before we were supposed to launch it. You know, the antibodies came out of the company and Ali had to fly up to Redmond and sit there. There was one engineer that just said, not doing this. This is not going to go. They actually put a guy in place, Microsoft, who was actually super, and had a great reputation, but he was a builder. So he just had huge problems with this. It's like, this is not a product I built. Why would I make this successful? So yeah, usually there's like many times. So like if you don't have grit, those deals will die because this deal died multiple times, as Ben said.

31:53It was like completely over. Like it was completely blocked by some exec that said, absolutely not. I'm blocking it. It's veto. It's over. And no one wanted to overrule him. So you have to go in there and work. And the only way we did it, like they call it the nerd bird. I would take the, you know, SF Seattle flight up there. I was up there so much. I knew all the buildings, all the rooms, everything. So you just have to spend time on the ground and talk to as many people as possible and sort of influence that organization from within. I will say, look, you know, with all the difficulty of the deal and, you know, and Microsoft being Microsoft, they've been as good a partner as not only we've had at Databricks, but in the entire portfolio.

32:34I mean, they've really, you know, lived up and delivered what they said they would do, which is, I think you have to give Satya a huge credit because like in the whole Gates and Balmer era, they were never that good a partner to anybody. And he's really turned that around. And, you know, they've been fantastic with us. This was around the time where Satya had taken over. And, you know, he was giving to everyone at Microsoft the book Growth Mindset or Mindset, which is about growth mindset. So there was this kind of aura in the air that, you know, we should try. Like, let's try to make things happen.

33:07Let's have a growth mindset here. Let's see. Is there a way we can partner? So this would have been impossible five years earlier. So it's kudos to Satya. And they put us on the map. And he's been a great partner ever since, you know, whenever there's been issues, they always resolve it. So, you know, we are very thankful. We wouldn't be where we are without them. Yeah. Just amazing. Amazing, really. I want to open up the conversation to dealmaking more broadly. Now that you're not a small company anymore, you're a big company making acquisitions, you know, Tabular, Neon, Mosaic, just to name a few.

33:38What is your sort of your approach in terms of when to build versus when to buy? How do you think about acquisitions more broadly? Yeah, I mean, what we try to not do, so let's start with a simple thing, is a lot of companies, especially at scale, they'll buy revenue. So they'll look at a company, they'll say, hey, this company is this size. We'll just buy that company. We'll put more salespeople on it. Then we can accelerate the revenue. We're buying that revenue. And that's how they're doing it. We're not doing that. You know, what we're really doing is, number one, we spend a lot of time with the team and the founders.

34:09So we're trying to see, hey, can we build together? Like you come here and you build together. That's very different from that buying revenue model. The buying revenue model, oftentimes you part ways with the CEO from day one. Like you can see the big companies, they literally have a plan. Like I have some execs that come from these big companies to say, hey, our plan usually is to part ways with the CEO. Like you make a deal and the CEO can leave. And then, but also the key people in those companies quickly leave, all of them. Like the top management, and then, you know, you keep promoting the people from below that couldn't get promoted before.

34:37And then eventually you bring in your own people to take over the company. And then the company is dead. There's nothing left of it. And there's no integration between that asset that you bought and the platform that you have. So to avoid all of those, can you get people that really feel like they're your co-founders? So we spent just enormous amount of time with who we're buying. Like the company we're buying, who are the founders? How do they work? Are we culturally the same? Spend time with them. Do we get along? Do we see the world the same way? Are we going to click? Are we going to do this together?

35:04Are we going to be able to build in the next five years? So that's where we spend, number one. Number two, we spend a lot of time on the product. What's the product experience? How would we integrate this? What would it look like? How much can we rewrite most of it? Can we not rewrite it? What programming? I always ask this, and people are like, that's such a dumb question. I ask, hey, what language did you write it in? Why do you want to do that? What does that matter? No, because we're going to integrate the code bases. right? It's like the build systems won't work it's not going to even compile so the product is something we spend a huge amount of time and talking to customers understanding what the excitement around that product looks like and how the integration would look like.

35:39The last thing we do is we'll look at the financials what's the revenue multiple and how much can we grow it and what's the three year plan five year plan and so on and I feel like big companies, corporate departments do it exactly in the reverse order of this they start with hey the revenue is this but we could accelerate it and the multiple is so low And like, you know, in my Excel sheet here, this makes perfect sense. You know, and then second, they go to like, hey, is this a good product? And then lastly, like, hey, how do we convince these knuckleheads? I mean, we probably don't want to have them here, but we got to pay them off somehow.

36:09So I think, you know, thinking about it that way, you get more longevity out of it. Yeah, and this really comes, it sounds like he's talking like a product guy, but this is really the thing that people get wrong on the go-to-market Because what happens is, if you've got multiple product architectures, that's going to mean multiple SE forces, multiple post-sales things, and your entire sales efficiency is going to go through the floor. And because, you know, they have a keen eye on that, everything they buy ends up looking like a Databricks product. You know, like, and that work is going in. They're not just selling some shit to get some money to, you know, go on a corp dev.

36:55thing. And I would say so many, like, when you bring in a professional CEO, this is what they screw up. Because they don't understand that, yeah, engineering goes, yeah, yeah, we can take it on. There's another set of engineers. We don't care if they work on that, blah, blah, blah. And engineering gets less efficient, too, but it wrecks the field. And that's, and then the customers hate it. Customers hate it. Yeah, like, okay, I've got to learn another access control model. I got to do this. These are not things anybody wants to be part of. Yeah, 100%. It's the go-to-market side that you're worried about.

37:31That experience that those customers will have. They're going to come back immediately and say, hey, we were already upset about these things before the acquisition. Maybe you can fix them now. It's like, no, actually several of those people actually quit and now we're going to just work on integration and that thing now got pushed out another two years. So you don't want to be in that situation. So there's a lot of companies that do that. And by the way, what they're doing works revenue-wise. They are getting the revenue. They are getting the stock swap works. Like, you know, if they're multiple of the companies.

37:57It's a creative deal temporarily. Yeah, it works. And then the first year you get the bump in the revenue and you get a second year boost in revenue growth as well. So the financial engineering actually works great for those companies. It's just long-term. It ends up being like, you know, a bag of crap that doesn't work together. And it affects the brand. You know, like one of the things is, one of the reasons Databricks is so powerful is, all their customers want to buy all their products because they're like, we know that's the best software we buy. And as soon as you start chipping away at that with these financial strategies, like you can't get it back because the reputation is every customer's experience.

38:37There's no marketing through that. It's the best software because it was written by the engineers and built by those that were the best, including the acquisitions that we got. They were phenomenal people that came in and they continue. And since we gelled, they continued building it. So that's why it's great. So we pay a lot of attention. That's like back to the, you know, who are you getting into your company? Yeah. Yeah. That's the other thing, right? Like you can buy something that's got a lot of sales where you're downgrading your whole company. Ross Perot actually wrote about, in Citizen Perot, his biggest fear, which definitely came true, was he built this elite thing at EDS and then they would actually acquire IT departments.

39:22And he was like, they're going to absorb us, not vice versa. And that does happen. Yeah, there is one really good company that, well, one really successful company that we never acquired. And I always vetoed it whenever it came up because I just think that the quality of their employee base is not great. And I didn't want it to dilute Databricks. Otherwise, from every other angle, that deal always made sense. And I always vetoed it because I felt that, you know it's just they're all gonna quit or be super unhappy let's just not do it yeah it's also why like merger of equals are because the cultures aren't equal the people aren't equal and what made you feel that way you just spent time with them and they just didn't exude to a Databricks culture well I mean it's look it's like everything else like it's like when we were grading students at the university it's like okay the rock stars are super easy to find out so they're like there and then the people that are really really bad that's like it's not hard and then there are people in the middle that's in the gray zone this was a company that was I feel like the talent is not phenomenal and you don't need to be a genius to know that.

40:22And then some startups you know immediately. Like, okay, these guys are Olympia winners and they're phenomenal and they're executing like crazy and they have a track record. So I don't think those are that hard. And we try to hire these and this is the one that I vetoed. The hard part is what do you do with the ones in the middle? That's always where you spend all of your energy. You're trying to suss out. Like, okay, they're not stellar stellar, but maybe they are. Maybe they just didn't have, maybe they didn't have the go-to-market, they didn't have the funding, they didn't have the support that they needed and so on.

40:46Maybe they could if we give them a chance. or maybe they're just mediocre. And that's where you spend a lot of your time. But you've got to spend time with them. You have to interview all the people. You know, you have to have your people interview all the people. Can't just be, this can't be an Excel sheet exercise. Yeah. And Silicon Valley has a lot of lopsided companies. So, you know, you'll have a great engineering team and a bad company because it's like, you know, bad leadership, bad go-to-market. You also can have, like, guys who can sell anything with a ridiculously, like, poor engineering team and they can just sell it.

41:17And, you know, you got to be very, very careful about that. Actually, our, you know, our CRO at Databricks is, you know, he came from a company that, you know, he'd sell anything. He was selling SFTP, secure FTP, which is free. And he was selling it for a lot. That's how you know he's good. He was selling it for a lot. He was making a lot of money. He was saying, you know, the electronic medical health records, you know, how important are they? If they got dropped, you know, how much of a risk is it to your business? Well, this is secure FTP. Yeah, you need it to be secure. Yeah, and somebody grabbing that file.

41:52Yeah, he's good. Yeah, the only thing I'd add, too, is this strategy is probably making you more attractive to the people you want to acquire, too. They don't want to sell if they're going to get fired right away. Yeah, for sure. It's very competitive. Yeah, 100%, yeah. I mean, you know, there's also a reputation, right? People know. Like, they'll look back and say, okay, well, what happened to your previous acquisitions? Yeah. You know, was there a huge fight and everybody's quitting left and right? Or, you know, did they work out? You know, how are you taking care of those people? You know, what roles do they have?

42:15Do they have influential roles in your company? you know, that's also important. So you're setting a precedent. You're setting a precedent in many, many ways with acquisitions, M &A, you know, deal dynamics, the price, the, you know, when you go through, the lawyers come back and that you're spending all those 20, 30 days doing the definitive agreement. Every little thing you agree to there is a precedent for the next deal. Yep, totally. Maybe actually just to turn, so we're talking about Databricks as an acquirer. If we go back in time again to maybe a moment where you thought about selling and maybe that, you know, you didn't actually seriously consider that.

42:48But I wanted to actually just sort of quote this infamous email sort of circulating our firm that Ben sent to Ali. Yeah, Ali brought it. I had forgotten about it. He brought it up at a board dinner. And I was like, oh, shit, I said that. But actually, this was not pertaining to selling the company, but it was, I think, selling a candidate, right? And you talk about, hey, Ben, can you sell this candidate on the fact that it will be worth$10 billion, maybe$25. I thought he was worried about that company getting sold. Yeah, he wanted to have a double trigger because the company, if Databricks sells, and they fire me as a salesperson, what equity am I going to get?

43:25So give me double trigger so I'm protected. If we get bought and I get fired, I vest all my equity immediately. Yep, exactly. And so, you know, in response to this, Ben, and I'm going to paraphrase this a little bit, but he writes back to you, and I'm like thinking about Ben's tone in this, you are severely underselling the opportunity. We are Oracle in the cloud, and we will be worth 10x what Oracle is. But what was your reaction when you saw that? And did that give you more fortitude to not sell the company? Yeah, Ben's crazy. I think the first thought was exactly Ben's crazy. But no, I think both Ben and Mark always kind of pushed us to think bigger.

44:07I remember we did the pitch at A16Z for, I think, our Series D, which would have been around 2017. or so. And the question was asked, you know, what's your biggest bottleneck? And I said, biggest bottleneck is hiring. He said, okay, well, who are you losing to? And I said, well, it's Google. You know, it's the Fangs. And the response I got back was, well, you need to just add the Databricks to Fang. It needs to be FangDB. With a straight face. And my reaction was I laughed. I literally said, yeah, yeah, yeah. I mean, this is not serious. It's like, yeah, that's the bottleneck. I was like, no, I'm serious.

44:43You need to add Databricks to Fang, you know? And then there was like a pause and there was like this, and I think it's doable. And so then actually I went back and thought about it a lot. And I was like, hmm, is it doable? Like, am I the crazy one or are they the crazy one? Who's the crazy one here? Like, who's nuts here? And, you know, and that kind of pushed us to think about how do we change our comp philosophy? How do we, if we wanted to go and get the best of the best out of Google, what does it require? And we developed a new model where we're like, actually the way to think about it is your market cap divided by number of employees.

45:14That's how much money you can give away in terms of dilution. And actually we calculated the number at that time and we're like, wait we're actually richer than Google in terms of how much dilution we can afford per engineer because at that time this was like before the Twitter downsizing so all the companies were oversized. So we did the calculation and it turned out that we actually can probably pay P95th percentile. We did the math on P95th percentile for engineering and it was like, yeah actually the math works out. We moved all the comp bands. And we told the employees about it. It's like, hey, we're paying you P9050, you know, and we can afford it.

45:44And so that came out of that simple, you know, so these simple, you know, your trillion dollars, just add your acronym to FANG and so on. They're silly and they're kind of crazy, but they do push you and you go back and think about, hey, what is the fundamental reason from first principles that we couldn't do something like that? Why couldn't we be a trillion? What's the bottleneck from being a trillion or being part of FANG? And then you think about it and you start zooming in on, like, can we unblock that? So it has helped us and has been a driving force, even though it's, you know, it's a little annoying, you know.

46:15It's like, you know, hey, mom, dad, I got the A+. It's like, yeah, but we ranked, I was number two in the class. So it was someone better than you? Yeah, for what it's worth, when I joined the firm in 2019, the Series F of Databricks was the first deal I worked on. And I think the valuation was$6 billion. Ben says to us, oh, well, it's going to be a$100 million company. And we're like, yeah, yeah, sure, Ben. Lo and behold. They're doing all this work. I'm like, what are you doing? Like$6 billion,$7 billion, doesn't matter. I was right. He was right. Yeah, that's when you have proven to be right.

46:48Yeah. Still have ways to go for$2 trillion. Well, the thing that you almost never get, and Ali and I had this conversation, the one time we did have a real acquisition offer on the company is, You just don't get this good a market opportunity with this good an entrepreneur. That's the rarest of rare things. We see great entrepreneurs, but their market opportunity is limited. And then we see companies that have a great market opportunity, but the entrepreneur is not big enough to fulfill that. But this was a case where we had both. Yeah, I remember actually the conversation that kind of flipped me.

47:31The acquisition offer was on the table. It was six times bigger than the valuation we had at the time. And I had done the mistake of telling my co-founders. Yeah, they were like, let's go. They were like, we're done. So everyone was like, stop the work, stop working. Take your hands off the keyboards. Nobody work anymore. We're done here, right? And let's count my money. You're like, you know, how much money do I have? You know, what would you buy for that amount of money? You know, so they were like completely like not doing anything. And there's just this crazy gossip going around. And then it was like they had told some of the exec.

48:00And then they were calling each other every day like, hey, what do Ali think? Like, you know, you think he's, he looked in a bad mood. Do you think he's going to say no? No. It's like, what did he say? Like he said this thing, he said this one. So there's just a lot of politicking going around and nobody was doing any work anymore. And I was like, you know, maybe they're right. Maybe we should just sell. And I remember having that conversation with Ben. And I think we were in a car, both of us. And, you know, he says that he drops the F-bombs and he pisses people off and so on. And they don't take the feedback.

48:26But actually he did exactly the radical candor thing with me, which is he said, hey, you can do whatever you want. I'll support you either case. And actually, if you sell for this number, it's really great for me, me being done. Like we make a lot of money at A6 and Z. I'll pay the investors back many times over. So honestly, if it's for me personally, that's probably the better option. But I'm just thinking back, I was CEO, LoudCloud, Opsware, and just the cards I were given, that company wasn't the company you have. And when I look back, how often do you in life get a chance to even have a company like LoudCloud or Opsware, let alone a Databricks.

49:02And it's just such a freaking big market. You can sell, you're going to make a lot of money and you'll be super successful in life. But, you know, if you're like me, you're going to look back the rest of your life thinking, you know, I missed that one shot. That was the one thing. I should have taken it all the way. And now I'll never know how far I could have taken it. What could have been. So do you want to live with that? Or do you want to just have the money? You know, I'll support whatever you want to do. I really couldn't care less. I really couldn't care less. And I was like, okay, thanks, hang up.

49:28We're never doing this. We're done. This is not happening. What a pep talk. Yeah. So that's how we did it. So it was excellent. I think I also said, I guarantee you, you'll never have an idea this good again as long as you live. This is the best idea you're ever going to have. Yeah. Yeah. Yeah. Well, an idea that also takes off and works, right? Yeah. So I want to tie one thing that you said in all of that is you were company building, but then also just sort of the calculus that founders but also your employees are making, and that's around comp. So in the early days, you could afford to pay 95th percentile, right?

50:07Today, there's crazy AI talent wars going on. We've talked about this a bunch throughout the summer. And we know that you can bring the best talent in the house, right, to Databricks. How do you keep them with all of this craziness going on? Because now 95th percentile, I don't even know what that means. is that like you pay a billion dollars? Yeah, exactly, exactly. Yeah, the joke is, which company says we're P50 yet? We pay P50 yet. Like, who does that? There's no company that does that. So how does this actually? Yeah, the 75th percentile is the single biggest lie in Silicon Valley. It's like a complete fabrication.

50:40Probably, probably. So, but, you know, I think that it is a crazy time with AI. And I do think, I feel bad. I did actually an exit interview with someone this morning. I feel bad for the kids right now because there's too much pressure on them. They feel like, oh, they have to start companies and they have to, and I've never actually had anything like this because every year I talk to the interns and I get questions about how do we build our own company, how do we succeed at Databricks and so on. The last two years have just been crazy. All the kids are like, when should I become a CEO? When should I start my own company?

51:11What's a good valuation? Am I missing out? If I do like an internship here for three months at Databricks, will I have wasted my opportunity in life? And this is like the time for AGI and I could have like been one of the guys that does super intelligence. And like, you know, how would you time that? How was it for you? How old were you? When you were 22, what did you do? And, you know, and so I do think it's kind of crazy times. And I do think it's also exaggerated. Like, you know, I don't think anyone's getting $100 million offers. You know, I mean, yes, there's like one, you know, character that's AI and so on, but I don't think it's actually true.

51:42And it's also in the interest of CEOs, you should know, to say that, hey, you know, you know, people try to poach people from Databricks for a billion dollars and they said no. It's in our interest to say that, right? Because that kind of sets the bar at the billion. And then any employee that gets an offer for half of that is going to feel really insulted. It's like, when did I get a billion dollar offer? I heard like on the news that the other people are getting a billion. So I do think that the most - By the way, Sam used that in reverse on Meta. He's like, oh yeah, they offered all our guys a hundred million dollars.

52:11And so the next guy who got the 50 million dollars - Now they have to pay a hundred at least, right? That's like the smart move. But I would say that, look, Like, you know, and not all startups have the valuation of theirs. We're worth$100 billion. And, you know, with 10 ,000 employees, we actually can't afford to actually pay significant. And we do pay significant for the right talent. But, you know, what did you do when you're smaller? Like, we were smaller at some point. Well, then it's talk about how big you are going to get and what the opportunity is and what you could do together and what it would work together.

52:39But I think most people earlier in their career, they really want to learn. And they want to really feel that they can have impact. so if you can really bring them in and you can sort of mentor them you can stay close to them and as a CEO you have huge power if you just spend two minutes with you know a kid out of school it's immense to them and you say hey you know I'll even mentor you I'll help you like what do you want to do in five years I'm thinking about starting my own company actually in six months you know but I'll work at Databricks for 10 years but in six months I would love to be a CEO so then you can say hey I can coach you to you know I know how the fundraising I know the early days and so on and you can actually mentor a lot of them and that's actually worth a lot to them as well but in general like help them be successful and help them build their careers and also if you've done it before like we have you can kind of calm them down a little bit and say hey you have like a few decades you know don't worry about it it's like it's not you know it's the FOMO and the pressure you know has to be kind of reduced and I think that's also calming they feel good about it yeah yeah I always say the best cure for starting your own company fever is to start your own company and that'll teach you It's not that easy By the way, they come back like after start companies oftentimes they come back to Databricks and they're much more thankful and they understand and actually I didn't mention this earlier when you asked about acquisitions my favorite acquisition because I said start with the people, right?

53:58And then the product with the people I love to hire people who have seen great at a big company like or I don't know if it's great but they've seen process scale big company they've been at a Google they've been at Amazon they understand the processes so they understand how to navigate a bureaucracy and work with it. And they're not going to just be inundated by it. But then they've gone on and done their own startup. And that's really, really hard, right? It's like extremely hard trying to do everything yourself and you don't have any help. And you're trying to do this in this crazy market and you're trying to compete with$100 million offers when you have like nothing.

54:32So that takes a certain amount of grit and it's really humbling. So I love the people that have done both of those. They end up being actually the perfect employees at Databricks because they come in and they're really thankful. They're like, hey, what these guys have done at Databricks It's actually really, really hard. I tried it, and I'm really good. I was like one of the best at Google or somewhere. And then I did my own startup, and we absolutely failed. And so, hey, show some respect here. Like, you know, these guys know what they're talking about. So those are great employees, actually.

54:55So, you know, I think keep a great relationship with people who leave your company because they can boomerang back in a couple years. Yeah, and it's very hard to make these things work. And it also requires a lot of luck. I mean, I think one of the things people don't realize is a lot of things have to go right that should never go right. And a lot of things will go wrong, but like if you can grab your lucky moments, that's a rare thing. Yeah, one way to prove that is if Databricks started in 2013, if we had started in 2012, you know, that rocky year, that difficult year, 2015, would have then happened in 2014.

55:33Right? To start the funds, we don't have the revenue. but we were a cloud AI open source company. Those things didn't take off in 2014. So, you know, even if like, if we had to do the CEO change and all of that and I had become CEO a year earlier, it just, we were too early in the market. The cloud hadn't taken off. AI was not, nobody, that was not even a phrase. AI meant robotics. People use machine learning as a phrase. And so company would have failed. We wouldn't have had enough momentum. There's not enough cloud, you know, TAM there to be had. If we started the company in 2014, a year later instead, so a year later than we actually did, then we would have had our difficult year in 2016.

56:11But by 2016, the cloud was starting to happen. AI was starting to happen, you know. So we would have done the fixes in 2017 and it would have been too late to the party. And probably the hyperscalers would have taken it away. You know, our competitors were taking it away and we just wouldn't have get enough momentum to be able to succeed. And that's timing of when we started. So how did we clock it so well? We had to wait for Matei to finish his PhD thesis. That was the whole thing. So there's a lot of randomness, and you got to get lucky. And it was so on the edge as it was that on the Series C, Jan had a handshake with Redpoint, and Redpoint just stopped returning his calls to the point where the Series C was led by us, who also led the Series A, and NEA, who led the Series B, like we co-led the Series C.

57:04because nobody else would do it. It was that close to going under. And more companies went even, right, that would be it. Yeah, it was very close because we couldn't get funding for anyone. It's just funding freezed up and nobody wanted to invest anymore. So it was really a lifeline from A, C, T, and Z. Yeah, we were just, you know, we was burning a lot of cash. We weren't generating much revenue other than Spark Summit. We had a lot of downloads. We had a lot of downloads. A lot of downloads. And recurring conference revenue. Yeah, and recurring conference revenue. How confident were you in that time when things were at their list?

57:35Oh, I mean, I seriously considered taking the professor job at Berkeley because I, you know, I seriously thought this was going to be very, very hard to pull off. You know, it's like, you know, I think the sentiment at Databricks was, or at least my sentiment was, look, you win some things and you lose some things in life. We created Apache Spark and we made it a worldwide sensation. Everybody's downloading. The downloads are through the roof. We have this greatest conference, like, you know, thousands of people come to our conference. It's awesome. Let's go back. let's do it again let's publish another paper and do those kind of things we're just not business guys we just don't understand business you know that's okay you know we don't want to be business guys so that's kind of how I felt about it right but what I knew was that hey you know by the way Matei went back and became a professor like all this stuff happened yeah Jan went back you know and but you know in 2015 we knew that we tried everything and by the way PLG is something that we had tried very hard and it didn't work for us.

58:33Actually, one of our biggest failures was PLG at Databricks. Everybody kept telling us, PLG, PLG, PLG. And we're like, okay, product-led growth. And Amazon did it. And you just swipe your credit card. We don't need salespeople. But so in 2015, I had to kind of like... Except cranny. Exactly. Yes, that is true. Kudos to Mark. So that year, we had formed some hypothesis that we have nothing to lose. What if we just pivoted these things? What if we went all in into B2B enterprise sales? because certainly PLG is not working. At 3 million ARR, that's not going to take you anywhere. And they're just taking our open source software.

59:07So we have to have proprietary code around it. And yeah, the execs team are all PhDs. So what if we bring in someone that doesn't have a PhD and see how it goes? I never forget Arsalan going, we made the number. I was like, you made a ridiculous number. You made the number. If you keep making that number, you're going to go bankrupt. You didn't make the number. You made a number that you set that was way too low. Ben was very nice and complimentary in our board meetings that year, 2015. We were in a bit of trouble. Let's say it was very truth-seeking. But yeah, so we had nothing to lose. So we didn't know that we were going to succeed, but we had nothing to lose to make those big changes, and we made them in 2016.

59:48And it turned out those were the bottlenecks, you know, giving away your software for free, not having execs that have seen the movie before, like Ron who came in. And, you know, just the PLG motion is not going to cut it. So maybe we should just try. We weren't certain that B2B would work, but we knew that PLG is not working for sure. Yeah, well, another, like, I mean, you know, we got Ron. I mean, like the fact that the first sales guy we hired was a sales savant, like a genius, shock. I mean, like that never happens. And he was a guy we didn't know. Like, our talent team, like, found him from some company we never heard of.

1:00:34Yeah, a French company, Axway. And the only, really, the only reason we hired him was because he was the only guy Cranny ever liked. Like, in all the sales guys he ever interviewed, he was like, this is the guy. Wow. Yeah, he is a new generation, more Cranny T2. But we just, like, stumbled into him. Yeah, yeah, like, unbelievable. and without Ron very hard to see this company getting to where it got to so there's some luck involved in us even finding him but then he was phenomenal and also kudos to Jan who actually led the search in 2015 so you know but yeah Ron was game changing for us but Ron was a very uncomfortable hire because he did not have a PhD and he did have an engineering degree yeah he does have an engineering degree from Stanford that helped a little bit.

1:01:25But he's a sales, you know, true and true sales guy. Like he's not a, you know, he's not one of these he's a classic salesperson who grew up in sales, even though he has an engineering degree. So the comfortable thing would have been to pick someone, and we had some candidates in the mix who weren't a super technical using the product, giving us feedback, but they probably would not. And that would have been much more comfortable for us. Yeah, Ron was uncomfortable. He was a very uncomfortable hire, and he made it very uncomfortable for us for many years, and he still does. But that's a lot of the key to the company.

1:01:58Yeah. It forces a customer focus that would be impossible to have without somebody that smart and crafty about getting his way. I mean, just like unbelievable. Yeah. If you can keep also the original team together, that's important. We're, you know, seven co-founders still. Many of the co-founders, like, you know, you said data warehousing was a big push for us. My co-founder, Reynold, was really the one that kind of pushed this. Yeah, like, well, the contribution level from a large number of co-founders is unique in the industry. I mean, you've got Patrick, you have Reynold, you have Matei, you have Arsalan.

1:02:38I mean, like, it's crazy how much the original team contributes. Yeah, so the PhDs all contribute. Like, Arsalan really made the go-to-market work, you know, And he really made the sort of Ron work with the rest of the company. That was super critical. Matei continued doing lots of innovations over the years. Patrick led all of engineering in big chunks of it. And, you know, so on. And we've had other people. We've been lucky to get such folks. So hiring is critical and keeping the original talent, I think. Those were some of the things. Yeah, usually founders, usually only one of the co-founders contributes long term.

1:03:09And so to have, you know, to have that going and Jan's still on the board and Scott's still on the board. But I mean, like, it's very unusual. We have a lot more we can get into, but we're at time. So we'll leave it for future episodes of Boss Talk. This is a great episode. All right. That was fun. Thanks so much. Thank you so much. Thank you. Thanks for listening to this episode of the A16Z podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify.

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