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Ben Horowitz and Ali Ghodsi: How to Run a $100 Billion Business

Ben Horowitz founded Loudcloud in the middle of the dot-com bust and sold it for $1.6 billion, then led Andreessen Horowitz from its founding to $46 billion in committed capital. Ali Ghodsi co-founded Databricks, stepped in as CEO during a crisis, and led it to a valuation of over $100 billion. In this episode of “Boss Talk”, Ben and Ali join a16z General Partners Sarah Wang and Erik Torenberg to share founder war stories, how to hire and make deals, how to keep culture intense without burning employees out, and why founders should raise their ambitions even higher. Follow Ali on X: https://x.com/alighodsi Learn more about Databricks: https://www.databricks.com/ Timecodes 00:00 Boss Talk returns 01:01 Why Ali became CEO of Databricks in 2016 09:45 From academic to CEO 16:00 Radical candor feedback and developing high performance 19:10 Scaling intensity and culture with Databricks’ ethos 31:55 The Microsoft deal strategy timing tactics 39:00 Fighting through setbacks and sealing the partnership 42:05 Building vs buying, how Databricks approaches acquisitions 54:55 Turning down acquisition offers and aiming for trillions 1:03:45 Key pivots luck and the Databricks founding team legacy Follow Ben on X: https://x.com/bhorowitz Follow Sarah on X: https://x.com/sarahdingwang Follow Erik on X: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see a16z.com/disclosure

Ali GhodsiguestErik TorenberghostBen HorowitzguestSarah Wanghost
Oct 15, 20251h 4mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:001:01

    Boss Talk returns

    1. AG

      I was like, "Maybe they're right. Maybe we should just sell." And I remember having that conversation with Ben, which is he said, "Hey, you can do whatever you want. You can sell, you're gonna make a lot of money, and you'll be super successful in life. But, you know, if you're like me, you're gonna 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."

    2. ET

      It could have been.

    3. AG

      "So do you wanna live with that, or do you wanna just have the money?"

    4. ET

      [laughs]

    5. AG

      "You know, I'll support whatever you wanna do."

    6. ET

      [laughs]

    7. AG

      "I really couldn't care less."

    8. ET

      Excited to bring back Boss Talk. This was a series that you guys did a few years ago on Clubhouse that was a-

    9. BH

      Yeah

    10. ET

      ... a big hit.

    11. BH

      Yeah, we had fun. It was Ben's idea.

    12. ET

      Yeah.

    13. BH

      Yeah.

    14. ET

      Ex-excited to bring it back. So in the spirit of, of, of Boss Talk, let's talk about the, the first time that you became a boss in terms of running, uh, uh, Databricks. Um, let's talk about the moment in 2016 when Databricks was, was, uh, not-- things weren't as smooth as perhaps they should have been, and we were looking for a new CEO, and, uh, Ben, you recommended Ali.

    15. AG

      First of all, like kudos to Ion for building the company originally and, uh, Ben-

  2. 1:019:45

    Why Ali became CEO of Databricks in 2016

    1. BH

      Yeah

    2. AG

      ... uh, you know, investing and believing in us. And then also, I kinda couldn't have done the CEO job. Uh, Ben basically babysat me-

    3. ET

      [laughs]

    4. AG

      ... uh, the first couple years. You know?

    5. BH

      It was a short, short babysitting job. [laughs]

    6. AG

      You know, so, uh, um, but I, I did know what was kinda wrong with the company 'cause I had been there for two, three years, and I had seen from inside, you know, what we should change and what the issues were. Uh, but we had an open source project that actually became very successful-

    7. BH

      Yeah

    8. AG

      ... thanks to those first two, three years. Apache Spark became a worldwide sensation, and we could pride ourselves on the number of downloads, uh, of the software.

    9. BH

      Well, and, and, and the, uh, the Spark Conference.

    10. AG

      Yeah.

    11. BH

      You know?

    12. AG

      Yeah, Spark Conference-

    13. BH

      Now the Data and AI Conference.

    14. AG

      Yeah, but the problem was that, uh, you know, as it is of-often with open source is that you just, uh, um, everyone's just downloading the open source version.

    15. BH

      Yeah.

    16. AG

      Actually, your biggest enemy, uh, is your open source project. The main thing you have to fight in the market is, "Hey, why can't I just download the open source version? Amazon is offering it. The cloud vendors are just offering it. I'm just gonna use that."

    17. BH

      Right.

    18. AG

      So this was the biggest challenge that Databricks had at the time, and we needed to do, like, very serious, aggressive pivots internally, which were gonna be very, very painful to lots of people, like, to the whole ethos of the company internally. And, uh, uh, so I kinda knew that for almost a year. So when I got the shot, uh, that's kinda like the, the... what we started doing.

    19. BH

      The strategy was, like, make Spark the biggest open source thing. I mean, I, I, I can remember it on all the slides now. And then, you know, Databricks would have the best Spark. But we never... Da-Databricks never had [laughs] the, like, necessarily... We didn't do a lot to make it the best Spark or, or not differentiate it enough, and that was kinda the first thing Ali did on the product side. And then he hired, um, Ron Gabrisko, which that was transformational 'cause that kinda dragged the company into the world.

    20. AG

      Yeah.

    21. ET

      So obviously, that was the right de-right decision and, and paid off. May-maybe zoo-zooming out, Ben, you've worked with, and, and you know all the great CEOs of our era and worked with them. Um, where, where does Ali spike? And where are his superpowers as a, as a CEO, as a boss that have, uh, helped, you know, contribute to the impact?

    22. BH

      I mean, Ali's really good. So, like, I always rate CEOs. [laughs] It's like, okay, if I was running that company, would I do a better job or a worse job? And, and with Databricks, I'd do a way fucking worse job.

    23. ET

      [laughs]

    24. AG

      [laughs]

    25. BH

      So, so he's good on many, many dimensions. So I, I, I'd say, first of all, you know, he, he is a real technologist, like, not a, you know, pseudo-technologist, um, like his competitors. [laughs] I'm sorry.

    26. ET

      [laughs]

    27. AG

      [laughs]

    28. BH

      Um, so he really knows the product. He understands the product strategy and detail. He also, uh, ran engineering before he was CEO. So, you know, mostly what I worked on him with, with him on the early days was just, okay, go to market and BD, and, um, and he's really good at both of those. Uh, you know, th-that's where we had to catch up. You know, Snowflake had an amazing go to market. Uh, and then we needed a big deal with, you know, kinda big partners. And I remember, I mean, I [laughs] I got him, like, a little BD tutor, John O'Farrell, who, who did a nice job, came in and kinda taught Ali about how you structure a deal, how you do things. But, like, he learned everything so fast. And then probably the thing that he does that is... I wish I could get all our CEOs to do is he doesn't, he doesn't hesitate. He trusts his eye.

    29. AG

      Mm-hmm.

    30. BH

      Like, he'll see something, and he doesn't know if it's right. And so if you look at the strategy changes Databricks has had, you know, one big one was building a data warehouse. Like, that, that, like, is a pretty big swing and a seemingly, like, quixotic, insane idea given where they were. Um, but, you know, he, he both knew... He's paranoid enough that he knew that that could be an issue, and then he trusted himself enough to go get deep enough to decide whether to do it or not, as opposed to, you know, ignore it. Like, "These guys are trying to kill me."

  3. 9:4516:00

    From academic to CEO

    1. AG

      conversion ratio is 5%, but I can't divide any of those two numbers to get 5%."

    2. BH

      [laughs]

    3. AG

      And then the person freaked out, and I'm like, "Don't freak out. Just tell me which of the two numbers do I divide to get 5%?"

    4. BH

      [laughs]

    5. AG

      " 'Cause I've divided all of them, and none of them is five."

    6. BH

      [laughs] They're like, "Am I gonna be fired?"

    7. AG

      [laughs]

    8. BH

      So, so, so he does a much better version of that, which is he'll, like, if, if somebody's really, really screwed something up or messing, he- he'll just go, "How do you think it's going?"

    9. AG

      [laughs]

    10. BH

      And I was like, since he told me that, I was like, "Oh yeah, that's a better way to do it. That's even better." [laughs]

    11. AG

      [laughs]

    12. BH

      Uh, so yeah, yeah. He, he's, he's a very good student.

    13. AG

      Can I riff on that? So like, you know, I, I think that's a... You know, there's this book called Radical Candor, and I think people take it too far, and they misunderstand it and so on. But I think the essence of that book is that, um, if feedback, if, if, you know... Are you criticizing me?

    14. BH

      Yeah.

    15. AG

      Are you saying I'm stupid, I can't do division? 'Cause my point is not about the 5%. I was trying to make a different point, and now you're just... This is a cheap shot. And now I'm, like, hurt, and I think, by the way, I think you're wrong. It's not five, I said six and a half.

    16. BH

      Yeah.

    17. AG

      So are you criticizing me, or is it like, "No, no, no, I'm here, like, to help you. I can, like, not help you, but if you beg me for help, maybe I'll help you." So which of the two modes? So if you can get people into the mode of like, "Oh wow, I'm, like, being helped. Like, they're helping me, and I'm gonna get further ahead in my career, and I'll be more successful. Uh, please, no, no, no, please don't leave. Come back and tell me more, like, 'cause I wanna... I'm taking notes here." So if you can flip to that. And I think a lot of, uh, feedback can be recast into, you know, "I'm, I'm just here to help you, but feel free to completely ignore this advice. But, you know, if you wanna be really successful, if you wanna get that job, or if you wanna get that project next time, if you did it this way, then you probably would've had a higher probability of getting that. But, you know, I don't care. You do whatever you want." And then le- people are much more receptive. They're like, "No, no, no, please, I wanna know more."

    18. BH

      Yeah. Yeah, yeah. Well, and then just the frequency of it I think helps a lot too, where if you, if I see you once a year at your review, and I tell you what's wrong with you, you're gonna be offended no matter what it is. No matter how wrong it is, no matter how correct I am, it's gonna be offensive. But if every day if I see you doing something I don't like, I go, "No, don't do it that way. Do it this way," then you get desensitized to it. And so I think the mistake a lot of particularly engineers make is they just don't-Say what they think when they think it 'cause they're afraid of hurting someone's feelings. But that's how you save their feelings, 'cause they're used to you. Um, you know, that's... You're, you're always doing that, and you're doing it with everybody. They see it. They're like, "Oh, yeah, fuck Ben's an asshole. He's, like, always doing this." But, like, that's how he is, and, like, that's how we work, and it's no problem. Um, as opposed to, you know, the, the hammer. And you try and put it in a shit sandwich. "Oh, you do this really well, but this is all fucked up."

    19. SW

      [laughs]

    20. BH

      "But this is good." And people are like, "Well, so, like, now in my written review, you're telling me that for the first time this is all fucked up? Like, fuck you." [laughs]

    21. SW

      [laughs]

    22. AG

      Yeah, this is, this is very common.

    23. BH

      Yeah.

    24. AG

      And, and you, you can see this in, in the industry, that, you know, people... Like, you know, the extreme version of it is, like, they get fired.

    25. SW

      Right.

    26. AG

      And then head of HR talks to them, and they're like, "Did you know... Did you see this coming? It was obvious, right? You knew this was gonna..." "No, I had no idea."

    27. SW

      [laughs]

    28. AG

      Like, it's like, "Wait, you didn't get any feedback on this?" Uh, "No. Like, I, I only got thumbs up all along for, like, a whole year, so I'm sh- in shock." Um, this is super common, right?

    29. SW

      Um, so maybe on the topic of managing talent, um, you have this incredibly high intensity culture at Databricks. Um, and there was this thread recently in our CEO thread where they asked everyone, but you had a great response on, "Hey, we have 50 people. How do we scale? We have this culture of 9:00 to 6:00, right? You work 9:00 to 9:00, six days a week." Um, how have you scaled that intensity well into 10,000 employees?

    30. AG

      I think, uh, start with, you know, setting the tone at the top. If you're the hardest working person, you know, it kind of everything will take care of itself from there on. Uh, if you're not working hard, it's very hard. I mean, it's... If you have... You know, it's a double standard. I mean, Ben has a whole book about that, like, which is, you know, the, you know, it's basically, you know, What You Do Is Who You Are is the whole title of the book, right? So it's like if you are working extremely, extremely hard, the rest of the organization is also as well. Uh, you know, are you calling people at 9:00 PM, 10:00 PM? Are you working weekends? Do they expect you... Not that you expect them and you're gonna be angry and yell at them if they're not dropping everything for you, not that. But the fact that they just know that Ali's working 24/7 and he's working seven days a week and, you know, he's working at 11:00 PM or 2:00 AM or whatever it is, uh, I think that gets a lot of it done. Uh, the second thing I would say is, uh, you can vet for this when you hire people.

  4. 16:0019:10

    Radical candor feedback and developing high performance

    1. AG

      it at scale at bigger companies, so I think that's highly recommended reading as well.

    2. BH

      Yeah, and I think, uh, you know, a lot of it at, at his scale ends up being things like organizational design, and do... Are people feeling like they're having an impact when they're... Like, it... If people are feeling like they're having an impact and they're good, then they'll work very hard. Um, but if you're in some kind of weird three-legged race that the CEO has constructed where everybody's got dependencies on everybody else, it do- it just doesn't matter. You know, like, you'll, you'll just have a lot of people who go, "Look, I know if I work hard, it's not gonna make a difference, so, like, why would I do that?" And, like, you can't overcome that with rah-rah, and, you know, lead by example or anything else. Like, that's just fundamental to how it is. And you see in, like, like in any company of any scale, um, you know, even at our scale, like, there are some groups who really, uh, can have impact and work extremely hard, and then groups who have lesser impact will work less hard, and you, you just see that.

    3. AG

      You know, people who are motivated and they feel excited about work a- and they know, see the impact that they're having, they're gonna work way, way, way harder. Versus if you're demoralized and you feel like it's, it's not going well, I'm not having impact, I don't have any autonomy, um, then, um, you know, you're not gonna... You, you just don't wanna even. You're, like, kinda depressed sitting down working. I do think there's one thing here where leaders can really help, which is to make your team feel like they're winning and that they're doing a great job.

    4. SW

      Mm-hmm. Totally.

    5. AG

      Like, you can ask more from people.

    6. SW

      Yeah.

    7. AG

      But if I feel like, hey, I'm losing, and everything we're doing is wrong, and I'm putting in all these hours, and it's stupid-

    8. SW

      Yeah

    9. AG

      ... like, there's like-

    10. SW

      Totally. Blurring-

    11. AG

      ... what's the point of this, then people don't wanna work. So you, you... So I think it's, like, feeling like we're winning, like we're the winning team, we're winning, like, you know, and wow, they're expecting more from me, and, you know, so then I think you can get... You need that motivation in people.

    12. BH

      Yeah. Yeah. Which is why, by, by the way, the hard job is when you aren't winning-

    13. AG

      Yeah

    14. BH

      ... to get the output.

    15. SW

      Mm-hmm.

    16. BH

      Like, particularly in, uh-Silicon Valley 'cause, you know, you- you're, you're battling attrition, this and that, and to get things on the right track, that, that, that, that takes a whole different kinda level of technique and storytelling, and show you how you could be winning [chuckles] and all that kinda stuff.

    17. AG

      Yeah.

    18. BH

      That, that gets very, very complicated.

    19. AG

      We've both done that, right?

    20. BH

      Yeah, yeah. Yeah, yeah. We've both been through it.

    21. AG

      There's, there's been phases in our companies' lives where we weren't winning.

    22. BH

      Yeah. Yeah.

    23. AG

      Um, I mean, especially, you know, this, the story you had in, uh, Hard Thing About Hard Things, which is-

    24. BH

      [laughs]

    25. AG

      ... probably the best business book I've read, which I read, by the way, before, uh, starting Databricks and it influenced us a lot. Um, you know, those are important.

    26. BH

      Yeah, very... Yeah. The, th- that's a, that's the difficult... [laughs] That's such an important point 'cause even if you're winning, people gotta feel like that. But if you're not winning, getting them to feel like you're winning is...

    27. AG

      We have a path to winning.

    28. BH

      Yeah, we have a path to winning. [laughs]

    29. AG

      We have a... You know, and it's, like, rock solid.

    30. SW

      Yeah.

  5. 19:1031:55

    Scaling intensity and culture with Databricks’ ethos

    1. BH

      feel that horrible pain again, so it's... [laughs]

    2. SW

      [laughs]

    3. AG

      Well, it's easier to be the underdog in some ways, right? You know, you have nothing to lose.

    4. BH

      In some ways.

    5. SW

      [laughs]

    6. BH

      In most ways, not. [laughs]

    7. SW

      Well, I wanna explore this leading from the top-

    8. AG

      Mm-hmm

    9. SW

      ... 'cause that was kinda the first thing you started with. Um, we actually hired an ex-Databricks employee to a16z, so we have some inside scoop on your leadership style.

    10. AG

      Uh-oh.

    11. SW

      And one of the things he said was you have this... And Ben sort of touched on this, too, but you have this amazing ability to be strategic, help your team focus, but you're also very in the weeds. Like, you're giving product feedback, you respond to emails super quickly, um, and product launch emails, no matter how small they are, you'll respond, "Congrats," which, you know, he found hugely motivating. How do you do all that?

    12. AG

      Yeah.

    13. SW

      Like, and where do you fly high? Where do you fly low?

    14. AG

      Yeah. By the way, I, I respond even to progress reports on all those products, and I follow them-

    15. SW

      [laughs]

    16. AG

      ... in detail, every one of them. I try to respond to every product.

    17. SW

      Insane.

    18. AG

      Respond. But, um, um, look, I think this is... I- if you're just gonna fly high and give high-level, like, inspirational speeches, and then, you know, we'll trust and we'll delegate to people, it's not gonna work. So my way is, you know, you gotta get in the weeds. You gotta understand. This is back to what I said at the very beginning.

    19. SW

      Yeah.

    20. AG

      Like, how, how do you become great at the head of engineering? How do you hire a great head of marketing? The only way you can do that is by being really excellent at it. So you need to study the game and become the best. So, um, so I try to stay, uh, you know, stay tuned to all of these things. Um-

    21. ET

      Th- there's this quote, "If you do everything, you will win."

    22. AG

      Yeah.

    23. ET

      And then the question is, you know, have you done everything?

    24. AG

      Exactly.

    25. ET

      [laughs]

    26. AG

      Exactly. Exactly. So yeah, so, you know, you just... It, it takes a lot of effort. Um, you know, you need to learn all your keyboard shortcuts.

    27. SW

      [laughs]

    28. AG

      Um, but, um, but I think that's... You know, p- people feel motivated, that, "Hey, I have, like, direct relationship." You know, we used to say, we used to have one of co- one of the culture principles used to be, "Hey, uh, be a co-founder," uh, and we don't wanna have any employees at Databricks. We just want co-founders. So, uh, a- and the key point was, like, "Hey, you're kind of the owner of this company. Uh, you're not just a renter. Come here, and yeah, we can talk about it. And you can, you can suggest an idea. You might have just joined, and you're straight out of school. You might have a great idea for a product. Tell me about it. You know, I'm, I'm happy to push it." And so it's, it's making people feel like they, they have an impact, and they're inspired, back to Ben's point. Then it's gonna be much more, more exciting for them, right? Than following some bureaucracy. So I tr- I don't follow the bureaucracy, basically. I go talk to anyone I like. Uh, you know, I try to go to the person that is actually the closest to the work that's being done at any given time.

    29. SW

      Wow.

    30. AG

      Uh, but there are some tricks and rules around how you do that without breaking the whole organization. So you can't just willy-nilly, uh, talk to anyone. Uh, but yeah, that's, that, that's part of it.

  6. 31:5539:00

    The Microsoft deal strategy timing tactics

    1. AG

      extremely beneficial both sides. There has to be a trade that makes sense. Microsoft really wanted that product. We really wanted their distribution channel.

    2. BH

      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, and we lost that deal. [laughs]

    3. AG

      10 times.

    4. BH

      10 times.

    5. AG

      [laughs]

    6. BH

      And, like, w- including, like, the day before we were supposed to launch it, um, the, you know, the, the antibodies came out of the company and, uh, Ali had to fly up to Redmond [laughs] and sit there and-

    7. AG

      There was, there was one engineer that just said-

    8. BH

      Yeah

    9. AG

      ... "Not doing this."

    10. BH

      Yeah.

    11. AG

      "This is not gonna go. We don't..."

    12. SP

      [laughs]

    13. AG

      He just... He, he was, like... They actually put a guy in place at Microsoft who was actually super... He had a great reputation, but he was a builder. So he just had huge problems with this. He's like, "This is not a product I built."

    14. BH

      Yeah.

    15. AG

      "Why would we, why would I make this successful?" Uh, so yeah, there's, like, usually there's, like, many times. So, like, if, if you don't have grit, those deals will die 'cause this deal died multiple times, as Ben said. It 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 you have to... And the only way we did it, I w- like, they call it the nerd bird. I would take the, you know, uh, SF, Seattle flight up there. I was up there so much.

    16. BH

      Yeah.

    17. AG

      I knew all the buildings-

    18. SP

      Wow

    19. AG

      ... all the rooms, everything. So you just have to just spend time on the ground and talk to as many people as possible and sort-

    20. BH

      Yeah

    21. AG

      ... of influence that organization from within.

    22. BH

      And I will say, look, you know, w- with all the difficulty of the deal and, um, you know, and, and Microsoft being Microsoft, th- they've been as good a partner, um, as not only we've had at Databricks, but in the entire portfolio. I mean, they've really, you know, lived up and delivered, uh, what they said they would do, which is... I, I think you have to give Satya a huge credit 'cause, like, in the whole Gates and Ballmer era, they were never that good a partner to anybody, and he's really turned that around. And, um, you know, they've, they've been fantastic with us.

    23. AG

      This was around the time where Satya had taken over, and, you know, he, 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, we should try. Like, let's try to make things happen. Let's have a growth mindset here. Let's see, is there a way we can partner? So this would've been impossible five years earlier, so it is kudos to Satya, and he put us on the map.

    24. BH

      Yeah.

    25. AG

      And he's been a great partner ever since. You know, whenever there's been issues, they always resolve it. Uh, so, um, you know, we are very thankful. We wouldn't be where we are without them.

    26. BH

      Yeah. No, just, just amazing. Amazing, really.

    27. ET

      I, I wanna open up the conversation to deal-making more, more broadly now that you're not a, a, a small company a- anymore, and you're a big company making acquisitions, you know, uh, Tabular, Neon, Mo- Mosaic just to name a few. W- what is your sort of your, your approach in terms of when to, to, to build versus when to buy/how do you think about sort of acquisitions more broadly?

    28. AG

      Yeah, I mean, what we try to not do, so let's start with a simple thing, uh, is a lot of companies, especially at scale, they'll buy revenue. So they'll look at a company and they'll say, "Hey, this company is this size. We'll just, uh, buy that company. We'll put more salespeople on it, then we can accelerate the revenue. We're buying that revenue." Uh, and that's how they're doing it. Um, 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, so 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 from the C- with the CEO from day one. Like, you can see it. The big companies, they literally have a plan. Like, I ha- you know, I have some execs that come from these big companies. They say, "Hey, our plan usually is to part ways with the CEO." Like, you make a deal and the CEO can leave. Um, 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, and then eventually you bring in your own people to take over the company, and then the company's dead. There's nothing left of it, and there's no integration between that asset that you bought and the platform that you have. Um, 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 bu- like, the, the company we're buying, who are the founders? How do they work? Are we culturally the same? Spend time with them. Like, do we get along? Do we see the world the same way? You know, are we gonna click? Are we gonna do this together? Um, are we gonna 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, uh, on the product. You know, what's the product experience? How would we integrate this? What would it look like? How much can we... Can we rewrite most of it? Can we not rewrite it? What's the w- what programming? Like, I always ask this, and people are like, "Why? That's such a dumb question." I say, "What, what language did you write it in?" And they're like, "Why do you wanna do that? What does, what, what does that matter?" No, 'cause we're gonna integrate the code bases, right? It's like the build systems won't work. It's not gonna even compile. So, um-Uh, so the product is something we spend a huge amount of time and talking to customers, understanding what the, um, what the, what the excitement around that product looks like and how the integration would look like. The last thing we do is we'll look at the financials. You know, what's the revenue multiple, and, you know, 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 this, in my Excel sheet here, this makes perfect sense.

    29. BH

      [laughs]

    30. AG

      Uh, 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-"

  7. 39:0042:05

    Fighting through setbacks and sealing the partnership

    1. AG

      get a second-year boost in revenue growth as well. So finan- define- 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.

    2. BH

      And it affects the brand. You know, like one of the things is th- 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 'cause the reputation is every customer's experience. There is, there is no marketing through that.

    3. AG

      It's the best software because-

    4. BH

      Yeah

    5. AG

      ... it was written by the engineers and built by those that were the best.

    6. BH

      Yeah.

    7. AG

      Including the acquisitions that we got. Like, they were phenomenal people.

    8. BH

      Right. Yeah.

    9. AG

      They came in and they continued, and since we gelled, they continued building it, so that's why it's great. It's like the, you know, the-

    10. BH

      Yeah.

    11. AG

      So we pay a lot of attention. That's like back to the, you know, who are you getting into your company?

    12. BH

      Yeah. Yeah. Oh, that's the other thing, right? Like, [chuckles] you can buy something that's got a lot of sales where you're downgrading your whole, like-

    13. AG

      Yeah

    14. BH

      ... company. Ross Perot actually wrote about, uh, 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, and they're like, he was like, "They're gonna absorb us, not vice versa."

    15. AG

      Yeah.

    16. BH

      And that does happen.

    17. SP

      Sure.

    18. AG

      Yeah. The, there, there is one really good company that, um... Well, one really successful company that, uh, 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 di-dilute Databricks. Uh, you know, 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, so.

    19. BH

      Yeah. It's also why, like, merger of equals are c-

    20. AG

      Yeah. Very hard

    21. BH

      ... 'cause the cultures aren't equal. The people aren't equal.

    22. SP

      And what made you feel that way? You just spent time with them and you, they just didn't exude sort of Databricks culture? Or you heard-

    23. AG

      Well, I mean, it's, it's... Look, it's, it's like with everything else. Like, it's like when we were gra-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, it's, that's in the gray zone. This was a company that was, you know... I feel like the talent is not phenomenal, and you don't need to be a genius-

    24. SP

      Yeah

    25. AG

      ... to know that. And then there's some startups you know immediately. Like, you know, okay, these guys are Olympiad winners, and they're like phenomenal, and they're like-

    26. SP

      Yeah

    27. AG

      ... executing like crazy, and they have a track record. Uh, so I don't think those are that hard, and we try to hire these, and these, 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 trying to suss out. Like, you know, 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. Maybe they could if we give them a chance, or maybe they're just mediocre. Uh, and that's where-

    28. BH

      Yeah

    29. AG

      ... you spend a lot of your time. But you gotta spend time with them. You have to interview all the people. Um, you know, you have to have your people interview all the people. Can't just be, this can't be an Excel s- sheet exercise.

    30. BH

      Yeah. And Silicon Valley has a lot of lopsided companies, so, you know, you'll have a great engineering team and a bad company 'cause it's like, you know,

  8. 42:0554:55

    Building vs buying, how Databricks approaches acquisitions

    1. BH

      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. And, you know, you gotta be very, very careful about that. Actually, our, [chuckles] you know, our, our, our CRO at Databricks is, you know-

    2. AG

      He loves us

    3. BH

      ... he came from a company that, you know, he, he sell anything.

    4. AG

      Yeah.

    5. BH

      [laughs]

    6. AG

      He was, he was, he was w- w- he was selling SFTP, secure FTP-

    7. BH

      Yeah

    8. AG

      ... which is free.

    9. BH

      [laughs]

    10. AG

      And he was selling it for a lot.

    11. BH

      That's how you know he's good.

    12. AG

      He was selling it for a lot.

    13. SP

      Yeah.

    14. AG

      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."

    15. SP

      Yeah. [laughs]

    16. BH

      You need it to be secure.

    17. SW

      Yeah. [laughs]

    18. BH

      Right.

    19. SW

      [laughs]

    20. AG

      Bet on somebody grabbing that file.

    21. BH

      Yeah. He's good.

    22. SW

      Yeah, the only thing I'd add, too, is this strategy is probably making you more attractive to the people you wanna acquire, too.

    23. AG

      Yeah.

    24. SW

      They don't wanna sell if they're gonna get fired right away.

    25. AG

      Yeah. For sure.

    26. SW

      It's very competitive.

    27. AG

      Yeah. 100%, yeah.

    28. SW

      Yeah.

    29. AG

      I mean, you know, there's also reputation, right? People know. Like, they'll look back and say, "Okay, what happened to your previous acquisitions?"

    30. SW

      Yeah.

  9. 54:551:03:45

    Turning down acquisition offers and aiming for trillions

    1. AG

      'cause I said you start with the people, right, and then the product. And with the people, I love to hire people who have seemed 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-

    2. BH

      Mm

    3. AG

      ... so they understand how to navigate a bureaucracy and work with it, and they're not gonna just be inundated by it. But then they've gone on and done their own startup and, um, and that's really, really hard, right? It's like, it's like extremely hard, uh, trying to do everything yourself, and you don't have any help, and you're, you know, you're trying to do this in this crazy market, and you're trying to compete with the $100 million offers when you have, like nothing. Um, so that takes a certain amount of grit, and it's really humbling. Uh, so I love the people that have done both of those. They end up being actually the perfect employees at Databricks 'cause they come in and they're really thankful.

    4. BH

      Yeah.

    5. AG

      They're like, "Hey, what these guys have done at Databricks is actually really, really hard."

    6. BH

      Yeah.

    7. AG

      "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. So-

    8. BH

      Yeah

    9. AG

      ... you know, I think, uh, keep a great relationship with people who leave your company 'cause they'll, they can boomerang back in a couple years.

    10. BH

      Yeah. Yeah, and look, it, it's, it's very hard to make these things work. Um, and, and, and you... It, it also requires a lot of luck. I mean, I think one of the-

    11. AG

      Yes

    12. BH

      ... things people don't realize is a lot of things have to go right that should never go right. [laughs]

    13. AG

      Yeah.

    14. BH

      Um, and a lot of things will go wrong, but, like, if you can grab your lucky moments, that's a rare, that's a rare thing.

    15. AG

      Yeah. One, one, one way to prove that is if Databricks... Databricks started in 2013. If we had started in 2012, you know, that rocky year, that difficult year, 2015, would've then happened in 2014-

    16. BH

      Yeah

    17. AG

      ... right? To start the funds. They're saying we don't, we don't have the revenue. But we were a cloud AI open source company. Uh, those things didn't take off in 2014. So-

    18. SP

      Yeah

    19. AG

      ... you know, even if, like, if we had to do the CEO change and all of that, and I had become CEO in... a year earlier, it just, we were too early in the market. The cloud hadn't taken off. AI was not... Nobody... That, that was not even a phrase. AI meant robotics. People used machine learning-

    20. SP

      Yeah

    21. AG

      ... as the phrase.

    22. SP

      Mm.

    23. AG

      And, uh, so company would've 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, uh, we would've had our difficult year in 2016. But by 2016, the cloud was starting to happen, AI was starting to happen, you know.

    24. BH

      Yeah.

    25. SP

      Mm.

    26. AG

      So we would've done the fixes in 2017, and it would've been too la- to- late to the party-

    27. BH

      Yeah

    28. AG

      ... and probably the hyperscalers would've taken it away, you know, our competitors were taking it away, and we w- just wouldn't have get enough, uh, momentum to be able to succeed. And-

    29. BH

      Yeah

    30. AG

      ... that's timing of when we started. So how did we clock it so well? Uh, we had to wait for Matei to finish his PhD thesis.

  10. 1:03:451:04:51

    Key pivots luck and the Databricks founding team legacy

    1. AG

      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.

    2. BH

      Yeah.

    3. AG

      Patrick led all of engineering and big chunks of it and, you know, so on. And we've had other people. We've been lucky to get s- such folks. So hiring is critical, and keeping the original talent, I think.

    4. BH

      Yeah.

    5. AG

      Those are some of the things.

    6. BH

      Yeah, usually founders, usually only one of the co-founders-

    7. AG

      Yeah

    8. BH

      ... contributes long term, and so to have, you know, to have that going, and Jan's still on the board, and Scott's still on the board, I mean, like, it, it's very unusual.

    9. AG

      Yep.

    10. BH

      We have a lot more we can get into, but we're at time.

    11. AG

      Yeah.

    12. BH

      So we'll leave it for future episodes of Boss Talk, but this is a great first episode.

    13. AG

      All right.

    14. BH

      I'll leave it at that.

    15. AG

      Well, that was fun.

    16. BH

      Thanks so much. Yeah.

    17. AG

      Yeah, thank you.

    18. BH

      Thank you so much, guys. [upbeat music]

Episode duration: 1:04:51

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