Databricks’ Ali Ghodsi Never Wanted to Be CEO. Now He’s Among the Best

0:00 And is that Monday morning meeting really useful? Or is it theater? Can't you just have a Google doc and get it done that way? >> We're talking about humans. Why should I like you or trust you if I never get to meet you? >> Mhm. >> I don't know if you're married, but do you want Why do you Why do you have to meet your wife at all and their kids? Can't you just have a Google doc?

0:18 >> We just write down the stuff you want to like if there's something you want to teach your kids of, put it in the goddamn Google doc. Maybe you don't even need to respond to the Google Doc. Cloud cam. Hey everybody. Today we have Alli Goatsy on the podcast. He's the founder and CEO of Data Bricks. I've wanted to have him on for a while now. I had Ben Horowitz from A16Z on a few months ago and I asked him who is the best CEO out there and without thinking much about it, he said Ally. And after interviewing him, I kind of agree. He's really sharp. A younger me would have loved to have worked from for him and learned from him. Hope you like it. I'll be back at the end with my takeaways from the interview. Ali, welcome to Long Strange Trip.

1:21 >> Thanks so much. Excited to be here. >> You had an interesting road to the CEO chair at your company. From what I understand, the company was founded. There were seven co-founders at Data Bricks. And a few years in, it wasn't exactly ripping. The board decided it wanted to make a CEO change. Can you kind of take us into the room when those conversations were happening and I assume they interviewed you like what happened? >> Yeah, I don't know. I think I knew I was hearing from the grape wine that they were like interviewing other CEOs and I would hear, oh, they interviewed that guy and they interviewed this guy. So, as far as I knew, I was like, they're not gonna even pick me. I knew the identity of at least two people. So, you know, it was I mean 2015 was kind of a turbulent year for data bricks because we were having great success with our open source project Apache Spark. we were just not having commercial success.

2:12 Revenue was, you know, gap revenue came in at like one and a half million that year. So, the vibe wasn't great. And so, I I kind and I'm like a glass half empty guy. So, I was like, I you know, I'm probably going to leave and we're all probably going to leave. So, I actually like Yeah. So I actually applied for you know a faculty job at Berkeley and >> oh >> and I was going to take that actually kind of towards the end and I was like kind of facing the dilemma which one should I should become CEO which is I never wanted to be CEO or should I go back to my dream of being a professor which is what I always wanted to do.

2:46 >> Fascinating. did they interview you? >> Not no like hey this is a CEO interview like what's your strat? No not really. Maybe they had some one-on- ones with me that I knew like, okay, are they kind of like filling me out or something, but all this was very hush- hush. Actually, I was not allowed to know that there's like a process going on kind of. >> The interesting thing about them picking you is my sense of the the problem the board had with the company is it had very little commercial success. You would have thought they would have hired someone with a lot of commercial background. You had negative amounts of that. What do you think was going on with that?

3:23 >> I think it's a 16Z and Ben. This is the period also. I mean they're still that way but they were like religious about like founders only and you know because they had themselves been through it. Remember Ben famously was asked at some point hey when are you going to bring a real CEO into your company and he felt like He wrote about it in his book right so I think he didn't want to do that to you know us founders. So I think he really believed like let's let's let's pick someone that is a founder. I he later then said hey this was anyway just a trial. we didn't even give you a CEO salary. So, we were like really testing you out. So, I think from his point of view probably, I don't know, he should you should ask him. He's probably like, "Yeah, we'll try it out for six months, 12 months. If we're going to do a search, we'll, you know, we'll put another guy in place in six months or so." And what do I know? Maybe the search they were doing didn't turn out very great. Maybe they hadn't seen any very good candidates. So, >> I see. How do you think your life would have turned out if you had left and gone back to be a professor? Like, do you ever think about that?

4:20 >> Yeah. well I mean right now academia is not doing super well so it would have probably been a big mistake but also I I introspected a lot during that period like which one should I pick like my dream is professor the CEO thing I'm not even sure I want to do it like I in the business world I don't have that much respect for it even it's kind of like going to the dark side but then I like looked over my life and the decisions that I had done up until that point and I kind of like realized a pattern. So when I was a kid, I grew up programming. I wanted to be a game programmer. My dream was to move to LA from Sweden and work for Electronic Arts because they were making the best weeks.

5:00 And in high school, I kind of, you know, someone I knew floated, hey, you can come to the US, you can get paid, I think it was 80K and be a game programmer. So I was like, this is it. This is my dream. At that point, my parents were like, no, no, no, you're going to university. No way. And I thought like this is like end of life. like they're destroying my but then I went to university and it actually turned out I learned a lot of things I learned a lot about computer science actually I thought I knew everything about computer science but then at the university I learn I I didn't know anything I knew a little bit of programming and and then I was a startup in the year 2000 and I was doing an internship and that startup I did really well and they like offered me to be number two guy there like drop out of school be number two the startup was called room 33 it was actually I think Europe's largest like mobile startup at the time so it was like wow this is like opportunity of my life. But then at at that time I went back to university and then you know the IT bubble burst and it turned out to be like the best decision of my life. Then that very university which was kind of like in a city far away they offered me professorship even without a PhD. And that even that I kind of was like oh do I take the professorship now and I'll be a full professor or do I go do an actual PhD at the top university which is very difficult to get into and challenge myself. And I picked the challenging option and again it like opened my horizons like it was way harder and it was much more difficult for me and you know but I learned so much and it's like challenged me and actually so eventually I became a professor at that university.

6:23 >> Okay. >> So then I had the opportunity to come to Berkeley at some point and at Berkeley they wouldn't take me as a professor they would only take me as a measly posttock. So kind of what happened is I took the chance and I went to Berkeley and I took the posttock and it again like widened my horizon. So I was like facing this decision. I was like I should probably take the thing that challenges me. I know nothing about being CEO. I know nothing about businesses. Probably the most challenging thing I can do is probably take the CEO on. Going back to Berkeley, it's kind of like I know how the game works. I know academia. So that's and I I think that was the right thing. And now it's kind of become a philosophy of mine. I want to sort of challenge myself as much as possible because you know how many years do we have on this planet?

7:01 >> Yeah. Okay. Love that. you were obviously successful. At some point, did the board come back to you and say, "It's not interim anymore. It's full-time." And I I'll give you the background on why I'm asking this. I'm a ginormous Boston Red Sox fan. And the Red Sox were terrible at the beginning of the season. They fired their manager and they brought in the interim manager, Chad Tracy, who has he broke a 125 year record of wins in a row. like he's just done a fantastic job, but he's still got the darn interim title, and it's like when are they going to drop the title?

7:38 Did they have a conversation with you? And what precipitated it after that six-month, one-year trial >> again? Like it was like about one year in >> Yeah. >> One of the one-on- ones I had with Ben, he first of all, they gave me like much bigger equity package. >> Yeah. >> And they bumped my salary >> and it talked about like the things that we strategically need to do. So it was kind of started to become clear, okay, this is not just, you know, a practice run or, you know, this temporary. They have like a little bit longer term perspective. So I think but they never said it, you know, officially. then a couple months after that, I invited Ben to our company, All Hands, where he kind of said, "Yeah, we didn't think he's going to do it either. We gave him like a temporary salary."

8:19 I had been on the pod and I asked him who is who is the best CEO in Silicon Valley not in the Andre portfolio and he didn't hesitate he said you. which I thought was quite a nice compliment. what can other firsttime CEOs learn from you're stuck in the chair, you didn't know anything about it. What can you teach firsttime CEOs that that led you to where you are today? >> Well, I think that, you know, you have to be on this extreme learning curve.

8:55 So, you know, it's not going to be easy. I mean, you're going to be working 100 hour weeks. That's what I was doing. I was making sure that I was networking with all the bests and learning from everyone that I could find. I was reading all the books. I was doing all these kind of things. but I was applying first principles thinking to everything I was sort of sucking in. So, I was making sure that it's actually making sense to do these things. I was I wasn't just like, "Okay, let's copy this. Let's copy that. Oh, that person said this. I'm going to do it that way."

9:20 you know, I was kind of building my own like kind of Bruce Lee built his own jet kundu based on all the different, you know, martial arts. I was building my own CEO playbook based on all the ingredients I was learning from the different places. And that way was like self-consistent. I think that was the that was one thing. That's one thing I would recommend to do. The second thing that's kind of been with me this whole time is I think typically companies are failing because one major problem, you know, I mean, maybe they have two major problems or three, but usually it's like one giant bottleneck.

9:52 And I think you should at that point identify what that giant bottleneck is and then focus the whole company and your all attention almost to an extreme like orders of magnitude of attention and focus should just go to this one issue and if you overdo it and you go too extreme overboard on that one issue that's great. >> Yeah. >> The problem is because you know you most likely won't be able to actually unclog or remove this bottleneck. So you should just turn all your attention to that. So for me at that time it was you know open source project check super successful you know tech super awesome no commercial success so put all the attention on figuring out how do we get this you know commercial engine humming so that was like laser attention I was getting the whole company mobilized I was talking every all hands about this I was thinking only about this one issue and so I think that's a useful way of operating a company I still operate the company that way I try to identify what the main bottleneck is at the time and I try to just focus on unclogging that because there's so much other stuff you have to do every day to hire people there's drama people are quitting the board this and that legal department customers revenue missing this there's like million things coming your way every day you don't have any time to move the needle on anything so focus on that main bottleneck >> okay and typically so you're laser focused on that bottleneck like what is the cycle on that there's one bottleneck a year you're tackling or one every three years or one every three months like kind of what is the cycle cycle.

11:19 >> Yeah, it's a longer cycle. So like I would say if I would if the answer to that would have been months or week then actually that's what everybody's doing every day. I think that's all the CEOs like you know cuz disaster lands in your knees you have to drop everything else you got to fix that thing that is not a strategic focus that's just tactical stuff. So I would say a year, two years, sometimes three. Like creating the lakehouse category took I think multiple years. You know when we announced the lakehouse category, we were ridiculled online. but it was a long journey to get to the launch of the lakehouse because there was so much resistance internally and from you know consultants and whatnot. Then when we finally launched it, people like were laughing at us. So you got to give things a few years. you can't you can't just give up immediately. So I think you should that that's it's really important that you identify that focus really clearly because if you pick the wrong thing and you're focusing on it for two three years needless to say you're not going to go anywhere.

12:16 >> Okay. Super helpful. what I read was the one of the first things you did on that bottleneck was you went out and hired I forget 13 kind of been there done that enterprise sales reps. First is that correct? And second, like how did you even know how to interview them? How did you know who was good? Like how does so many of the CEOs I'm working with are going through this process. How did you do that?

12:45 >> Actually, the first thing I did was kind of more or less revamp the whole executive staff. So I would say a year, year and a half later, the executive staff that was running the company was completely different from the one that I kind of inherited. so I would say that's like the one thing that I knew we got to we got to change that. because it's not working like the go like engineering a product I handed it off to a co-founder and I basically ignored it for two years I focused my attention on everything else to building up the rest of the muscle of the company and so that was that was the first one we have been doing this PLG thing so we wanted to product led growth we loved AWS people swipe a credit card we didn't want to have any sales people so that was kind of codified into the sort of ethos and culture of the company we don't want sales and we had hired sort of sales engineers and they were actually the sales department. We had a couple of AES but it became clear that look PLG is not working and actually in 2015 before I became CEO for a little while we ran an experiment called zero touch which was we shouldn't even ever talk to a customer it should all be automated funnel because it's PLG and actually you could see that there before that revenue was going up and it just flatlined for two quarter when we started doing that so you know at one and a half million revenue and you know you know that sales AES have a quot of like a million or two million in most companies you Like gosh, if we just get one AE and that guy or that gal crushes it, that would be the whole thing that we've done for the last few years. So, we should probably that's all the other options make no sense. We should just double down on hiring sales people.

14:20 Okay. But what kind of sales people should we hire? >> Yes. And how did you know even what questions to ask in the interview? >> Okay. Well, I ran this little experiment in my head which was let's look at companies where this is working. Are the best salespeople technical? Super technical, super smart. Do they have PhDs? Like the PhD technical, you know, kids are the best sales guys and no like absolutely not. So then I learned two things from that. It's like, okay, so probably that's like not the main thing. And secondly, it probably doesn't even have any advantage because if it had an advantage, there would be some some of these sellers that were great salespeople who also happen to have a PhD would be at the top making all but no, you found none of those guys.

15:05 >> I I don't think it's not only not an advantage, it's a disadvantage to have a PhD. >> There you go. There you go. So it became pretty clear that okay the way we are hiring AE is like we should change that. Like we were testing them on whether how technical they were because how smart are they? But I just looked at the best and none of the best are technical. So what are we even doing here you know? So we have to change revamp who we're hiring now. We also had an amazing sales leader that we hired Ron Grisco who knew what grade looked like. So we worked with him and you know he should get 99% of the credit for what happened on the sales side. but it was pretty clear that we don't just get only the technical people. It started becoming clear that there's you know other skills that sales people have that you should probably go after those. one of them is you know I think great technical people tend to be kind of more introverted. I'm generalizing here and they're sort of maybe not the most aggressive opinionated people that are just like toe stepping and so on, but I learned quickly that the best sales people actually they're kind of aggressive.

16:08 >> Very aggressive. >> Yeah. And the first one of the first ads that Ron had hired, Dave, got us a meeting with a customer that we couldn't get a meeting with. And in the meeting, the exec that had gotten us the meeting said that AE, get him out of here. I don't want to see that guy ever again. >> You know, he's he's emailed my boss, everybody else. This is like unacceptable. So like, got Dave guy. I don't want to see him at all. So then after I'm like, "Hey Dave, you've like pissed off the customer." Like, "Well, what the hell is going on?" He's like, "Ron told me get in into the building.

16:40 Figure out some way of getting in." Nobody was responding to an email. So I went through every door I could and I had to break glass. I got you the meeting. You know, what are you complaining about? So it suddenly became clear that okay they need to be professionally aggressive otherwise you know so it's kind of a little bit the squeaky wheel gets all the grease. so that itself is actually kind of counterintuitive for engineers you know from professor land that those are the kind of you know so that was one but also there was another meeting with one of the early ones I remember Keith we were in the room and the customer somehow got pissed at this guy and kind of told him like hey who the hell are you what are you even telling you like you should you know I was like that's pretty bad then he suddenly just started asking her these weird questions he's like okay so what is your team working on. I thought we're supposed to do sales. What does he do? I'll shorten the story. At the end of the meeting, she was hugging him saying, "I'm so sorry for saying that." And you know, so I was like, "Oh, wow. What did you do in there?" Like, he's like, "Well, I noticed she was emotional, so I wanted to bring it to subject that she's comfortable with. Everybody's comfortable talking about what their team members are working on." So, I moved the subject to an area. So I learned, okay, these these guys, they're just like really really amazing EQ of handling really difficult conversations, you know, that get really uncomfortable, you know, they're, you know, they're the kind of people that it's kind of hard to ignore them. You got to like if they email you, you got to respond back to them. So it started becoming clear that there's like a rubric. They need to be a little bit professionally aggressive.

18:06 They need to have amazing EQ. They need to be the kind of, you know, command of the room. and then eventually I started learning that okay the really smart ones they actually figure out what's called the power base of the company like how decisions get made high up in an organization. It's actually complicated. Not a single person will say I'm going to buy this for $100 million. It's a complicated web of influencers and people inside the customer you know you know that make this decision. So they have to work that power base. So it started became clear that this is an art and it's a very different art from what I grew up doing and we should just hire the pros and since it's so humanly intensive it's sales people are dealing with other humans a lot of the things we learned about how to deal with computers and math and logic and physics it doesn't apply over here and humans haven't changed so probably these techniques that they've learned over the last 30 years we should trust them so that that that was kind of the journey we went through and we revamped our sales team that way and a lot of this I learned learned from Ron. I pushed back and we had like all these arguments but you know eventually turned out he's right and we you know landed this model.

19:09 >> Okay. So many of the CEOs I'm working with are struggling with this. They have PLG they should go to enterprise then they're like I need my Ron. How did you find your Ron and talk about the early Ron because every it seems like everybody's looking for their Ron. >> Yeah. Well first of all I think he was unique because he's a classic salesperson. like he's the classic they call them, you know, meat eating, doing push-ups, you know, he's the classic, you know, they call him PTC, BMC style school, seller.

19:40 >> By the way, I'm a PT, I grew up at PTC. >> Okay, so then, you know, so, you know, he had been selling FTP, which is free, and making a lot of money on selling free FTP. >> Very hard to sell. >> It's hard to sell free stuff. so he was good at this is a phenomenal sales guy. But Ron was special. Ron also happened to have an engineering degree. He actually had a, you know, undergrad engineering degree and then when he at Stanford did his GSP degree, he also kind of got an engineering masters just for fun because he had cycles to burn. So I think he kind of could push back on us and he could kind of sort of talk in our kind of our language, you know, but he was really from that breed, but could speak our language and we could talk to each other and he would like entertain. So it wasn't like oil and water.

20:29 >> Y >> so >> he was smart. He was smart. >> He's smart but also are kind of smart. You know we've already covered now other types of smart that maybe an engineer won't have but he had both types of smart. >> By the way those people are very very rare that they not only have an engineering undergrad but they have masters in engineering with Stanford GSB. >> Correct. The second thing I looked for is you know and this comes back to you know can they build it? I like to think of it as can they build the machine or can they just run somebody else's machine?

21:00 >> Yeah. My joke is kind of like, you know, do you have a driver's license? Are you a good driver? Okay, can you build the car for me? >> Yeah, totally. >> You know, very different, right? >> but Ron had been in a in a startup called Cyclone and I think they went from 0 to 50 million AR-ish. So, he had seen that journey from 0 to 50. Then company eventually sold I think to Axway and there he had seen the growth up until hundreds of million.

21:22 >> Okay. So he had really seen 0 to 50, 50 to 100ish, you know, so he understood that scale very in in sort of very detailed way and he was very cerebral. So you could kind of really figure out can he he's either a guy that can build the the car or you know he just he's along for the ride and he's a great driver. but no, he he he knew how to build the car and you could like argue with him like hey why don't we put the engine on the back or why don't we change the design this way like we could but then that would break over this that wouldn't make any sense. So he had that third he had been in these two company like basically not changed company for 11 years. So it meant he had longevity because a lot of these folks will just bomb out again back to if you're doing something strategic like figuring out go to market motion it's going to take you two three four years.

22:06 So if the guy or gal is like bombing out after two years it's you got to reset and start overturns the organization. So he'd been there a long time. So I knew that he's going to kind of be loyal. So like if the going gets rough, he's not going to quit in the first instance, which also meant that I can probably be pretty rough like managing him. Like I can be pretty aggressive and he's not going to leave. Like we can we can have huge fights and he's not going to leave cuz he didn't leave from that, you know, hole is kind of how I felt. so then he's not going to leave from this hole. you know, okay. that turned out to be crucial because, you know, the classic PTC sellers, they're hard to manage. They're aggressive.

22:44 you know they're they're they're a handful to manage. They're very very difficult to manage. Ron as amazing is and he's created our like you know 1 million to 7 billion ARR engine. >> Okay. So Ron is still running sales. >> He is. Yeah. CRO. Yeah. We have a president but yeah Ron is CRO. >> That's very rare. >> It's very in fact these days I would say VPs of sales because these companies are growing so much faster than they used to. They're churning through them every like two or three years and they say, "Well, they can't scale. They haven't seen the scale." so that is congratulations on you and Ron. That is a really rare thing. Okay. You built out your exec team. Can you talk about that?

23:26 And then same thing like did you turn people over? Did you miss hires? Did people not scale? Like everyone's struggling with this that I work with. >> Yeah. Look, I think that by the time you know that you need to hire some an exec, it's too late. And there's sort of a trade-off. If you give me infinite time, I'll hire the best person. You know, I can find the best person. If you give me like five, six years, I can find an phenomenal person. But if you give me a very short amount of time, I can also hire someone quickly, but then the quality will not be great. So, what I did is I tried to hire ahead of the curve. So, like before we needed it, that would give me more time so that I could run the search for a longer period of time. And I could sort of increase false negatives and decrease false positives.

24:12 >> Wait, how did you do that? >> False positives means that you hired someone that you thought was going to be great and they're not great. You made a mistake. Now you have to fire them. >> You know, it's going to take you a year to figure out that they're not great. I mean, you might know after six months, but you're not going to fire your executive for six months. So, you're going to say that, oh, that's h you know, it's not clear. So, you're going to give it another six months. Then, after a year, if you have the guts, you're going to tell them it's not working out. You know, that might that might end there. It might take another six months. Now they've once they've left, you got to do the search again.

24:40 You're doing the search now. You're gunshy because last time you screwed up. So now you're hesitating. You might go for you might go for a compromised candidate which doesn't have any strengths but also no weaknesses. And then you have to ramp that new person. And so like you lost two two and a half years. So try to avoid that whole thing. So how do you do that then? I mean it sounds obvious. Well be really really picky. So skip on a lot of candidates who could be great. So at databicks I've skipped and said no to phenomenal people who've gone on and done great things and they have like a chip on their shoulder with respect to me. They're like I can't believe you didn't hire me. Look at what I've done since then. Like a picked mistake by you. I was like yeah but my my playbook was air on the side of being just extremely picky. Take decent amount of time start early and most of those guys that have been with me and gals have been with me like a decade. I >> Okay. So you you haven't seen the turnover in these >> I have. I am, you know, I probably I think I would say two two cases where I made a mistake. maybe more, but two like really come to mind.

25:40 >> And then and then you said give yourself some time. Is that 3 months, 6 months, nine months to be picky. >> I think it takes at least six months to do a good search, maybe longer, could take a year. We have had searches that took a year, right? keep looking. People settle, you know, people settle and they say, "Look, I looked at everybody. This is the best we can get. you know, we haven't had a person in this role now forever. You know, just get someone in the seat right now. And that's the problem. Okay. So, you knew like look, the two that didn't work out.

26:11 When I looked back at the process I ran to hire those two, all the signals were there. You know, even in the interview process, they told me stuff that kind of was outrageous. And I knew it was outrageous, but I was like, well, yeah, I guess this person had a big fight with that person. None of my business. It's like, wait, I could be that person next. So I when I look back and I do a postmortm I always see like hey all the signs were there like what what was I doing or you know in one of those cases I rushed through the hire like I hired it looked good they like you know I went fast and then I think that back doors are phenomenal like do just do a insane amount of back doors.

26:45 >> Yeah >> you you get like a phenomenal 360 view of a person if you just talk to all of their managers in their past. Just go talk to all of their managers. do also all the front doors. I would say like 10 20% of the front doors end up actually being truthful. 80% are >> Ally, I want to switch topics on you. You had a rivalry obviously with Snowflake. It was an interesting rivalry over time and my sense is you were pretty far behind and at least from a revenue standpoint, you've passed them. And I just remember at HubSpot we were looking at the two when we picked Snowflake Snowflake way back when. What was the chess moves that worked relative to them? And I guess I have a thesis that that was a very salesdriven company. the CEO was a sales guy. He cold called me actually and you folks were product driven. Any thoughts on that in advising founders and CEOs about that kind of thing? Yeah, that was the consensus at the time that that the companies were like that. I felt like at the time people would saying that were saying that I thought that was unfair to us cuz I thought with Ron and everybody we had like an amazing team and then we had Andy come here and build up like an amazing crazy machine that you know it's like an army. So I I thought that was unfair at the time when they were saying that. But it is true that we were half the revenue and we were growing slower. So to accelerate the revenue, you know, so much that you can sort of overtake someone that's got double your revenue and, you know, bypass them, we knew it's going to take several years. Back to the, you know, good strategies take multiple years. You can't do them overnight. So, you know, study your enemy carefully, understand their weaknesses, and apply your strength to their weaknesses. This was a great company. They had built an amazing product. It was a game-changing product that disrupted all the data warehouses of all the hyperscalers. So the hyperscalers were getting destroyed by Snowflake because it was such a great innovation, such a great product. So it's this is not like hey it's a PTC like company and you know like no this is like hardcore but they had a few weaknesses one was that it was proprietary cuz the folks came from Oracle h so it's a fully proprietary stack and still today all the data gets stored inside of their proprietary format. They've now added open source stuff but that's just small fraction of what they do. Most of the customers we bump to they have this proprietary and people didn't want to get locked in. So that was one weakness. second weakness they had was that they had no support for AI or they would say that they they would but we knew that that was pretty weak. So the second thing that we we wanted to push really really hard on and you know those two combined with third it was pretty expensive. Now it was expensive to be fair probably because it was a great product and they could extract a lot of margin out of it. So you know winners do that you know they have great product.

29:44 So we went exactly for those three. So we said, "Hey, open lakehouse means you own your own data. It's completely open. Don't lock it up over there. you can do AI on it because we were like our roots were AI. We'd been doing machine learning and AI since 2009. So that's where we came from. So like apply that strength. And by the way, at the time it wasn't clear that was going to work because AI was not a big thing in 2019, 2020. But we knew that that's a weakness. We push keep pushing on that weakness. And then cost. So let's make sure that the TCO is a third and still today TCO is just would typically win on TCO. So and then we just hammered that extremely aggressively in account after account. We had very careful playbook and the playbook were you know it wasn't just like let's just go out and say that Snowflake sucks or anything like that.

30:29 It was emphasize identify the Achilles heel and press on those. Don't just go say hey rip out Snowflake. It was a coexist strategy. Go in there look at the exact workloads that could be amendable to machine learning. pull those out, move the format to open source. So we have very clear concise playbook and this kind of contradicts that our sales would suck or that they would be good at sales because sales executed display at data bricks. They went account by account and did that. So you know I would say and then it took multiple years and we also had a category that sort of exemplified this playbook. The category was lakehouse. So so we had a three-year strategy, four year strategy to create this category of lake house which by the way was controversial. People didn't believe in it but eventually the category took off.

31:16 Now everybody says they have a lakehouse even will say that and they say that they have open format and so on. So so yeah so that's what I would say study your enemy study your competition carefully and then you know go after those weaknesses. >> I had a professor Alaldo Hacks and Arnaldo was one of those guys he didn't have a double chin. and he had like a quadruple chin and he always had a line watch the competition but never follow the competition. He do it his chin would wag for another minute.

31:49 >> So that second part is really important. Some companies are not customer obsessed. I think that's a >> you know they're not competition obsessed. I think that's a mistake. You have to study the competition. If you know from the art of war which they say all the CEOs should read like art of war is all about studying your enemy right their position. Is it high, low? Do they have you know you know more troops and so on. So you got to study your troops your competition. But then there are the companies that actually are obsessed with your competition. Like they're absolutely obsessed. And we have some companies right now that are obsessed by us.

32:21 >> Yeah. >> So then what they do is they just copy the competition. So they're just always trying to chase what capabilities or what positioning did the competition do and they're just copying that. I think this is the most common failure mode. I think it's covered really well. in in a book great book not innovator's dilemma but innovative solution talks about the solution and it talks about how product managers tend to just build the same features as the competition and so this is this is the second pitfall that I see a lot of CEOs fall into like either you don't obsess by the competition or you obsess and just copy them so in our case we didn't just go and build a data warehouse and say hey we have a data warehouse that's better than Snowflake's data warehouse no one would have believed us they would have just said what are you talking about they're the leaders in this they they are the they created this category. What what are you even talking about? So we have to say no no no no this is a different thing and it's different in multiple secular sort of trends. So we actually out innovated there on the product side as well. So you got to do that as well and not just copy.

33:21 >> Okay. So how did the idea for Lakehouse come? Was it your idea? Was it kicking around in your head? How did you sell it internally? And how did you set it up as an initiative? Did the core team do it? Did you break a team off company? A lot of the CEOs I'm working with are working on second acts and you know some are really struggling with it. How did you guys do that? What what did you do right? What did you do wrong?

33:45 >> Yeah. It was a controversial decision internally. >> Yeah. >> And you know a lot of the seasoned folks were saying don't do it. It's a funny word. It's a you know it's technical. What is a lake in a house? It's like a house in front of a lake. What does that have to do with what we do? Like it's kind of funny. like this is kind of ridiculous. We're trying to be an enterprise company. We're going to talk to execs and you're going to talk about getting a house on a lake. But then so we went to strategy firms and strategy firms outside also said they did actually surveys with people and they said yeah indeed it doesn't work.

34:17 >> So they came up with like bland category names for us. I think unifi data science platform was their proposal. And then we ran it by some of our sales folks internally and they're like yeah this doesn't make any sense. It's too technical. How about and then they will propose something like you know. So we had to kind of put, you know, kind of march ahead and have a lot of conviction and that was not easy because you know there's like hey you're risking you have a company that's pretty successful you want to risk it all and going on this weird thing. but we did and initially all those people that said don't do it were vindicated because people were ridiculing it and saying it's such they were making all these haha data rapids going through the data river data you know so on. So, people are having a lot of fun with that, but I think it was also in the category of any PR is good PR. So, it wasn't that bad in the big scheme of things. but we really did mobilize the whole company behind it.

35:10 >> Okay. It wasn't a separate team. It was the whole company. >> It became the whole company. And it was really, you know, we would do it across the board. Like, oh, there's an article about the brakes. Amazing. It said great things about us. And we were like, no, no, wait, wait. They didn't mention lighthouse in the article. >> I see. >> This is horrible. Can you go contact the reporter? What are you even doing? you know, oh, we got a big win here. Here's a customer win. Here's what the customer said. Hey, but but the customer didn't mention lake house. What the hell, you know? So, it became like a completely like maniacally, religiously across the board in the company. You know, it's got to be a lakehouse, otherwise it's a loss. I don't care, you know. And, you know, I think I saw at some point great ads from data bricks that I was receiving on Facebook. I was like, these are not mentioning lakehouse. What the hell? And, you know, my head of marketing said, yeah, you know how well the ROI is on putting a word lakehouse in an ad. Spark is the thing we're known for. Like, here's the conversion rates.

36:00 You're a data guy. Look at the conversion rates. Spark sells. This other weird funny thing you have doesn't sell. I said, I don't care. Get rid of all those ads that, you know, work and use this ad that doesn't work. So, it took, you know, concerted effort by the whole company for multiple multiple years. >> I'm sure sales reps are motivated by their comp plan and it was easier to sell the core product. How did you incent selling lakehouse? complans was always a thing we were obsessed with. I always personally obsessed with it. So there would be always multipliers and you know extra spiffs and gravy on top of the comp plan and things of that nature.

36:40 We were every year we would make sure that the comp plan for sure will make sure like don't argue with sales that's dumb. Put it in their comp plan. You know if sales doesn't want to do something then put it in the comp plan to do that thing >> if you believe it's the right thing right you might be wrong but it's the easiest thing in the world. So, I don't really I I don't engage in those debates. I just I mean, I'll try to figure out are they right about it or not. But if I'm convicted, I put in a comp plan and stop the debate and the debate immediately stops. Okay. A couple of times in your history at the company, you decided to take a step back in hopes that you would take 10 steps forward.

37:14 This is one. My sense is also moving from PLG to enterprise, really doing AI. There's been a few points where you take that step back so you can go faster. I see a lot of CEOs nervous to take that step back. Nervous what the investors are going to say if revenue slows down in the short term. Advice to those CEOs or CEOs generally too timid. >> Well, I mean, first of all, I don't know if those CEOs you're referring to are public company CEOs or private company CEOs?

37:42 >> Private. >> Yeah. Okay. Interesting. I would say on the private side, you have more latitude. I was greedy and I had bigger hopes for data bricks than when we were at. I was disappointed. So at this point when we did Lakehouse right 2018 19 we were you know multiple hundreds of millions of dollars of ARR and so we were a successful company by some metrics but I was pretty unhappy and I wanted the company to be much much much bigger and much much more impactful at the time and we were talking to investors and I was telling investors you know I'm talking public company investors we were talking to who were trying to understand what databics does and I would paint them this big vision of what I want databicks to do one And I was being truth seeeking with myself after the meeting and saying, "Wow, we're not doing that." Like this picture that I'm painting is amazing.

38:29 But that's not what we're doing. We're just selling Spark right now. So it came from a place of like, "Hey, do we want to be that big thing or not?" And for me it was like, "Okay, I don't want to do this job." Remember, I didn't even want to be CEO. So if I'm going to do this job, we want to be that that, you know, that amazing vision. If you want to do that amazing vision, we got to transform ourselves. Otherwise, we just get stuck.

38:48 What I saw happening in Silicon Valley when I was studying companies was that these companies that end up being one trick ponies they're amazing companies amazing innovation. Splunk this amazing observability security sim but it's like one trick but Amazon Google Microsoft they had many many products and you couldn't define them by saying oh they just do that that's too simplistic. So how do we become one of those? So if that's what your target is, you have to start taking the big bets and you know you might not succeed with them. And then I was stubborn. So I kept going with those bets a few years more you know and then eventually started to see the success out of those. It really came from that. So like I was not content. I didn't want to have a single product company. I wanted to have multiple diversified product portfolio that each of them were successful. You did the same right at Hopspot.

39:35 >> We did the same. We were marketing app company. We became a CRM platform. We took a massive step back so we could take 10 steps forward and we sold it hard to the public investors and they didn't give a crap about the big vision until the revenue started showing up for the new products. Was is that kind of similar for you? >> Yeah, I think that public markets are kind of, you know, sounds great. We've heard so much BS on earnings calls.

39:59 >> Yeah. >> Like the slick, you know, smooth operator CEOs who are like BSing every earnings call. Like you listen to them, it's like some of us look at it's like, "Oh my god." I mean, I can't stand this more than 2 minutes. They've heard that all the time on every earnings call. So, I think they're just like discounting all of that and saying, "Show me the money." So, yeah, it takes multiple years until people start paying attention to the thing that's going to pay off. I I've seen this again and again again, right? Like data bricks was cloud only AI and no one gave a damn. It was like onrem is where all the business like is at you should move to that until it took off. Then suddenly was like, "Oh my god, how did you guys do it so fast?"

40:35 Like, "Yeah, we've been at it for 5 years." So yeah, you you do have to have stamina. You have to do the thing you believe in. You know, it has to be non-conensus, but you also have to be right. And you have to do it for four or five years. Then at that point, people start looking at it. And by the way, people's reaction will be like, oh my god, how did this happen so fast? How did you build all these products? Where have you been, Brian? I can't believe you guys build all these things. And you're like, it's completely different company. Like, how did you do it so quickly? You're like, actually, we've been doing it for five years. You didn't pay attention.

41:02 >> That rings a bell for me. >> Yeah. Ali, I spoke to a bunch of people who have worked with you or worked for you, and one of the quotes I got is, "He's a killer. He plays more aggressive than you think is possible." And I'm hearing I'm hearing this come out. How does a mildmannered computer science professor turn into a killer that's incredibly aggressive? Where's this come from? You know, I think I have a chip on my shoulder, you know. I you know honestly I think growing up in Sweden as an immigrant and you know switching schools environments you know it's like you know there's there is this you have to have this kind of aggression to succeed and you know there's probably a lot of kind of tough anger that piles up over the years. United States has softened me a lot you know because this is like a happy place for me like it's like okay this is kind of harmony. I know it sounds but yeah I thought you know probably immigrant in Europe gave me a lot of chips on my shoulders and a lot of things to prove to myself and the world.

42:09 So it's probably comes from there I would guess or maybe it's just genetic. Who knows? but as a CEO you learn very quickly that probably the number one trait that is terrible for a CEO is if they're conflict averse. so I learned that very quickly that conflict averse CEOs is like the worst thing possible. It's nothing worse than that. I'm not saying they're bad people. They're wonderful people. Like in fact, maybe the most wonderful people in the world are conflict averse, right? But the CEO job you have to be crystal clear and the reason is I think that you know everybody's pushing you, right?

42:50 Everybody wants to get something from you. Can you do this? Can you prove that? Can we do this? If you're confident diversity, you're just going to say yes to them or you're gonna lie to them or you're gonna like try to avoid the subject. You got to be crystal clear. We don't do that here. Like no, like no, we're not going to do that. No, I'm not going to prove because you caught me in the hallway here. Go through the formal processes. Like just cuz you're chit cchatting with me in the elevator and I'm being nice and you're being nice back and now you're trying to jam in approval for something. That's really sneaky of you. So let's go through the proper process for this. So like this this all this push all the time. If you don't do it, the company start, you know, going in all kinds of directions instead of laser focusing all that energy on that one bottleneck that you wanted to solve, right? I also think that it helps you being more consistent and clear so everybody kind of gets the message. People don't understand nuance.

43:35 I think Ali meant this. No, no, no. I think he meant that. No, no. I think you're totally misunderstanding. No, let's be crystal clear. Then let's make it black and white so that there's no doubt. So everybody knows. Let's give them the cheat sheet. So, you know, you got to be aggressive for with that. and then you start getting people that are more like-minded and you kind of start growing in the same direction. I feel like big companies otherwise like we're 12,000 employees. It's like they start canceling each other out. B atoms bouncing off of each other, you know, strategies that don't make sense. I saw it in big companies. So, I'm trying to avoid that, you know, really >> just pulling on that thread. I I have a thesis and I think you agree with it is a pivot point in a lot of startups is when you get to 150 employees Dumbar's number and things start to really slow down. You guys hit 150 and then you know you're you're 12,000 today. Do you agree with that? So many of the companies I work with are ripping by that 150. What is your advice to founders to create some structure and process but not really slow the damn thing down?

44:44 >> Yeah, some slowdown is sort of necessary. The dumber number definitely happened. I felt for us I felt like it was like 250 or something, but you're right. it was around the time actually we did the CEO transition, right? I think it goes from being everybody knows everyone and you as a CEO know everything that's going on. So in some sense you can run the company kind of like a star like you know there's like one person that knows everything or two two people that knows everything and then there's a bunch of people around but every you know everything. So you have to start putting structure in place so that you know you don't know everything. You just trust that you know this part of the go to market will take care of itself. this part of so you have to basically start putting in processes where you're scaling indirectly it's in a way I know it sounds funny because I'm sure you have managers and managers of managers but really it's the first time the company is going through the transition of you have managers of managers they might have had it before but those managers of managers didn't matter because the CEO knew everything anyway so they were just managers of managers in name but what happens when you actually can't reach down because there's like too many people you actually can't reach down and understand what's going and on you really have to go through the intermediate layer. You got to put structure in place and make sure that the everything reviews, KPIs, measure it in a way so you can make sure that the ship is going in the direction you want it to without going and tapping people's shoulders all the time because there's too many shoulders now. You don't even know the name of everyone any anymore.

46:20 >> Yeah. I've also interviewed I interviewed Jack Dorsey on this podcast and I read a lot about Brian Armstrong and they're trying to recreate the CEO model and rethink it and the way Dorsy kind of describes it is the company is an AI and the employees kind of sit around the AI and their main job is to train the AI and give it context over time and that he wants more no more than two layers between himself and the frontline employees and Brian and Armstrong's doing kind of similar things like not just shrinking the org but really collapsing the number of levels in the org. What is your take? It seems like there's a movement starting around this and a bunch of the AI native companies I'm working with are pretty intrigued by that.

47:07 >> Yeah, I think directionally it's correct. we're doing same but I think we should separate two things that are I think a little bit sometimes being conflated. Okay, which is what is the official or chart you want to have in a company and then what is the way in which your company disseminates information, aggregates information, makes decisions and collects those. we should separate these two. So 10 20 years ago these were the same thing. There is no way to collect information other than you know you ask your person they ask their people like you kind of you know so you go up and down the tree structure of the or charts that's how information disseminates up and down and decisions go up and down that's the only way and now you can do it more broadcast that's like a top down company or you can do bottom up but those are the only options you have or you can just be random poorly run company today what has happened is that u you know we have extremely smart AI I keep asking this question every audience I go to and I ask them you know how many of you think that the AI is smarter than most of the people around you most of the time and I get like 90% of the hands up well I define that as AGI it's artificial general intelligence it might not be super intelligence but it is as good as most of the people around you right this is undisputed every time I ask this audiences all agree on that they don't agree that AGI is here because they have a weird definition of AGI. So we have these models that are super super smart. Then we look at how AI is being used inside corporations.

48:43 >> And by the way, people complain about them hallucinating, but humans hallucinate too. >> I make mistakes all the time. >> All the time, >> you know. So, so these things are phenomenal already. And let's just say they're smarter than most of the people around you most of the time is what I've gone from every I by the way I asked that at Moscone Center to 32,000 people and I asked them to raise their hands and almost everybody raised their hand.

49:04 But then you look around you and say, "Okay, what's happening inside the enterprise? How are AI being used?" And they're just using them as stupid chat bots. They're going to the chatbot, asking it the question, and getting an answer. That's all that's happening. And then they're using them for coding. So they have a coding agents that are writing code. By and large, it's a little bit of an oversimplification. This is what's happening inside the enterprise today. So this huge gap between the capabilities the models have and you know, it is just not true. I asked this question too. Do you have hundreds of agentic co-workers collaborating with each other pro providing proposals to you, keeping you up to date and doing that? Nobody raises their hand. I've never had a single person raise their hand on that. Okay.

49:41 So, what's what's lacking is the enterprise context. So, you need to capture the enterprise context that's in people's heads, decisions that are being made every day, what's happening inside every meeting that's being recorded, every email that's being sent. everything has to be captured and be put part of the context and then fed to the AI. We call this ontology. So we want to capture the ontology and feed it to the AI. So we actually built a product that does that. It's called Genie. And for data bricks, so it's not just a product, buy this product and you will solve this problem and you're done. No, absolutely not. Turns out you have to also build this ontology. And at data bricks, we actually have a phenomenal ontology we built for ourselves. We've noticed our customers don't have they use the same product but they haven't built up the ontology the same way we have. So for us now it's magical. So we we have an orc chart of people they report up and down and we can decide what the fan out should be and spans of control and all of that. But then we have Genie and Genie pretty much answers any question I have in any meeting about anything. And it can also start automating tasks for us and getting us, you know, so we're all just sitting on our phones and using the Genie app all the time on all of these kind of things and feeding more context to it, building up more context, automating more and more processes in the company that we find. So yeah, I think it's true and my the Genie product does this and it builds ontology. But then what about the humans?

51:06 >> Yeah. What about that pyramid-shaped org chart? Yeah, I think that that is TBD and here's why. Where where I think there's a lot of stuff that's being said in the market that I'm not sure is correct. So I think the intelligence is true. So I agree philosophically with Jack Dorsey. The question is does that apply to the or chart of humans too? Like should we should so maybe I should just have you know one layer below me or two layers. Here's the problem. And I see some companies saying okay so there therefore we're moving to 25 people fan out. So each manager should manage 25 people. There should also be player coaches because now we have AI that can write code for you and so on. So I want every manager to write code, ship it to production and manage 25 people. And I'm like, okay, so how's that going? You look at what are managers doing? Well, a lot of it is like human stuff. You know, this person is unhappy career choices, you know, unclear what the goals are that they want to do. Like there's a lot of human interaction. You can't have 25 direct reports reporting to a person and being super h happy and aligned and understand what they're going to do and all of that. And also you're asking the managers to also at the same time being player coach and submit code and be they should be vibe coding 80% of the time and 20% of the time they're like managing 25 people.

52:22 >> You're skeptical. >> Yeah, I think it's BS. I think things will break down. You're going to get unhappy. You think you're going a lot of unhappy employees who don't know what the hell is going on because you know there's like they don't meet their manager because the manager is busy vibe coding most of the day and you know there's 25 of them. >> Mhm. >> You know and to tie break just decisions across these all these groups. So I I'm I'm not fully bought in to how you resolve that you know it's like a double whammy of you know manage more people and do I work yourself. Fair enough.

52:57 I put out on X that I was having you on the pod and I got a bunch of interesting questions and one of which was, do you still code? >> I do. Well, first of all, I always was coding. So, I I never quit coding. Yeah. >> I mean, remember I ran engineering in product, right? And I I've been coding since third grade. So, like I never stopped coding. I would code on the weekends just for fun and stuff. But November last year, I started also like committing stuff to production like just to get understand exactly how hard is it to go all the way into production. It started with an experiment where I built something a connector. It took me two days to build a connector and our current teams were taking three quarters to build those connectors for one person. I was like how can I do it in two days and it's taking you guys three quarters and they said well you know your thing is not production ready. It's not secure. It hasn't thoroughly actually basically it doesn't really work. You got like a proof of concept working. You can't get into production.

53:58 So I really wanted to figure out are they right? Like what's this gap? How how can it be that the core thing took me two days but all the kind of other extraneous stuff on top that takes three quarters. So that's kind of what got me into the journey of like hey I need to get commit code into production that goes and faces the customers. only then can I have a feel for how this really works. And what we learned is actually it was kind of interesting. The team went back, they used my kind of push and they came back and they said, you know, you kind of were right. AI is very effective. We haven't been using it. We can now compress the time it took. So, we're going to compress it down from three quarters one person to seven and a half months, one person.

54:42 >> Okay. >> Okay. >> Wait a minute. Like, how's that even possible? Yeah. >> so, so yeah, they were like, look, it's not production ready. It's not secure. It's not that. >> Then we got, you know, I went and I found a person. It's like, we have a person that's, you know, he's kind of not going to he he's he's not going to stand all this BS. He went in and together the team worked hard to revamp the process. So, after we inserted this person and it was an FTE and after, you know, three quarters, they came back and they said, you know, we can do seven connectors in one quarter.

55:15 >> Better. And I was like, okay, what happened? And like, oh, you know, yeah, technology got better, models got better. It's that's it. But I pulled them aside and I said, hey, can you like tell me the real inside scoop of what's happening? Why is it why was it so? And I said, look, here's the thing. You're right that the code can be written very quickly. But first of all, to build these connectors, we would go talk to customers. It would take us one quarter to collect feedback and write the PRD.

55:39 And we write very good PRDs. We have very skilled PMS. That quarter, the whole pipeline is stalled. There's no nothing being written that quarter. Then we have to set up the systems that we connect to. Salesforce workday, Netswuite. We don't know how to do that. We're not experts at that. Those companies maybe don't want to help us to set that up. We hate that part of the work. We're that takes a very long time. It's errorprone. We found consultants that can just do that for us. And now we can do that super fast. The quarter of PRD getting the requirements. Let's do that in one week. Quickly snap right down in an MD file and if it's not great, it's okay. we can fix it later.

56:15 And then the testing, we would do one quarter of testing at the end. Well, let's just move that up front. Let's do this end to end with AI. And that way they were able to compress things. And instead of having one person per connector, let's have seven people, seven connectors. So if one person gets sick, they go on path leave, matt leave, vacation. So we had to re-engineer the whole process. So that's that's so that kind of got me into coding to understand you know what are all the processes that are needed and what are all the bottlenecks that's making it so slow and that kind of informed my view now that I've had for a while I've been saying this for you know I think since the beginning of the year end of last year it's going to take humanity a decade at least to absorb and diffuse AI because of what I just experienced in a tech company with super smart people who want AI and they're all like you know you have to basically the process re-engineering of all organizations on the planet.

57:09 so that's going to take a long while. and so that's what got me back into coding. I'm still doing it, but not as much as I did earlier this year. >> So you're doing some coding. What is a day in the life of of Ali? Like it's Monday. I'm eating up an hour and a half of your time in this podcast. Like what is your cadence? Like when do you get up at the morning? What do you eat? What are your meetings? How do you schedule your meetings? Do you have like Monday is a certain thing, Tuesdays? Like what what is your operating system yourself?

57:40 >> Yeah, I actually think that it's it's not like one consistent thing. It changes you know throughout the year and you know you have bursts of like okay board meeting strategy our big summit in the year. So it's not the same thing throughout. but you know I I see it as kind of three things. One is the main bottleneck that I'm obsessed with. Yep. >> I want to carve out a lot of time for that. So, I'll get to that in a second, but that's like my main that's like my main focal point. I want I want to unblock that big thing that I think is the thing that's going to get us 10x.

58:11 And I think only I will do it because everyone else is busy running their trains on time. So, nobody's thinking about this next big thing that we need to do. So, that that's the front. I'll come back to this one. Then there's a whole bunch of stuff you have to do as CEOs. I don't need to tell you guys. Everybody, all the CEOs are doing it. You know what it is? It's all the that comes at you every day. It's the thing that packs your calendar back to back, you know, all those things. You got to do those. So, I try to do those.

58:36 I try to compress that as much as I can so it doesn't take too much of my time. But I do that. Then I'm a product CEO. So, you know, I try to spend as much of the remaining time looking at what's happening inside the product. What are we building? What are the features? What are customers saying about the product features? So, I try to keep up up to speed with all the technical details of our product end to end. And it's a pretty big portfolio now with 3,500 engineers. So the portfolio has gone pretty big. So I spend a lot of my time on that. The remainder of the time I go back to the first thing I want to like do that. So on the weekends in the morning when I wake up early like you know I try to like think through how can I unblock that main thing. If we unblock that then you know the company can be worth 10x more. And do you actually go in your calendar and say, do you create think time to think about that kind of thing or it's nights and weekends back burner? Like how do you do that? Do you work from home a day to like work on things like that? I try to compress the calendar. What I mean by that is I try to like keep it like try to put nothing on the calendar. It ends up being packed anyway, but there are many blocks that are, you know, free where I can, you know, go back to this main thing. I think if I do the, you know, 8 am back to back to back to back to back to 56 PM.

59:48 >> Yeah. >> I consider those days I've just been a slave to my calendar. I'm just working for my calendar. So I've been just working on behalf of It's good. It's my job. >> You're working on everybody else's priorities. >> Exactly. Monkeys on my back, right? So how do I actually kind of carve out time? So I I will tell my CEO office team like you know this like this day is terrible. I get nothing done. We've done nothing today. I told them I've done nothing for the company today in terms of progress. Like I've done no CEO thing. I've just done block decisions, collaborating, this and that. The the random crap that comes my way. you know, we need time to really go after the big bottlenecks. That's what I want to do.

60:26 >> Okay. What is the cadence of the organization? Are you weekly staff meetings? Do you have one-on- ones with all your directs? How often do you do offsites? How do those work? Like how does a big company like yours operate, keep the trains on time and work on that big initiative? >> First of all, there's a lot of trust. So a lot of people have been here 10 years plus, >> right? >> And you I know the weaknesses and strengths. So I know this is like that person is responsible for this, but they will screw it up in this way, but they'll be great at these other three ways. So I know what they're like. So that helps a lot. The context and you know, history helps a lot. But we do staff meeting Mondays an hour, an hour and a half focus on top priorities.

61:06 So we kind of go through the KPIs of the top priorities that we're every every year we have one or two or three goals >> and those are like the thing the whole again back to it used to be like >> okay so you you in a year you'll have one HubSpot every year we had three I was like can't be more than three. Yeah, I wanted it to be less. So this year we had two.

61:25 >> Okay. >> two goals and I actually wanted it to be one but it became two. so you know to get because you know it's just otherwise it just becomes everything. >> And is that Monday morning meeting really useful or is it theater? Is it like is it can't you just have a Google doc and get it done that way? >> Okay. This goes back to this can we just have an AI the Jack Dorsey thing. We're talking about humans.

61:49 Why should I like you or trust you if I never get to meet you? >> You know, why I don't know if you're married, but do you want Why do you Why do you have to meet your wife at all and your kids? Can't you just have a Google doc? >> We just write down the stuff you want to like if there's something you want to teach your kids, put it in the goddamn Google doc. Maybe you don't even need to respond to the Google doc. Claude can.

62:09 So, so my staff meets three times a week. Also, Wednesdays, also Fridays. Wednesdays and Fridays are 30 minutes in the morning. So like 8 a.m. 30 minutes. >> And what are you talking about on Wednesday 8 a.m. to 30 minutes? >> Look, a lot of it is just like, okay, what's the main bottleneck right now? What's what's the main thing? It'll be something that's like, you know, popped up that's like top of mind for everyone. We got to like do this right now.

62:33 sometimes we just go around the horn. It's just 30 minutes to get the day started. A lot of them we're just joking around and like having fun and like, you know, talking about the biggest thing like if there's something big in the news yesterday, it could be unrelated. Like, you know, we could shoot the about that. It's just a way to get the day started and some people will be on the phone, some people will not, some people will not come. but you know, if if you want your e staff to be tightly knit and you want them to prioritize each other over their second team, which is the people that report to them, mind you, all the people that report to them are of the same. all sales people reporting to Ron or they're all legal people reporting to John or like you know it's like so the natural gravity is that you build up walls between departments and they don't like each other and they're butdding hard against you know I need to close the quarter get out of my way no this is not legally possible or no marketing needs to do so how do you how do you change that so that we're doing the right thing for the company so that the company's priorities are first well we got to make sure that these people feel like they're a team. If those people feel like they're a team, they have to hang out.

63:39 If they never talk to each other and they're just writing Google Docs, it's not going to happen. So, so yeah, so we do meet three times a week and we do these. We have QBRs every quarter. >> Is that a day? Is that a week? >> Two three days. There are multiple types of QBRs now at companies. Product QBR, go to market QBR, but you know, we make sure that every this is the scaling part, right? So you got to make sure that everything is happening across all the regions, all the departments, all the products. this has to happen like this that's if some if some product is stops delivering or is veering off or some region is stopping to sell or sales leadership is bad whatever it is how do you detect that so you have to have these QBRs in the QBRS as well it's all gets sused out and you take action plans on like okay we're going to change this we got to make change on this we got this thing wrong we built the wrong thing all that that happens in those and a lot of my my exact team is the ones like running all of these and making sure all those are running right >> do you do off-site strategy off sites where you gaze at the stars or gaze at your enables.

64:37 >> Yeah, we do. And we focus on the top bottlenecks. Yeah, we just did one >> once a year, once a quarter. >> There's definitely at least one per quarter. I see. You know, they might be a little bit focused for a department, you know. but absolutely. Yes. >> Okay. I I had someone on X ask me to ask you, why do you want to go public? The valuations tend to be less than the private markets.

65:04 the scrutiny is not great. Like stock price changes every day is kind of weird for employees. There's plenty of liquidity out there in the private markets. Why? >> Yeah. So, first of all, I think that if Databix was public today, I think we'd be worth more. >> Okay. >> Now, that answer might vary over time. There are times at which I knew we're worth more as a private company than we are as a public. But right now, if we're public, I think we would be worth much much more actually. And I know that at the last fund raise, you know, we had close to 15. You had Tro and the big guys in there.

65:34 >> Yeah, but we raised five and the interest was 20 billion. >> Yeah. >> So, I just know that, you know, based on the supply demand curve, we could have set the price much much much higher if we wanted to, >> but that's not what we're optimizing for. I I do think that markets tend to sometimes be fickle for us. we're basically facilitating a big marketplace for the employees to get liquidity every year. >> You don't have to be public to do that.

66:01 It's a complicated operation, you know, across, you know, probably close to 100 countries and you have to make sure that the tax laws of every country is kind of y >> taken into account. You got to facilitate this for, you know, if we're 12,000 people, we do it for ex employees, too, so they can participate in these tenders that we do that's probably 15,000 people. So, you have to like it's a big undertaking. You're facilitating a marketplace. You're basically emulating a NASDAQ in a private market. And you know at at some point I think that it just makes sense to be public to do that and I don't think that will be too far into the future. I just don't want to go during this time where we're going through this big crazy transition. If we're going through a big crazy transition, you want to do it in private markets. Companies when they go through big transitions themselves, you know, like when they went from, you know, perm licenses to like, you know, SAS licenses, they go private. They take them private, then they do the thing and then they go back out. So as the world is going through this crazy AI transformation, you're like want to be public right now. That makes no sense to me. Now anthropic open is a different story. They need a lot of capital. They have huge capital needs. We're free cash flow break even. So we don't need the capital. So I think it's just better right now. We will go when I think the waters are more calm like when there's a little bit more predictability. Like this nonsense of all SAS companies are and SAS apocalypse is going to destroy all AI companies. Oh my god. Oh, the last had a great earnings. All SAS is great. We should like buy SAS.

67:27 There's a wrong. Oh, we should put all our money on semis because, you know, semiconductors, the future is a bottleneck. We just go there. No, no, no. The semis over there. Let's sell it all. Okay, that big fund is going under and like, you know, it's like just don't want to have to deal with this crazy back and forth. It seems public markets also are not very good at handling this big revolutionary transition that the world is going through.

67:50 >> They're also having a hard time wrapping their heads around that. They're much better at the normal. Whereas this big transformation, they can't figure it out. You know, software >> is the value of software zero. >> Oh, wait. Maybe it's like, no, but why is revenue going? Oh, revenue is accelerating. Oh, this should be high. So, we just want to avoid that. I think things will settle in in a year or so. You've used the word and detector a bunch and you talked about being comfortable with conflict.

68:18 Let's just say you're not comfortable with conflict and you're a normal homo sapiion and you become a CEO and it's starting to scale. How do you develop that detector and use it and how do you get used to this conflict because it's unnatural for most people. Yeah. Well, don't lie to yourself, you know, is the most important thing. I feel like a lot of people lie to themselves. They don't tell themselves what's wrong with the company, what's wrong with their when they come up with excuses, self-defense mechanisms get in the way and they say, well, you know, they find excuses. So, start seeing the truth of what's actually not working with individuals or the company or your strategy. And if you want to take truth seeeking to its extreme, you can't be conflict averse about it. You kind of have to face the and challenge that, you know, that gap, that discrepancy head on. Don't don't swallow that. just go after it. Like be aggressive about it and push yourself. It's like, okay, hey Ali, you're not conflict averse. Some people are conflict averse. Well, I'm It's kind of like saying, oh, you know, some people they don't like to go to the gym and work out cuz it's like too annoying. But other people, they just seem to have this gene that makes them work out. No, it's hard for everyone. It sucks for everyone to go to the gym and work out or eat healthy or do these things. Yet, we push ourselves right now. Maybe it's slightly easier. Maybe some people have more motivation. It's easier to push themselves. Maybe some people have an act for it. Maybe for some people it's harder. But I think I put it in that category that you should, you know, eat your vegetables and you should live a healthy life. And that the natural thing is just to eat a bunch of sugar and like, you know, just sit back and do nothing.

69:57 >> Okay. So if you're if you're conflict averse, get over yourself. >> Yeah. Get over it. Like if you want to be CEO, you do not want to be a CEO. If you want to be CEO, don't say I'm a conflict. Change that. Like don't say, "Hey, I want to be an athlete, but I'm the kind of athlete that doesn't work out." Because you know in my family we don't work out. So we don't practice. We don't work out. The results are not great but I'm not the kind that works out and is healthy and eats healthy food. I'm the other kind. No, that doesn't. If you want to be in the sport, this is the name of the game. Like you got to be crystal clear with people. And you have to tackle the conflicts head on. I don't love the conflicts. Who likes a conflict? I would say it's human to hate conflict. You know, it's like it's unpleasant. You know, it's it's a conflict means someone pushes back.

70:40 They're unhappy. They're they might criticize you back. It's not pleasant. Nobody likes that. It's a human thing to not like conflict. Now, some people really avoid it. Some people avoid it less. But get over it if you're a CEO. Ali, thanks for coming on. Congratulations on all your success. You were fantastic. Appreciate all the wisdom you dropped down the crab. >> Oh, likewise. Pleasure to talk to you and and saw you do similar things at HubSpot. So, thanks for having me on.

71:07 >> My pleasure. Hope everyone liked that interview with Ali. I think he's fantastic. A couple of my takeaways. First is kind of a vibe takeaway. Like don't be a wuss is sort of sort of a piece of his CEO advice and he reminds me a lot. I interviewed Nikesh Aurora from PaloAlto. Like they don't put up with any BS. They have strong BS detectors. They use those BS detectors. They both believe that conflict aversion is kind of cancer in a CEO. And I suspect they're right about that. And neither overindexes on being liked. When I was CEO of HubSpot, I I think I did overindex on it. We won the, you know, all those glass door prizes back in the day. I'm not sure that's correlated with long-term success. We did pretty well longterm, but I think I overindexed on it. And you look at like Steve Jobs and these guys, they definitely don't.

72:03 Speaking of not being a wuss, you have to have the courage of your convictions and you have to have staying power on that conviction. You know, conviction without staying power is like a fat diet in January. It just doesn't work. And the best conviction is kind of there's an old saying, you need to be right about something that everyone thinks you're wrong about. And if that happens to be true and you are convicted and patient with it, that's where the big big outcomes come from. Now a lot of people talk about conviction around the founding idea.

72:34 I found because I mostly work with scaleup CEOs that conviction around second acts is even more important than conviction around the first idea. And Ally did this a couple times, but he talked the most about a product he launched a few years called Lakehouse, which was sort of, you know, a big competitive offering. It was unique in the market. Everyone thought he was wrong about it, including most of his employees, and he really, really just stuck to it. He had a lot of conviction and patience with it, and it paid off over a long period of time. I was in a board meeting yesterday with one of my CEOs, and they've got an application.

73:13 The business is ripping, but they need to move to more of a platform. It's going to be a very difficult shift. He's going to get a lot of push back. His sales organizations really not going to want to sell it. And the advice I gave him is sort of the advice I gave myself at HubSpot. Like at scale, those second acts, you need to like swing the pendulum all the way to the other side and get the whole darn company focused on the second act. And just overindex on it because if you're in the middle, people will stick with that old first act. And I see him doing that. And what I liked about what he did was he only had one or two focus areas a year. He's very focused. He focused on the bottleneck. It sounded like his number one focus for 2 or 3 years on his annual plan was that lakehouse product. So overindex on the thing you want to change. Changing is harder as you get bigger and so overindexing is really important. I hope you liked it. I really enjoyed the interview. Follow us here if you want to tune in to all the long strange episodes with lots and lots of great CEOs. see you next time.