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

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? 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 wanna, like if there's something you wanna teach your kids, put it into the goddamn Google Doc. Maybe you don't even need to respond to the Google Doc. Claude can.

Hey everybody. Today we have Ali Ghodsi on the podcast. He's the founder and CEO of Databricks. 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 Ali. And after interviewing him, I kind of agree. He's really sharp. A younger me would've loved to have worked from or 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.

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 7 co-founders at Databricks, 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 grapevine that they were like interviewing other CEOs and I would hear how they interviewed that guy and interviewed this guy. So as far as I knew, I was like, they're not gonna even pick me.

Yeah.

I knew the identity of at least 2 people. So, you know, it was, I mean, 2015 was kind of a turbulent year for Databricks because we were having great success with our open source project Apache Spark. We were just not having commercial success. Revenue was, you know, um, GAAP revenue came in at like $1.5 million that year. So the vibe wasn't great. And so I, I kind of, and I'm like a glass half empty guy. So I was like, oh, 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, 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 I 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?

Fascinating. Did they interview you?

Not, no, 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 problem the board had with the company is it had very little commercial success. You would've thought they would've hired someone with a lot of commercial background. You had negative amounts of that. What do you think was going on with that?

I think it's a16z 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, 'cause they had themselves been through it. Remember Ben famously was asked at some point, hey, when are you gonna bring a real CEO into your company? And he felt like shit. He wrote about it in his book, right? So I think he didn't want to do that to us founders. So I think he really believed like, let's pick someone that is a founder. 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, you should ask him. It's probably like, yeah, we'll try it out for 6 months, 12 months. If we're going to do a search, we'll put another guy in place in 6 months or so. And 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've turned out if you had left and gone back to be a professor? Like, do you ever think about that?

Yeah. Well, I mean, right now academia is not doing super well, so it would've probably been a big mistake. But also 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 wanna do it. Like I, 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 cuz they were making the best games. 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, yeah, this is like end of life, like they've destroyed 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 learned out I didn't know anything. I knew a little bit of programming. And then I was at a startup in the year 2000 and I was getting an internship and that startup, I did really well and they like offered me to be number 2 guy there, like drop outta school, be number 2. 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 the, 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 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.

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 postdoc. So kind of what happened is I took the chance and I went to Berkeley and I took the postdoc and it again, like widened my horizons. 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 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?

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'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 gonna drop the title? Did they have a conversation with you and what precipitated it? After that 6-month, 1-year trial?

Again, like it was like about 1 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. Yeah. And they talked about like the things that we strategically need to do. So it was kind of starting 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. Uh, 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 was going to do it either. We gave him like a temporary salary.

And I had Ben on the pod and I asked him, who is, who is the best CEO in Silicon Valley? Not in the Andreessen portfolio. And he didn't hesitate. He said, you, uh, which I thought was quite a nice compliment. What can other first-time CEOs learn from your stuck in the chair? You didn't know anything about it. What can you teach first-time CEOs that led you to where you are today?

Well, I think that, you know, you have to be on this extreme learning curve. So, you know, it's not gonna be easy. I mean, you're gonna be working 100-hour weeks. That's what I was doing. I was making sure that I was networking with all the best 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 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. You know, I was kind of building my own, like kind of Bruce Lee built his own Jeet Kune Do based on all the different martial arts. I was building my own CEO playboat based on all the ingredients I was learning from the different places. And that way was like self-consistent. I think 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. I mean, maybe they have 2 major problems or 3, but usually it's like one giant bottleneck. 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 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. You have to hire people, there's drama, people are quitting, the board, this and that, legal department, customers, revenue missing. This is like a 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 the bottleneck. Like, what is the cycle on that? There's one bottleneck a year you're tackling, or one every 3 years, or one every 3 months? Like, kind of what is the cycle?

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, because 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, 2 years, sometimes 3. Like creating the Lakehouse category took, I think, multiple years. You know, when we announced the Lakehouse category, we were ridiculed online, but it was a long journey to get to the launch of the Lakehouse 'cause 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 gotta give things a few years. You can't just— give up immediately. So I think you should, 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 2, 3 years, needless to say, you're not gonna go anywhere.

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?

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 change that because it's not working. Like engineering a product, I handed it off to a co-founder and I basically ignored it for 2 years. I focused my attention on everything else to building up the rest of the muscle of the company. And so 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 salespeople. 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 2 quarters when we started doing that. So, you know, at $1.5 million revenue and, you know, you know that sales AEs have a quota of like a million or $2 million in most companies, you know, 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.

Mm-hmm.

So we should probably, that's all the other options make no sense. We should just double down on Hiring salespeople. Okay. But what kind of salespeople 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, there's like, absolutely not. So then I learned 2 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 of these sellers that were great salespeople who also happened to have a PhD would be at the top making all, but no, you found none of those guys.

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 AEs, 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 Gabrisco, who knew what great 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 need to just get only the technical people. It started becoming clear that there's other skills that salespeople have that you should probably go after those. One of them is, 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 salespeople actually, they're kind of aggressive.

Very aggressive.

Yeah. And the first, uh, one of the first, uh, uh, AEs 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.

Okay.

You know, he's, he's emailed my boss, everybody else. This is like unacceptable. So like that Dave guy, I don't want to see him at all.

Okay.

So then after, I'm like, hey Dave, you've like pissed off the customer. Like, what the hell's going on? He's like, Ron told me get into the building, 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 started to become 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 an counterintuitive for engineers from professor land that those are the kind of, 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 me? Like, you should, and I was like, ooh, 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 is he doing? I'll shorten the story. At the end of that meeting, she was hugging him saying, I'm so sorry for saying that. And, you know, so I was like, how? 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 that get really uncomfortable. They're the kind of people that it's kind of hard to ignore them. You're going to like, if they email you, you're going 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. They need to have amazing EQ. They need to be the kind of 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 becoming 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 salespeople 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 was kind of the journey we went through and we revamped our sales team that way. And a lot of this I learned from Ron. I pushed back and we had like all these arguments, but, you know, eventually it turned out he's right and we, you know, landed this model.

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 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.

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 it. He's 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 GSB degree, he also kind of got an engineering master's 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.

Yep.

But he could speak our language and we could talk to each other and he would like entertain. So it wasn't like oil and water.

Yep. He was smart. He was smart.

He's smart, but also our kind of smart. 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 master's in engineering with Stanford GSB.

Correct. The second thing I looked for is, and this comes back to, 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?

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.

Very different, right? But Ron had been in a startup called Cyclone and I think they went from $0 to $50 million ARR-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 millions.

Okay.

So he had really seen 0 to 50, 50 to 100-ish, you know, so he understood that scale very, in sort of very detailed way. And he was very cerebral. So you could kind of really figure out, can he, is he the guy that can build the car? Or, you know, he just, he's along for the ride. And he's a great driver. But no, 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? It's 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 2 companies, 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 2, 3, 4 years. So if the guy or gal is like bombing out after 2 years, it's, you got to reset and start all over. It churns 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 gonna leave. Like we can, we can have huge fights and he's not gonna leave because he didn't leave from that, you know, shithole. It's kind of how I felt. Uh, so then he's not gonna leave from this shithole. Uh, you know, okay. Uh, that turned out to be crucial because, you know, the classic PTC sellers, they're hard to manage. They're aggressive. Uh, you know, They're, they're, they're a handful to manage. They're very, very difficult to manage. Uh, Ron, as amazing as he 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.

Yeah.

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 2 or 3 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? 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 5, 6 years, I can find a 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.

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. It's going to take you a year to figure out that they're not great. I mean, you might know after 6 months, but you're not going to fire your executive for 6 months. So you're going to say that, oh, it's not clear. So you're going to give it another 6 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 6 months. Now they've, once they've left, you gotta do the search again. You're doing the search now, you're gun-shy cuz last time you screwed up. So now you're hesitating. You might go for a, you might go for a compromise 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 2, 2 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 Databricks, 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, it was a big mistake by you. I was like, yeah, but my playbook was err on the side of being just extremely picky. Take a decent amount of time, start early. And most of those guys have been with me and gals have been with me like a decade. Okay.

So you haven't seen the turnover in these executives?

I have.

I have.

You know, I probably, I think I would say 2 cases where I made a mistake, maybe more, but 2 like really come to mind.

And then you said, give yourself some time. Is that 3 months, 6 months, 9 months to be picky?

I think it takes at least 6 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 2 that didn't work out, when I looked back at the process I ran to hire those 2, 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 was like, wait, I could be that person next. So I, when I look back and I do a postmortem, I always see like, hey, all the signs were there. Like, what was I doing? Or, you know, in one of those cases, I rushed through the hire. Like I hired, it looked good. Like, you know, I went fast. And then I think that backdoors are phenomenal. Like, dude, just do an insane amount of backdoors. 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. Um, do also all the front doors. I would say like 10, 20% of the front doors end up actually being truthful. 80% are bullshit.

Ali, 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 and we picked 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 sales-driven company. The CEO was a sales guy.

Yeah.

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 the companies were like that. I felt like at the time people were saying that, I thought that was unfair to us because 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 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 was 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 this is not like, hey, it's a PTC-like company and, you know, it's like, no, this is like hardcore, but they had a few weaknesses. One was that it was proprietary because the folks came from Oracle. So it was 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 a small fraction of what they do. Most of the customers we bumped into, they had 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 would, but we knew that that was pretty weak. So it was the second thing that we wanted to push really, really hard on. And those 2 combined with the 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 winners do that. They have great product. So we went exactly for those 3. 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'll keep pushing on that weakness. And then cost. Let's make sure that the TCO is a third. And still today, TCO is just, we 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. 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 amenable to machine learning, pull those out, move the format to open source. So we had a 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 Databricks. They went account by account and did that. So I would say, and then it took multiple years. And we also had a category that sort of exemplified this.

Product.

playbook. The category was lakehouse. So we had a 3-year strategy, 4-year strategy to create this category of lakehouse, which by the way was controversial. People didn't believe in it, but eventually the category took off. Now everybody says they have a lakehouse. Even Snowflake will say that. And they say that they have open formats and so on. So yeah, so that's what we would say. Study your enemy, study your competition carefully, and then go after those weaknesses.

I had a professor, Arnaldo Hacks, and Arnaldo was one of those guys. He didn't have a double chin. He had like a quadruple chin. And he always had a line, watch the competition, but never follow the competition. He'd do it, his chin would wag for another minute.

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, more troops and so on? So you gotta study your troops, your competition. But then there's the companies that actually are obsessed with their competition. Like they're absolutely obsessed. And we have some companies right now that are obsessed by us.

Yep.

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 a book, great book, not Innovator's Dilemma, but Innovator's 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 the second pitfall that I see a lot of. CEOs fall into. 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've believed us. They would've just said, what are you talking about? They're the leaders in this. They created this category. What are you even talking about? So we had 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 gotta do that as well, not just copy.

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'd you guys do that? What did you do right? What did you do wrong?

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, 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 gonna talk to execs and you're gonna 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. So they came up with like bland category names for us.

Yeah.

I think Unified 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 there's like, hey, you're risking, you have a company that's pretty successful. You want to risk it all and go in 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 hockey, you know, so on.

Exactly.

So people were 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.

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 Databricks, amazing. It said great things about us. And we'd be like, no, no, no, wait, wait, wait. They didn't mention Lakehouse 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 the customer didn't mention Lakehouse. What the hell? So it became like a completely maniacally, religiously across the board in the company. It's gotta be a lakehouse, otherwise it's a loss. I don't care. And I think I saw at some point great ads from Databricks that I was receiving on Facebook. I was like, these are not mentioning lakehouse. What the hell? And 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. You're a data guy. Look at the conversion rates. Spark sells. This other weird funny thing you have doesn't sell. And I'm saying, 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 and get them to start selling Lakehouse?

Comp plans was always a thing we were obsessed with. I always personally obsessed with it. So there would be always multipliers and extra spiffs and gravy on top of the comp plan and things of that nature. 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.

Yeah.

If sales doesn't wanna 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 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. 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 gonna say if revenue slows down in the short term. Advice to those CEOs, or are 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.

Private.

Yeah. Okay. Interesting. I would say on the private side, you have more latitude. I was greedy and I had bigger hopes for Databricks than where we were at. I was disappointed. So at this point when we did Lakehouse, right, 2018, '19, we were 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, I'm talking public company investors we were talking to, who were trying to understand what Databricks does. And I would paint them this big vision of what I want Databricks to do one day. And I was being truth-seeking with myself after the meeting and saying, wow, we're not doing that. Like this picture that I'm painting is amazing, 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. 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 SIEM, 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. 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 HubSpot?

We did the same. We were a 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. 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.

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 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've seen this again and again and again. Right? Like, Databricks was cloud-only AI and no one gave a damn. It was like on-prem is where all the business is at. You should move to that until it took off. Then suddenly it was like, oh my God, how did you guys do it so fast? Like, yeah, we've been at it for 5 years. So yeah, you do have to have stamina. You have to do the thing you believe in. It has to be non-consensus, but you also have to be right and you have to do it for 4 or 5 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.

That rings a bell for me. Ali, I spoke to a bunch of people who have worked with you or work 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 this come out. How does a mild-mannered 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. 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 this, you have to have this kind of aggression to succeed. And, you know, there's probably a lot of pent-up 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. So it 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 It's 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? Everybody wants to get something from you. Can you do this? Can you approve that? Can we do this? If you're conflict averse, you're just going to say yes to them, or you're going to lie to them, or you're going to 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 approve because you caught me in the hallway here. Go through the formal processes. Like, just because you're chit-chatting 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 is all this push all the time. If you don't do it, the company starts, 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. I think Ali meant this. No, no, no. I think he meant that. No, no. I think you're totally misunderstanding him. 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 with that. Um, and then you start getting people that are more like-minded and you kind of start rowing 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, 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, Dunbar'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?

Yeah, some slowdown is sort of necessary. The Dumber number definitely happened. I felt for us, I felt like it was like 200, 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 2 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 on. You really have to go through the intermediate layer, you gotta put structure in place and make sure that the everything— reviews, KPIs— measured 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.

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 And the way Dorsey 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 2 layers between himself and the frontline employees. And Brian Armstrong's doing kind of similar things, like not just shrinking the org, but really collapsing Uh, 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.

Yeah, I think directionally it's correct. Um, we're doing the same, but I think we should, uh, separate 2 things that are, I think, a little bit sometimes being conflated.

Okay.

What is the official org 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 2. 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 org 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 we have extremely smart AI. I keep asking this question every audience I go to, and I ask them, 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.

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— 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. 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 chatbots. 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 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 coworkers collaborating with each other, providing proposals to you, keeping you up to date and doing that? Nobody raised their hand. I've never had a single person raise their hand on that. Okay, so 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 an 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 Databricks, 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 Databricks, 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 have an org chart of people that 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 kinds 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, the Genie product does this and builds the ontology. But then what about the humans? 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 org chart of humans? 2. Like, should we— should— so maybe I should just have, you know, 1 layer below me or 2 layers. Here's the problem. And I see some companies saying, okay, so therefore we're moving to 25 people fan out. So each manager should manage 25 people. They 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. This person is unhappy, career choices, unclear what the goals are that they want to do with that. There's a lot of human interaction. You can't have 25 direct reports reporting to a person and being super 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.

You're skeptical?

Yeah, I think it's BS. I think things will break down. You're gonna get unhappy people. I think you're gonna get a lot of unhappy employees who don't know what the hell's going on. 'Cause you know, there's like, they don't meet their manager 'cause their manager is busy vibe coding most of the day. And you know, there's 25 of them.

Hmm.

You know, and to tiebreak 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 IC work yourself.

Fair enough. Um, 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 never quit coding.

Yeah.

I mean, remember I ran engineering and product, right? And I've been coding since 3rd 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 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 2 days to build a connector and Our current teams were taking 3 quarters to build those connectors for one person. And I was like, how can I do it in 2 days? And it's taking you guys 3 quarters. And they said, well, you know, your thing is not production ready. It's not secure. It hasn't been thoroughly— actually, basically it doesn't really work. You got like a proof of concept working. You can't get into production. So I really wanted to figure out, are they right? Like, what's this gap? How can it be that the core thing took me 2 days, but all the kind of other extraneous stuff on top, that takes 3 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 3 quarters, one person, to 7 and a half months, one person.

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 gonna— he's not gonna 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, 3 quarters, they came back and they said, you know, we can do 7 connectors in 1 quarter.

Better.

And I was like, okay, what happened? And like, oh, you know, yeah, technology got better, models got better. 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. And we write very good PRDs. We have very skilled PMs. That quarter, the whole pipeline installed. There's no, nothing being written that quarter. Then you have to set up the systems that we connect to Salesforce, Workday, NetSuite, 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 error-prone. 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. 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 7 people, 7 connectors. So if one person gets sick, they go on pat leave, mat leave, vacation. So we had to re-engineer the whole process. So that kind of got me into coding to understand 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, 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 do process re-engineering of all organizations on the planet. 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 Ollie? 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 in the morning? What do you eat? What are your meetings? How do you schedule your meetings? Do you have like Monday as a certain thing? Tuesday? Like, what is your operating system yourself?

Yeah, I actually think that it's not like one consistent thing. It changes. Uh, 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. Uh, but, you know, I, I see it as kind of 3 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 to, I want to unblock that big thing that I think is the thing that's going to get us 10x. 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'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 shit 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. 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 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 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's 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 do that. So on the weekends, in the morning when I wake up early, I try to 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, 8:00 AM back to back to back to back to back to 5, 6:00 PM. Yeah. Um, 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 other— it's good. It's my job.

You're working on everybody else's priorities.

Exactly. Monkey's on my back. Right. So how do I actually kind of Carve out time. So I will tell my CEO office team like, you know, hey, this is 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, tiebreaking, this and that, 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.

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'll screw it up in this way, but they'll be great at these other 3 ways. So I know what they're like. So that helps a lot. Context and, you know, history helps a lot. But we do staff meeting Mondays, uh, an hour, an hour and a half, focus on top priorities. So we kind of go through the KPIs of the top priorities that we were— every, every year we have 1 or 2 or 3 goals. And those are like the thing, the whole, again, back to, it used to be like—

Okay. So you will, you, in a year you'll have 1, 2, HubSpot every year we had 3. I was like, can't be more than 3.

Yeah. I wanted it to be less. So this year we had 2.

Okay.

2 goals. And I actually wanted it to be 1, but it became 2. So, you know, to get to, 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. Why should I like you or trust you if I never get to meet you?

Hmm.

You know why? I don't know if you're married, like, 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 wanna, like, if there's something you wanna teach your kids, put it into the goddamn Google Doc. Maybe you don't even need to respond to the Google Doc. Claude can. So, uh, so my staff meets 3 times a week. Also Wednesdays, also Fridays. Wednesdays and Fridays are 30 minutes in the morning. So like 8 AM, 30 minutes.

And what are you talking about on Wednesday, 8 AM for 30 minutes?

Look, a lot of it is just like, okay, what's the main bottleneck right now? What's the main thing? It'll be something that's like, you know, popped up that's like top of mind for everyone and we gotta like do this right now. 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. If there's something big in the news yesterday, it could be unrelated. Like, you know, we can shoot the shit about that. It's just the 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 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 salespeople 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 butting hard against, you know, I need to close the quarter, get outta 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 gotta 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. If they never talk to each other and they're just writing Google Docs, it's not gonna happen. So yeah, so we do meet 3 times a week and we do these. We have QBRs every quarter.

Is that a day? Is that a week?

2, 3 days. There are multiple types of QBRs now at companies, product QBR, go-to-market QBR. But we make sure that every— this is the scaling part, right? So you gotta make sure that everything is happening across all the regions, all the departments, all the products. This has to happen. Like, is that's if some, if some product stops delivering or is veering off or some region is stopping to sell or sales leadership is bad or whatever it is, how do you detect that? So you have to have these QBRs. In the QBRs as well, it all gets sussed out and you take action plans on like, okay, we're gonna change this, we're gonna make change on this. We got this thing wrong, we built the wrong thing. All that, that happens in those.

And got it.

A lot of my, my exec team is the ones like running all of these and making sure all those are running. Right.

Do you do offsites, strategy offsites where you gaze at the stars or gaze at your enables?

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.

Uh, I see.

You know, they might be a little bit focused for a department, you know. Um, 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. 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 Databricks 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 because the last fundraise, you know, we had close to $15, $20 billion.

You had T. Rowe and the big guys in there.

Yeah, but we raised $5 billion and the interest was $20 billion. 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 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.

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 taken into account. You got to facilitate this for, you know, for 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, um, you know, 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, SaaS 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, wanna be public right now? That makes no sense to me. Now, Anthropic OpenAI 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 SaaS companies are shit and SaaS apocalypse is going to destroy all AI companies. Oh my God, Atlassian had a great earnings report. All SaaS is great. We should like buy SaaS. There's like wrong. Oh, we should put all our money on semis because, you know, semiconductors, the future is the bottleneck. We'll just go there. No, no, no, semis are overdone. 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. 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 bullshit and bullshit detector a bunch, and you talked about being comfortable with conflict. Let's just say you're not comfortable with conflict and you're a normal Homo sapiens and you become a CEO and it's starting to scale. How do you develop that bullshit 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 fund. 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 seeking to its extreme, you can't be conflict averse about it. You kind of have to face 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, it's kind of like saying oh. You know, some people, they don't like to go to the gym and work out because 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 a knack 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.

Okay. So if you're, if you're conflict averse, get over yourself.

Yeah, get over it. Like if you wanna be CEO, you do not wanna be a CEO. If you wanna be CEO, don't say I'm a conflict averse, change that. Like don't say, hey, I wanna be an athlete, but I'm the kind of athlete that doesn't work out. 'Cause 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 this 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 a conflict means someone pushes back, they're unhappy, 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 on the crowd.

Oh, likewise. Pleasure to talk to you, and, and I saw you do similar things at HubSpot, so thanks for having me on.

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 a piece of his CEO advice. And he reminds me a lot— I interviewed Nikesh Arora from Palo Alto. 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.

Yeah.

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 Glassdoor prizes back in the day. I'm not sure that's correlated with long-term success. We did pretty well long-term, but I think I overindexed on it. And you look at like Steve Jobs and these guys, they definitely don't. 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. Conviction without staying power is like a fad 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're 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. I found, because I mostly work with scale-up CEOs, that Conviction around second acts is even more important than conviction around the first idea. And Ali 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. 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 gonna get a lot of pushback. His sales organization's really not gonna want to sell it. And the advice I gave him is sort of the advice I give 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 over-index 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 1 or 2 focus areas a year. He's very focused. He focused on the bottleneck. It sounded like his number 1 focus for 2 or 3 years on his annual plan was that lakehouse product. So over-index on the thing you want to change. Changing is harder as you get bigger. And so over-indexing is really important. I hope you liked it. I really enjoyed the interview. Follow us here if you want to tune into all the Long Strange episodes with lots and lots of great CEOs. See you next time.

Thank you.