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

25:29Brian Halligan:Okay, so you haven't seen the turnover in these. I have. I have. You know, I probably, I think I would say two cases where I made a mistake. Maybe more. But two like really come to mind. And then you said, give yourself some time. Is that three months, six 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 lift at everybody. This is the best we can get. You know, we haven't had a person in this role now forever.

26:03You 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. when I look 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 postmortem, I always see like, Hey, all the signs were there. Like what was I doing?

26:34Or, 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 back doors are phenomenal like dude just do an insane amount of back doors 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

26:58Brian Halligan:actually being truthful 80 are bullshit Ali I want to switch topics on you you had a rivalry obviously was 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 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 the 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?

27:47That 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 an amazing team and then we had Andy come here and build up 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.

28:32This 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. No, this is 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. That's just a small fraction of what they do.

29:10Most 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. They would say that they would, but we knew that that was pretty weak. so the second thing that we wanted to push really really hard on um and um 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 it could extract a lot of margin out of it so you know winners do that you know they have great product so we went exactly for those three so we said hey open lake house means you own your own data.

29:52It'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 keep pushing on that weakness. And then cost. Let's make sure that the TCO is a third. And still today TCO is just, which typically we notice here. And then we just hammered up extremely aggressively in account after account.

30:22We 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 this play at Databricks.

30:54They 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 we had a three-year strategy, four-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 lake house. Even Stelphic will say that. And they say that they have open format and so on. So yeah, that's what I would say. Study your enemy. Study your competition carefully. And then go after those weaknesses.

31:31Brian Halligan: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 as 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?

32:07Do they have, you know, more troops and so on? So you got to 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 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 uh in in a book great book not innovators 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 uh 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 snowflakes 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 are you even talking about so we have to say no no no this is a different thing and it's different and 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

33:19Brian Halligan:and not just copy okay so how did the idea for lake house 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 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 it's 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 um so into 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 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 have to kind of put you know kind of march ahead and have a lot of conviction and And that was that easy because there's like, hey, you're risking, you have a company that's pretty successful.

34:41You 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 like they were making all these 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 NEPR is a good 3R. so it wasn't that bad in the big scheme of things um but we really did mobilize the whole company

35:09Brian Halligan:behind it okay it wasn't a separate team it was a 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 theater breaks amazing it said great things about us and we'd be like no no wait wait wait they didn't mention lake house 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 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 lake house otherwise it's a loss i don't care you know and you know i think i saw at some point great ads from databricks that i was receiving on facebook i was like these are not mentioning lake house what the hell and you know my head of marketing said yeah you know how well the roi is on putting a word lake house in an ad spark is the thing we're known for like here's the conversion rates.

36:00You're a data guy. Look at the conversion rates. Spark sells. This other weird, funny thing you have doesn't stop. I don't care. Get rid of all those ads that work and use this ad that doesn't work. So it took a concerted effort by the whole company for multiple, multiple years.

36:18Brian Halligan: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 was personally obsessed with it. So So there would be always multipliers and, you know, 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. You know, if sales doesn't want to do something, then put it in the comp plan to do that thing.

36:51If 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 committed, put in a comp plan and stop the debate and the debate immediately stops.

37:06Brian Halligan:Okay. A couple of times in your history of 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 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.

37:42Private. Yeah. OK, interesting. I would say on the private side, you have more latitude. I was greedy and I had bigger hopes for Databricks 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.

38:17We 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. 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, you know, that amazing vision.

38:43If you want to do that amazing vision, we've 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 durability, security, same, 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 might I could not succeed with them.

39:18And 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? The top spot.

39:35Brian Halligan:We did the same. We were a marketing app company. It 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 two minutes.

40:10They'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 again right like that databricks was cloud only ai and no one gave a damn it was like on-premise where all the business is like is that you should move to that until it took off then suddenly was like oh my god how did you guys do it so fast like yeah we've been at it for five years so yeah you you do have to have stamina. You have to do the thing you believe in.

40:42You know, it has to be non-consensus, 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 a completely different company. Like, how did you do it so quickly? You're like, actually, we've been doing it for five years. Yes.

41:02Brian Halligan: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, there's this, you have to have this kind of aggression to succeed.

41:46And, you know, there's probably a lot of kind of anger that piles up over the years.

41:50Brian Halligan: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-diverse. So I learned that very quickly, that conflict-diverse CEOs is like the worst thing possible.

42:34It'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 prove 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've got to be crystal clear. We don't do that here.

43:00Like, 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 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 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 be more consistent and clear so everybody kind of gets the message.

43:34People 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. 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.

44:07I saw it in big companies. So I'm trying to avoid that, you know, really.

44:10Brian Halligan:Just pulling on that thread, 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'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 number number definitely happened. 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 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 there's like one person that knows everything or two people that knows everything and then there's a bunch of people around but you know everything so you have to start putting structure in place so that you don't know everything.

45:25You just trust that 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.

46:00You really have to go through the intermediate layer. You got to put structure in place and make sure that everything reviews, KPIs, measure it in a way so that 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. And you don't even know the name of everyone anyway. anymore. Yeah.

46:20Brian Halligan: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 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 no more than two layers between himself and the frontline employees. And Brian Armstrong is 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.

47:02Brian Halligan:And a bunch of the AI native companies I'm working with are pretty intrigued by that. Yeah, I think directional is correct. We're doing the same. But I think we should separate two 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 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 org charts that's how information disseminates up and down and decisions go up and down that's the only way you know 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 uh today what has happened is that uh 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?

48:15And 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

48:41Brian Halligan: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 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.

49:10They'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 agent 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 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 raises their hand. I've never had a single person raise their hand on that.

49:41Okay, 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 ontology. So we want to capture the ontology. feed it to the AI so we actually built the 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 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 the ontology

51:04Brian Halligan: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 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 too like should we 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 therefore we're moving to 25 people fan outs 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 our managers doing well a lot of it is like human stuff you know this person is unhappy career choices uh you know 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 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 they should be vibe coding 80 percent of the time and 20 percent 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 going to get unhappy i think you're going to get 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 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 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 i never quit coding yeah i mean remember i ran engineering and product right and i've been coding since third grade so like i never stopped coding i would code on the weekends just for fun and stuff.

53:21But 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 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 that 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 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 commit code into production that goes and faces the customers.

54:17Only 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.

54:41Brian Halligan:That's okay. okay wait a minute like how's that even possible yeah um so uh 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 he's not gonna he's 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 fde and after you know three quarters they came back and they said you know we can do seven connectors in one quarter better and i was like okay uh 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 and we write very good prds we have very skilled PMs.

55:43That quarter, the whole pipeline is stalled. There's 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. 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 then 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, mat leave, vacation so we have to re-engineer the whole process so 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?

56:42And 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 do process re-engineering of all organizations on the planet. Uh, so that's going to take a long while. Um, 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.

57:18Brian Halligan:So you're doing some coding. What is a day in the life of, 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 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? Tuesday? What is your operating system yourself? I actually think that it's not like one consistent thing. It changes throughout the year. And you have bursts of like, okay, board meeting strategy, our big summit in the year. So it's not the same thing throughout. But I see it as kind of three things.

57:56One is the main bottleneck that I'm obsessed with. 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 focal point. I want to, 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.

58:26It'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 you know i try to spend as much of the remaining time looking at what's happening inside the product where are we building what are the features what are customers saying about the product feature 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 The remainder of the time I go back to the first thing, I want to do that.

59:05So 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 the company can be worth 10x more.

59:16Brian Halligan: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? How do you do that? Do you work from home a day to work on things like that? I try to compress the calendar. what I mean by that is I try to keep it, like try to put nothing on the calendar. It ends up being packed anyway, but there are many blocks that are free where I can go back to this main thing. I think if I do the 8 a.m. back to back to back to back to back to 5, 6 p.m., I consider those days. I've just been a slave to my calendar. I'm just working for my calendar.

59:53So I've been just working on behalf of others. It's good. It's my job.

59:56Brian Halligan: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 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 tell 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, type rating, 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?

1:00:28Brian Halligan:Are you weekly staff meetings? Do you have one-on-ones with all your directs? How often do you do off-sites? How do those work? 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 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. 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 one or two or three goals and those are like the thing to hold again back to it used to be like okay so you will you in a year you'll have one true 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 goals.

1:01:27I actually wanted it to be one, but it became two. Otherwise, it just becomes everything.

1:01:33Brian Halligan: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? 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? 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 up 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 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 for 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 and we gotta like do this right now uh sometimes we just go around the horn uh it's just 30 minutes to get the day started a lot of that 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 uh 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 um 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 they're all sales people reporting to ron or they're all legal people reporting for each other 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 out of my way no this is not legally possible or no marketing so how do you how do you change that so that we're doing the right thing for the company so the company's priorities are first well we've got to make sure that these people feel like they're a team.

1:03:36If 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 going to happen. 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. It's a product QBR, go to market QBR, but we make sure that 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 is that's if so if some product he 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 get sussed out and you take action plans on like okay we're going to change this we're going to make change on this we got this thing wrong we got the wrong thing all that that happens in those and 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 off-site strategy

1:04:34Brian Halligan:offsites where you gaze at the stars or gaze at your navels 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 asked 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.

1:05:18Okay. Now that answer might vary over time. There are times at which I knew we're worth more as a private company than we're as a public. But right now, if we're public, I think we would be worth much, much more actually. And I know that the last fundraise, you know, we had close to 15, 20.

1:05:32Brian Halligan:T-Row and the big guys in there. Yeah, but we raised five and the interest was 20 billion. So I just know that, you know, based on the supply demand curve, we could have got 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 a hundred countries. And you have to make sure that the tax laws of every country is kind of taken into account.

1:06:10You got to facilitate this for, you know, for 12 ,000 people, we do it for ex-employees too. So they can participate in these vendors that we do that's probably 15 ,000 people. So you have to like, it's a big undertaking. You're facilitating a marketplace, basically emulating a NASDAQ in a private market. And 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 air is a different story they need a lot of capital they have huge capital needs we're free cash flow uh 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 uh all sas companies are shit and sas apocalypse is going

1:07:21Brian Halligan:to destroy all ai companies oh my god the classian had a great earnings all sas is great we should like buy sas who's a wrong oh we should put all our money on semis because you know semiconductors the futures is a bottleneck we'll just go there no no no 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. They're also having a hard time wrapping their heads around that.

1:07:52They're much better at the normal, whereas this big transformation, they can't figure it out. Is the value software zero? No, 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.

1:08:09Brian Halligan: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 the conflict and you're a normal homo sapien 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, it's 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 their way and they say, well, you know, they find excuses.

1:08:53So 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 diverse about it you kind of have to face and challenge that you know that gap that discrepancy head off 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 diverse some people are conflict diverse 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 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.

1:09:57Brian Halligan:Okay. So if you're, if you're conflict diverse, 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. 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.

1:10:29I don't love the conflicts. Who likes the 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 there. 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.

1:10:53Brian Halligan:Ali, thanks for coming on. Congratulations on all your success. You were fantastic. Appreciate all the wisdom you've dropped on the crap. Likewise. Pleasure to talk to you. 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. way. 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 Arora from Palo Alto, like they don't put up with any BS, they have strong BS detectors, they use those BS detectors.

1:11:36Brian Halligan:They both believe that conflict aversion is kind of cancer in a CEO. And I suspect they're right about that. And neither over indexes on being liked. When I was CEO of HubSpot, I think I did over-index on it. We won 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 over-indexed 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. You know, conviction without staying power is like a fad diet in January.

1:12:14Brian Halligan: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.

1:12:55Brian Halligan: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 going to get a lot of pushback. His sales organization is really not going to want to sell it. And the advice I gave him is sort of the advice I gave myself at HubSpot.

1:13:28Brian Halligan: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 one or two focus areas a year. He's very focused. He focused on the bottleneck. It sounded like his number one focus for two or three 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.

1:14:08Brian Halligan: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.