The Exchanges

Q know when to listen to customers? Oh, I'd love you to solve this. It may not actually be the right thing to do now. It may not actually be the right thing for the rest of your customer base. And it's only that small segment. How do you know when to listen to them and do the camera and the safety platform or not? And that's not where we're going.

A Yeah. We try to use like an eighty-twenty rule. So if 80% of our customers would benefit from something, we want to bring it onto the platform. Now there's a bunch of stuff that we get asked for by customers that are You know, exotic or esoteric. That's where we tend to partner. So we have customers that, uh, route produce, right? Like the groceries. And, uh, they have very specific rules around like the crispness of lettuce, right? Like something has to be delivered early in the morning versus in the afternoon, because they don't want it to spoil. That's not going to be applicable to a customer in construction or, you know, a local government or someone like that. So there we partner. But if you hear something like the dash cameras, we heard about apps from our customers. We heard about tracking equipment. Those kinds of things you say, oh, I'm hearing this all over the place, and I'm hearing in multiple geographies, multiple market segments. We should build something there. That's kind of what we tend to do.

AI assessment note: “We try to use like an eighty-twenty rule.”

Q What's the worst capital allocation decision you've made on the flip side?

A You know, I, I think I mentioned, uh, some of these products that we've tried out. Sometimes you, again, become really deeply enamored with the product or the technology. You really want it to work. You really want to believe in it. Machine vision, which was that product line I mentioned earlier, there were signs probably a quarter or two into it that it wasn't going to be scalable because of the manual installation required for it. I think we were like, okay, let's see if we can just like power past those, right? And at some point, you need to call it and reallocate. And, you know, we basically took the teams and Some of those people now work on our AI for the dash cameras and other products. We should have made that call a little bit earlier, but it was single digit millions. It's not like the huge downside.

AI assessment note: “We should have made that call a little bit earlier, but it was single digit millions.”

Q What are you seeing in terms of fastest adoption of EVs and then slowest adoption in terms of countries?

A So fastest adoption of EVs would probably be China. Uh, Norway is maybe technically the fastest. I think eighty-something percent of all new vehicles sold there are EV, which is remarkable given the weather. You know, that's, there have been a lot of government subsidies, lots of initiatives there. China is pretty far along. I think that's also maybe driven by the government. Again, air quality is a, is a significant issue for them. So EV and kind of Um, the energy transition there. And then slowest has been really in the U S um, and it actually varies by regions of the U S. Some of that is because our geography is so broad, right? Like we've got a lot longer distances here to cover and the, the, the very slowest has actually been heavy vehicles, what are called class eight. So these are the big semi trucks that you see or HGVs that you see in Europe. Those are the hardest to transition and they're, they're starting to happen now because the technology hasn't quite been ready.

AI assessment note: “fastest adoption of EVs would probably be China. Uh, Norway is maybe technically the fastest.”

Q Why did you decide to raise venture money? We bootstrapped. You doubled revenue. Product was selling. Customers liked it. Why raise?

A Yeah. So we got to close to a million dollars in, in revenue. And by the way, with Meraki, there was a hardware component. So we were building these routers. And what that means is you need cash upfront to get the product manufactured. Um, and so that was a big challenge, which is essentially having working capital for that. The other piece was we were bootstrapped, but we were kind of, I guess, ramen profitable would be like the YC or Paul Graham phrase. Phase. And we had all been graduate students. So we were used to like living below the poverty line. That was all good with us. We just enjoyed the work. When you went and tried to hire people, you realize they needed to make a lot more than a graduate student did, right? So we realized, okay, while we're profitable, it's not going to really be scalable unless we, we get a little bit of additional money. Now we could have taken a bit longer and just, you know, gone with taking our time, but actually the venture capitalists started knocking on our door quite literally. They found our dingy office space, which is like a I think a sublease of a sublease in the warehouse district, and, you know, these people with very nice cars would pull up and quite literally knock on the door, because word spread that, like, this group of MIT students was out there building routers and doing some interesting things.

AI assessment note: “what that means is you need cash upfront to get the product manufactured”

Q know when to listen to customers? Oh, I'd love you to solve this. It may not actually be the right thing to do now. It may not actually be the right thing for the rest of your customer base. And it's only that small segment. How do you know when to listen to them and do the camera and the safety platform or not? And that's not where we're going.

A Yeah. We try to use like an eighty-twenty rule. So if 80% of our customers would benefit from something, we want to bring it onto the platform. Now there's a bunch of stuff that we get asked for by customers that are You know, exotic or esoteric. That's where we tend to partner. So we have customers that, uh, route produce, right? Like the groceries. And, uh, they have very specific rules around like the crispness of lettuce, right? Like something has to be delivered early in the morning versus in the afternoon, because they don't want it to spoil. That's not going to be applicable to a customer in construction or, you know, a local government or someone like that. So there we partner. But if you hear something like the dash cameras, we heard about apps from our customers. We heard about tracking equipment. Those kinds of things you say, oh, I'm hearing this all over the place, and I'm hearing in multiple geographies, multiple market segments. We should build something there. That's kind of what we tend to do.

AI assessment note: “We try to use like an eighty-twenty rule.”

Q Who's best place to win the AI battlefield? Is it startups chasing distribution or is it incumbents chasing innovation and speed of integration of models into existing technology?

A So I think on the large scale infrastructure side, if you look at who's won the hyperscaler wars, right? Like who, who runs the biggest clouds? It was actually the, some of the best capitalized companies, right? You've got Amazon and Microsoft and Google and now Oracle. So in that sense, AI infrastructure may be well suited for companies that can invest billions of dollars ahead of time in building big data centers. The applications on the other hand, I think that sort of rapid feedback loop Um, and kind of creativity is really well suited to startup. So again, I think AI is going to be transformative in many ways. And so it maybe isn't an either or it's where, where do people play, uh, in the stack?

AI assessment note: “it maybe isn't an either or it's where, where do people play”

Q Why did you decide to raise venture money? We bootstrapped. You doubled revenue. Product was selling. Customers liked it. Why raise?

A Yeah. So we got to close to a million dollars in, in revenue. And by the way, with Meraki, there was a hardware component. So we were building these routers. And what that means is you need cash upfront to get the product manufactured. Um, and so that was a big challenge, which is essentially having working capital for that. The other piece was we were bootstrapped, but we were kind of, I guess, ramen profitable would be like the YC or Paul Graham phrase. Phase. And we had all been graduate students. So we were used to like living below the poverty line. That was all good with us. We just enjoyed the work. When you went and tried to hire people, you realize they needed to make a lot more than a graduate student did, right? So we realized, okay, while we're profitable, it's not going to really be scalable unless we, we get a little bit of additional money. Now we could have taken a bit longer and just, you know, gone with taking our time, but actually the venture capitalists started knocking on our door quite literally. They found our dingy office space, which is like a I think a sublease of a sublease in the warehouse district, and, you know, these people with very nice cars would pull up and quite literally knock on the door, because word spread that, like, this group of MIT students was out there building routers and doing some interesting things.

AI assessment note: “what that means is you need cash upfront to get the product manufactured.”

Q You know, I know Paul Graham has talked before with regard to you about doing things that don't scale. Can you talk to me about that? And how do you think about doing things that don't scale today? Whether it's always held true for you and how you think about it today?

A First of all, in retrospect, that project was a bit like a startup, right? Like we were trying to do something. We had very scarce resources. We had no money. It was just like spare parts in the computer lab kind of thing. And so just finding a way To make it happen was the key. And the brute force was, was one of the ingredients to that, which is like, you know, we couldn't get everyone's support or people were busy at the time. So it was just hard to get, and there were, you know, privacy questions, like, are we allowed to give this kid list of names from the roster kind of thing? So I said, well, the yearbook's not private. I'll just use that. So it was just finding a way, I guess. Um, this actually happened over and over. If, if we kind of fast forward, the first research project that my co-founder John and I worked on at MIT was called RoofNet. We built the network by literally installing antennas on people's roofs and we got like a 40 foot ladder and like, again, in retrospect, that was kind of crazy and definitely wasn't research, but it was just what was needed to build the platform up. So over and over that's, it's been an unlock, just being willing to kind of roll up your sleeves and go for it.

AI assessment note: “over and over that's, it's been an unlock, just being willing to”

Q natural tendency there. When I listen to both, I just think about kind of Product market fit quite early, both in Samsara and in Meraki. If you were advising an early stage founder on that very difficult and lonely process from zero to one in search for product market fit, having done it twice so well, what would you say to them over a coffee or sitting by a fire?

A Well, um, I think product market fit is something you don't want to force. And, and the way that I've always kind of Gone about it is just to get out there with customers with beta testers and and listen for the wow where you're showing them something and you know what we've done in the past is kind of what we call an allergy test so we'll bring them a few different ideas that we're playing with and sometimes they'll kind of nod their head or they'll be very polite and that sort of thing but then you show them something that's truly useful to them and they will quite literally stop you right there and say like hey can you click on that like show me that again or Even better is when they call someone out into their office or in from the hallway and say, hey, so-and-so, you need to see this, right? That's when you know you have something that's a true solution to a big problem that they have. It's probably the beginnings, right? It's not robust enough to be a full-on product, but you listen for that feedback loop and then you double down there. That has worked for us across both companies and many, many products that we've built.

AI assessment note: “listen for that feedback loop and then you double down there”

Q of cases, like real businesses, traditional, amazing producers of hard materials. My question to you is twofold. One, um, is on customer education. Often people are like, oh, they're a nightmare customer base to serve, because when it comes to technology, you have to really educate them. What advice do you have for founders who are told, oh, customer education is a nightmare, and you don't want to do that?

A It just never occurs to me to even frame it that way, because I really view it as you're partnering with the customer to solve their problems, right? And so if they're not super high tech, you're going to take them from zero to one and have a tremendous amount of impact in their day to day. We've had customers, by the way, that literally were planning The routes for thousands of trucks using giant maps on the walls, right? Like, so to take them from that to doing something, you know, online, it was just game changing for them and, and their eyes light up and very few people want to live in a cave. Like, you know, if you, you show them a smartphone, they're like, oh my God, this is amazing. And they're already there on their personal side of their lives. Like they're using smartphones, they're, you know, on Instagram or Facebook or whatever. So that's the kind of interesting connection that we've been able to draw, which is people know what digital, Transformation can look like how powerful it could be, how they make it happen is actually the challenge. So I view it as like a huge blessing to be able to spend time with customers and walk them through that journey. And once you do it once or twice, or maybe 10 or a hundred times, you have notes that you can share with them of here's how we did change management for 10, 20,000 drivers when you bring them new technology. And we've …

AI assessment note: “I really view it as you're partnering with the customer to solve their problems”

Q I'm completely unemployable, but I am good at what I do, and I am unhinged in many ways. I would be a good hire if you unleashed me on my own in a dark room. Is there ever a time to hire not a team player or a role where it's okay? And the answer may be no, and Harry, you're just meant to be unemployed. I'm fine with that.

A Well, you know, it's, it's also about talent fit, right? So if that person comes in, like if, if Harry comes in and is basically unabashed that I'm not a team player and I, I take out other people, that's just counterproductive, right? We're going to burn more calories managing and working with Harry than what Harry can produce. So in that sense, it's like, is it a fit? Are you going to be happy? Kind of question. Now, I will say we have some people who are, um, extraordinary technical architects and they would say, I'm not a people manager. I'm not a, Big people person. I don't like big meetings and that's totally fine. We don't want a lot of big meetings anyway. So there, what we say is, Hey, you help build the next product, right? And then we will bring in product managers and we'll have, you know, engineering managers and so on that will help get the thing made, but we need someone to architect it. So those, you know, there are some personality types and some roles where it is a little bit more of kind of individual Brilliance and that fits, but you want those people to have the ability to work with the other people in the company, right? Otherwise it's, it, it really isn't going to be productive.

AI assessment note: “roles where it is a little bit more of kind of individual Brilliance and that fits”

Q So, how do you embrace that transition? Because it's incredibly hard to let go, or to realize that actually, we can't do that unscalable thing, and we need to build process. What would you advise? It's something that I struggle with today, actually, honestly. What would you advise me?

A Yeah, you know, so, um, I go through a process which I call rehiring myself, um, and it's, it's a little bit, like, I actually write a job description of what do I think the job needs in the next year, or the next couple of years, and I check, like, does my, Time and, and sort of how I'm doing things match what, what needs the company needs for me and the organization needs for me. And usually there it comes out that, you know, Hey, I probably need to stop like designing hardware or trying to be involved in every sale or, you know, being, being in all these details, which makes sense at the beginning. Like when you're getting off the ground, the other thing is people will tell you if you listen, right? Like they're very polite about it, but they might kind of give you a hint or two. And so you have to have these really big ears and listen.

AI assessment note: “I go through a process which I call rehiring myself”

Q think about sales cycles, compressing them, reducing them, making them more efficient, one thing that's astonishing with Samsara is how much more efficient you are as a business, and how that's kind of changed over time. What's driven the efficiency bluntly? When I was looking at, I was thinking these different charts of your efficiency, and over the last eight quarters, it's been pretty unparalleled. What's driven the efficiency gains?

A Well, I'd say two things. One is we have a direct sales force, so they become more productive the longer they're in seat, and we've been growing so much as a business, we're adding capacity on a continuous basis, so you need to give them time to ramp. The sales reps are financially inefficient because they're kind of, and you know all this, right? Like, They're still kind of coming up to speed and still learning the product, learning the customer base, building a pipe. Once they have that, the cruising altitude has always been very efficient. And so it's kind of just seeing that through that. That's maybe area number one. Area number two is we have developed just a clearer sense of process of what needs to happen next. And customers actually want to move quickly because they don't want to spend time in the sales process. They want to kind of get the product and get going. So we found that aligning more closely with how the customer likes to buy. Has, has really unlocked, uh, you know, a tailwind of growth.

AI assessment note: “Well, I'd say two things. One is we have a direct sales force”

Q Yeah, it totally does. Sanjay, I listen to you now. When does being a CEO become natural? Because now, you know, I hear you speak. You're a very natural, gifted CEO, and I interview many CEOs. You go back to your engineering, no offense, less CEO, obvious candidate. When did it feel natural?

A I'm trying to remember. There was a moment where I realized that my Salary was allocated under GNA, not R and D. So it's a very in the weeds sort of sort of view. I was like, wow, I guess I'm overhead. So, uh, but, but for me, that was actually an important milestone, which is like, this is an important job, right? The leader of the company, you're, uh, we talked about capital allocation. You're as a founder CEO, you're the soul of the company as well. So I, I think those kinds of things make it feel natural over time, which is, Hey, This is the job, right? It's not being an engineer. It's not, you know, being the chief salesperson. It's actually being the leader of the whole business. And so that probably for me happened maybe as Meraki became a hundred people or something like that.

AI assessment note: “happened maybe as Meraki became a hundred people or something like that.”

Q What about Mark? What have you learned from Mark?

A So Mark is very different personality as I think many people know. What I learned from Mark, uh, Has been his information diet. So he's talked about this a little bit, but I think Mark spends time on X or Twitter and, you know, gets a lot of what's, what's going on in the moment. And then he reads some really old, old books, right? Like stuff that's maybe out of print and hard to find sort of the timeless, timeless, um, sort of thought classics. That barbell of information is really fascinating because we all have a limited amount of bandwidth to take in. And so being able to kind of do the timeless stuff and then what's current is really interesting.

AI assessment note: “What I learned from Mark, uh, Has been his information diet.”

Q Frontline workers will be removed by AI. Contrarian sim. That's not what I actually believe, but like discussion topic. How do you feel about that?

A I think we're going to have frontline workers for a very long time because some of these jobs are, uh, difficult to automate. Uh, if you think about what's going on with AI, a lot of the sort of disruptive impact might be in the back office or the sort of white collar jobs. Frontline work transformed a hundred, 150 years ago when, uh, agriculture, you know, got the, the combine harvester and diesel engines started showing up everywhere. And what, what happened is A bunch of jobs transitioned, right? A bunch of jobs that weren't so fulfilling, were hard work, were actually quite dangerous, kind of went away because automation kicked in and cranes showed up and, you know, you didn't have to work in the field and that sort of thing. So I actually think that disruption happened In our great great grandparents generation. What we're seeing now is a similar disruption, maybe on the white collar side. And I actually think we're going to come out of this with better jobs that are more fulfilling, which are again, more creative and more unique to us and where we get leverage from technology like AI.

AI assessment note: “I think we're going to have frontline workers for a very long time”

Q natural tendency there. When I listen to both, I just think about kind of Product market fit quite early, both in Samsara and in Meraki. If you were advising an early stage founder on that very difficult and lonely process from zero to one in search for product market fit, having done it twice so well, what would you say to them over a coffee or sitting by a fire?

A Well, um, I think product market fit is something you don't want to force. And, and the way that I've always kind of Gone about it is just to get out there with customers with beta testers and and listen for the wow where you're showing them something and you know what we've done in the past is kind of what we call an allergy test so we'll bring them a few different ideas that we're playing with and sometimes they'll kind of nod their head or they'll be very polite and that sort of thing but then you show them something that's truly useful to them and they will quite literally stop you right there and say like hey can you click on that like show me that again or Even better is when they call someone out into their office or in from the hallway and say, hey, so-and-so, you need to see this, right? That's when you know you have something that's a true solution to a big problem that they have. It's probably the beginnings, right? It's not robust enough to be a full-on product, but you listen for that feedback loop and then you double down there. That has worked for us across both companies and many, many products that we've built.

AI assessment note: “just to get out there with customers with beta testers and and listen for the wow”

Q So, how do you embrace that transition? Because it's incredibly hard to let go, or to realize that actually, we can't do that unscalable thing, and we need to build process. What would you advise? It's something that I struggle with today, actually, honestly. What would you advise me?

A Yeah, you know, so, um, I go through a process which I call rehiring myself, um, and it's, it's a little bit, like, I actually write a job description of what do I think the job needs in the next year, or the next couple of years, and I check, like, does my, Time and, and sort of how I'm doing things match what, what needs the company needs for me and the organization needs for me. And usually there it comes out that, you know, Hey, I probably need to stop like designing hardware or trying to be involved in every sale or, you know, being, being in all these details, which makes sense at the beginning. Like when you're getting off the ground, the other thing is people will tell you if you listen, right? Like they're very polite about it, but they might kind of give you a hint or two. And so you have to have these really big ears and listen.

AI assessment note: “I go through a process which I call rehiring myself”

Q I get you. Did you feel like in a bit of an imposter in that situation?

A Yeah, absolutely. And I think you have that even as a grad student when you're doing research, like how am I going to further the state of the art? So you kind of get used to this idea of being uncomfortable, but it's very different because there's a shelf of business books. You go to a bookstore and there's like all of these management books and so on. You read through a couple of them. They're actually kind of hard to relate to. And I ended up just kind of putting them all down at the beginning and saying, look, this is actually just a big project, right? So let me do what I know how to do, which is lead a project. And kind of get it to the next stage. And that's where some of these kind of operating principles of kind of working backwards from winning essentially, like what, what is the next stage goal look like? And then let's reverse engineer that. That's where that came from.

AI assessment note: “Yeah, absolutely. And I think you have that even as a grad student”

Q And I was like, is there ever a time when the founder's not involved in sales?

A You know, there, there might be, no two companies are the same, right? So for us, it benefits us tremendously to be out on the front lines. And I, I love it. I love to get out on the road. Our customers are sometimes in the middle of nowhere, so it can be a little bit challenging from a travel perspective, but it's always worth it. To get up, get out in front of them and see what their problems are firsthand. I personally get a tremendous amount of value from it. You just can't be everywhere at once. So that's the only thing to be aware of is you can, you know, fly to a certain state, but you can't fly to all the different countries. You can't fly and see all the different industries. So you do need a more scalable process than just the founder doing all that kind of product management work.

AI assessment note: “there might be, no two companies are the same”

Q of cases, like real businesses, traditional, amazing producers of hard materials. My question to you is twofold. One, um, is on customer education. Often people are like, oh, they're a nightmare customer base to serve, because when it comes to technology, you have to really educate them. What advice do you have for founders who are told, oh, customer education is a nightmare, and you don't want to do that?

A It just never occurs to me to even frame it that way, because I really view it as you're partnering with the customer to solve their problems, right? And so if they're not super high tech, you're going to take them from zero to one and have a tremendous amount of impact in their day to day. We've had customers, by the way, that literally were planning The routes for thousands of trucks using giant maps on the walls, right? Like, so to take them from that to doing something, you know, online, it was just game changing for them and, and their eyes light up and very few people want to live in a cave. Like, you know, if you, you show them a smartphone, they're like, oh my God, this is amazing. And they're already there on their personal side of their lives. Like they're using smartphones, they're, you know, on Instagram or Facebook or whatever. So that's the kind of interesting connection that we've been able to draw, which is people know what digital, Transformation can look like how powerful it could be, how they make it happen is actually the challenge. So I view it as like a huge blessing to be able to spend time with customers and walk them through that journey. And once you do it once or twice, or maybe 10 or a hundred times, you have notes that you can share with them of here's how we did change management for 10, 20,000 drivers when you bring them new technology. And we've …

AI assessment note: “I really view it as you're partnering with the customer to solve their problems”

Q think about sales cycles, compressing them, reducing them, making them more efficient, one thing that's astonishing with Samsara is how much more efficient you are as a business, and how that's kind of changed over time. What's driven the efficiency bluntly? When I was looking at, I was thinking these different charts of your efficiency, and over the last eight quarters, it's been pretty unparalleled. What's driven the efficiency gains?

A Well, I'd say two things. One is we have a direct sales force, so they become more productive the longer they're in seat, and we've been growing so much as a business, we're adding capacity on a continuous basis, so you need to give them time to ramp. The sales reps are financially inefficient because they're kind of, and you know all this, right? Like, They're still kind of coming up to speed and still learning the product, learning the customer base, building a pipe. Once they have that, the cruising altitude has always been very efficient. And so it's kind of just seeing that through that. That's maybe area number one. Area number two is we have developed just a clearer sense of process of what needs to happen next. And customers actually want to move quickly because they don't want to spend time in the sales process. They want to kind of get the product and get going. So we found that aligning more closely with how the customer likes to buy. Has, has really unlocked, uh, you know, a tailwind of growth.

AI assessment note: “Well, I'd say two things. One is we have a direct sales force”

Q What have been the biggest hiring mistakes you've made, Sanjid? They're, they're inevitable. What do you think have been the biggest?

A The biggest hiring mistakes. So, I think you're right. It's inevitable, and it's kind of statistical. You hire a thousand people, you're not going to get them all right. The ones that come to mind are when it wasn't a stage fit. So, For example, there may be someone who's been very successful at a bigger company. Maybe they grew a business from X hundred millions to, to Y billions, right? If you're an early stage startup, it doesn't make sense to bring that person in quite yet, or you could, but you're taking real risk, right? Because that person's not going to have all the infrastructure they're used to. They're not going to have the brand behind them. They won't have a huge number of reference customers. Those sorts of things happen over time because you get Wow. You're like, oh my gosh, this person is so amazing on paper, but are they appropriate for this stage? So that's one. And then two is sometimes, uh, I would say when we move really fast on hire and not done the references, it can backfire on you because someone, again, may look great on paper. And then you realize, wow, they're really a terror to work with behind the scenes. Like they're not cooperative. Um, and, and again, it's a team sport at this scale, right? Like you have to have people coordinating and collaborating, and that could be within the sales and sales ops functions. It could be with product, could be w…

AI assessment note: “The ones that come to mind are when it wasn't a stage fit.”

Q I'm completely unemployable, but I am good at what I do, and I am unhinged in many ways. I would be a good hire if you unleashed me on my own in a dark room. Is there ever a time to hire not a team player or a role where it's okay? And the answer may be no, and Harry, you're just meant to be unemployed. I'm fine with that.

A Well, you know, it's, it's also about talent fit, right? So if that person comes in, like if, if Harry comes in and is basically unabashed that I'm not a team player and I, I take out other people, that's just counterproductive, right? We're going to burn more calories managing and working with Harry than what Harry can produce. So in that sense, it's like, is it a fit? Are you going to be happy? Kind of question. Now, I will say we have some people who are, um, extraordinary technical architects and they would say, I'm not a people manager. I'm not a, Big people person. I don't like big meetings and that's totally fine. We don't want a lot of big meetings anyway. So there, what we say is, Hey, you help build the next product, right? And then we will bring in product managers and we'll have, you know, engineering managers and so on that will help get the thing made, but we need someone to architect it. So those, you know, there are some personality types and some roles where it is a little bit more of kind of individual Brilliance and that fits, but you want those people to have the ability to work with the other people in the company, right? Otherwise it's, it, it really isn't going to be productive.

AI assessment note: “there are some personality types and some roles where it is a little bit more”

Q When you say that didn't make a ton of sense, no offense. Why do them then?

A Because if you build for the longterm, you're going to be glad you did them three years out. Right? So again, like products two and three, I'm super glad we have them now. Like product two for us, safety is now our number number one revenue product. It's pretty exciting, right? And so, very glad we did that. Maybe we could have acquired our way in, but it would have been a different customer experience. Maybe the product wouldn't have been as deeply integrated. Doing it organically, for me, feels like it was the right answer. I'm really glad we did that. And along the way, we tried a couple of other products, you know, you know, products three, four, five, that maybe won't have the same trajectory, but you won't know until you try.

AI assessment note: “Because if you build for the longterm, you're going to be glad”

Q Why do you say you most need to improve, improve as the leader today?

A Oh, how much time do we have? Um, uh, you know, I, I think for, for me, you know, as we kind of talk about rehiring myself, we're entering the next phase of growth for Samsara, which is really scale growth, right? And The way that you continue to achieve scale, you mentioned you've, you've interviewed people like Mark Benioff and others. They've seen tremendous scale. The CEO they are today and the way they operate is very different than, you know, early stage startup CEO. You're getting a lot more leverage. You're thinking a lot more strategically. You're, you're thinking like three, five, seven years out. So for me, that's where I'm constantly pushing myself of, Hey, as much as I love, you know, being involved in the details, Am I spending enough time on the long term? And, and that's a question of time allocation, which is you really have to carve it out.

AI assessment note: “Am I spending enough time on the long term? And that's a question of time allocation”

Q Is it tough for you as well? Because you have this kind of unbelievable business and now bluntly wall street and everyone around you is like, well, everyone needs an AI story. And it's like, no, Graham shorts. I'm sorry. Amazing things with AI. But can we focus on the amazing business we have as well and on AI story? Is that frustrating?

A Not really. So we talked about our safety product, the dash cameras. Those were really, what differentiated us is we incorporated AI in them years ago. So we have been deep believers in this area for some time. Again, it's the application. So when we talk to investors on Wall Street, a lot of what we're doing is connecting the dots, educating them about these end markets, like a Construction or, you know, uh, field services type vertical industry and saying here is how a raw technology like an AI can be impactful. It can speed up, uh, workflows. It can actually detect risk and help you avoid it. It can help you, you know, really be more efficient in terms of how everything runs. It can help you with sustainability transitions. Those sorts of things are really exciting for investors. I think they say, wow, there's going to be a lot of value unlocked there and you could build an even bigger business. So We just try to connect those two dots together.

AI assessment note: “Not really. So we talked about our safety product, the dash cameras.”

Q a hundred million an hour. I'm sure numbers are updated now, but that's when I saw it. How do you know when is the right time to release a second product? Because you're right, I'm a VC, and I always say to founders, you've got so much more room to run on your first. People try and diversify too early. When's the right time, and how do you advise me?

A You know, just the Samsara anecdote is fascinating. So our first product was, that really kind of got us going was real-time GPS tracking. So think about all the work trucks that are out there as part of different fleets, not just in supply chain businesses, but construction, Field services, all these different kinds of businesses. What we found even in 2015 is people didn't have real time visibility of their operations. So they wanted GPS tracking. They wanted a nice interface. They wanted reporting and alerts and that sort of thing. So that was our first product. What was interesting is that got our foot in the door and we started talking to these operations users. What quickly happened is they, they loved the GPS tracking product. And then they started asking us, Hey, is there a dash camera that you all recommend that works well with your system? You hear that five, maybe 10 times. And then, you know, we said, well, if we built a dash camera, would you use it? And they say, oh yeah, absolutely. I'd prefer that the dash camera was in the same system. So that's how we built our second product, which was basically what's now our safety product. Um, and we've, we've now added AI and workflows and a bunch of deep analytics on top of that. But those conversations were happening when product one was maybe ten million in revenue. So it was really happening very early for us. And so …

AI assessment note: “we organically built It was product line number two, because the customers wanted more.”

Q What do you think was the best capital allocation decision you made? Be it the decision to invest in a new product, a specific person, a new geography. When you look back, you're like, that was the best capital allocation decision we made.

A Maybe I'll answer the question in a little bit of a meta way, which is I'm glad we took risk period, right? So we were talking about multiple products earlier and how we went from GPS tracking to safety cameras. That was again, early in the company's trajectory. We were doing maybe 10, 10 or maybe fifteen million in ARR. A lot of people might have said, just stay focused. Just, you know, there's still bugs in the product or still new feature asks, like just allocate all the capital there. We said, hey, we're gonna fix those and we're gonna invest, but we're also gonna try this new thing. It didn't cost us a tremendous amount of money to build that first prototype of the product and then V one and V two, but it took time and you needed to plant those seeds so you could harvest them years out. So I'm glad we did that. You mentioned geographies. We did the same thing with Mexico, for example, which is now a growing business for us. It's doing really well. We've done the same thing with Western Europe, which is where, um, we've got customers growing as well. Those are areas that didn't make a ton of sense at, at that moment because there was so much more market in the U S. But I'm glad we planted those seeds and we tried things. So that's maybe the meta answer is like, it's really important to again, have a sort of ladder of risk where you're saying, Hey, this is low risk, but we'r…

AI assessment note: “Maybe I'll answer the question in a little bit of a meta way”

Q a hundred million an hour. I'm sure numbers are updated now, but that's when I saw it. How do you know when is the right time to release a second product? Because you're right, I'm a VC, and I always say to founders, you've got so much more room to run on your first. People try and diversify too early. When's the right time, and how do you advise me?

A You know, just the Samsara anecdote is fascinating. So our first product was, that really kind of got us going was real-time GPS tracking. So think about all the work trucks that are out there as part of different fleets, not just in supply chain businesses, but construction, Field services, all these different kinds of businesses. What we found even in 2015 is people didn't have real time visibility of their operations. So they wanted GPS tracking. They wanted a nice interface. They wanted reporting and alerts and that sort of thing. So that was our first product. What was interesting is that got our foot in the door and we started talking to these operations users. What quickly happened is they, they loved the GPS tracking product. And then they started asking us, Hey, is there a dash camera that you all recommend that works well with your system? You hear that five, maybe 10 times. And then, you know, we said, well, if we built a dash camera, would you use it? And they say, oh yeah, absolutely. I'd prefer that the dash camera was in the same system. So that's how we built our second product, which was basically what's now our safety product. Um, and we've, we've now added AI and workflows and a bunch of deep analytics on top of that. But those conversations were happening when product one was maybe ten million in revenue. So it was really happening very early for us. And so …

AI assessment note: “we organically built It was product line number two, because the customers wanted more”