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The Two Ways to Sell AI: Lighthouse or Landgrab?

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The Two Ways to Sell AI: Lighthouse or Landgrab?

The podcast episode, featuring A16Z's Joe Schmidt and Andy McCall, explores two dominant go-to-market strategies for enterprise AI startups: the Lighthouse and LandGrab playbooks. Joe introduces a framework based on a two-by-two matrix, with buyer exposure (risk) on one axis and the transferability of proof on the other. High-risk markets where proof travels, such as regulated industries, require a lighthouse approach—winning a few prestigious customers to build credibility. Conversely, low-risk markets with existing budgets and less need for social proof favor a land grab, where startups rapidly capture market share by demonstrating better math than incumbents. Andy shares insights from Samsara, highlighting the ELD mandate as a land grab opportunity; instead of chasing large accounts, they targeted mid-market customers for quick feedback and deployment. The discussion contrasts examples like Stewart, an AI-powered accounts receivable company that succeeded by proving immediate cost savings, with Harvey, a legal tech firm that won top law firms to validate a risky new category. A key takeaway is that founders often mistakenly focus on high-profile San Francisco companies, ignoring practical opportunities elsewhere. The hosts emphasize that a land grab occurs when buyers are willing to engage and purchase quickly, while a lighthouse is necessary for educational, high-stakes sales. Ultimately, they advise founders to assess their market's dynamics and, sometimes, stop strategizing and start selling.

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There's a moment right now to go sell big software again. We're now looking at a different way of doing business entirely. What are the Lighthouse and LandGrab Sales Playbook? Here's the framework for evaluating which playbook should you be following. There's this very obvious one. Go after the very obvious companies here in San Francisco that probably have some sort of proof or social value associated with them or like go out and sell in Ohio. Find people who need your solution. If you think about sort of the enterprise networking world in 2009 people thought we were crazy. Like they had no chance of getting into the largest corporations in the world, Lighthouse because Cisco and HP had them all tied up. But what we could do is we could say listen we can configure, we can deploy faster, we're simpler to use. And that was very much a LandGrab strategy. Two few people are willing to pick up the phone and willing to go down the plane and willing to get you know in front of those customers right now because they feel like it sounds way more sexy to sell the JP Morgan Chase and make me more fit. I think the biggest mistake that I see founders make in an early stage honestly is just today. Elena Berger sits down with A16Z's Joe Schmidt and Andy McCall to unpack two competing go-to-market strategies. Lighthouse versus LandGrab. Do you win a handful of high-profile customers and use their credibility to unlock a market? Or do you find customers with existing budgets, prove the math and capture as much of the market as quickly as possible? Drawing on today's AI companies and lessons from building the sales organizations at Sam Sara and Muraki, they break down how to know which game you're playing, when to switch strategies, and why sometimes the best sales advice is simply to stop strategizing and start selling. You can read Joe's article in the show notes. Welcome back to the A16Z podcast. Today we're getting into the single most expensive question an AI founder makes how you sell. Joe Schmidt just wrote a piece called Lighthouse or LandGrab which gets into the two dominant playbooks he's observed among enterprise AI startups. Joe tell us about the piece in your own words what are the Lighthouse and LandGrab sales playbooks. Yeah and this piece actually all stand back from an observation that I had actually driving up the 101 freeway. Maybe this is three for five months ago. I can't remember. And you just realized that you have the same kind of two competing companies like one's on one side of the freeway and the other's on the other side of the freeway and there's something exact same piece of software and for some reason they all have decided that the only relevant companies for this piece of software are in San Francisco and driving on the 101 freeway. And then this has gotten even more ridiculous. It's obviously every bus has been wrapped in every it's like planes are flying up above and they're now towing startups. And so I think it's all very clever but it's all targeting the same kind of sales motion. Reality is you don't always have to do that. You don't always have to sell the same companies in San Francisco. And so what I wanted to try to do is tell founders like, Hey, here's the framework for evaluating which playbook should you be following. There's this very obvious one which is like go after the very obvious companies here in San Francisco, in New York City, in a major metro that probably have some sort of proof or social value associated with them or go out and sell in Ohio, go out in selling Chicago, go out and selling St. Louis, find people who need your solution. And so that was the whole point of the piece is you don't always have to go sell these notable logos and we'll see how that plays out. But that's why. And just to get a little bit deeper, like when does it make sense for a founder to go and buy a giant billboard that you see when you're driving from SFO into the city? When does it make sense for you to kind of do a more targeted sales activity or emotion elsewhere? Yeah. And I think the way that we tried to make this make sense, of course, we did very consulting style with the two by two matrix. I did never work at a consulting firm, but I'll do my best. And so we really were thinking about, okay, what are the axes that we should be kind of mapping opportunities against? And so we decided upon the y-axis is really what we called the buyer's exposure. And it's intentionally called exposure because there's the exposure of making a mistake with the solution that you buy. There's also the exposure of the solution inside of your company. Does this product that I'm selling to my customer end up being shipped? Is it shown to their end customers, right? Which is actually an important distinction. And really just kind of the overall risk associated with buying this piece of software. So that was like kind of the y-axis and it goes from high to low. And then the x-axis is whether or not proof travels in any given market. And so if you think about the top right would be proof travels in this market and it's high buyer exposure and high buyer risk. And the bottom left would and that's a light us market, right? This to be clear. And the bottom left would be low, low, low proof traveling, but also low buyer exposure. And that would be a land grab market. And so I think those are actually quite different. And if you think about the standard markets that fit into the lighthouse model, it's regulated industries. Oftentimes there's a more constricted number of logos. If you're wrong in the industry, like if the buyer buys the wrong piece of software and it ends up doing the wrong thing, it can lead to very bad things happening for your firm, including potentially getting in trouble with the regulator, even going and doing something illegal. That's very bad. Of course. And then on the flip side, when you're looking at the more of a land grab market, there's an established budget. People have it very used to and accustomed to paying for a type of service. And you can kind of come in there and show like the end buyer, the math of, hey, my solution is better than whatever solution you're using today, whether that's a software driven solution or human driven solution. So the kind of distinction that we drew was between like proof on the top right of the of the quadrant and math on the bottom left of quadrant. And that's how we kind of thought about the framework. Yeah. And Andy, we'll get into your background in a little bit. But I think first, maybe it's good to kind of categorize some of these modern day AI startups within these two frameworks. And I know you both work with a lot of these companies. So Joe, I'm not sure if you want to call out specific examples or Andy, if you want to call out specific examples and really just kind of like talk through the sales strategies that you're seeing. Yeah. I mean, well, you're like the land grab mastermind. So maybe you want to talk about some of the stuff that you've seen? Yeah. Well, I think you framed it up really well in your article. But yeah, I think that concept of like the the lighthouse being more in industries that require regulation, a lot of social proof and so forth. And those tend to be companies that are going after like a category creation, right? It doesn't exist today. So therefore you got to go out and you got to kind of prove yourself with the big names. And obviously we have a bunch of portfolio companies out there. There's a bunch of the companies that you mentioned a couple of your article that are doing that. And then on the other side of the sort of land grab less social proof. But those tend to be especially in the AI world today. Those are companies that are maybe replacing or improving workflows that already exist. And there's existing budget. And again, we have a whole bunch of portfolios. Yeah. But he's a couple in the article that are doing that today. They're inserting themselves in saying, hey, we built a better way to go after this through AI. And I think those are the great companies going after the land grab strategy. Yeah. And it's interesting. I mean, for those that aren't familiar with Andy's background, he's he's built some of the the best sales organizations that I've ever heard of at Sempsara and Maraki. And I've always found like these these stories like really fascinating and luminating like the the Sempsara, you know, story around kind of the ELD mandate is the way I understand it kind of basically forcing the category to happen everywhere all at one point. And it's just who can go out there and do it fastest. Maybe just if you could for the audiences' edification share a little bit about what that like big why now moment was. Sure. Because we're kind of having one right now. Yeah. And how you guys just kind of went and captured it. Yeah. Yeah. I think if you're in the industry for long enough and I've got the gray hair to prove that I have been blonde. Yeah. Yeah. Bortering on gray. You tend to see these big transitions. And I'm old enough to have seen the internet come about and certainly mobile and cloud and obviously now AI in each of those causes this transition and it causes new ways to think about you go to market not hold cell changes but always tools to help improve upon them. And I think the other thing I would say I can't name too many companies that have become hugely successful without some element of timing and luck. Right. And so you talking about samsara and the company was founded back in 2015. I joined in 2017. And the idea back then was at the very beginning it was like internet connected sensors like all the value chains are going to come censored up. How do we get sensors out there and just this data give it back to business owners in digestible and usable ways. And one of the first products that started gaming traction were these telematics units and taking a step back if you think about the world of transportation, long haul trucking, right. Prior to like 2016 they had these manual logbooks. If you were driving a truck and you stopped to take a break you would write down in your logbook. I just drove for four hours. Now I'm taking a 20 minute break and then you drove for two more hours and you stopped for lunch. And if you got pulled over by a highway patrol they would ask to see your logbook and they audit and make sure you weren't driving too long. It was a safety regulation. And in the US around about 2016 they implemented this ELD mandate right and sent it to electronic logging devices. And the idea there was hey we can use technology to actually track when the vehicle is moving and when it isn't and are they taking enough breaks and so forth right. Take the human and data element out of it the human element rather. And so over a two year period that was basically implemented between 2016 and 2019 with various phases of sort of compliance. But what it did is it provided the huge tailwind for anybody making these electronic logging devices. And we just happened to be one of the newer companies doing it. And there were some very very established players right. AT&T had a solution for Ryzen had a solution. There were a number of companies that were in sort of the you know hundreds of millions half a billion in revenue already doing this. And Ryzen tide floats all boats it helped everybody. But if you were a new entrance into the market like we were at Sansara it really helped because basically the entire industry all the sudden had to find budget to go out and buy these things. And a certain percentage of them clearly would say let's check out what's new out there. Yeah. How many new entrants into the field. And so really helped kind of give us a boost. How did you navigate like the social proof side of that? Because I think the casual observer might think about that and say okay wow this is regulated. We can't through this up. So you probably have to go win. I don't know what the largest long haul trapeze company is. I'm trying to make it the ones I see on the freeway, but in any event, you probably have to go win that one, but it doesn't sound like that's what you did for what I understand, that's not what you had to do. So how do you navigate that social proof all of that? - Yeah, well, I think, you know, I would, and maybe I'm doing a little bit disservice to the amount of strategy that went into this, but there wasn't a lot of strategy that went into, like, do we chase lighthouse accounts or do we go after land? - We're going to pass. - We kind of listen to our customers, right? And it doesn't take too many cold calls into the largest trucking and transportation firms when you're, you know, 18 month old company that they've never heard of. Here, we're not buying you, click to figure out, hey, who can we sell to? And, you know, in 2017, 2018, we had minimal features. We were just looking for, do we have something that somebody wants to buy? And so for us, at that point in time, the mid market was the place to go. For a couple of reasons. Number one, it didn't require as much social proof, right? It was more about, hey, are you satisfying my need for telematics? Do you fit the requirement? And then, you know, the other reason was, we could get really fast feedback product, right? 'Cause the sales cycles were short. We could get it implemented quickly. They would deploy quickly, right? The bigger the account, the longer these deployments, the longer the feedback loops. And so it really helped us with the sort of product innovation side as well, just to get as many deals out there as many wins as we could. Yeah, and I think this is actually really important, though, like, as like, you know, really sage founders evaluate this moment in time, like, what do we, we don't exactly have like, you know, the mandate from the, you know, US government saying you have to adopt AI, but like, you know, CEOs everywhere are saying, you do have to adopt AI company. There are AI boards at every enterprise right now saying, like, here's what we need to buy, and we need to do it by expere at a time. And that surely will go away, but there is this moment of like, crazy, you know, kinetic energy inside of the companies. And so I think that like, what he just said, actually what Andy just said is, is actually a good, a good bill other of whether or not you're in a land grab versus a lighthouse market, are people willing to actually buy from you as part of the land grab, you know, math here, is like, are they willing to get on the phone with you? Are they willing to buy your product? Are you going through POCs and are you figuring out like how to get someone to use it? You know, and so if you can't get that done, then it's all about going and like doing like, very deep, you know, forward deployed lighthouse, like, you know, arrangements and figuring out how to then get to your next customers. But I just think like too few people are willing to pick up the phone and willing to go down the plane and willing to get, you know, in front of those customers right now because they feel like, oh, this is like this new category moment, I have to go, I have to go to JPMorgan Chase to this home ideal. - Yeah. And you said a really good thing there. It's, you know, do they have existing budget? Do they have, you know, is it a replacement product? Because it is, then you're probably going to lean more towards a land grab. - Yeah. - If this is a brand new product and there's so many of those today, right? We talk to founders every day, companies are being born with brand new products and they're going after brand new markets. If you have to do a lot of education to your market, if they don't have existing budget, if you're going to have to take them to this educational journey before they can go out and justify the purchase internally, that's probably more of a lighthouse strategy. - Yeah. - You're taking them on this educational journey and it's a lot more missionary work than it is. Hey, take that money that you're spending with vendor A and move it over to us. - Yeah. - So maybe it's worth getting specific about some of these companies. I know in the piece you talk about, Hevia and Harvey as classic lighthouse examples and then Stutt and Deccogon as land grab. So maybe do you guys want to talk about some of those playbooks that you've seen or maybe give other examples? - Sure. Yeah, sure. I mean, I can go and you jump in. So for example, I highlight Stewart in the article as like the prototypical example of a land grab company that we're seeing in this new age. And so Stewart, this amazing business founded by two incredible entrepreneurs, Tark and Ben. And what they are going after is the accounts receivable market. And for listeners who maybe have never thought about like AR accounts receivable, basically, this is when someone owes you money in enterprise context and you have to go collect the money from them. This is not glamorous. But however, there has been a mechanism to do this historically, right? There are collections teams and there's big pieces of software like, I won't say their name because the compliance will probably bleep them out anyway. So there are big companies that do lots of error that sell on this market. But it's been very manual, right? These human teams have to interact with this piece of software and they have to go out there and sell, or they have to go collect. And so what Stewart said was, hey, AI is actually quite good at, you know, basically having conversations with people. It's very good at looking at information internally and basically doing this process end to end. And so we could reimagine this historic way of doing collections and instead of having humans do it, we can have humans plus AI do this and do it even more effectively. And that, they then saw that open up was like the rest of kind of like, you know, order to cash and basically entire accounts receivable suite. And so what they basically went out and showed all of their early sage buyers was in doing this, we have the math to prove it. We will be more effective than your current solution and your current human teams at collecting. And this will do xyz4, you know, I'm proving we're in capital by a tremendous amount. It'll save you money, it'll actually make you more money. So they were able to go out to the mid market and just basically show the math and be like, would you like to, you know, have this solution, yes or no? So that's a really good example of a land grab market. And those entrepreneurs are just like unbelievable sellers. They hit the pavement better than anyone, just as good as anyone as anyone I've ever seen. And they're doing a great job. You know, another example on the lighthouse side would be, you know, we highlight Harvey in our article. And they just did a fantastic job of winning the right law firms for this very new, very, you know, theoretically high risk initiative where you're augmenting your human workforce with, you know, a capabilities and really automating what, you know, you know, junior lawyers would be doing on a day to day basis. And so when they won the first kind of, you know, few critical lighthouse accounts inside of their market, like that proved traveled like big time. And then, you know, the buyers that had like this tremendous amount of exposure realized, hey, it's actually safe for me to buy this solution. So those are the two kind of counter-example, or you know, two examples in this market. I don't know if there's anything you would highlight from other companies you're working with. I mean, thank you for seeing. - Yeah, I mean, those are two great examples. I'm doing a decent amount of work with a company who invested in it called Pylon. They're basically the AI native customer support. And they're a great example of land grab. They're doing a fantastic job right now. I'm just going out and saying, hey, we've got a better way of doing this. And, you know, they have, you know, they've been climbing up the ACV ladder, but, you know, they started it pretty modest ACVs. And they've been working their way up just by going out and replacing. And they have a fantastic go-to-market team that's just out executing. - This ACV question is actually kind of an interesting one. And I'd be curious how you thought about it at Marock here at SamSara. You know, there's so much demand out there. And there's so many different ways of like kind of building you go to market engine. Like how much did you actually even think about what you were landing at? What these, like, you know, it maybe go back to when you're at like, I don't know, 10 or 50 of ARR, at one of these businesses. Were you optimizing for that? Or was it just like, let's basically figure out how to get enough reps in and-- - Yeah, it's a good question. Now, the answer is you think about it a lot and then you try and not think about it at all. And what I mean by that is you want to make sure that the ACV that you're going after, it has to, it has to top the hurdle, right? In other words, you look at your unit economics and is it healthy or not? You don't want to be taking deals that are, you know, negative to your unit economics. But if it passes the threshold, then the answer is, you don't think about it, you just go. You can, as many of those as you can. So if you can build a go to market engine just theoretically, they could live off of 15 KACV deals. - Yeah. - Fantastic. Like, don't take eight KACV deals, but go get as many 15 KACV deals as you can. And you want to just build a repeatable engine and pour fuel on the fire and get as many of those as you can. And then what happens over time is you start inching up, right? - And bigger and bigger companies, like what you're doing, and you start stacking up, you know, the winds and going up the ACV ladder. - And can I, one follow up on that because this is interesting. And I'm so much enjoying getting you talking about this stuff, but like Maraki you guys had, and maybe tell the audience what Maraki does. But you know, basically access points, right, for internet connectivity. And you guys had this really clever program where you would kind of give an access point away. - Yep. - Free is the way I understood it on most. But, and then of course, like you do that, that impacts gross margin. But also, you then have a hardware element as a part of your gross margin calculus. Like, we don't have as many companies out there that are doing, you know, maybe AI applications with a hardware element, but there is an inference element, which impacts gross margins. And so, I don't know, how did you think about, like these kind of trade-offs in the early days in Maraki, and of course, you had the same thing at Sintara with hardware too. - Yeah, so just for the audience's education, so Maraki was basically a cloud networking company at this point, 20 years ago. - So, still is a very healthy business within Cisco. We were required by Cisco back in 2012. But the company was actually founded back in 2006. The co-founders were working on a research project as PhD students in MIT and started the business. And what's interesting about that, the research project was called RoofNet. The technology they built was basically a large scale, like Mesh Wi-Fi, and they'd installed on the roofs in Cambridge, and the idea was you could, you know, outfit these municipalities and parks and public areas with Wi-Fi. It was fantastic technology. Within the first couple of years, they figured out it wasn't a great business model. There wasn't a lot of revenue in municipal Wi-Fi. And so they made this pivot into enterprise. And the reason I say that is, you know, if you think about sort of the enterprise networking world in 2009, 2010, like people thought we were crazy. Like, why would you be trying to build an enterprise networking company in 2009? You don't you know that? Maraki was one 10 years ago by Cisco and HP. But the reality was, and again, back to sort of the time, timing, that was right when Cloud was coming back. And the big innovation around Marocky was the product and engineering folks, fantastic team there figured out how to configure and manage this never-ending equipment through the Cloud, which sounds like, yeah, total of course. Back then it was a little bit innovative. Anyway, our problem, and that was very much a land grab strategy, right? We had no chance of getting into the largest corporations in the world, the Lighthouse, because Cisco and HP had them all tied up. But what we could do is we could say, listen, we can configure, we can deploy faster, we're simpler to use. Well, who cares about that? The mid market, right? Well, they don't have substantial IT teams that have been trained in command-line code and this kind of stuff. And so our kind of firm belief at that point in time was, well, what's the best way to get them to understand that our networking equipment is simpler to use than their Cisco that they're about to buy? And the answer is get them to try it. Yeah. So what we do is we'd run these webinars and we'd say, hey, you attend the webinar, we'll send you a free access point. You plug it in, try it out. And the idea was if they try it, the light bulb goes off and I say, wow, this is just so much easier than what I'm using. I don't know why I use that. And it was very, very successful for a long period of time. And even as the company matured, we were very, very liberal in our trial and evil because you just fundamentally want customers to experience the technology. And realize that it's better than the alternative. And do you think there's an element of, that people can learn from that right now? It's hard though because there is an aspect of configurability with a lot of the new AI stuff. If you just give somebody this Ferrari, they might not exactly how to even turn it on. And so I don't know how you even think about the delivery mechanism for some of these trial periods, POCs with some of the companies you're working with right now. Yeah. I think it's become more challenging, right? In the world of AI because number one, things are moving so fast, like things are changing daily. And if you think about like a proof of concept or a trial, the whole idea if you're on the sales side is, I want the customer to experience this, I want to prove that it works for them. But I want to do it in a period of time that doesn't go on forever, right? And so what you have to stay away from and I think one of the world's dangers today is these things turn into like science projects. I'm going to deploy this, well, can I do this? Can you show me this? And of course things are advancing every day. So the answer is probably yes I could. But then you run the risk of these trials or proof of concept going on forever. Yeah. And so it just takes a lot of discipline, I think, in today's day and age to really box that in and say, listen, here's what our solution does. And we're going to define it this way and we're both going to agree that if it has done this after 45 days, it's success and you're going to move forward with the purchase. And so there is a lot of that today. And did you, well, I guess would you recommend having auto converts on these as much as you can? Or other learnings and lessons from this type of 30, 45 day. And then we even talk about the right amount of time that you're giving people with the product. I think the timing depends a little bit on the complexity of your product. If it's going to take two weeks to set up, then you can't make it a two week trial type thing. But I think the two biggest things are make sure you have an end date. It's a 30 day trial, it's 45 day trial, it's a 60 day trial period, end of story. And then the second one is you have to define the success criteria up front. Here is what we are proving that we can do for you. And in some of these companies, you can't do a proof of concept because maybe it is regulatory, maybe it's too much risk in there and they're not going to let you do it. But where you can, I think you want to make sure you have both an end date and you have the success criteria clearly defined. Yeah, I think this is so tricky right now where somebody, you have to basically define the scope that you're going after and this is such a criteria. But oftentimes if you're like automating something that has never been automated before, there's like significant amount of configuration and that cost money. And then your product could work, but it might be deployed improperly and or the results take longer than 30 or 45 days. And so how do you actually kind of, there's like a difference of, hey, the product is working and you just, and basically you need to work with the customer then optimize whatever they're doing with the product. Yeah. Right, like imagine you're, I mean, I don't always go back to sales 'cause it's easy to think about sales, but like imagine your, you know, sales tool, like the product needs to work and then you need to use it and target the right customers for whatever you're selling. And they're kind of like two different parts of the equation. And so if all of a sudden you're taking risk on for whether or not your product works and whether or not it's being used correctly, very tricky. And so I think this is actually a really important topic for founders and for early stage revenue leaders today to figure out how you're educating your customer on, like here is the thing we are signing up for. Yeah. We are not signing up for, you know, you know, maybe you are, maybe you aren't, but you know, whether or not your employees are using our tool the right way. Who have you seen that does the best of evangelizing and kind of like taking people through the onboarding process? You know, I think who would I put in that bucket? I mean, I think like Decagon is an amazing job at this. Like I think they go in, they basically evangelize that they're doing customer support better than anyone else. And then they're very good about saying, here are the benchmarks that we are signing up to hit and then they hit them, you know, in their time period, right? And so I think this is, you know, I think some people might trivialize, you know, this, it's very hard to do customer support effectively. Like this is a high risk exposed market, you know, where like you don't want to screw this up. And so I think they've done a really good job of evangelizing. I think the guys it's due, but back to like the example I just, I just talked about. And then another example would be excuse me, a company that I'm on the board of called further AI. And they were, they saw them to be an insurance space. And they're kind of, you know, basically evangelizing the idea of bringing AI to insurance. You know, people have been using AI and insurance. Like this is not, you know, generally a first adopter of technology, but a lot of their customers are some of the biggest insurance companies in the world. And it's because they're very comfortable with like, okay, hey, here's like an AI solution that's built in a government, you know, secure, you know, governance first, you know, form and fashion. And then they work with with forward employee teams, you know, their customers to get up and running. So those are a couple of examples. I don't know if you have any. And that's that that last one's a good example of like a lighthouse trash. Very much. Very much. They've gone after the bigger insurance companies. And then you get that social proof and, you know, on down the long tail of insurance. And I think like sometimes people think that you have to be from a given market to do a lighthouse strategy. And maybe there's someone sitting in a hoech and they're like, oh, like if only like I worked at this company, I could go do this. And it's like, no, the reality is like go build a relationship. Yeah. Yeah, I see you laughing. Because I know you're like, yeah, go build a relationship with your customer, go find someone and show them like, here's, you know, I have an earned secret. This earned secret is that AI can help your business or technology can help your business in this way. Yeah. And you know, work with us on that. I'll also say that, you know, every, every small company wants to go to a big company. I don't know too many very large successful companies that at some point in time, haven't deployed both strategy. You might start off with land grab, but then you mature and you have a lighthouse strategy or you start a lighthouse and then you get big enough that you can go broad, you know, into land grab. So I think for founders, when I get this question early on, do what makes the most sense for your business right now? Does that mean go out and talk to customers and find out where the earliest and easiest sales are and pursue that strategy. It doesn't mean you're completely, you know, punting on the other one. It just means come back to it. And in both of the last companies that I work for, both Maraki and Sam Sara, we started with land grab, but as soon as we matured and started getting up into enterprise, then what do you do? Well, you verticalize and all of a sudden like great. Who are the top five, you know, Transfaces companies? Who are the top five warehousing companies? Who are the top five, you know, public sector? And then you want to go take those down. And so you can morph into a land grab strategy. You just want to do what's most efficient and most effective for the stage of the company you're at. Can you talk a little bit about like one of those like key markets that you unlocked with like you went from land grab early to, you know, lighthouse in a market? Like what is you, how did you set up that team? Or like was it just you were the founders that was going into this new market? And then like, you know, maybe a little bit about some of those deals that you close. I'm just curious how this played out with the sequencing. Well, I think I, you know, it both Maraki and Sam Sara, the sort of earliest example of light house was when we verticalized. And in both those instances, it was basically in the light public sector at Maraki was going after like school districts. So interesting. Because that was sort of low hanging fruit. And, you know, if you're, if you, anybody, anybody's ever sold the school districts like they all talked to each other, they all know each other. You want to find the biggest school districts in each state. And if you can take that down, every school district underneath them, so what did that one buy? Great. All the sudden the social proof is there. Now why, why use a light house strategy in say school districts or in Sam Sara's case when we went into public sector when you start selling to cities and counties and states? You know, why shift? Because the sales motion is fundamentally different. Like the sales cycles are different. The way you sell, the decision makers are different. The way they procure is different. And so asking the same sales team to shift from, you know, selling to a mid market customer and enterprise customer over to selling to a city or a county or a school district, it's just, it's just different. And so, you know, that's a point where you might want to shift and say, okay, great, you know, once we're verticalized, we want to shift to a light house strategy. What would you say there, the differences are between great sellers in lighthouse models versus great sellers and lamp-grab models. Are there any differences like from what you saw? Maybe when you're opening new markets, is there a profile that was most effective? It's always difficult. the generalize, I think in a true lighthouse strategy, and when I envision lighthouse, it's like, hey, we're going to go after whatever the financial sector. Here are the top 15 accounts in finance, and here are their logos. How many can we get into this quarter, next quarter, next quarter, right? That's a lighthouse strategy. Generally, you want more seasoned enterprise sellers that know how to work within those accounts. They understand the sales cycles. They understand the the procurement cycles. In more of a land grab strategy where you're just saying, hey, we have the best technology. We're replacing this workflow or replacing this product. You just want very aggressive, like higher for attitude and aptitude. You can go earlier in career. You just want those people to get out there and hit as many of those customers as you can, because at that point, it's like you're hitting a big market. You just want to stack wins as fast as you can. My unsolicited advice to any early-in-career or potential seller right now is there's never been a better time to work at some of these companies in our portfolio. That's absolutely true. It's a super fun time to be in the market. I wanted to ask about maybe a third kind of selling or product diffusion that we haven't talked about, which is the developer bottoms up, more grassroots adoption. Is that something that you guys are seeing? Is the idea of the seller sort of becoming, I wouldn't say obsolete, but for a particular kind of product, just less relevant now, like a developer saying to their CTO or their CIO or whoever, this is great. Let's just get this. And there's less of a sales motion needed. I guess definitely not. There's a bunch of PLG that's still happening today. I think people are buying things in a consumer fashion all the time. And I think that there's new buyer behaviors being kind of discovered. Of course, we are big investors in cursor. Everyone saw that played out. There's a bunch of other examples of this. However, if I take a giant step back and talk about where we are in this current cycle, I wrote this long piece called Trading Margin for Moat about a year, year and a half ago, whatever it was, talking about the cycle. And if you think about why the last 12 years before 2024 or 10 or 15 years before 2024, you saw so much PLG is just where we were in the software innovation cycle. A lot of the big cloud platform businesses, if you think about CRM, HR, ITSM, security, a lot of those big platform businesses were founded in the call it 2000 to 2008, 2010 period. And those businesses went out and solved the big platform opportunities. And so then the only way to really break in at the enterprise, and we're talking more about enterprise enterprise sales or market enterprise sales, was to build some sort of wedge product, wedge in with this product, and say, "Hey, I'm going to solve this part of your suite for you and then try to expand over time." And so this land and next land model became super, obviously super invogue. But it was really based on where we were in this adoption cycle. And there were other people, of course, that said, "Hey, I want to go build a new CRM. I want to go build a new HR. I want to go build a new ITSM." But the reality was going from on prem to cloud was a big enough shift for people to switch to something new. But going from cloud to cloud for CRM, I don't care if the button is green or blue. I don't care if there's one little feature difference. I'm not going to switch. And so you compare that cycle where we were looking at everything from the last 15 years, which was all PLG and all the time. This is incredible. To where we are now, there's this crazy kinetic energy inside of companies where they're saying, "Hey, it could be even something as fundamental as CRM." It could be as fundamental as HR or ITSM. This is not a skeomorphic one-to-one replacement green to blue. We're now thinking about humans are going to be doing something completely different. Way more high value. We're going to do way less of the same mundane work. Instead, agents are going to be doing that. That's the opportunity right now. Instead of talking about PLG and all these other sales models, there's a moment right now to go sell big software again and to go sell platforms. It's because of this moment. I think people need to be studying the 15 years or go models of how people build this and the ecosystems around it to go and have success. I think that's right. I will say I think the consistent trend as long as I've been doing this is that every year and with every technology transition, buyers become more and more educated. The buyer today just fundamentally has a better idea of what they want than they did five years ago, 10 years ago, 15 years ago. That does lend itself more towards. If you can hit that buyer when they're in their decision mode, you're going to have a better chance. It doesn't have to necessarily be PLG, but it can be more self-serve. It should be an easier sell than 10, 15, 20 years ago where you had to take them on this entire education journey. Why do you need this? How it works? Here's how you're going to write. There's just so much more educated now on what they want to buy that your job just convinced them that your company is the right solution for that. I guess the lighthouse definition just gets pushed ever-hour. It's kind of like just have to keep on conquering new territory. I assume a company just can't stay a lighthouse forever and you've been alluded to this Andy. What is the average amount of time that a company can just chew off those bigger logos? What is that transition moment like, I guess? See, you could if you were a company that was dedicated or committed to a multi-product strategy, you could just keep coming out with new products and keep going after more verticals. You could theoretically do that. I think there's probably some example we could come up with if companies did that. But in general, if you start with a lighthouse strategy, you've built a social proof, you've gotten these big names, then what you want to do is you want to run the category underneath it. If I've gotten the top five financial companies in the world, I want to run down the list after that. And so that fundamentally becomes a little bit different of a sales motion. You're spending less time with the huge organization, the big logo selling and you're spending more time. Less time in the social proof and more time on, hey, here's a reference if you need it. Otherwise, this is why my products best buy it. Yeah. And to Andy's point, there are certain companies that actually do just stay light-os the entire time. And that would be like, the best example might be like applied into tuition in our portfolio. There is a very set number of people who are buying that kind of autonomous software and a certain number of car manufacturers and so on and so forth in the world. Not to say that that's the only people that get sell to you, but of course, these are Australian markets. And so you then have to treat every one of these with immense care because they are huge ACP opportunities. And they've obviously, I think they're arguably the best in the world doing that. So yeah, that's a good example of that. Why would a founder sort of misjudge what game they're playing or how have you seen founders kind of misjudge whether they're doing lighthouse or laying ground? I mean, it sounds way more sexy to sell the JP Morgan Chase than to, you know, make me more than this. I think the biggest mistake that I see founders make at an early stage, honestly, is just spending too much time trying to figure it out. It's like too much time on the strategy. The strategy is important, but you should spend like 1% of your time on the strategy, pick it and then spend 99% of your time to execute. So rather than sit back and say, well, should we do lighthouse or should we do land grab, get out, talk to your customers, figure out which ones are willing to buy your product, the features and the services that it delivers today, and then chase that path. There's no bonus points for hard-run revenue. You don't get extra multipliers on your revenue if you get the big logo or something. Go after the customers you can. And then constantly be improving your product and then you can always reassess your strategy. You have for the first year, if you've got all your revenue milestones, you can look at and say, well, could we be more effective doing this? Maybe. Just don't spend too much time in analysis paralysis mode. Yeah, totally agree with that. I totally agree with that. Joe, you had some fun questions for Andy. I was a lighting round. Yeah, I think round. I'll see what other ones I can come up on the top of my head. The first one is maybe your favorite place, your weirdest place you ever close the deal. We've had some customers that have taken us to some funny places. I've closed deals on fishing trips. I've closed deals out at shooting ranges and I've closed deals at ballpark. I think those are all unique. Any one that wasn't a meeting really. Air perch, joeys? Probably. Probably over the years. Certainly it seems all right. We're selling to logistics and transportation companies, a lot of truck yards and that kind of stuff. Sanitation sites. When you're doing land grab motions, I think this is the permeating theme is just like people need to go and sell. Maybe Andy, if you go back and tell yourself one thing when you're building out these teams or like early in your career, what would you tell yourself? Early maker. Well, I mean, this is the advice I give a lot of early career folks. It was a mistake I made early on. The only thing you should really be focused on when you're starting your sales career is find the best company you can possibly find a work. for. I made this mistake early in my career. I was chasing, you know, where can I make the most commission? Where can I make the most money? What's the hottest technology? What, where can I go get the biggest title? At the end of the day, none of that matters. You want to find as you want to find the, the, the great company that's going to grow. And if you do that, then it's like a career elevator, right? Like you will grow with the company. Yeah. Totally. You can't, you can't let your ego get in the way. And I want a director title of this big of a base salary. I think I can get this much of a commission rate. Just go find the best company you can work for. Yeah. Totally agree. What's one role you think companies should hire for earlier than they normally do in the sales work? I mean, it really depends on the company and how, and you're specifically like, how comfortable the founders are. Like if you're a founder, it's very comfortable sales. And, you know, you can wait longer to hire sales leader and that kind of stuff. So it's a little bit of a generalized question. But I would say sales operations is probably one that I see companies waiting a little too long on. And I am not a proponent. I don't think you need to, to, you know, stand up a gigantic revenue operations organization. It can be literally like one person. But you need somebody that every day is thinking through territory alignment, you know, name lists, doing, you know, commission skirmishes, setting a sales constitution. Like all that kind of stuff becomes really, really, really important because when you get into like, you know, scale mode, you want all that stuff like largely figured out. You don't want to become speed bumps. Otherwise, yeah, totally. So you want somebody thinking about that. And it's, it's generally not going to be your sales leader. Yeah. Because they're thinking about how do I hire the next person? How do I bring the next deal on? So I'd say, yeah, maybe your sales operations sale revenue operations. Yeah. Maybe, you know, one sentence or two sentences on, you know, how you think about how, what percentage of sales teams at the early stage companies you're at should be hitting quota. And like kind of like, you know, sales comp thinking 100%. Oh, yeah. I never said. What I think there's, you have some interesting comments on like basically, you know, trying to keep them low, get everyone kind of rabid and, and, and, I mean, listen, I think in the early days, like sales teams run off a momentum, right? You want to hire winners and give them a chance to win. So yes, you want to, you know, be able to bring people in, you want to set reasonable goals. It's got to be profitable. Well, for the company, you're an after-omics have to work like you can't, you know, you can't change the math. But at the end of the day, like if you're an early stage company and you've got a great product, you want to hire the best possible sales talent to get that product solution out to market. And the way you do that, the way you attract those people is give them a chance to hit quota. Totally. So yeah, I think, you know, some of these companies today where, you know, 40, 50% of the teams hitting quota, I think they're probably doing themselves a disservice. Either their quotas are too high or, you know, they're hiring profiles off. But yeah, I think, especially in the early stages when, you know, cost of sales isn't as important. When you're a public company and, you know, you've, you've gone out and you've conquered your market, nobody looks back and says, "You know, gosh, you know, six years ago your cost of sales was really terrible." Yeah. Totally. Nobody cares about that. What they care about is, you know, did you get on a path where you could, you know, be successful? Well, I think something that's cool about this conversation is just how, like, timeless a lot of the wisdom is. It just seems, it seems like, you know, these frameworks and ways of thinking about the industry are pretty consistent just throughout the different software cycles and, you know, eras of that word that we've seen. So anyway, Joe and he, thank you so much for joining us. This was great and excited to have you guys back on. Yeah. Yeah. God, the goat. Thanks for having us. Fantastic. Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X at A16Z and subscribe to our substack at a16z.substack.com. Thanks again for listening, and I'll see you in the next episode. As a reminder, the content here is for informational purposes only. Should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the company's discussed in this podcast. For more details, including a link to our investments, please see A16Z.com/disclosures.

Podcast Summary

Key Points:

  1. The Lighthouse and LandGrab sales playbooks offer two contrasting go-to-market strategies for enterprise startups: pursuing high-profile clients for credibility versus targeting existing budgets with proven efficiency.
  2. A two-by-two matrix defines these approaches
  3. Lighthouse markets suit regulated industries with limited logos, where mistakes are costly and social proof is essential; land grab markets have established budgets and favor showing clear math over reputation.
  4. Samsara's success with the ELD mandate illustrates a land grab
  5. Modern examples include Stewart (land grab) in accounts receivable, using AI to replace manual processes and prove cost savings, and Harvey (lighthouse) in legal tech, winning prestigious law firms to validate a risky, new category.
  6. Founders often over-prioritize selling to notable San Francisco companies, neglecting opportunities in less glamorous regions; the key is to identify whether buyers are willing to engage and buy quickly, which signals a land grab.

Summary:

The podcast episode, featuring A16Z's Joe Schmidt and Andy McCall, explores two dominant go-to-market strategies for enterprise AI startups: the Lighthouse and LandGrab playbooks. Joe introduces a framework based on a two-by-two matrix, with buyer exposure (risk) on one axis and the transferability of proof on the other. High-risk markets where proof travels, such as regulated industries, require a lighthouse approach—winning a few prestigious customers to build credibility.

Conversely, low-risk markets with existing budgets and less need for social proof favor a land grab, where startups rapidly capture market share by demonstrating better math than incumbents. Andy shares insights from Samsara, highlighting the ELD mandate as a land grab opportunity; instead of chasing large accounts, they targeted mid-market customers for quick feedback and deployment. The discussion contrasts examples like Stewart, an AI-powered accounts receivable company that succeeded by proving immediate cost savings, with Harvey, a legal tech firm that won top law firms to validate a risky new category.

A key takeaway is that founders often mistakenly focus on high-profile San Francisco companies, ignoring practical opportunities elsewhere. The hosts emphasize that a land grab occurs when buyers are willing to engage and purchase quickly, while a lighthouse is necessary for educational, high-stakes sales. Ultimately, they advise founders to assess their market's dynamics and, sometimes, stop strategizing and start selling.

FAQs

Lighthouse involves targeting high-profile, high-risk customers where proof and credibility are crucial, while LandGrab focuses on finding customers with existing budgets and proving value through math and efficiency to capture market share quickly.

Use a matrix with buyer exposure on one axis and whether proof travels in the market on the other. High exposure and high proof indicate a Lighthouse market, while low exposure and low proof suggest a LandGrab market.

Regulated industries with a limited number of logos, where buying the wrong solution can lead to severe consequences, such as legal trouble. Winning a few key accounts provides social proof that unlocks the market.

Markets with established budgets where you can replace or improve existing workflows. For instance, an AI company showing better math than current solutions, like Stewart in accounts receivable, can quickly win mid-market customers.

Founders often find it more exciting to sell to notable companies like JPMorgan Chase, but this can be a mistake. In a LandGrab market, they should focus on willing buyers and fast wins instead of chasing high-profile logos.

Samsara targeted mid-market customers who needed electronic logging devices due to the mandate. This allowed quick sales, fast product feedback, and avoided the need for extensive social proof, helping them grow rapidly.

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