The Exchanges

Q Are consumer expectations high when you're selling into the biggest enterprises like you do when they're traditionally working off pretty shitty legacy enterprise software in their professional lives?

A Right, so this is the first time I'm seeing what they're doing in their personal lives carry over to their professional lives. In their personal life, they're teaching their kids with ChatGPT, Anthropic, and now they're coming in and they're Expectation is totally different. Like, if you look at the intent logs of how people are using rocks, they expect software to not just do some work. In some cases, they wanted to do all the work. Humans across the board, including my mom in India, everybody has been obviously sold on the promise of AI and LLMs. When they come into the workforce, they actually want the software to do as much work as humanly possible. Specific word is humanly. The software should do anything that a human can at scale. So that they could do more, and more in my domain is support more customers.

AI assessment note: “this is the first time I'm seeing what they're doing in their personal lives carry over”

Q I am coming into one of your working sessions. How do we spend that hour and a half?

A Try to overshare context. Kind of Silicon Valley ethos is don't hide anything. Just share what you're working on because if somebody beats you in your own game, that's on you. So like, I just share everything. Like, hey, here's the product strategy. Here's where we are. Here are customer case studies. That's probably about the first 30 minutes. So I, when I'm doing it, I'm trying to see the questions that they're asking. They might ask about pricing or case studies, what worked, what didn't work. That could take a lot of time, like 30, 45 minutes, and I do that for every candidate because that's, I'm trying to understand kind of how they would go about it because that's where we want them to abstract it, build a list from there. Their brain should be running. After that, we get into specific scenarios. Okay, now that we want to do a scenario, let's say we're working a strategic deal called a large company in Europe. If I gave it to you, how would you run this deal? And then I flip, then I ask them questions, right? Like, what if this happened? What if that happened? So, the first 30 to 45 minutes is me sharing context and them asking. The next 30 minutes is, like, them walking through a deal. The last 15 minutes is, if you feel it, you're talking about next steps. If not, you wrap early.

AI assessment note: “The first 30 to 45 minutes is me sharing context... The next 30 minutes is”

Q is everything. So, like, totally get you there. You mentioned that, like, hey, Consideration, uh, if it's free, it's like a website. I see a lot of people today doing design partners and heavy collaboration with early partners instead of the PLG let everyone test and then we iterate from there. How do you feel about the free design partners and build with them versus open and iterate and learn?

A We don't do any free design partners. Like we really focus on doing paid customers with like a pilot clause. If the customer is not separating with some sort of cash, there's just not enough skin in the game for them to put in the time to work with you for a few weeks, for a few months, for a few quarters to build a product. So I'm very anti unpaid design partners because the cost for them to just say yes is a lot lower than it is for you to keep kind of making them happy. So my view is kind of first have paid design partners who are on an alpha or a beta, like we're on an open beta now. In parallel, the product has to be open, especially if you're competing with incumbents. Incumbent enterprise software is gated by demos and implementation steps. This is three to six to nine month time to value. If you are a product shipping machine, you have to have it out. Even if you're extremely embarrassed, like we are at Rocks, like, oh man, this, this is not perfect by any means, but you got to have it out there because at the very least, it reduces friction from your sales motion. At the core is this undeniable confidence that you can ship your way out of holes and also ship your way to the promised land because you're not hiding anything. So, so my view is paid pilots and paid design partners, and then as the product gets better, keep it open. Don't put gates.

AI assessment note: “We don't do any free design partners. Like we really focus on doing paid customers”

Q I want to start with a little bit of kind of foundation story. New Relic from zero to a hundred million. I want to start on actually the PLG motion that you developed there. There's so many founders that listen that are building their PLG motions as we speak. What did you do specifically well that you think was so instrumental to the growth from zero to a hundred million?

A The central word is like focus. So we centralized the entire go-to-market engine on a captive audience of developers for whom New Relic was still the default brand. New Relic kind of lost its aura, but there was this audience of about a 100,000 plus developers who joined the workforce, 2008, seven, 14. For them, New Relic was still the hot brand. So we basically shut everything down, reallocated investments to really go after them and earn the right for them to use the product again. And that's what the whole machine was built on. Divest everything else, invest where we are default. So we came in, in a position where the company had Reduce their investment or shut down the PLG motion. So there was this kind of latent demand that we just had to unlock. So we just went back out to the developer community and say, Hey, we have this unlimited free offering. You get all of what you need in a pretty kind of cost effective manner. And then that just was like drilling into an all reserve.

AI assessment note: “we have this unlimited free offering. You get all of what you need”

Q Like we call Manav beforehand and ask tons of questions. I totally get you. Do you think we have a generation of salespeople who are not ready for the challenging nature of sales that is to come?

A Yes. And it implies to most functions in venture, venture, founders, builders, we had it relatively easy the past four to five years. And I don't want to be morbid, but things are hard. Winning is hard. It's hard, hard work. And if you look at sales specifically, when everybody's spending and everybody's kind of buying, it became pretty easy. You're kind of becoming order, order takers, or as they say, like shooting fish in a barrel. But When you're selling something new or selling something large, there's no easy way around deeply understanding the customer's pain and how to actually solve it. I'm seeing that constantly, like honestly, candidly, like we've done really well the last year, but it's taken me maybe two to three months longer to find those outlier sales reps is because it's just, it was pretty easy.

AI assessment note: “Yes. And it implies to most functions in venture”

Q is everything. So, like, totally get you there. You mentioned that, like, hey, Consideration, uh, if it's free, it's like a website. I see a lot of people today doing design partners and heavy collaboration with early partners instead of the PLG let everyone test and then we iterate from there. How do you feel about the free design partners and build with them versus open and iterate and learn?

A We don't do any free design partners. Like we really focus on doing paid customers with like a pilot clause. If the customer is not separating with some sort of cash, there's just not enough skin in the game for them to put in the time to work with you for a few weeks, for a few months, for a few quarters to build a product. So I'm very anti unpaid design partners because the cost for them to just say yes is a lot lower than it is for you to keep kind of making them happy. So my view is kind of first have paid design partners who are on an alpha or a beta, like we're on an open beta now. In parallel, the product has to be open, especially if you're competing with incumbents. Incumbent enterprise software is gated by demos and implementation steps. This is three to six to nine month time to value. If you are a product shipping machine, you have to have it out. Even if you're extremely embarrassed, like we are at Rocks, like, oh man, this, this is not perfect by any means, but you got to have it out there because at the very least, it reduces friction from your sales motion. At the core is this undeniable confidence that you can ship your way out of holes and also ship your way to the promised land because you're not hiding anything. So, so my view is paid pilots and paid design partners, and then as the product gets better, keep it open. Don't put gates.

AI assessment note: “We don't do any free design partners. Like we really focus on doing paid customers”

Q Don't worry, I send Twitter DMs, as you know, it's fine. In a world where you have this infinite supply of outbound emails because you create it, and you're able to do so much more, does outbound become less effective when supply becomes infinite?

A Yes and yes. So supply is infinite. Does, yes, it becomes less effective. What our view is, how do we make the communication authentic? So very basic thing, the email needs to come from your email. Second, the email that comes out should be personalized in your voice and tone, and then you should probably review it. And that's the only way to actually rise above the noise floor, because noise floor is increasing exponentially. Everything else just will not work. So the second thing is you kind of brought up like multi-threading and kind of talking through it. The key thing is the human has to create a human connection, and one email is not going to do it. It usually takes 13 to 15 touches. So emails, LinkedIn, meeting them in person, getting on plane, as Jason says. So again, like our idea is how is this kind of swarm of agents help you kind of produce the content, but you have to really put in the work to have those touch points. If people think that you can close enterprise deals, but having like one email go out That's not gonna happen.

AI assessment note: “Yes and yes. So supply is infinite. Does, yes, it becomes less effective.”

Q Given the rise of PLG and the centrality of product being so good and people just wanting to touch and feel it so much sooner, The importance of marketing and content like we discussed before. Does the role of sales become ever reduced in a world where PLG starts, marketing helps it along, and then really sales is kind of signing the enterprise deal?

A Ultimately, I do think the largest customers need humans to actually work with to build non-transactional long-term relationships between a buyer and a vendor. And what I look for is customer pull. When the customer's pulling the company along, both in terms of Building out the roadmap or coming up with a commercial construct. That's where you have to learn enterprise sales. Fully believe that you need humans because customers want their problem to be solved. They don't give a F about products or services. They want their pain to be solved, and they want to build a non-transactional relationship with these vendors. So that's where sales comes in. So my view is get the product to do product, yes. Get humans who are super strategic to do the commercial, yes, but they're doing non-transactional commercial, yes. They're not just signing an auto form. They're really working with the customers, figuring out what is the multi-year and a roadmap, both from a product perspective, and that's how I think about the future of sales. The top 10% were working with customers, building long-term, non-transactional relationships, both from a product and a commercial standpoint.

AI assessment note: “Ultimately, I do think the largest customers need humans to actually work with”

Q You said that, that the frank statement was one school of thought. What was the other school of thought?

A The other school of thought was the more traditional thing, where every account has Account executives, AMs, CS, customer success, sales engineers, it's kind of five to six percent part, but there's only one true hunter there. The AE is the one who's actually commissioned. Everybody else is on a, is on a fixed salary, right? That's a fine way to go about it. Datadog has a similar model. If you have really good leadership, where you can kind of manage the incentives well, but in most companies, like in my case, is really high, as Charlie Munger says, it's all about the incentives. It's really hard to set up the incentives across a five to six person team to make sure they're all focused on making the customer happy and for them to actually kind of increase kind of usage or consumption.

AI assessment note: “The other school of thought was the more traditional thing, where every account has”

Q Yeah. Reps get paid a lot, actually, in a lot of cases. What's your take on, hey, I'm willing to pay over market for the best. We pay market and then comp. How do you think about lessons on that?

A So my framework is a framework of explainability. Like the idea is comp and how much money make people make an equity. I'm still old school. It doesn't need to be public, but let us say it did leak and we came public. Like everybody's compensation, Should be explainable. There should be a rational reason as to why somebody is compensated a certain way. So I have guardrails, explainability guardrails that I don't want to kind of breach because if you're giving somebody some irrational package and it leaks and it's going to have like trickle down effects on the team and the company's the team, the team's the most important part. So what I try to do is if somebody's truly outlier and they've kind of went through the thing and they're really like capitalist and thinking about kind of incentives, Very aggressive with performance-based either compensation or equity grants. And a hundred percent, like, like, outlier victories happen when you go, you break rules, right?

AI assessment note: “if somebody's truly outlier... Very aggressive with performance-based either compensation or equity grants”

Q I want to start with a little bit of kind of foundation story. New Relic from zero to a hundred million. I want to start on actually the PLG motion that you developed there. There's so many founders that listen that are building their PLG motions as we speak. What did you do specifically well that you think was so instrumental to the growth from zero to a hundred million?

A The central word is like focus. So we centralized the entire go-to-market engine on a captive audience of developers for whom New Relic was still the default brand. New Relic kind of lost its aura, but there was this audience of about a 100,000 plus developers who joined the workforce, 2008, seven, 14. For them, New Relic was still the hot brand. So we basically shut everything down, reallocated investments to really go after them and earn the right for them to use the product again. And that's what the whole machine was built on. Divest everything else, invest where we are default. So we came in, in a position where the company had Reduce their investment or shut down the PLG motion. So there was this kind of latent demand that we just had to unlock. So we just went back out to the developer community and say, Hey, we have this unlimited free offering. You get all of what you need in a pretty kind of cost effective manner. And then that just was like drilling into an all reserve.

AI assessment note: “we centralized the entire go-to-market engine on a captive audience of developers”

Q Given the rise of PLG and the centrality of product being so good and people just wanting to touch and feel it so much sooner, The importance of marketing and content like we discussed before. Does the role of sales become ever reduced in a world where PLG starts, marketing helps it along, and then really sales is kind of signing the enterprise deal?

A Ultimately, I do think the largest customers need humans to actually work with to build non-transactional long-term relationships between a buyer and a vendor. And what I look for is customer pull. When the customer's pulling the company along, both in terms of Building out the roadmap or coming up with a commercial construct. That's where you have to learn enterprise sales. Fully believe that you need humans because customers want their problem to be solved. They don't give a F about products or services. They want their pain to be solved, and they want to build a non-transactional relationship with these vendors. So that's where sales comes in. So my view is get the product to do product, yes. Get humans who are super strategic to do the commercial, yes, but they're doing non-transactional commercial, yes. They're not just signing an auto form. They're really working with the customers, figuring out what is the multi-year and a roadmap, both from a product perspective, and that's how I think about the future of sales. The top 10% were working with customers, building long-term, non-transactional relationships, both from a product and a commercial standpoint.

AI assessment note: “Ultimately, I do think the largest customers need humans to actually work with”

Q Which other company sales strategy have you been most impressed by recently?

A I think my time horizon from a recency perspective, like, let's call it, like, maybe the five years, I would say MongoDB, Dave, and that whole crew, I see their leaders in every great company. Like, ex-Mongo people running go-to-market in AI companies or fast-growing companies is so common. Like, they just build a winning culture, and he's completely transformed the business, and it's a huge success. I learned a lot from him. And the other one would be Ramp, like Eric and those folks, they were our kind of second private, private beta customer. Now we have, like, one of the most used products. And there, what I've seen is really high horsepower sales folks who've really grown from selling one thing to selling multiple things and now going up market, selling to some of these largest, large customers. And it's all because of this kind of core talent base that they had, those two things.

AI assessment note: “I would say MongoDB, Dave, and that whole crew... And the other one would be Ramp”

Q You mentioned that reinventing the wheel, where maybe you don't need to, or you don't have to. In a world of AI, do we need to reinvent the way that we do enterprise sales?

A A hundred percent, like across the stack, and that's what I learned the hard way. You talked about New Relic, obviously we had a lot of success in the first part of my time there. The second half, like the backside of COVID, we just realized the game had changed. And specifically what the game changed was, there's a boring detail where the way you sell, the revenue models, It's changed from commit-based revenue to usage or consumption-based revenue. So now you had the dollar values in the contract were just words. You only made money when people actually use the product. When you do that, you have to have the right leader. You have to retrain your entire frontline kind of work workforce, and the underlying systems have to fundamentally change, and that's where ConorRox comes from. So that's that core thing, like that has changed. And now with AI, What we're seeing with Cursor and Cognition on the building side is the best are going to get better. Your president's club sellers, your best VP sales, your best CEOs, like Eric at Ramp, they're just going to get better. They're not going to stop. This is an information arbitrage game and they'll get better. So the rest has to adopt AI to fundamentally get better or the, the risk kind of, uh, being irrelevant, i.e. the sales of the power law, the top 10% bring in 90% of the revenue, and it's going to get more acute. If you're not usin…

AI assessment note: “A hundred percent, like across the stack, and that's what I learned the hard way.”

Q What's the biggest mistake you've made with rocks between us?

A Between us and everyone listening in. I think I spend 40 to 16% of my time on talent, the team. I underestimated how important and how powerful it is. Like, we built a founding team of mostly all kind of top AI engineering talent, and that team has built the product, the culture, and hindsight, I would have moved faster to build out that team, and then kind of going back after going to San Francisco, like, I need to spend more time. So the biggest mistake is I would have maybe five X'd the value I would put on just hiring. Second is very detailed. When thinking about AI hiring specifically, the first three months, I wasn't pragmatic enough. Like I was still looking for, hey, maybe we could do research and let's hire like researchers. No, we're pragmatic. We're building apps here. We're building product. So let's work with the best intelligence providers, opening eyes to the world and tropics to the world and together to the world. And let's centralize our focus on working with them to build an amazing application. So about month four, month five, we learned that, hey, we will hire amazing, that kind of applied AI engineers who are shipping products. We're not a research company. I've said those are the two things.

AI assessment note: “the biggest mistake is I would have maybe five X'd the value”

Q Moving step along, how do you think about SEM and SEO? That will shift so significantly over the next few years, bluntly with the rise and dominance of ChatGPT. I've seen also Guillermo Rauch at Vassell's mentioned it's moved from like one to four percent of their kind of inbound. How does that change, and how does that impact how you think about it?

A I think SEO is a long-term strategy. It takes a lot of time to build credibility, and that will change in form factors with kind of AI answers and kind of search, I guess, perplexity-like systems, but that's not going away. You need a core engine that produces high-quality content that's indexed and is kind of discovered in new form factors. For me, it was not an option. I owned a fourteen-year-old brand. Like, the first few blogs still outworked every new blog that you wrote. So, what I look for is, what's the top 10 to 15 kind of percent blogs or pages that return 90% of your value and then distribute it really well. I think SEO, you still have to produce a super thoughtful content, but just do fewer but higher quality ones and make sure they're distributed. SEM, right, you want us to be proactive, like I came in first principles, I think it's a complete cartel. So if you really look at how you invest capital into the SEM game, you're just kind of selling your soul to a pretty messy market.

AI assessment note: “that will change in form factors with kind of AI answers and kind of search”

Q You mentioned that reinventing the wheel, where maybe you don't need to, or you don't have to. In a world of AI, do we need to reinvent the way that we do enterprise sales?

A A hundred percent, like across the stack, and that's what I learned the hard way. You talked about New Relic, obviously we had a lot of success in the first part of my time there. The second half, like the backside of COVID, we just realized the game had changed. And specifically what the game changed was, there's a boring detail where the way you sell, the revenue models, It's changed from commit-based revenue to usage or consumption-based revenue. So now you had the dollar values in the contract were just words. You only made money when people actually use the product. When you do that, you have to have the right leader. You have to retrain your entire frontline kind of work workforce, and the underlying systems have to fundamentally change, and that's where ConorRox comes from. So that's that core thing, like that has changed. And now with AI, What we're seeing with Cursor and Cognition on the building side is the best are going to get better. Your president's club sellers, your best VP sales, your best CEOs, like Eric at Ramp, they're just going to get better. They're not going to stop. This is an information arbitrage game and they'll get better. So the rest has to adopt AI to fundamentally get better or the, the risk kind of, uh, being irrelevant, i.e. the sales of the power law, the top 10% bring in 90% of the revenue, and it's going to get more acute. If you're not usin…

AI assessment note: “A hundred percent, like across the stack, and that's what I learned”

Q So now I can outbound way more effectively with way more personalization?

A Absolutely. The second is outbounding. We're the anti-AISDR. My, my kind of view on automation is the human evolves to become an orchestrator, a quarterback, so we do all the work of composing your sequences, who to reach out to, but the human reviews and sends. This year, we look at this data pretty closely. We're not at a point where a CEO or a CRO can just fire in the hole, kind of fill the pipe with these kind of outbound systems because it's going to dilute your brand. On the outbound, we basically do compose all of our outreach with a human kind of reviews and sends. That's the second part. So it's called Rocks Outreach. After that, when you do reach out, it does all your meeting work. So it does your pre-meeting research, in-meeting support, follow-ups. Again, the mindset was, let's call it Obama or like a president. Before you go into a meeting, you usually get a brief, like a folder with everything lined up. Like that's kind of what you want to do is what if you had every knowledge worker had a kind of team of analysts who are basically preparing you to be the best version of yourself.

AI assessment note: “Absolutely. The second is outbounding. We're the anti-AISDR.”

Q If I'm a founder listening today, what can I do to dramatically increase the sales efficiency performance of my team with AI today?

A So first hire the right folks who are future proof, like they understand the word. So are they using these tools? Maybe illegally in their personal lives. If they don't run using it, they don't see the alpha in their personal life, they're probably not going to get it. Second is, I might be completely wrong here, but ramp much faster. Because A, you can just do it faster. B, the consumer expectations are changing too fast that you have to do so. Once you're fully ramped, push the envelope of how many customers that they could support. And that, those would be three things without obviously losing overall quality and entertainment levels. Will there be teams which are much dramatically smaller who are pulling in the same numbers? I think it has to be proven, but strong kind of intuition that that's where we'll get to.

AI assessment note: “So first hire the right folks who are future proof”

Q You mentioned earlier everyone's spending in a prior generation and how it impacted actually the quality of sales reps maybe. There is a real belief today that we are seeing this massive contraction in spending. Are we seeing CFOs spend less and consolidate more?

A Consolidate more? Yes. The definition of spend, what I'm seeing is changing, and it's changing from program to people. What I mean by that is when you look at traditional SaaS, and I was saying New Relic, and I've been in the space for a while, We're thinking about CC, you're thinking about productivity tooling and kind of basically selling from the IT budget. Now a lot of sophisticated buyers are looking at systems, hopefully like rocks as well, is, hey, can I just make my humans a lot more productive so that I might not have to hire as many? Just kind of brass tacks, right? So it's their view of kind of the ROI is changing from ROI on just software to kind of the people spend. So what we focus on is We want to be the only, for right now, is we only convert if we hit our ROI metrics. We run a 30 day, white glove, like, Palantir, like, kind of boot camp, where we work with the CFO, the CRO, and the C-suite on three metrics. The first one's dollar normalized outcomes, whether that's pipeline generated or progressed, the second one's adoption, third one's activity. The system needs to return all three. If not, you can fire rocks.

AI assessment note: “Consolidate more? Yes. The definition of spend, what I'm seeing is changing”

Q In those reps, do you want reps who've sold that size deal before or sold in that segment before?

A Yeah. Should have held the number at that ACV size for two to five years. Not less than two, highly not more than five, Within those, they need to show that they've been innovative in the pocket. Within deals, they either build tools on their own, or we're actually creative in kind of progressing or closing the deal, because early-stage selling requires a lot of creativity. The founders can come in, and we can use investors, and has involved, because involved, to kind of paper over cracks, but they need to be kind of creative. That's the number two thing. The number three is just, they need to want to make money, right? Like, I really can't deeply think about it. You would be surprised that a lot of AI companies AEs are not compensated with commissions.

AI assessment note: “Should have held the number at that ACV size for two to five years.”

Q Where does that shift to then? If it goes from 40% to 15%, that's not going to be a 25% difference in technology spend. So where else does it get redistributed to? Are they just much more margin, like, much healthier businesses?

A Like, 50% of the customers that we work with, this is boring stuff, is private equity on. Like, New Relic is, yeah, 50% people who come inbound are Portfolio wide rollouts. So there is definitely an element of efficiency. Can businesses run dramatically more efficient manner when they're not kind of growing at all costs? Yes. That's a huge part to it. Where does the capital go? Hopefully some of it goes to increasing the compensation of your supercharged kind of frontline sellers. The other I'd hope, I'm kind of contrarian, I still do think there's so much more to invest in R&D. I think if you're a technology business who wants to be a winner or be the number one, I still feel like R&D is severely underinvested in most scale businesses. I'd hope for their kind of frontline quota carrying reps to gain time to make more money so the company is doing well and that capital to be reallocated to R&D because we don't do enough of it.

AI assessment note: “Where does the capital go? Hopefully some of it goes to increasing the compensation”

Q Do you not kill data providers? When you look at, like, your Zoom Infos of the world, respectfully, I don't want to choose them out, but your Zoom Infos or your Apollos or any of the others, you don't need them if you're supported by an agent swarm.

A We didn't start Rocks or this amazing company is kind of working in this space, kind of deeply thinking about how to source agents, but the agents have gotten phenomenally good at scale gathering information that is in the public internet. And now, like, systems like Lean and stuff in the intranet or in internal systems. So yes, the agents will get more and more capable to just collect information, especially with search APIs at the access of the world. Having said that, the data providers, they provide a kind of source of value where they have 10 to 15 years of back-tested data of human kind of gathered kind of contact information, LinkedIn information, that they've been verifying through a lot of software, but also a lot of operational rigor. That's really hard to replicate. Like Henry and ZoomInfo, for example, a phenomenal business. They have probably the highest quality contact data. They have a huge machine that they've basically, like, kind of built up to have that.

AI assessment note: “data providers, they provide a kind of source of value... really hard to replicate.”

Q If I'm a founder listening today, what can I do to dramatically increase the sales efficiency performance of my team with AI today?

A So first hire the right folks who are future proof, like they understand the word. So are they using these tools? Maybe illegally in their personal lives. If they don't run using it, they don't see the alpha in their personal life, they're probably not going to get it. Second is, I might be completely wrong here, but ramp much faster. Because A, you can just do it faster. B, the consumer expectations are changing too fast that you have to do so. Once you're fully ramped, push the envelope of how many customers that they could support. And that, those would be three things without obviously losing overall quality and entertainment levels. Will there be teams which are much dramatically smaller who are pulling in the same numbers? I think it has to be proven, but strong kind of intuition that that's where we'll get to.

AI assessment note: “first hire the right folks who are future proof... ramp much faster”

Q In those reps, do you want reps who've sold that size deal before or sold in that segment before?

A Yeah. Should have held the number at that ACV size for two to five years. Not less than two, highly not more than five, Within those, they need to show that they've been innovative in the pocket. Within deals, they either build tools on their own, or we're actually creative in kind of progressing or closing the deal, because early-stage selling requires a lot of creativity. The founders can come in, and we can use investors, and has involved, because involved, to kind of paper over cracks, but they need to be kind of creative. That's the number two thing. The number three is just, they need to want to make money, right? Like, I really can't deeply think about it. You would be surprised that a lot of AI companies AEs are not compensated with commissions.

AI assessment note: “Should have held the number at that ACV size for two to five years.”

Q So you partner with them then and use that internally?

A So when we go into a customer, like, our agents will go enrich contacts, like, hey, if you have data, ZoomInfo data in Salesforce or whatever, it's gonna go search and kind of verify the information. And internally, we have kind of OEM'd a few data partners, and that'd be Waterfall, like Clary, just to kind of bootstrap us. So these agents today are enriching the information that you already have. Versus going and actually gathering it. There's a split, like, company data is free game. Company data is public. Agents are, like, pretty much at par. Contact data is where the divergence happens. Like, if you look at what the question that you brought up is, like, LinkedIn information. Like, LinkedIn is a walled garden, rightfully so. It's an extremely, kind of, valuable network that Microsoft and LinkedIn have. People who have LinkedIn data as a data product that they sell into is just a different world that we don't see ourselves going into.

AI assessment note: “internally, we have kind of OEM'd a few data partners”

Q Dude, you're a pro. What are your biggest lessons in sales comp? Imagine you're a first time founder now is Rox, and you've never done this before. It's really hard to know. What would be your advice to someone building sales comp plans for the first time knowing all you know?

A Now I support some of the best go-to-market leaders in the world, and honestly, I know, like, .1%, right? So like it was GC at OpenAI and these, these folks are legends. What I see is two folks. Some CEOs and CROs and CFOs want to run a go to market engine where they're really going for high revenue targets and they want to keep the vibes good. Like they want more and more people to be attaining 80 to 90% of their revenue. The other are more who really want to see a normal or bimodal distribution. The top 10%. So there's actually two different philosophies. So first philosophy is you set up the comp in a way where everybody's kind of winning. Yes, you have your club killers, but most people are hitting quota. In that, that model works if the whole company is growing, the time's large, and you're getting there. The rest is the power law, which is now getting more and more extreme. My general view, I'm doing early stage sales at this point. In early stage sales, the most important thing is to find these outlier sellers who can sell without A massive brand, a demanding engine, and perfect product market fit. And you're trying to find those outlier humans.

AI assessment note: “there's actually two different philosophies. So first philosophy is you set up the comp”

Q But so I give you the CRM, and then you get all of the company level data of all of my targets and all my pipe, and that allows you to do what?

A Let me go back to the origin story a little bit, because you kind of brought up New Relic earlier. When I was competing head on with six or seven public companies, the difference what I was seeing in the trenches, in customers, in calls, where most account customer-facing refs were just not proactive enough. They knew a partial view of the customers, but they had no real-time understanding of How much are they using? What do the support tickets look like? What are they looking to buy? How are they growing? Everything was not in the CRM. So the kind of feature of sales is how do you feed in real time context? Hopefully, I'll kind of complete context about the customer so that the human in front of the conversation is extensively supercharged with this kind of bat suit and actually moving the deal along. So what we do is Rocks gets installed in parallel to your CRM, HubSpot Salesforce Dynamics. It runs in your warehouse. It indexes all internal context. And brings in public context. And it's trying to do the work for you. So you have a team of ROX agents or this team of analysts working for you so that you have full context and basically kind of moving the conversation along.

AI assessment note: “you have a team of ROX agents or this team of analysts working for you”

Q Dude, you're a pro. What are your biggest lessons in sales comp? Imagine you're a first time founder now is Rox, and you've never done this before. It's really hard to know. What would be your advice to someone building sales comp plans for the first time knowing all you know?

A Now I support some of the best go-to-market leaders in the world, and honestly, I know, like, .1%, right? So like it was GC at OpenAI and these, these folks are legends. What I see is two folks. Some CEOs and CROs and CFOs want to run a go to market engine where they're really going for high revenue targets and they want to keep the vibes good. Like they want more and more people to be attaining 80 to 90% of their revenue. The other are more who really want to see a normal or bimodal distribution. The top 10%. So there's actually two different philosophies. So first philosophy is you set up the comp in a way where everybody's kind of winning. Yes, you have your club killers, but most people are hitting quota. In that, that model works if the whole company is growing, the time's large, and you're getting there. The rest is the power law, which is now getting more and more extreme. My general view, I'm doing early stage sales at this point. In early stage sales, the most important thing is to find these outlier sellers who can sell without A massive brand, a demanding engine, and perfect product market fit. And you're trying to find those outlier humans.

AI assessment note: “So first philosophy is you set up the comp in a way where everybody's kind of winning.”

Q Do you do hiring panels? Are you happy to make a decision after that 90 minutes?

A Yeah. I try to, like, Founder led early stage sales, which is what customers and talent, like you need to be able to make deals in the room. Again, a big difference between going back to obviously I idolize kind of Dave and Mongo and Amit delivered data. If you look at these dialed in machines, a lot of the times deals don't happen because the account team has to go back, talk to deal strategy, come up with some, the best teams are enabled with tools that they can make things happen. Like if there's some heat there in the room. So if a candidate has gone through it, I'm spending an hour, hour and a half. And I try to kind of progress things along.

AI assessment note: “Yeah. I try to, like, Founder led early stage sales”