The Exchanges

Q I feel a little bit bad for the rest of the CROs. Like, how do you think about effective sales comp setting today?

A So, well, just to, to start it off the top, ours right now, it depends on the mark, it depends on the segment in the, in the region, but ours right now are between sort of eight and 12 x. Um, is where, is where we sort of landed, but we don't just take a multiple and like apply that to the sort of competitive market OTE. You've got to really take like a bottoms up approach to it and look at all of the metrics we were just talking about before. So look at ramp time, productivity per head, AR per head, uh, pipe, pipe, pipe evolution within certain territories. We did a bottoms up approach of that last year and we got to, we got to those sort of range. But we also had a year last year where we absolutely blew out every metric that we put in front of the team. So, you know, I don't know how effectively we're doing that, but that's, that's, that's how we're doing it right now.

AI assessment note: “You've got to really take like a bottoms up approach to it”

Q Can I, don't worry about being too specific. How does that look then for like sales training then? Like first week, what do I get? I get like a notion link and like a load of video libraries?

A No. So this is actually something we've really elevated and something I'm really proud of. So when I first joined, Uh, Vilgat told me to go to Best Buy and buy an Apple computer, and then I went and had a couple videos of Max doing a demo. Now, every two weeks, we have a new hire class. And at this point, it's between 40 and 50 people joining every, every two weeks. We send everyone to Stockholm, do an immersive five days. And this is not, like, something where you're just gonna go do a couple video things and then go, like, walk around Stockholm. Like, this is intense, immersive. We expect GTMs and LEs to come out of that week to be You know, ready to go. You know, from a ramp perspective, it's, it's a straight line up. Like, we expect people, we expect to drop people in and see them be very productive very quickly.

AI assessment note: “We send everyone to Stockholm, do an immersive five days.”

Q I feel a little bit bad for the rest of the CROs. Like, how do you think about effective sales comp setting today?

A So, well, just to, to start it off the top, ours right now, it depends on the mark, it depends on the segment in the, in the region, but ours right now are between sort of eight and 12 x. Um, is where, is where we sort of landed, but we don't just take a multiple and like apply that to the sort of competitive market OTE. You've got to really take like a bottoms up approach to it and look at all of the metrics we were just talking about before. So look at ramp time, productivity per head, AR per head, uh, pipe, pipe, pipe evolution within certain territories. We did a bottoms up approach of that last year and we got to, we got to those sort of range. But we also had a year last year where we absolutely blew out every metric that we put in front of the team. So, you know, I don't know how effectively we're doing that, but that's, that's, that's how we're doing it right now.

AI assessment note: “You've got to really take like a bottoms up approach to it”

Q Do you think Salesforce faces the threat of being a database which agents crawl on top of and you have no interaction slash engagement with?

A I think all the traditional SaaS companies are definitely under threat right now, but I have to say I've been so impressed with Salesforce. If you look at, they, they sort of Did a hard break glass in case of emergency pivot last year. And at their scale, they went full, they went full agentic and sort of the go to market framework and positioning and, you know, credit for them for being, you know, they're very early on that ahead of every other big tech company. And I don't know how it's going to shake out, but I know we did a survey of all the other sort of hyperscaling AI companies and most of them are using Salesforce.

AI assessment note: “I think all the traditional SaaS companies are definitely under threat right now, but”

Q Okay, dude. Everyone has a flip side. Take me to a deal you lost. And when you look back on it, what's the post-mortem? Like what more could we have done?

A I'm, I'm thinking about one right now, and as always with enterprise, it goes back to multi-threading and who you get to and who you don't. And so with, within a law firm context in particular, the decision-making is sometimes opaque and it's, there's oftentimes there's these panels. And sometimes let's say there's five people on the panel. Sometimes you get to meet all five people. Sometimes you meet four out of five. Sometimes you meet, you know, like one in terms of like one to one engagement and relationship. And there was one key member of the panel that we never got time with and weren't able to build a relationship with. And they did. And oftentimes with a panel making decisions, sort of the loudest voice gets, you know, Gets what they want, and we, we weren't able to, to get that, so that was really painful.

AI assessment note: “one key member of the panel that we never got time with”

Q maybe are questioning whether they took the right step or did the right decision. You mentioned the interim moves that you did, and with all respect to companies, some decisions don't work out, don't want to require anything like that, but any lessons or advice to someone who's thinking, ah, I don't know if I made that right step. I don't know if it was the right decision. Any advice?

A Mostly, When people come to me and ask and ask that question, I say, are you, are you hitting your numbers? Like, are you, you know, are you, are you doing well in your role? Do you like your boss? Are you learning? Are you getting better? And is this serving you in the way where you're making an impact on the company and the company is making an impact on you to help you level up and get better? And if the answer to all three of those things is yes, then typically I think you're in a good spot. If you've got two out of three or one out of three, You know, maybe it's time to think about what's next.

AI assessment note: “if the answer to all three of those things is yes, then typically”

Q who are at traditional SaaS companies, traditional enterprise companies, and are contemplating, should I move to an AI company? There's so much hype, there's so much buzz around them. I don't want to be left behind. Braze is an incredible company, but it's a traditional company. Um, what advice would you have for those operators who are thinking about moving to an AI first company and a next gen company?

A Yeah, for sure. And, and I've become that person at Braze that people call when they're, you know, I'm thinking about leaving and how'd you think about it and dah, dah, dah. So I've, I've, I've had this, this talk a lot with, with friends and colleagues and well, the first thing is always it's what do you want to do? Because I can tell you working in this world is, is completely insane and unhinged and it's over, it's all consuming. So you've really got to want to do it. You've got to want to lean in and it's very different than traditional SaaS. The pace of development, the pace of the market, um, in terms of the competitive market, competitive dynamics, and things like that, um, it's, it's very different, and you've got to really want to come in and build and figure stuff out and do things differently, get a little uncomfortable. If you're okay with that, um, I'm always encouraging people to make the leap.

AI assessment note: “If you're okay with that, um, I'm always encouraging people to make the leap.”

Q So what, what is, sorry, if I'm a founder listening to this, what does that actually mean? So we use pilot data to then encourage net new customers. We say, hey, 84% of people that use this type of email actually convert better. Like, can you, what does that mean?

A Yeah, exactly. So, so within a law firm context, for example, we'll, we'll segment out by practice area. And so let's say that they've, a big firm's got, let's say, 10 practice Practice areas. And then you have, let's say X number of people within each practice area. We can report out on consumption and usage by practice area. And also we, we track and create like frameworks and use case banks for like actual applications and workflows that we're building. So let's say within that example, we've got 10 practice areas, seven of them we see really high, high usage. We're creating and capturing new use cases. We're sharing that back with them on a regular basis, but maybe there's three where we're not. And You can start measuring things like, did the quality of your work increase? Did you decrease the amount of non-billable work that your associates were doing? Were you able to attract more talent? You know, using a tool like Lagorix, people get excited about using the latest and greatest in AI. And so if you, if you take that and you applied it to the three practice areas where maybe we're not doing as well, we can show them insights as to like, who's really leaning in and who's not and where we need help from, you know, from a change management perspective.

AI assessment note: “within a law firm context, for example, we'll, we'll segment out by practice area.”

Q Can I, don't worry about being too specific. How does that look then for like sales training then? Like first week, what do I get? I get like a notion link and like a load of video libraries?

A No. So this is actually something we've really elevated and something I'm really proud of. So when I first joined, Uh, Vilgat told me to go to Best Buy and buy an Apple computer, and then I went and had a couple videos of Max doing a demo. Now, every two weeks, we have a new hire class. And at this point, it's between 40 and 50 people joining every, every two weeks. We send everyone to Stockholm, do an immersive five days. And this is not, like, something where you're just gonna go do a couple video things and then go, like, walk around Stockholm. Like, this is intense, immersive. We expect GTMs and LEs to come out of that week to be You know, ready to go. You know, from a ramp perspective, it's, it's a straight line up. Like, we expect people, we expect to drop people in and see them be very productive very quickly.

AI assessment note: “We send everyone to Stockholm, do an immersive five days.”

Q I come from an industry that is traditionally called sheep-like in terms of following others. I don't understand why anyone would attribute that to us. Um, to what extent is legal a sheep-like industry where it's like, oh, Clifford Chance, Slaughter and May, you name it, use X. To what extent do they follow others?

A There's certainly an aspect of a flight to safety during these, these sort of category creation moments, because this is all new. The sort of general understanding of how agents work and how AI works and how to think about use case design is still being developed. And the sort of, you know, the executive buyers at the firms and at the companies, you know, generally aren't as up to speed on, on that. Some of them are, but you know, broadly, probably not. And so There is this flight to safety. And I think generally people want to feel like, you know, you never got fired for hiring IBM. And at the end of the day, there's an aspect, there is definitely an element of that.

AI assessment note: “There's certainly an aspect of a flight to safety during these, these sort of category creation moments”

Q Um, I think Max is one of the, my, well, pretty great theories, I'm very lucky. Um, what does no one see about Max that you think makes him special?

A I think he leads with a lot of like, he leads from the front, leads from the front. So he's always up early online, you know, pushing the ball, setting the tone for the team. So as a leader, he's someone who, you know, he's going to get on the flight. He's going to take the call. He's going to jump on an escalation. He's going to, you know, call into a deal. He's going to do whatever it takes. And I think that that permeates throughout the organization, but also he's very kind. And, you know, he cares deeply about the business and he cares deeply about building the business in the right way. He wants to build a business that's remembered with a culture that like made a big impact on the people that work there. And he's very focused, not just on Legora being successful, but all the people at Legora, you know, developing their career and taking that next step. And he takes that stuff really seriously. And we've, you know, um, we work on that as a leadership team.

AI assessment note: “he leads from the front... he's very kind. And, you know, he cares deeply”

Q Okay, dude. Everyone has a flip side. Take me to a deal you lost. And when you look back on it, what's the post-mortem? Like what more could we have done?

A I'm, I'm thinking about one right now, and as always with enterprise, it goes back to multi-threading and who you get to and who you don't. And so with, within a law firm context in particular, the decision-making is sometimes opaque and it's, there's oftentimes there's these panels. And sometimes let's say there's five people on the panel. Sometimes you get to meet all five people. Sometimes you meet four out of five. Sometimes you meet, you know, like one in terms of like one to one engagement and relationship. And there was one key member of the panel that we never got time with and weren't able to build a relationship with. And they did. And oftentimes with a panel making decisions, sort of the loudest voice gets, you know, Gets what they want, and we, we weren't able to, to get that, so that was really painful.

AI assessment note: “there was one key member of the panel that we never got time with”

Q maybe are questioning whether they took the right step or did the right decision. You mentioned the interim moves that you did, and with all respect to companies, some decisions don't work out, don't want to require anything like that, but any lessons or advice to someone who's thinking, ah, I don't know if I made that right step. I don't know if it was the right decision. Any advice?

A Mostly, When people come to me and ask and ask that question, I say, are you, are you hitting your numbers? Like, are you, you know, are you, are you doing well in your role? Do you like your boss? Are you learning? Are you getting better? And is this serving you in the way where you're making an impact on the company and the company is making an impact on you to help you level up and get better? And if the answer to all three of those things is yes, then typically I think you're in a good spot. If you've got two out of three or one out of three, You know, maybe it's time to think about what's next.

AI assessment note: “And if the answer to all three of those things is yes”

Q who are at traditional SaaS companies, traditional enterprise companies, and are contemplating, should I move to an AI company? There's so much hype, there's so much buzz around them. I don't want to be left behind. Braze is an incredible company, but it's a traditional company. Um, what advice would you have for those operators who are thinking about moving to an AI first company and a next gen company?

A Yeah, for sure. And, and I've become that person at Braze that people call when they're, you know, I'm thinking about leaving and how'd you think about it and dah, dah, dah. So I've, I've, I've had this, this talk a lot with, with friends and colleagues and well, the first thing is always it's what do you want to do? Because I can tell you working in this world is, is completely insane and unhinged and it's over, it's all consuming. So you've really got to want to do it. You've got to want to lean in and it's very different than traditional SaaS. The pace of development, the pace of the market, um, in terms of the competitive market, competitive dynamics, and things like that, um, it's, it's very different, and you've got to really want to come in and build and figure stuff out and do things differently, get a little uncomfortable. If you're okay with that, um, I'm always encouraging people to make the leap.

AI assessment note: “the first thing is always it's what do you want to do?”

Q So what, what is, sorry, if I'm a founder listening to this, what does that actually mean? So we use pilot data to then encourage net new customers. We say, hey, 84% of people that use this type of email actually convert better. Like, can you, what does that mean?

A Yeah, exactly. So, so within a law firm context, for example, we'll, we'll segment out by practice area. And so let's say that they've, a big firm's got, let's say, 10 practice Practice areas. And then you have, let's say X number of people within each practice area. We can report out on consumption and usage by practice area. And also we, we track and create like frameworks and use case banks for like actual applications and workflows that we're building. So let's say within that example, we've got 10 practice areas, seven of them we see really high, high usage. We're creating and capturing new use cases. We're sharing that back with them on a regular basis, but maybe there's three where we're not. And You can start measuring things like, did the quality of your work increase? Did you decrease the amount of non-billable work that your associates were doing? Were you able to attract more talent? You know, using a tool like Lagorix, people get excited about using the latest and greatest in AI. And so if you, if you take that and you applied it to the three practice areas where maybe we're not doing as well, we can show them insights as to like, who's really leaning in and who's not and where we need help from, you know, from a change management perspective.

AI assessment note: “within a law firm context, for example, we'll, we'll segment out by practice area”

Q I come from an industry that is traditionally called sheep-like in terms of following others. I don't understand why anyone would attribute that to us. Um, to what extent is legal a sheep-like industry where it's like, oh, Clifford Chance, Slaughter and May, you name it, use X. To what extent do they follow others?

A There's certainly an aspect of a flight to safety during these, these sort of category creation moments, because this is all new. The sort of general understanding of how agents work and how AI works and how to think about use case design is still being developed. And the sort of, you know, the executive buyers at the firms and at the companies, you know, generally aren't as up to speed on, on that. Some of them are, but you know, broadly, probably not. And so There is this flight to safety. And I think generally people want to feel like, you know, you never got fired for hiring IBM. And at the end of the day, there's an aspect, there is definitely an element of that.

AI assessment note: “There's certainly an aspect of a flight to safety during these, these sort of category creation”

Q What are the signs that someone's not going to make it?

A We score demo quality using AI. Uh, we use Gong and then you can create like a scoring mechanism for how the call went. How was the discovery framework? What was the, you know, what was the demo flow, et cetera. Um, and then when we get a red flag on that, our team goes in and like our enablement team goes in and sort of looks at the call and does like a, a playback with that person. So if you look at call quality scoring plus opportunity development from a pipeline perspective, you can see pretty quickly who's tracking We know what good looks like, and we know what good doesn't look like, and you can see pretty quickly within about 45 days.

AI assessment note: “call quality scoring plus opportunity development from a pipeline perspective”

Q Um, I think Max is one of the, my, well, pretty great theories, I'm very lucky. Um, what does no one see about Max that you think makes him special?

A I think he leads with a lot of like, he leads from the front, leads from the front. So he's always up early online, you know, pushing the ball, setting the tone for the team. So as a leader, he's someone who, you know, he's going to get on the flight. He's going to take the call. He's going to jump on an escalation. He's going to, you know, call into a deal. He's going to do whatever it takes. And I think that that permeates throughout the organization, but also he's very kind. And, you know, he cares deeply about the business and he cares deeply about building the business in the right way. He wants to build a business that's remembered with a culture that like made a big impact on the people that work there. And he's very focused, not just on Legora being successful, but all the people at Legora, you know, developing their career and taking that next step. And he takes that stuff really seriously. And we've, you know, um, we work on that as a leadership team.

AI assessment note: “he leads from the front... he's always up early online”

Q What was the single biggest sales lesson that you took with you from Braze to Lagora?

A That's a great question. Um, I think the biggest thing that we did really well at Braze that I've sort of taken over is, is implementation change management. So Braze is really hard to implement, or at least it was, uh, when I was there. Uh, so, you know, you're on a legacy product, you're consolidating one, two, three, four, five different tools into one tool. Implementations take, you know, six to 12 months. There's a lot of effort. There's a lot of, you know, stakeholder management, technical work streams, all these different things. And for us at Lagora, Obviously we have an amazing product, but at the end of the day, you know, our focus and our obsession is around like helping our customers adopt those tools, like the Legoro tools into their workflows, which is really hard. So general change management strategies and take all the learnings I took from Braze and taking that Legoro is probably the biggest thing.

AI assessment note: “the biggest thing that we did really well at Braze that I've sort of taken over is, is implementation change management”

Q That's interesting. How do you run them differently today than you used to?

A We have a lot more tools. We have a lot more reporting. Um, we have a lot more specialty in terms of, in terms of, uh, implementation change management. So going back to like the, the, the firm context, as an example, you can't just have like a litigation attorney, go talk to an M and a team. Like you gotta have an M and a attorney, go talk to an M and a team. And so as we've scaled out from, you know, just me to, you know, much bigger team in the U S right now, we've, we've hired specialists who focus on different areas of the law. Who can get, again, sort of go in bed with our clients and the folks and pilots and sort of build those bespoke workflows for them. And we're able to do that. We're able to get on site. Getting on site is super critical because people don't pay attention on Zoom. We all know that, right? And so on sites.

AI assessment note: “We have a lot more tools. We have a lot more reporting.”

Q What are the signs that someone's not going to make it?

A We score demo quality using AI. Uh, we use Gong and then you can create like a scoring mechanism for how the call went. How was the discovery framework? What was the, you know, what was the demo flow, et cetera. Um, and then when we get a red flag on that, our team goes in and like our enablement team goes in and sort of looks at the call and does like a, a playback with that person. So if you look at call quality scoring plus opportunity development from a pipeline perspective, you can see pretty quickly who's tracking We know what good looks like, and we know what good doesn't look like, and you can see pretty quickly within about 45 days.

AI assessment note: “call quality scoring plus opportunity development from a pipeline perspective, you can see pretty quickly”

Q That's interesting. How do you run them differently today than you used to?

A We have a lot more tools. We have a lot more reporting. Um, we have a lot more specialty in terms of, in terms of, uh, implementation change management. So going back to like the, the, the firm context, as an example, you can't just have like a litigation attorney, go talk to an M and a team. Like you gotta have an M and a attorney, go talk to an M and a team. And so as we've scaled out from, you know, just me to, you know, much bigger team in the U S right now, we've, we've hired specialists who focus on different areas of the law. Who can get, again, sort of go in bed with our clients and the folks and pilots and sort of build those bespoke workflows for them. And we're able to do that. We're able to get on site. Getting on site is super critical because people don't pay attention on Zoom. We all know that, right? And so on sites.

AI assessment note: “We have a lot more tools. We have a lot more reporting.”

Q What did you spend money on that was an absolute banger, and you learned something from that, that I should know?

A When they go really well, these sort of fireside chat type executive dinners, So we hosted one, um, some of our investors, their offices at zero bond in New York. And like everyone was, one thing is true is like everyone still wants to go to like, like a fancy restaurant and hear someone smart, you know, speak. And so we still find that these sort of thought leadership AI thought leadership dinners are super effective and they cost a lot of money and you have to, you know, get some talent in the room from a, you know, from a thought leader point of view and to have them do like a fireside chat with Max. That's highly, highly effective and something that we, we do very often and really well.

AI assessment note: “these sort of thought leadership AI thought leadership dinners are super effective”

Q What did you spend money on that was an absolute banger, and you learned something from that, that I should know?

A When they go really well, these sort of fireside chat type executive dinners, So we hosted one, um, some of our investors, their offices at zero bond in New York. And like everyone was, one thing is true is like everyone still wants to go to like, like a fancy restaurant and hear someone smart, you know, speak. And so we still find that these sort of thought leadership AI thought leadership dinners are super effective and they cost a lot of money and you have to, you know, get some talent in the room from a, you know, from a thought leader point of view and to have them do like a fireside chat with Max. That's highly, highly effective and something that we, we do very often and really well.

AI assessment note: “these sort of fireside chat type executive dinners”

Q Honestly, it's a savage world. I can't wait for them to create an AI Harry. If Lagora can do that, I'll pay double. Um, but if we start at the pipe, what's the biggest lesson in how to construct an effective pipe in an AI world, and how that pipeline building process is done?

A This has been a big point of evolution for us. So for example, we just did a big brand campaign with Jude Law. But before you do something like that, you have to do a ton of work in terms of the plumbing, in terms of like, what's our inbound lead scoring? How do we do data enrichment? How do we do lead routing and lead scoring from a probabilistic perspective? So there's a ton of infrastructure you have to put in place first before you can really sort of go big on, on, you know, from an inbound perspective. So Um, on that basis, we've done a ton of work leading up to that campaign, but like even last year of like getting our systems in place, getting the territory assignments in place, like all the rules and sort of, uh, you know, SLAs around if we get a lead, you have to respond in this amount of time. There's a, and even last year, you know, from an SMB perspective, we had so many leads that we weren't able to follow up with them as many as we, as we wanted, you know, in a timely, in a timely way. So the other thing was staffing and we've had to hire a tremendous amount. When I started, we were at 40 people. Today we're over 500, um, and we still need more people and more systems to keep up with the, with the demand.

AI assessment note: “you have to do a ton of work in terms of the plumbing”

Q a two-sided fight, or however we want to say, it's a war, it's you versus Harvey. How do you advise founders? I don't want to make this like Lagora versus Harvey. How do you advise founders? Because there are a lot of markets where it's Brax versus Ramp, or Stripe versus Airwallex, whatever. How do you advise founders when it's one versus the other, when you're in that sales process?

A At the end of the day, it comes under preparation and execution. And, and one of the camp, one of the companies I, I really admire and try to model after his ramp, like you said, and we, we talk a lot about, about them internally in terms of how they've built the execution layer from a go to market perspective. If you've talked to anyone who's engaged with like a ramp sales team, they're always prepared. They don't have to like take things back to get answers, right? There's, there's a degree of professionalism and preparation that goes into every conversation. And, and also, You know, if you think so often in go to market, people talk about using AI to automate different processes like, oh, I want to like, you know, update my opportunity notes or like draft this email. And, and of course we do all that stuff. But the other thing that people don't think enough about is like, what, how are you using AI to sort of deliver more like differentiated from a services and insights perspective? We have a lot of data from, from like pilot participants. How can we give, you know, insights into that data that are going to help the, the firms and the companies that we work with make decisions around Adoption frameworks, ROI, and things like that.

AI assessment note: “At the end of the day, it comes under preparation and execution.”

Q How do you bring in people with true buying power? I imagine they're not always on the first course. How do you make that transition of like, I'm so pleased, Patrick, that you're excited about Lagora. Can we please try and get your boss in now? Because I want to progress this.

A I have to say one of the things about Lagora that's like floored me in, you know, at Braze we had this problem. So Braze, the executive buyer was the CMO. And getting access to a SEMA was so hard, and we would get it done, you know, very, very rarely, and we always, you know, we sort of bend over backwards to get this done. With Legora, because There's so much chatter in the market about AI and the firms and corporates both want to understand what others are doing. We actually get access to power pretty easily and people want to learn because on a law firm side, they're getting asked by their clients, how are you using AI and what tools are you using? Like, what are the use cases and where are we going to see this value in our bill, for example? And then the corporate side, they're getting a ton of pressure from the board and the CEO of like, Hey, go figure this shit out. Like, You know, we need to operate, we need to optimize like XYZ process and AI everything. And so we get access to senior stakeholders who want to like lean in and learn from us. But I think typically if you don't have that access early to your, to your question, what we try to do is we try to, you know, focus on the highest value use cases and highest value impact as quickly as possible. So you want to grab attention really, really fast. And lucky for us, the LaGuard product's awesome. So coming in with the …

AI assessment note: “what we try to do is we try to focus on the highest value use cases”

Q Honestly, it's a savage world. I can't wait for them to create an AI Harry. If Lagora can do that, I'll pay double. Um, but if we start at the pipe, what's the biggest lesson in how to construct an effective pipe in an AI world, and how that pipeline building process is done?

A This has been a big point of evolution for us. So for example, we just did a big brand campaign with Jude Law. But before you do something like that, you have to do a ton of work in terms of the plumbing, in terms of like, what's our inbound lead scoring? How do we do data enrichment? How do we do lead routing and lead scoring from a probabilistic perspective? So there's a ton of infrastructure you have to put in place first before you can really sort of go big on, on, you know, from an inbound perspective. So Um, on that basis, we've done a ton of work leading up to that campaign, but like even last year of like getting our systems in place, getting the territory assignments in place, like all the rules and sort of, uh, you know, SLAs around if we get a lead, you have to respond in this amount of time. There's a, and even last year, you know, from an SMB perspective, we had so many leads that we weren't able to follow up with them as many as we, as we wanted, you know, in a timely, in a timely way. So the other thing was staffing and we've had to hire a tremendous amount. When I started, we were at 40 people. Today we're over 500, um, and we still need more people and more systems to keep up with the, with the demand.

AI assessment note: “you have to do a ton of work in terms of the plumbing”

Q How do you bring in people with true buying power? I imagine they're not always on the first course. How do you make that transition of like, I'm so pleased, Patrick, that you're excited about Lagora. Can we please try and get your boss in now? Because I want to progress this.

A I have to say one of the things about Lagora that's like floored me in, you know, at Braze we had this problem. So Braze, the executive buyer was the CMO. And getting access to a SEMA was so hard, and we would get it done, you know, very, very rarely, and we always, you know, we sort of bend over backwards to get this done. With Legora, because There's so much chatter in the market about AI and the firms and corporates both want to understand what others are doing. We actually get access to power pretty easily and people want to learn because on a law firm side, they're getting asked by their clients, how are you using AI and what tools are you using? Like, what are the use cases and where are we going to see this value in our bill, for example? And then the corporate side, they're getting a ton of pressure from the board and the CEO of like, Hey, go figure this shit out. Like, You know, we need to operate, we need to optimize like XYZ process and AI everything. And so we get access to senior stakeholders who want to like lean in and learn from us. But I think typically if you don't have that access early to your, to your question, what we try to do is we try to, you know, focus on the highest value use cases and highest value impact as quickly as possible. So you want to grab attention really, really fast. And lucky for us, the LaGuard product's awesome. So coming in with the …

AI assessment note: “focus on the highest value use cases and highest value impact as quickly as possible”

Q What level of contract do we need to justify an FDE model, which is more costly? It's human hours upfront. It's margin reduction. What level of ACV do you think is needed?

A Well, it's a great question, and people keep asking me why we raise so much money, and I'm like, lawyers are expensive, man. You know, it's like, it's, uh, you know, we can afford to take, you know, to take this sort of human, this very human-centric approach right now, but we do it for, you know, pretty much anything in, in, in six figures and above. Um, you, you've gotta really lean in and make that, make it happen, because otherwise what you do is you sell, you're in danger of selling software that doesn't get used, and our, we're very focused on, You know, again, like I said, adoption frameworks and making sure that if we sell you 10 licenses that you use all 10 and you get a lot of value out of it.

AI assessment note: “pretty much anything in, in, in six figures and above”