so 2010 and during the great financial crisis. You know, the Fed lowered interest rates down to very, very low rates. And we had low interest rates, meaning of freely abundant capital, from 2010 to when, you know, they started raising interest rates, which, you know, I think maybe 2023 but maybe it was 2022 so what's the point? The point is, well, I don't know about you, but if you worked, if you came of age from 2010 to 2022 that's 12 years. That's 12 years. So, so a lot of the lessons that you've learned about, that we've learned, that I've learned about how to structure the team, about how to compensate the team, about how to motivate the team, all of those were in an era of artificially, not artificially just, you know, an era of very free capital, cheap capital, where growth at any cost was favored over profitable, efficient growth. Now we're in a different operating environment, and that last column that you see on the right. So Jamin ball, from clouded judgment, puts out, you know, some data. He works at altimeter, and he just told us that for q1, new ARR for public SAS was down 30% year over year. So think about that. In 2024 there was a number. That number for new ARR, net new ARR is down 30% year over year. So what's what's happening here? The bar is raised. That's the point. The bar is raised. And what I mean by that is the degree of excellence that is required to execute in this environment is higher than it's ever been. It's higher than any of us have experienced so far, right? This is a different operating environment. There is no thing that's easy, you know, again, maybe if you are one of the lucky few that works at open AI or works at Anthropic or works at bolt or cursor or replit, maybe things feel easy for you, but for the rest of us, there's nothing easy. It's not that outbound is not dead. Cold calling is not dead. You know, Account Based Marketing is not dead. And 10. Data is not dead. Nothing is dead. It's just harder. It's just much, much harder, right? And that's something we have to internalize, that the degree of execution, and therefore the profile of the people that we work with on our teams, that has to change because, because we have to be more perfect, we have to hit that Bullseye more frequently than perhaps we ever had to right that that's it's not that you know that we're doing anything necessarily wrong. It is just that the degree of difficulty has increased, and the quality of our execution therefore has to increase. So what do I think? You know, let's talk about leading with humanity, right? And I want to counter that. I want to balance some of these ideas against how to incorporate AI, because AI is incredibly important, but AI is not going to replace the things that make human special, or at least not yet. And we want to learn how to use AI in the right way so that we can create more headspace for our teams, so we can we can outsource and offload administrative and manual tasks. And of course, that's where otter comes into play. That's where great tools like clay come into play. So we want to use AI and technology in the right way so that we can give our teams the ability to spend more time with customers, to spend more time with prospects, and to and to show up in the right way. Now, again, it depends. You know, your values may different, but but one of the things I really want to underscore here is that leadership with humanity doesn't necessarily mean ruinous, ruinous empathy. I think it starts with clarity and accountability. So if you want to just pick out two things that you see on the screen from my perspective, but again, what I hope is that we, you know, we'll wind down my prepared remarks, such as they are in, you know, 1015, minutes. And then what I would really love is, is an interaction and a contribution from, from, from folks. So if you have any reactions to what I'm saying, Please drop them into the chat. And if, if you don't like anything I'm saying, you can say that too. But the point is, what I think is required is, particularly if you're remote, first is clarity and accountability. There's a great book, if you want to write this down. There's a great book called first break all the rules. And first break all the rules is sort of about management and leadership. It's an old book, but it's one that I often recommend. And I think there's 12 different principles of leadership that are really important when you're leading your team, and it's really 12 questions that you have to answer, and the first two are the most critical, the most critical, and these are your team is asking these two questions. There's a number of different questions that they asked, but these are the first two. The first is, do I know what is expected of me? Do I know what is expected of me? And the second is, do I have the resources necessary to execute what is expected of me? And that's where clarity and accountability come into play. We do need to empathize, but in a remote first world where we cannot look over everybody's shoulder, the very first thing we need is clarity, right? We need to understand. Here are the goals, here are the expectations that we have set. Here's what good performance looks like, here's what bad performance looks like. And then we need to create systems and structures. Those could be OKRs. Those could be monthly operating sprints. It could be some mechanism that you have so that you can clearly identify these are the things I'm expected to do. I have the resources necessary to do them, and now I am working towards accomplishing that goal. In my experience, the number one cause of burnout is not working too hard, working too hard and seeing measurable progress and understanding how what you're doing fits into the broader organization that often creates joy. The thing that creates burnout is a sense that you're moving in a variety of different directions all the time without a clear plan, that you don't understand the plan, and that again, to that first question of, you know, first break all the rules that you do not know what's expected of you. So I think you know, if you're out there and you want to figure out, like, how do I do this, these don't have to be your values. But I think it starts with, what are your values, what is important to you, and is that clear across the organization? So that's one thing that I would I would really forcefully underscore. And then I would say, let's make sure that we're using artificial intelligence in the right places. So there's all this anxiety and panic. I feel it every day about how are we going to use AI in the right way? I would say, as you see, we want AI to do things that we don't feel like doing. And AI can do things like manually update CRM. It can make sure that people are adhering to, you know, selling methodologies like MEDDIC or medpic. I certainly think, you know, we've otter. For us has become a verb. Did you send your otter? Can you send your otter into that meeting? Because one of the things we want to. Use AI to do is to capture data and capture information about our organizations. But I really think the two things that you see in the middle there and on the right side of the screen are super, super critical. And one of my, if you want to know, my biggest concern about AI, it is that, and I've shared this on my on the podcast that I do top line. I think, if you assume that you understand how the model is working, and you assume that it is a prescient, omniscient, all knowing intelligence that is accessing a perfectly structured database in order to give you a precise, correct answer all the time, that is not how the system is working, and that is not how it is designed. And what is the point of that? The point of that is we need humans. We need our teams, and we should clarify that we need them, because they cannot outsource critical thinking skills just to AI, many, many times. And I'll give you a specific example. I you know. So to the point of clarity, what is one of the ways that at pavilion, as an as a CEO, I try to provide context and clarity and to to the organization. Well, I write a weekly update. So I write a weekly email every Sunday that I send out to the entire organization. Now, the inputs to that weekly email often come from department heads, so they, they send me everything, and I've created a GPT, you know, in chat, GPT, where I upload all of these weekly updates so that I can synthesize everything and then share a consolidated Company update out to the entire organization. Now, if I didn't fact check that or quality control, that we would be in a world of hurt, because oftentimes the AI is making up data points, is making up or drawing or referencing information that was not previously made available to it. It's saying things that are not true and and so I correct it, and I and I review it every single time, and there isn't a single instance where I'm not making a specific correction. So my point is, what is the role of humans leading with humanity? What is the role of humans in our new world? Certainly for now, it's to provide quality control. We cannot just copy and paste something into chat, GPT and send it out to the organization. We need to be in the loop. I will share with you. You know, you may know this, but there, you know it's it's probably well known that, you know for a long time, for probably 20 years now, maybe 25 you know, a computer can beat a human, the best chess player at chess. But what may not be known is that actually a human with a machine can beat just a machine, and they call that a centaur. And I think it's also true in in Chinese go checkers, that is, you know, that is like their famous, you know, problem problem solving, game and, you know, and difficult and complicated, complicated game. And the point is, a human plus a machine can often beat a machine, and so we need to be in the loop, because we cannot just outsource all of our critical thinking skills to artificial intelligence. And I think if you're thinking about the role that you can use with your teams, they need to be making you need to be making sure that they are fact checking the AI, that they are providing oversight and quality, and that you are encouraging them, that that is their place in the organization. Now we can't, you know, we have to. We should talk about, what are some tools like? Okay, if we want to have humans with human conversations, interacting with our customers. And I think that should be the goal, right? I think the goal should be, if we have a sales team, if we have a Mar you know, we want as much time talking to customers and humans, interacting with each other as possible, most of the time we saw in that previous slide that, you know, CROs are spending 85% of their time firefighting. Well, what percent of the time do sellers spend actually selling? And it's an abysmally low percentage, because so much of what they do pre AI is data entry. So we really want to focus on making sure that you know the manual stuff, the stuff that leads to boredom, the stuff that leads to people looking for new jobs, is replaced by technology. So here's some tools that I think if you're looking for specific use cases for where can I use AI on the team? So first of all, obviously, I think you should use otter. We use it because and I use it so that it can record every single meeting, and then it can have an intelligence. And I can query that broad intelligence. I can ask it things about trends in the organization. I can ask it things about, you know, my tonality or my perspective. I can, you know, interact with it in a way that that tells me what's happening in the organization and synthesizes all of these different meetings to its transcription. So, you know. And again, as I mentioned, it's become a verb at this point. So we say, Send in the otter interactive role playing and coaching. So Avara, there's, there's, there's so many that are emerging right now. But one of the things that you really can do from an enablement perspective is you can, you know, pilots spend 1000s and 1000s of hours in the flight simulator. And, you know, I sometimes refer it as as hours in the sim, you can train. AI to provide interactive role playing and coaching to your reps. And Avara is one of the companies. And, you know, I advise some of these companies, but not all of them, but Avara is, is a really interesting company I know. Owner.com uses Avara to train their reps and onboard their reps. One of the things you can do is you shorten ramp time and and you, of course, improve adherence across the organization. Obviously, everybody knows about clay at this point, there's so many capabilities that you can do using data enrichment and automated workflow triggering. I'll give you a specific example, which is really quite cool. We built a clay workflow where, if you honestly, all you have to do is, like, one of my posts on LinkedIn, Clay enriches your information that it finds from LinkedIn, and it finds your email address, and then it can drop you a note saying, Hey, do you want to hear more from pavilion and Sam Jacobs? And that's just one of the things that you can do with with clay, automated messaging and calendar management. That's fixer. And then you know, hockey stack is doing all kinds of things on intent data and really building out like a full scale marketing stack. So those are some tools that you can use. Of course, we can talk about,