Please welcome to the stage EVP Global Investor Relations, Mark Murphy. Thank you. Welcome, everyone. Great to be here. Look at the energy in this room. Love it. As mentioned, I am Mark Murphy, EVP of Global Investor Relations with Salesforce. We have just a fantastic investor day lined up for you. I want to start by thanking everyone in this room. We are so grateful to you for your time and attention. We hope you are going to make the most of this unbelievable event by getting out there and engaging with customers and partners. Ask them anything you want, ask them what is changing, ask them how this transformation is occurring for them. This is at least my 20th Dreamforce, if you can believe that. I have kind of lost count, but it is at least 20, and it is just unbelievable to be here and to be on this side of the room for the first time. It means so much to me. As I reflect back on having been here through 20 Dreamforces, what is actually amazing is what has not changed at all. The location hasn't changed. We are still here in San Francisco, in Moscone Center. The keynote is in the same room. The founders haven't changed. We have Marc, we have Parker sitting right over here. They are going to be on stage later today. The energy level hasn't changed. At the beginning of the keynote, the Hawaiian ceremony hasn't changed. I think a lot of the jokes that get made have not changed somehow in 20 years. What has changed is the technology. The technology has changed quite a bit over the summer. There is a new ability to unlock trapped value that has legged up in a pretty exponential way in the last couple of months. Because of that, we are going to have a totally different structure to the analyst day. It is going to be unlike other analyst days you have seen. We are going to be opening up laptops, and we are just going to be showing you live this kind of transformation that is happening, and we are going to be trying to show you what is possible. We are also going to have many more customers on stage. We are going to have Siemens, we are going to have Adecco, and we are actually going to have Anthropic on stage toward the end of this event. One more thing that has not changed in the last 20 years is the legal disclaimer. I am not going to read it to you, but we are going to make some forward-looking statements that are subject to change. We would strongly encourage you to refer to our most recent SEC filings, including 10-Qs and 10-Ks. This agenda is going to be fast and efficient. We are going to really fly through this. We are going to start with Patrick and Rohan. They are going to go a lot deeper on the technology. We are then going to move to the go-to-market execution engine. We are going to have Miguel and Alexa for that section. Then, batting cleanup, we are going to have Robin with the financial framework for the agentic opportunity. After that, Marc is going to join us. Marc will be on stage, and we will have a Q&A with the full leadership team for as long as they want to go at the end. After that, we are going to have an investor reception and demos. That is actually going to be right outside this room. With that, I am going to hand it over to Patrick, who is President of Applications and Marketing. Patrick, welcome. You want this? You want this? That's all I need. I need your boon too. Give me that. You got it. All right. Thanks, everybody. Does anybody want to take any bets on whether this agenda is fast and efficient, as Mark put it? Because I'll be happy to take a couple bets. I think I know where it'll get slow, but that's okay. Okay, so I'm psyched to be here with you all today. Don't look at me like that, Miguel. We're going to walk you through a whole bunch of stuff about where we're going. We're going to break down what you saw in the keynote a little bit more today. I've been getting a lot of questions from yesterday on how did we do that? It's funny, there's two sides of belief. There's the side that kind of has an inkling and wants to know more detail, and then there's the other side that's like, "That couldn't have been real." It totally was. We're going to break that down and show you how all of that works. Rohan and I, the way to think about these two sections in the agenda here is, I'm going to start by walking you through how I think our apps are going to change, and how they need to become agent ready, or a more technical term, agent legible. Meaning every app needs to be usable by agents in a composable environment like Coworker like you saw earlier. Rohan is going to come up and start walking you through how we are in the midst of transforming into a much bigger data company, and how we'll leverage that data in an enterprise harness for the future. That's the course of the next 30 minutes or 40 minutes or so. Now, what I want to do as something just mildly annoying for a moment is, I want to hop out of the slides and I want to go to the demo screen just for a second, if we could. Thank you, team back there. Okay, so I mentioned. Actually, how many of you saw the keynote yesterday? Oh, most of you. Okay, great. I thought it would be about a third of you. Good job, everybody. I mentioned in the keynote yesterday that you can go from nothing to something pretty usable in about six to eight minutes. After that, you might have a few days of iteration as you build and you refine and you design the user. I have a prompt up here, and I worded it kind of in a funny way, but I am saying build a one-shot artifact. An artifact is actually a capability within Coworker, which you will see in a moment. I want it to list my open Salesforce opportunities. I want it to use the Headless Toolkit to do it. Then I want it to build a model where Claude drafts a task and posts that over to Slack. Then I say, "No questions." One shot at the front and no questions at the back are me trying to get Claude not to ask me any damn questions and just build the thing so that I do not have to keep coming back in and hit enter while this is going. What I am going to do is, this is like the cooking show, if you have ever seen a cooking show where they pull the turkey out of the oven even though it has been in there all day, is we are going to hit enter and you are going to see this start, and it is going to start working on this application, this opportunity application that I just asked. It is loading the tools, and all in all, this is probably going to take about six minutes end to end to come back with a completely working application. This is really no longer vibe coding, right? This is, we are taking the acceleration that these coding agents have delivered to developers, and we are putting it in the hands of knowledge workers. That is really what Coworker is. You are never going to see any code here. You are not going to see any of that background. Coworker just takes care of all of it for us. In fact, we can kind of expand and see what is going on. This is going to take maybe eight minutes or so, and so we are just going to let that run, and we are going to go back into our slides, and then when we come out of our slides, God willing, it will have produced something mildly useful, and we will take a look at it. Okay. We can go back to the slides. Okay. I think you heard yesterday that we really believe that there is a big interface revolution going on. Another way that I like to say this is that there is a user behavior or a user experience revolution going on, which is that most people in the world, in software at least, are starting to figure out or starting to sense that there is a better way to use software. The way that we've used software for 50 years is we have to know what we want to do, and we have to know then how to use the software itself, and we have to click around and hunt and peck. The analogy that I like to use is that if you're a digital photographer, like a wedding photographer, part of your job is having a good eye and knowing how to use your camera, but most of your job is just knowing how to use Adobe Photoshop. It's a big, complicated application. Salesforce is the same way. It's a big application. It has a ton of surface area, and your ability to extract value out of it is limited to the human's ability of what they know about how to use the application. What's happening now is we are taking an agent and putting it between the software and the human, and we're just taking intent from the human. It's giving it to the agent, to the knowledge worker agent. In this case, what you'll see today, that knowledge worker agent is Claude. Claude is looking across all of the tools and capabilities which have been connected inside of Coworker, and it is composing a response based on all of those tools. So you are getting a tremendous amount of additional value out of not just Salesforce, but any other platforms that you plug into it. The other interesting thing that's happening there is it's kind of aggregating software into one environment, because no longer do I have to do a discrete task in Salesforce and then a discrete task in SAP and a discrete task in Workday. If I have a task that requires all three of those systems, if they're all wired up in the same way that we just showed you yesterday, like we can do with Salesforce, if they're all in that Coworker environment, it's now all aggregated, and that agent can go off and kind of work and operate across those systems in ways that frankly we've been trying to build integrations for the last 50 years, and now we have this entirely new way to kind of drive these integrations. It's a big revolution. Of course, we've been working towards this. Marc talked through this yesterday, really trying to simplify our platform to make it ready for this user behavior change that we see happening. We've really focused on our deterministic systems, of course, our data layer, which Rohan will go into, our apps layer, where we have a lot of the semantics and business processes that are codified into Salesforce, and then we added our agentic layer, and then now the new AIforce layer on top. That's really where all of this starts to come together. So AIforce, you can think about it as three kind of new surfaces. One is Claudeforce, the second is Slack, the third inside of Lightning is Agentforce Coworker. We will do more of these in the future. There is no shortage of knowledge worker apps that are beginning to emerge where you would want to be able to use Salesforce in the way that I'm about to show you. All of that comes together on this platform with Data 360, Customer 360, Agentforce, and AIforce. When we click into Claudeforce, just for a moment, I'll show you this in the app. Basically, we came off of Headless 360 at our developer conference back in March. We launched Headless 360. We sensed the user behavior change that was happening. We were like, "We better get MCP servers out because our customers are trying to do this themself, and it's a little bit dangerous, so let's get some first-party MCP servers out." That was, I think, very successful and a little surprising. I don't think people expected that posture from a software company to actually endorse that pattern. We got out there with it quickly. We started seeing people pick up and use it very quickly. On top of that, we started seeing them run into problems that we needed to fix. Claudeforce is really the extension of that, and AIforce in general. It is us productizing the capability of those MCP servers into something that can get implemented and deployed across your organization way faster than every individual in the room having to connect their own MCP servers, which is just really not very practical. We'll talk more about this later across the sections, but we wanted to package all of that up into one relatively easy-to-buy platform edition. We have our new AIforce Max edition at $550 per user per month. It includes everything that you're about to see today, including Slack and Slackbot, which you'll see glimpses of from me today, but not a ton. Despite this new addition, for the time being, Claudeforce is in open beta. We're trying to maximize the surface area of customers that can touch it right now. One day soon, that will move into a GA, and you'll have to buy it to keep it turned on. But right now, we really want people to touch it. Okay. I'm going to go back to the demo. I'm going to break down a little bit what all that looks like. I actually have a customer, a little bit of a surprise for you in a moment. We're going to bring a customer up. We're going to see their live Claudeforce environment against their live production data as well. Let's go back to the demo. You'll see, there we go. I have to learn how to scroll. Oh, it did ask me a question. See, it's Claude, man. It's just constantly asking me a question. I'm just going to say a roll up command. I'm not really reading what it's asking me, so God knows what we're going to get, but I do have some confidence that it'll be pretty good. Okay, so we're going to let that keep running. I can go into the rest of the demo. You saw this big, beautiful dashboard yesterday, right? All this whiz bang stuff happening on the screen. That's a capability within Coworker. It's an incredibly exciting one, but it's also not the way most people start using Coworker. The way most people start using Coworker is they start on the chat screen. That's exactly what I'll do. I'm just going to create a new chat here. They just start asking questions. Before anybody figures out that they can build applications, this is the way people usually start. What would a typical Salesforce question look like? Well, it might be, tell me about my pipeline. Say open pipeline. So a fairly typical question. What's going to go on in the background here as this thinks, and you'll see the work going on here is first it looks at the question, and it's deriving the intent from the question. Just from the word pipeline, it is looking then at its tools that have been connected, and it is trying to connect a tool to the intent. Okay? In this case, it's going to connect Salesforce to that intent. It's going to say, "This is a question that Salesforce can likely answer." Then it's going to go ask Salesforce that question through the MCP server, and then it's going to bring back an answer. That is what is happening behind the screens. Not only did it bring back an answer, but you'll notice that it brought it back as a dynamically generated kind of mini application right here in the channel. That is all made possible through a new protocol within MCP called MCP Apps. Sorry to get mildly technical for a second. You'll also hear us refer to it as HXL, which is just our internal name for it. All it means is when we ask that question, Salesforce on the other side, it says, "Not only do I know the answer to that question, but let me give it back to you with some additional detail about what an application could look like on the other side." Then Claude says, "Thank you very much for that information." It draws the application right here in the chat. All of that took place, everything that I just said took place in, well, way faster than I was even able to tell you what was going on, right? It came back with our answer. What's cool about these little mini applications is they're actually somewhat interactive. I can scroll over them. These aren't just like images that come back. I can interact with these things as well. In fact, I can even design buttons in, and all of this kind of sits on the Salesforce side. We send these instructions over to Claude, and then Claude puts it on the screen. So I've got my North Star app here. This is our opportunity. This is actually the one that we were looking at yesterday, a $4.8 million opportunity. Let's say I wanted to ask a follow-up question. So tell me about the open activities. Effectively, you're going to see the same kind of thing happen. It is going to go to Salesforce. First it is going to read the intent, it is going to realize that this is a Salesforce question, it is going to look up the skills and the tools to see if it knows how to go get it. Then eventually it is going to come back with an answer, and ideally that answer is also going to be some sort of dynamically generated interface, which I expect that it will be. As soon as you see Headless Toolkit, yeah, there we go. These are all of the activities that are logged inside of Salesforce, just brought back immediately to me, and even a little activity chart, kind of a heat map where you can see when the activities were happening. Now, these seem like relatively simple queries, and they kind of are, but I want you to think through how much internal human clicking is going on inside of Salesforce to do this the old way. You have to know how to get to opportunities, you have to load all of your opportunities, you have to click into every single one. You have to look at the entire opportunity screen for every single opportunity. You have to commit to memory what is going on with those opportunities. Then you have to synthesize that as a human being, and that tells you what you should go work on. Or you can just ask Claude. That is effectively what we have done here with Claudeforce. Now, let me show you a couple other things. One thing that is very cool is if there are certain things that you do every single day, or every few hours or whatever it is, you can schedule these. That is what I have. I have a daily briefing skill here. Here is the daily briefing. This tells me what I should be worried about every single morning. I do not even have to come in and run this every single morning, I can just tell Claude to schedule it. It saves it as a daily briefing schedule, which you see right up here. In a funny way, what you have done there is you have basically created, just by asking, you have created an agent. You have created an agent that every morning is going to go out, it is going to inspect Salesforce, it is going to build your daily briefing, and it is going to bring it back and drop it right here in Claude. Of course, that goes to your phone as well. You get a notification every morning. So it is an incredibly powerful capability. I can also show you, here is the command center that we looked at yesterday. See if the sound is actually working. It is, which is unfortunate for Parker because that means Parker is going to come up. There `he is. We are just going to minimize Parker, because I think he has heard enough of that. But this is a very fancy version of that prompt that I started with. Remember that first prompt where I was like, "Build me an application"? That is where this started. Then it just grew and grew and grew in capability as I asked it for more and more, which I think somewhere, yeah, right here, you can kind of see all of those prompts going through, and there is actually more than this behind the scenes. In fact, I can even show you. Remember a few moments ago, I told you that the kind of cool thing about this is the aggregation of software? This is not just Salesforce, it is Salesforce and anybody else who builds these kinds of MCP connectors. Well, one of the companies that is really out in front on that is this company, I do not know where I put it. Here it is. Is this company called ElevenLabs. Everything you see here on this screen, as I scroll through it, is if I know how to scroll. I actually do not even know how to scroll on this. I guess we will go this way. There we go. Everything you see here, I did not create. This is ElevenLabs' internal capability for creating voice models and for creating 3D avatar models. I did not touch this. I did not create any of this. All I did was create an ElevenLabs account, hook up the MCP server, and then when I was building my command center, I said, "Here is a graphic of Parker in the silly Lightning costume." Then I gave it an audio file from a keynote that Parker has done in the past. Those were the only two inputs. The Claude connected to the ElevenLabs MCP server did every single thing else. Really powerful, and actually, there was a funny moment in here, if I can find it. It might be here. I forget, yeah. Look at all the silliness as it generates this all out. I think it is here. Filtered. Yeah. What happened is ElevenLabs did not like this graphic because it thought that it demonstrated violence because of the lightning bolt, and it actually stopped me and prevented me from going further. Then we just had to change the initial graphic to make it look less like a real spear, and that is how we got through this. These AIs are constantly stopping you to make you do things. Anyway, 0% of this was manually created. This was all just from those series of prompts and the capabilities all hooked up. Okay. I am going to wrap up here quickly by going back somewhere. Is it this one? No. Stefan, help me out here. The very top. This one? Keep going? Oh, here. Oh, it raised its hand. Okay. That is a good sign. That means it is about done. Okay, so it is ready to publish the artifact. The artifact is the application that I asked it to create at the beginning. So if I accept this, boom, there is my pipeline, and I should be able to expand this, and maybe shrink this a little bit. So there is my full roll-up of all of my opportunities across my team. Super simple, just from that one silly prompt at the beginning, and I can make this better and better. I can make it look like whatever I want. For example, there is mine, which looked super fancy and had all the whiz-bang stuff. What if I wanted it to look like a newspaper? All you would have to do is ask in the instructions, and you get a totally different view of all of your Salesforce data. What if you wanted to build something that looks more like a deck? This is Salesforce information kind of in slide format. You could actually build a full presentation if you had to go do a board presentation. Everything is just there, all from a couple sets of instructions. What makes this all work? It is pretty straightforward. It is this new plugin behind the scenes, where we have taken the many MCP servers that make Salesforce work and a handful of skills. Right now, most of those skills are focused on sales questions and salespeople, but we will be expanding across our entire platform. Things just kind of start to work because you have this powerful agent sitting between the human beings. The key here is this is not just about getting answers to your questions. This is about building full-form applications and dashboards that you need to go get your business done. In fact, there was a thing that happened this morning, I am not going to bring it up, I am going to kind of bring it up. There was a thing that happened this morning that I woke up, and the very first thing that I said is, "I need a command center so I can see the surface area of the problem that is going on." I just jumped into Claudeforce and built it out, and then got my team rolling on it. We are using it in real life. This is rolled out to Miguel and Alexa's entire organization. It is rolled out to the Anthropic selling organization. We have about 40 customers in the beta. In the pilot, as of yesterday when we put the beta link up, I actually have not checked to see how many customers have signed up for the beta, but it is probably several hundred or 1,000. With that, I would like to bring up one of those customers. We are going to bring up Rik Janssen, who is the CIO of Siemens. You heard a little bit from Siemens, and we will invite Rik up, and he is going to show us how he is using Claudeforce. We did not test his laptop before this, so we will see. Hey, Patrick. Hi, everybody. Thanks for having me. Thank you. Appreciate it. Yep. You're good. So let's see whether this is working without any direct Awesome. This is going to be fun. We turned Claudeforce on for Siemens, what, a week ago, Rik? Two weeks ago? Yeah. Stop sharing. There we go. Very good. When did we turn this on for you? A week ago? A week ago. A week ago? Roughly. Yes. Yeah. Yes. And you've built the full sexy command center with a 3D avatar of your co-founder by now as well, right? I actually had my team build a little avatar of you— Did you? —which I wanted to— No way. —show up here, but they didn't make it in time. You know what? I kind of deserve it. They didn't make it in time. I kind of deserve it, actually, if you did that. Yeah. Okay, well. That was our thought as well. Why don't you show us where you are? Yeah. Okay. I mean, first of all, to start with, we are really excited, and I would fully agree from a Siemens perspective to what you have been calling the interface revolution. We believe that this is really the necessary step, and it is great to see that Salesforce is taking that, some might say, disruptive step to open up, I think, the architectural readiness with Data 360. Headless 360 is there, and now introducing the partnership with Anthropic is just a great additional step. As you can see on my machine, I am running Claude Desktop. To also quickly share here in the settings, we are running Salesforce for sales, the plugin. Right. What you just shared. I also had the team provide me two skills. One is the Siemens report, just a layout and how we would like to create reports. The other one is the Salesforce demo masking. We are, of course, looking at productive data here, so we want some data obfuscation for the report we are generating in a second. We were coming up with this on Monday night. We were sitting in the W with his laptop, thinking about what to prompt. He is like, "But the problem is it is going to send production data." Miguel was trying to figure this out as well for his demo. I said, "No problem. Just tell Claude before it outputs the answer to obfuscate your data, and it will do it. Right. It does. We will take a look. So, what I prepared for the demo is basically a prompt, where I want Claudeforce to list me the top 10 Dutch accounts, and their opportunities. I want it generated as a report based on the skill I was just sharing in the skills section. I think, let me now hit Return, and of course, we are going to have to bridge a little bit of time here. We will. The system is starting to think and accessing our data. This is the fun thing about these demos is the AI works for a little while, and so you have to riff in between. The voice demos are also challenging because if you do not mute in time, then they do not. It is like a whole new world of figuring out how to do these demos. How was that for riffing? Did I go long enough? Nope. Nope. Nope. Nope. Maybe we can quickly discuss where we could take it next. Well, actually, maybe before where we go next, this is, you said, a little bold for Salesforce to do, but maybe equally as bold for you. This is an AI that now, click again, I told you the AI is constantly asking you. This is an AI that is looking at and reading your Salesforce data, and in some cases maybe even writing your Salesforce data. Yes. Maybe a scary thing, but you jumped into it. Why? Because we believe, as I just said, the revolution has just started, and maybe you are delivering the blueprint for what many other companies would follow. You maybe saw our CEO also on stage at the keynote. I think for him as well, it triggered somewhat some kind of process that he says we need to maybe open up in the same way. Yeah. You are the number one in CRM, so you have all the data about the customer and about how you are serving the customer. We have all similar paths. Another thing is that this is what I would call the Claudeforce version one, which we are now launching. Yeah. It takes away the need for many of our sellers, people in service and marketing, to really go through the already established interfaces, which we know from the past. It would most likely start with reading data. Yeah. Combining data. You are starting with read. We are starting with read. Kind of read and synthesis of information. Correct. Yeah. But of course, the real magic would happen as soon as we would be able to also write in a meaningful way back into the systems. Yeah. Because that is then doing exactly what you also were pitching. Yeah. It takes away the elements where software has the human do all the work. That is, I think, the next level of productivity, which we of course also want to achieve. Absolutely. There is maybe even cool things we can do together. We should've started this one before, just like I did the other prompt. It's rocking and rolling here. This stuff is going to get. Still going? Still going. This stuff is going to get way faster over time. Really what's happening in the background, it's not latency within the platforms. What it is overthinking, is what it is. Right now the AI is over-reasoning over the tools that it has available to it. All of that can be tuned as we move further in, and this is exactly why we want to get this out to as many customers as possible so that we can identify where you have what should be a simple question— Yes. —being over-reasoned on as you come back in. Another way to solve that also would be to change the model and go to something like Claude 3.5 Sonnet, which will do much less reasoning and thinking, and it'll just kind of immediately, the bigger the model you use, the more thinking it's going to do. Which by the way, is also more tokens. So, that's relevant as well. Let's see if we can expand. See, it gives you a little expand on that. Yes. It might not. Oh, there. It did, yeah. It is still working. This is what it is doing. You can kind of see all of the thinking, actually. This is what is called the chain of thought. You are actually seeing step by step what the AI did there. It got the Dutch accounts. Now I need to This is literally, it is writing down its thinking as it goes, and this is incredibly useful information for us from a tuning and performance perspective as well. Yeah. If we have the telemetry to look at it. It should be ready any second, but I think it's also worthwhile mentioning the additional connectors which we would be able to bring in over time. Yeah. Connecting to the Microsoft Office environment, having all the Office 365 topics, like conversations with customers, emails, documents, exchange tasks I noted down, documents I've shared in SharePoint, et cetera. Bringing that in as additional context is of course something which would also be a very meaningful addition. I think the teams are working on making that already happen. Then the SAP connection is also something which is kind of powerful because we do billing, cash collection, everything on the SAP side. Having the end-to-end view on what's really happening in the different customer accounts. How much of that, from the Salesforce side, we've kind of solved a lot of that for you. You said teams working on it. For the other platforms, maybe not so much yet, right? You guys are wiring it up yourself? Right. We are wiring up it ourselves, but I would expect that you're going to have connectors which are maybe then double tested or double checked with the different other tech partners to really have it rock solid. Yeah. And then out of the box basically. Yeah. Yeah. Yes. I got you. This is— This is what I meant when I said fast and efficient isn't going to work out. We're still rocking and rolling here at four minutes. I did somehow prepare for that scenario, and now something's happening. Oh yeah, you might have one already. I've created the. Okay. Here we go. Oh, there we go. Here we go. It's okay. Perfect. I would maybe just open it here in Google Chrome so that everybody can see it. It wants a nice extension, but I think here we go. There you go. Those are now the top 10 Dutch accounts, obfuscated as I said before. You would find it by value in the Siemens report as we defined it in the skill upfront. You could drill down into the opportunities, so you see where your pipeline sits, what the status of the different deals is, and which stage they are, whether they are closed. Then also what patterns maybe stand out. Win rate, cancellations. You could take it, of course, and dive deeper and double-click on the different elements to better understand what action you might want to take or to identify what maybe other people did to fix situations like this in other customer scenarios. Mm-hmm. You will notice it did something which I didn't expect, which is it actually went and got your real logo. It probably even went to your website and stole some of your CSS to kind of make it roughly look a little like your— That is the skill I showed before. Oh, you built that. We did a little bit of tweaking in the background. Oh, you did that. Okay, great. Yes, exactly. Amazing. Because then we know that the system would always provide it in that kind of style and layout. Incredible. Yeah. Incredible. Where are you going next with this? As I said, I think we want to make sure that Claudeforce is really used across the organization. Yep. We have now the pilot going on with 25 users. The first initial feedback is excitement. People love it. I think we want to sit down and need to figure out what we are agreeing in terms of the pricing model behind it. Ideally, we can bring it out to our sellers ASAP and then innovate from there. I think that is what now the market is expecting. I think we can speed up the transformation of our company with your support. You have 25 now. How many do you think it could be? 18,000. There you go, Miguel. Yep. 18,000. Amazing. All right. Rik, really appreciate it. Thanks so much. This is super exciting. If you have any problems, and you will, you will run into a few, you, yeah just come to me and we'll get it fixed up and we'll— Exactly. —we'll chase those 18,000 users. Perfect. Appreciate it. Thank you. Thank you so much. All right. From here, we are going to shoot it over to my colleague, Rohan, and we are going to start talking about trusted context and data. Rohan, over to you. Thanks. Getting the slides up. All right. It is fantastic to be here and be with all of you. Rohan Kumar, I joined Salesforce three months ago, and it has just been a lot of fun. As Patrick started off, there are two big focus areas. Obviously, how do we get all the value that we have to be agent readable? That is a huge focus with headless and the work we are doing there. The other big piece that I will get into is, we are transforming to become a data company, and I will talk about why is that and the importance of why we need to go there. It is interesting, you look at a lot of the value that AI is accruing, there are two very important things for these agents to be very successful. That is the model itself, which has the intelligence. It knows a lot about the world. The challenge is the model does not know anything about the business. When you look at customers, products, employees, and how those interactions happen, the history and memory of how your business functions, a lot of that the model does not understand. So by itself, no matter how intelligent the model is, it cannot reliably reason and act on behalf of your company. That is really where the data and the enterprise context, stuff like that, understanding of your business becomes very important. The challenge is building the enterprise context is very hard. You look at the data is in silos. A lot of times the decisions that get made, they get made in meetings. There is no structured way of capturing all of that. Without having that comprehensive understanding, this is where agents hallucinate. When you look at how do you build trust inside agents to do complex stuff, getting that enterprise context right becomes very critical. What I will walk you through is how do you go create that. Creation is one thing, but this is the most important IP of a company. With these agents, you have to make sure that you secure it, and then you have to manage it at scale when you have a huge workforce that is running in your enterprise. The first step in terms of creating the enterprise context is you have to get your data ready for AI. What I mean by that is today, if you look at any reasonably complex enterprise, they have many SaaS applications which have very high value data. They essentially have data lakes, data warehouses, storage systems, but a lot of high value data is getting stored. It is actually really hard to even discover this, right? We have this product suite called Informatica that essentially helps data leaders in an enterprise discover all their data assets, clean them, connect them, figure out the semantic meanings, and make that take that first step of having the data ready for AI. So before the agents really understand your business, it is important that our customers understand their data assets in the first place. So that is step number one. Now, once your data is ready, the next step essentially is to create what is called the enterprise context. There is a difference. Data being ready means you can have a bunch of structured data in your SQL tables that needs to be synthesized into figuring out what does revenue mean for the company, right? So that is a higher level concept as an example. Or what customer segmentation means for you. To sort of create that context, we have this product called Data 360, which essentially not just relies on Salesforce data, because there is obviously a lot of your enterprise data that is outside of Salesforce. We have built this cool technology called Zero Copy. What that does is it is able to reach into all the data systems that have been discovered by Informatica. Remember the first step? Without physically copying the data, it looks at the metadata of each of these systems, and it is able to synthesize the right context, in a central location. So that is the second step. So you have made your data ready for AI with Informatica, and then Data 360 using the Zero Copy is able to get your Salesforce data and everything else into your context layer. Now, once you have built out the enterprise context, the third step is essentially creating your semantic model. Semantic model essentially is your business glossary. When you think about what does customer churn mean, what does ARR mean, what does customer health mean? These are not just some static fields that you see inside a database. These are business metrics, business relationships that have been created over decades, which are very important, like this sort of information for an agent lens are becoming very important. So Tableau is the tool that we have, the product suite that we have that helps you create these semantic models. It is interesting, these manifest as dashboards today, right? If you look at Tableau is known as a BI tool. It creates dashboards, and of course, dashboards have been commoditized right now, like every AI tool helps you create dashboards. But the value of Tableau is never the dashboard itself. It is the semantic model layer that gets manifested as a dashboard. So in fact, if creations of the dashboards become very common, you can do that in every AI tool, the value of your semantic models essentially has really gone up. Because if your semantic model is not right, then all those dashboards are actually giving you false information. So that is really where Tableau comes in. Now, you have all this trusted context plus semantic models that you have created that is available to all your agents. This is great because it makes the agents a lot more accurate because they are working on a deep understanding of the enterprise, and then it also makes them more efficient, so they are not burning a lot of tokens. I think the point that Patrick was making where if you do not have the right data organized, then the agent is spending a lot of time trying to get to the right information, which is where they are spending a lot of cycles and a lot of tokens, so it becomes very expensive. So creating this enterprise context early on lands up becoming very important. The challenge, of course, is once you have all this information, now if you put yourself in the shoes of the security leader, it is extremely risky because if these agents that are using this context start leaking it, deleting it, that can become a huge problem. So this is where we introduced this product called Salesforce Guardian. It is the evolution of what we have at Trusted Services in Shield. In Salesforce, we basically had capabilities like encryption of your data masking, et cetera, to protect your assets. That is evolving into two additional capabilities. One is called Agent Identity, which is the embodiment of how the agent runs. For very complex tasks, you do not want the agents to run on behalf of the user because that gives them a lot of privilege. You want them to have identities which can be controlled. So that is one. The second thing is actually protecting this enterprise context itself. Like capabilities that can actually classify your data, mark things which are highly confidential, and have specific data policies that actually protect those. So that is how you secure AI. Finally, as this digital workforce starts getting built out, you can imagine you can start with tens of agents, hundreds, and then get into thousands of agents across your teams, platforms, applications, et cetera. That becomes a nightmare for the CIO, for the IT leader to go manage. This is really where, for several years, IT leaders have relied on the product called MuleSoft to manage their APIs which connect their business. That is what we are evolving into this product called Agent Fabric. Think of it as a single registry that helps you manage all your agents. Not the ones that have been built on Agentforce, but they are built on any provider. We basically are able to scan, monitor them, and do things like FinOps to really look at what value you are getting out of the agents, versus what you are spending on them. All right. Let me actually jump to the demo and actually show you specifically Agent Fabric and Salesforce Guardian, because there are two very important It is not very obvious, these sort of the boring tasks that need to be done in an enterprise, but it is extremely important that you get this right. So this is basically the homepage of Agent Fabric. As you can see, we essentially tell you there are 726 agents that are running. What you see are all the scanners. So these are basically tools that are running continuously in your enterprise to discover new agents as they are coming up. Right. If I go take a look at the Agents tab, let us go to the list view. You see on the provider side, agents from Azure, AWS, Google, Agentforce. All the providers, if I want to go deeper into any specific agent, let me just pick one of them. It is the recruiting agent. This was shown in the demo yesterday. As an admin, I get a bird's eye view of all the skills that the agent has. This is important because it helps you understand the logic that the agent is using to come up with decisions. As an admin, I can go deeper, look at lineage. Here is where you see the integration across products. This is the grounding data, the enterprise context that this agent is using. All this information has come from Informatica. Remember, Informatica helps you discover all your data assets, and that has been integrated into Agent Fabric. If I am an admin, I can actually map these data sources onto the agent, and I can look and say, "Hey, is it hallucinating?" I can come and debug things over here. The other important thing is you want to monitor these agents as an admin. Like what is the average latency? If these agents are front-ending your customer experience, then you really want to know how long does it take for the agent to respond? What is the error rate? How many policies have been violated? Then what is the total number of requests? How much of volume is being sent to the agent? Because that will be directly related to your cost. Here, as I see, the specific agent is seeing a spike in the number of requests. Let me go dig into the cost management piece of it. Here is where Agent Fabric does a really good job of enabling the IT leaders to manage their budget really well. You can think about creating sections of your budget, if you will, for a certain class of agents, and that is the maximum amount that they are about to spend monthly, and then you can manage things like that. Another interesting thing that Agent Fabric does is that behind the scenes, it actually observes the work that the agent is doing to come up with recommendations in terms of what changes can be made to make this agent a lot more optimized in terms of token usage. That is directly impacting the cost. In this case, I can go to the agent I was looking at. There are all these optimization opportunities. Obviously, you have to be careful that these do not change behavior of the agent, but assuming that is true, that it does not, then I just go apply, and that is it. Basically, that is very simple. You can manage and govern the agents, you can look at their performance and the value creation that is happening, and manage their cost. It is going to be very important as the volume of agents grow. That is the IT leaders part of it. Let us take a look at Salesforce Guardian. You will see the way we are trying to create this is you have this notion of a security score, which is overall, what does the security health look like? How many assets that you have across your enterprise context that are being monitored here? You see it is about 94% coverage. The two very important things when it comes to agents are essentially agent identity. As the agents do their work, we actually observe every action that they take. Now imagine, the scale at which these agents are running, and based on the actions the agent are taking, you determine whether this agent carries risk or not. For example, the agent was supposed to do X and is doing ABC. They are deviating from what they are supposed to do. We capture those as observability logs, and then analyze that and determine the risk of the agent. You see in the dashboard over here of all the monitored agents with different levels of risk, two of them have been called out as high risk. That is something for the security to take action on. The other important part is these data assets, which is your enterprise context is built out of a certain volume of data. How much of that data is being classified and understood? If that percentage is low, then there is a lot of risk that these agents might be touching data that you do not want them to touch. Anyway, that is just a bird's eye view of how Guardian works. Agent Fabric for the IT leaders, Guardian for the security leaders. Beyond just selling you the agents, it is this whole manageability piece, the security piece that lands up becoming very important. All right, we can go back to the slides. All the stuff that I just showed you is things that we have today, right? All these products, there is a method to the madness. It is not just a random suite of products that we have. The journey that I walked you through is exactly what an enterprise would do. The interesting thing now is I am going to pivot a little bit into the future of this Data 360 layer that you saw in the stack, how that evolves into what we are going to call the enterprise AI harness, and what is our perspective over there. It starts with the frame essentially is every role in the enterprise is evolving. We have sort of spoken from the perspective of the business users, but like I said, the IT leaders are going from just managing devices and apps, to sort of managing these agents. You take a look at the data leaders. They are not just managing data warehouses and lakes. Creation of that enterprise context that makes the agents accurate and efficient is going to be a very important part of their job. There are things like that for most of these roles, things are going to change. What is an enterprise harness? This term has sort of become like one of these platforms terms, right, which is extremely confusing. Fundamentally, this is the link between what your AI models, the intelligence that you have, and then the understanding of your business. The harness is essentially what brings it together for the business outcomes that you desire. In Salesforce, this is the stack that we showed. The bottom layer, Data 360, essentially is going to evolve into this Salesforce's version of the enterprise AI harness, and it has six capabilities. I will not go into the depth of each of these and an AI control plane that brings it all together. Fundamentally, today, there is a lot of discussions around harness to protect a single agent, right? Where does the agent run the runtime of that? The evals, which basically tell you whether the agent is efficient or not. You make changes to the agent, and then depending on what responses it's giving, you manage that against your evals. Think of that as your test set. And those are the only two things that enterprises are focused on. We believe there's a much larger play over here. Starting with trusted models, which is we wanted to give you a choice in the models that you pick. You don't need the most expensive of model for everything that you do. As a platform, we need to figure out, based on the outcome that the customer is seeking, based on price performance, what's the best model to pick? Trusted context is everything that I spoke about, which is synthesizing your business understanding, your semantic models, all of that sort of stuff. Agency and actions is how when a customer describes the outcome that they're seeking, the agent and the model, they create a plan, a sequence of steps that need to be taken to execute. That decision making comes in the agency framework. And then the actions, the trusted actions, is how you execute each of those steps. And every step that gets executed has to be governed just to make sure that the agent is not doing anything that it's not supposed to do. And then trusted governance is essentially getting all your data policies right, because that's going to influence how your trusted context gets created. And security is about agent identity and data protection. It's a very comprehensive view that at Salesforce we are taking in terms of harness definition, not just protecting the agent. But if you can wrap your arms around the harness, you should be able to bring that with the headless APIs to the AI of your choice. This is really where we are going towards the future. An example of the model choice is what we announced in the keynote yesterday, Koa. It's actually very exciting. It's the very first CRM reasoning model from Salesforce. We basically post-trained the open weight Nemotron from NVIDIA. Like 27 years of deep product understanding and appreciation of the CRM workflow, more than 10 years of data and AI research have been baked in, so there's a lot of value. Very excited. And this model has been designed for long-running agents. And what I mean by that is agents that can actually create a chain of thought which has multiple steps and make decisions at each step. You can imagine a complex sales opportunity where what's the next best step to take to go make that happen, or a very complicated service case that an agent is dealing with to get the customer to a better state. For complex situations like that, Koa can greatly help. Very excited about it. And then finally, evolving agent fabric into this AI control plane, which essentially helps you discover all your agents, govern them, connect multiple agents through standard protocols, and eventually do your FinOps, the cost control, all coming together. That's a big part. One important thing is it's a very open and composable system. While Salesforce is going to have a very comprehensive answer for each of these challenges, because we believe without having a complete solution like this, production deployment of agents is just not going to be successful. That's why we are taking a very holistic approach here, but it's open and composable. We realize that our customers may have a different security vendor, a different data vendor, or a different vendor for the AI control plane. All that's fine because through our headless API, we are able to integrate with each of these partners. That's a big design point from the very beginning, saying we have a complete solution, but you don't have to use everything from Salesforce. The thing that I'll finally say is, while we are sort of evolving this into the harness, the approach we are taking in terms of building this product is very incremental. If you're a Tableau customer, if you're a Data 360 customer, if you're a core platform customer of any of our clouds, Sales Cloud, Service Cloud, et cetera, MuleSoft, you already have taken steps towards actually getting into this harness because we are breaking down the capabilities of all these products and bringing it together in a very composable and a unified way. It's pretty exciting. I think this is something which is going to be very important for our customers to do their agentic transformation right. Would love to hear your thoughts on this after the session. Thank you. Thank you, Patrick and Rohan. The demos were sensational. Next up, we're going to have Miguel and Alexa, and I want to just jog your memory. A year ago, Miguel was on stage, and Miguel was our Chief Revenue Officer. His remit has expanded. He has all of go-to-market motion now. That includes customer success and partnerships, and along with that, Alexa's role has been elevated. How about a big round of applause for Alexa now, our new President and Chief Revenue Officer. I couldn't think of a more critical time to have you on stage, so thank you. Thank you. Thank you, everyone. Rohan, Patrick, thank you for teeing it up so nicely for us. Alexa and I are the lucky executives that get to take this amazing software stack to market. I was here a year ago, same exact location, I think it was October. How excited we were with the momentum that we were seeing in the business, the massive opportunity ahead of us with the agentic enterprise, and how we were investing heavily. The slide. How we were investing heavily and wisely to capture the opportunity. The interesting thing is, months later, we started hearing this chatter, this noise in the market, something called SaaSpocalypse, or the false narrative that AI was killing SaaS. You know what? We are very competitive. We are like, "What the hell is going on? This is not what is really happening. Luckily, the markets are starting to come to its senses, and fortunately, I think by now, all of us, I think we believe that it's time to put this false narrative to bed. Because the reality of the business that we've been operating on for more than four quarters already, more than a year, is the piloting phase of AI from two or three years ago came to an end. That's what we told you, and people were going in production at scale, betting on the big software platforms like us. That's been the case throughout. We call this new phase SaaSceleration. Some people call it RenaisSaaS. My accent is not great, but you get my point. The message here is AI is not killing SaaS. In fact, AI is making software vendors like Salesforce more relevant than ever, because AI needs the trusted context and the secure governed deterministic execution to drive value in the enterprise. That is fundamental, and we have all the pieces of that software infrastructure that you saw earlier. I'll give you a small anecdote. It just happened to me in the last meeting before coming here. I was meeting with one of the largest PE firms in the world. There aren't that many in this category. One of the leading partners, he was telling me they have 300+ large portfolio companies. 75% of them are on Salesforce. He told me something that I wrote down on a piece of paper that was pretty amazing. He said, "Miguel, I just want you to know that the Salesforce platform, your business application is the most prolific of all the platforms." He named SAP, he named ServiceNow, he named Oracle, he named Workday, in terms of driving value with AI to our portfolio companies. I'm like, "You're going to come on stage with me later and say that?" But he's conflicted because he's probably one of you. He may be here, I don't know. But the net is, it's a really renaissance era for us. These are the three key messages that Alexa and I would like to share with you today. Number one is we see increasingly strong demand in this area. AI is accelerating SaaS. We continue to invest aggressively, again wisely also, in the top AI markets to capture this opportunity. Very similar message than Robin and I delivered last year. Second, this is a bit new because we were learning last year. We, and Alexa is going to go in detail on this point, the second point, we have now many different levers to monetize AI. We identify a bunch of drivers that are making our customers buy packaged solution with AI embedded, and we also have multiple commercial frameworks to monetize that opportunity. We're meeting customers where they are. Not every customer is in the AI transformation journey at the same place, but we have a pricing, a commercial model for each of them. Then finally, hopefully, I was worried that you guys came today for this event and then left, and you were not at the Monday, Tuesday, the keynote. I'm very glad that two-thirds of you were at the keynote. Hopefully, you have talked to a lot of customers. I have talked to a lot of customers myself, and every meeting I had to pinch my cheek. I am like, "Oh my God, this is so incredible what the customers are telling me." The proof is in the pudding, and you have heard from many customers on the keynote, et cetera. You are going to hear from two more customers. We heard from Rik Janssen. We are going to hear from The Adecco Group. We have heard the marketing story. We are going to hear the real story here by their technical team. We are also going to hear from Anthropic. It is super exciting when you hear from customers. On the first point, I will cover the first point. I know that you like this slide on the left side from last year. Robin Washington and I, we were very confident about the business. We knew that things were going very well. We have had really strong and healthy succession of quarters. We told you last year that we were going to see an organic subscription support revenue re-acceleration within 12 and 18 months. Guess who said 12 and who said 18? This is like a partnership. It has been 12- 13 months. We have guided Q3 subscription support revenue. If your models work correctly, you will see that there is the beginning of a re-acceleration. Why? Because of what we told you last year is the chart on the left side. The magic word, net new AOV growth. Net new growth at that point when we were here, the lines were crossing. We knew they were crossing. They did cross in Q3. The net new growth outpaced the AOV growth. Mathematically, when that happens, the AOV accelerates. AOV always grows, obviously, but it was decelerating for years. Why? Because of this. Because we have some years after COVID where the net new AOV was actually even negative growth, and it was pulling down the AOV growth. Since Q3, the last 12 months, the last year, net new AOV growth has outpaced the AOV growth. We feel very confident in this net new AOV momentum going forward. Look at the business metrics. Most of them, I think all of them we have already shared at our earnings. cRPO, not a bad number, 14% we delivered in Q2. We have guided 14% this quarter for Q3. That 14% for Q3 does not include the Contentful and Fin acquisitions that we just closed last week, this week. Pipeline at record levels. That is a little bit of a new info for you guys, but it is in the very high teens, very healthy. Coverage ratios are healthier than other years with increased commits, obviously. It is looking good across the board, across segments. Contract lengths are increasing. We gave you this stat in Q2. We do 100,000 transactions per quarter, give or take. A lot of them are renewals, many of them are new bookings. It does not matter whether we are talking renewals or new bookings, we did the average of everything. It does not matter the segments. We took every deal band. Contracts were expanding in every deal band. That is good. Then you add the fact that seats, Sales Cloud seats, and Service Cloud seats. Remember, the world, in SaaSpocalypse world, the world is coming to an end. There will not be any more sellers. There will be no more service agents. Guys, you have a seat-based model. Salesforce is going to collapse. We haven't seen still any decline on number of seats for sales or number of seats for services. We are not even worried. When that point arrives, which so far it hasn't arrived, it's still growing. We have so many new commercial frameworks to monetize the AI opportunity that we'll be okay. But so far, it's increasing, of course. Slack seats are flying through the roof. It's the hottest product right now, I think in enterprise software, definitely within Salesforce, but I think in enterprise software. Then the consumption, AWUs are exponentially growing. Pretty much every quarter, we do as many AWUs, Agentic Work Units, which is the closest thing. It's not tokens, it's the closest thing to productive work delivered to the enterprise. We do more in one quarter than in the history until now. Obviously, mathematically, that will have to stop at some point, but it's a lot of consumption, a lot of customers, Agentforce customers consistently consuming. By the way, I didn't mention something, I think it's going to be in one of your slides, Robin. Every single AI company, the same AI companies that were going to kill SaaS and replace all the CRM systems, all of them are going full in into Salesforce. In just one year, this AI segment, we multiplied by, actually it's 400%, nearly 6x fold the business that we do with them. Not bad. You take the top nine AI companies in the world, the top 10, nine are wall-to-wall Salesforce. The 10th one, probably you can imagine who the crazy company is. It's an amazing company, by the way. They are actually not wall-to-wall, but all top 10 run on Slack, and nine out of 10, wall-to-wall Salesforce. They're multiplying by six the investment that they're doing in us on a year on year. These business signals are clearly not a SaaSpocalypse situation, so I'm not going to use the word SaaSpocalypse anymore. I hope you don't either. The market will come to senses little by little, and we are ready. Now, because we see this momentum, because we are excited, because we are talking to customers, because we are seeing the demo, because we're seeing the new surfaces, because we, I, Alexa, all our teams, we are now working. I go to work, I think I'm going to a video game. If you guys see my surface where I work, you don't believe that this is a serious company. This is like I'm having so much fun. I have a screen that looks like Patrick's demo. By the way, when we finish this session in the break, one person in my team is going to show you my cockpit, which is a skin that I put on top of Claudeforce. The good thing about Claudeforce is you can say a few things to Claudeforce, and it builds a new skin on top of it. Until yesterday, I couldn't demo, definitely not to the finance community, because particularly this is a public event, and it's broadcasted. You will see all my numbers, the numbers for Q3, which I'm sure you're super interested to know. All of them are going to be on my laptop. Ning, who works in my team, is going to show it to you. But we told something to Claude this morning, "Create a toggle button on the top right that says demo mode." So when she clicks that, everything that is data in our metadata model, everything that is data gets blurred. But she's going to do from time to time like this so that you see that it's real data. Because I think, Alexa, your demo is going to be dummy data? Dummy data. Okay. It's on Slackforce. It's another surface. It's the real system. But it's the same system with dummy data because you didn't ask Slackbot to do that. But if you do it- I will but listen, it's fun. And if it is fun for us, it's fun for our customers. Rik, he's just playing with it. I feel bad for him because he's just been playing with it for two days, and he was here in front of the world doing a demo. And this is very basic, what he just built. Imagine if you build that, you iterate one week, and you have the most amazing dashboard in the world, driving value to you, sending you signals. Every time that you put a prompt, you're creating an agent that does things for you. So I don't log into Salesforce anymore. Parker, thank you very much for leading the way. I think it was here when you said, "I don't understand why people will log into Salesforce in the future." You were totally right. I was sitting there, I'm like, "This guy is crazy." Okay? He's my age, basically, but white hair. I'm like, "This guy's becoming crazy. What?" But he's a visionary. And I pretty much a month later, I stopped logging onto Salesforce, and I use Salesforce 100 x more. Okay? Because of all this excitement, we are tripling down, investing in capacity. Also, under my new role, investing across the success area, FD's, builders. I have 20,000 more people in our remit because we're bringing the whole go-to market together. And I gave all of them one focus. And you guys can imagine which objective I gave to those new 20,000 people in customer success, professional services, partnerships. One metric. You can speak. Net new AOV. Not you. Not you. Look at the chart. Net new AOV. And why net new AOV and not customer success? Because net new AOV means is the ultimate metric of customer success. If customers buy more and are happier and adopt more, which is net new AOV, okay, it's good for everyone. So anyways, things are happening. We are doubling the capacity. We've added 30% more AEs in the last two years. And at the end of this year, we're going to have double-digit growth, 10%- 12% growth, more AEs in the core countries than a year before. We're also adding 1,000 builders as we speak. So we are very confident in the momentum, and the direction, and the net new momentum going forward. And then we are very confident about the software infrastructure. No one remember the words from the PE person. This PE person represents 180 companies, and these are not Mickey Mouse companies. They are pretty big companies because this is the biggest PE firm in the world, one of the biggest. We are the platform that drives more value to the end customers through AI because people want to consume AI through packaged applications. This is the trend. We take care of all the complexities. We take care, like ClaudeForce. Everybody can connect MCP servers and build their own MCP servers. You want to do it securely. You want to do it with zero data retention. You want to do it with all the skills that matter. That's a power of our platform. We are very confident. With that, I'm now going to hand over to Alexa. We already applauded her. I'm so proud to work with you. She's amazing. She's a force of nature. It's money time. Money time. I didn't get walk-up music. I was sitting in that seat wondering what it might be. Thank you, everybody, for having me here today, and thank you, Miguel, for the introduction. You guys don't know me yet, so maybe I'll share a quick personal tidbit. I grew up in a family where we had a motto that was [Non-English content] so through difficulty to the stars. I think it was really appropriate for what we've experienced over the course of the past couple of quarters, because difficulty, I think, sometimes is a necessary condition for success. I think what it did for us, as painful as it might've been, was forced us to get really clear on what our customers needed from us in that moment, and also what we do incredibly well. I think at the intersection of those two points is we discovered that our customers had a huge amount of trust in us, and our customers needed us more than ever to help them transform. That's what we've been really focused on. We're sort of ignoring the noise and focusing on how do we go execute to drive against that customer expectation of transformation and trust. Candidly, I'm even more excited to step into this new role in a period of, we won't use the old word anymore, but in the SaaSceleration or the renaissance. I think that difficulty has been a huge learning aid for us. Let me sort of help you understand a couple of things. Three things on this chart, although it's going to be a pretty dense discussion of those three things that I want you to take away. The first is that we think we have an incredible opportunity to go monetize AI. The TAM is exploding. I think that the word we will not reference anymore did not incinerate opportunity for software. It expanded it. Robin will talk a little bit in her section about some of the hard numbers and how we see that spread out across industries and customers. I think one interesting way to think about it is the expansion of knowledge workers. There are, give or take, roughly 1 billion knowledge workers today. We have 50 million of those knowledge workers, roughly, on our platform. There is huge upside to go capture a really significant portion of the market, and that is before we ever think about an agent as a knowledge worker, which I think is going to geometrically expand that knowledge worker base. There is so much that we can go do here. That is the first piece. I think the second piece is to think about how are we going to put our capacity. Miguel talked about all of this capacity that we are investing into the market, double-digit growth in the builders, and you are going to see us, I think, do a couple of things. The first is recenter on the markets where we think AI is going to grow the fastest. I think top markets has always been pretty central to our strategy. I have been here for a decade. But we are going to double down on the nine markets that we think are the biggest and are going to grow the fastest, where we have infrastructure to go in and accelerate. It does not mean we are not going to invest in the rest of the world. It does not mean we are not going to look for opportunities to move really quickly, and find upside potential that we have not tackled yet. But you are going to see us concentrate our put all the wood behind the arrow and go concentrate our effort and our energy. We are also going to be really thoughtful about what does the capacity mix need to look like. You saw the stat that we have scaled. We will exit this year scaling to 1,000 builders. As I sit with customers, and I probably met with, gosh, I do not know, 150, maybe getting close to 200 customers this week at Dreamforce, 75 CROs yesterday. The number one theme coming out of, I spent two hours with some of the top CROs in the world. The number one theme coming out of that session was, "Help me build this." They saw Claudeforce, the demo that you saw Patrick show earlier. They also saw a version of how we run our business in Slack. There will be other examples of that on other surfaces. They want and need us to help them build that. Part of the capacity modeling that we are doing right now is thinking about, I do not want to show up to a customer or anyone on my team to show up to a customer with a PowerPoint. I want to show up and build a prototype, and I want to push that into production as quickly as humanly possible. That is sort of a thought in terms of how are we mapping our capacity to the demand function that we see. Then I think in the spirit of how we started, we are being pretty thoughtful about, okay, what are the demand drivers. What are the patterns that we see. What I would tell you is this is indicative, right. You guys are talking to customers, and I think you recognize that there is alternate patterns, but I think this represents probably the most common one. Let me sort of walk you through what I see more often than not as the way customers adopt the platform and how we are sort of thinking about driving that monetization motion. The first, when I talked about knowledge workers, is we unlock new categories of knowledge workers. We unlock additional seats. Miguel talked about, we are really confident because I see seat expansion without even uttering the word AI. I see seat expansion as an opportunity. Everyone in the room is familiar with Replit, one of the fastest-growing digital native or AI native companies. They scaled from $10 million in ARR to $500 million in ARR. We scaled with them. Those are core sales seats that we landed into the account, and we are growing as they grow. The thing I think that is really exciting is it is not just sales, it is not just service, it is also Slack. You heard the story about Adecco on the main stage. We are going to tell you the real story today, so I will skip that one for now. I think the net message I will leave you with, and I think I heard this in the CRO Summit yesterday, too, people still need to build contact centers. They still need to build out pipeline management systems. They are still going to build marketing campaigns. So there is a big opportunity here for the core portfolio. I think, though, and Replit is a great example of this, as they expanded their core sales and service seats, they started to think about agents. So the most recent opportunity we had to engage with them, they expanded into agents. The place that I typically see clients start is in this employee agent use case. So they want to build out capabilities to make, just like we think about productivity, their own employees way more productive. I was with Bouygues, one of the largest European telcos in Paris, probably back in March, and I did a ride-along. This was really fun. I grew up in Canada. I have grade school Canadian French. They did the entire meeting in French, which severely tested my capabilities. We did a ride-along in their contact center. They have 6,000 people sitting in a contact center just outside of Paris. They have implemented Agentforce for internal use cases for those 6,000 contact center employees to help make them more productive. They wanted to stop swivel chairing, and they wanted to be able to help automate the process of sending texts and emails, searching knowledge articles, first and foremost, 600 knowledge articles, but also doing outreach to customers who are inbounding the contact center. So I think it is a really powerful example of how customers can start with their internal use cases, but they do not stop there. I think once they understand the power of an agentic capability, they start to think about, gosh, I have to get that in front of my customer. CrowdStrike is another really good example. I have worked with CrowdStrike for five, six years. They started their agentic journey as a Sales and Service Cloud customer. We implemented a whole bunch of agents, but the two biggest agents were an Ask Legal agent and they follow MEDDPICC, so they do sort of like a qualification process, and they wanted to help boost their pipeline quality. So we launched those two internal agents for them. Fast-forward, they now have multiple agents in production, but they now run an external agent, their service agent, and that is containing 83% of the inbound requests that come to their contact center. You cannot actually file a support ticket without touching Agentforce when you talk to CrowdStrike. So I think that is a really powerful example of the pattern. As customers do this, you heard Rohan talk about it, invariably, what they recognize is they need to harness their data to make sure that they are hydrating those agents effectively so that they can serve their clients and they can serve their employees. FedEx, another client that I spend a ton of time with, they produce an astounding amount, a petabyte of opt-in data sources, and they are using Data 360 to harness all that data and bring it together. Their two largest data sources are the data lake environments are Azure and Databricks, but we bring all that data across those 600 sources into internal agents that are helping them do a whole bunch of things, but two of the most powerful things they do is look at dormant accounts and look at quotes that have been abandoned. That process took them three or four hours, so the ROI has been tremendous, off the charts. I think that is a great example of how the discipline around agents ultimately drives the motion towards we need better data. As they build out more and more agents, they got to think about governance. ADT is another customer that I spend a lot of time with. I am giving you a lot of bright and shiny ones, so let me give you one that was a little difficult. Maybe a year ago, July 4th, actually, I got a call from Mark saying that he had heard from Fawad, who is the COO at ADT, and that he was not happy with his Salesforce implementation. We obviously parachuted the team in. I think Mark Sullivan got the same phone call. He had had a history with Fawad at State Farm. We had to do a bunch of work to rebuild their data model because what they wanted was to be able to go way faster. They were swivel chairing across a bunch of applications. They wanted to implement agentic technologies, and the apps or the orgs that they built just were not ready to go do that. We suitcased our team in. Great news. They have sunset a bunch of these legacy applications. Everyone is standardized now on Service Cloud. Again, an example of number one, but they are starting to think about, or they are working with us deeply to partner on, okay, as I build out all these agents, how do I do two things that are really important to them? How do I govern them? How do I understand where my agents are? How do I register them and manage their behavior? How do I manage their costs? They are super focused on managing their OpEx responsibly. I think this is a huge unlock for them as they continue their agentic journey. Finally, this is a little bit of a departure, it is a super new use case. I am being transparent and probably leaning in a little bit to an opportunity that we see from a monetization perspective that is really, really new. I love it for a lot of reasons. We did not see this kind of business opportunity at, call it the beginning of the second quarter. In the last 90 days, this has shown up. What we are seeing now is Slack emerge as the agentic operating system for agents. As people launch their agents into Slack, what they need is a super high latency performant pipeline to make sure that they are fueling their agents with Slack data. This is something that I am really excited about. We have probably three deals that we have closed, a bunch more in the pipeline. Think about digital natives as really being the target area for this. The thing I love is that it breaks the association. Miguel talked about seats. I feel really comfortable about the seat expansion opportunity that we have, but this breaks that association. I monitor every digital native and how they use our Slack system today. I think one of the really exciting things as you look at it is that the correlation between API calls and usage doesn't map to headcount. You can have a really small but fast-growing company that is building agents like crazy, and they don't need to have a lot of employees. I think that's really exciting. Finally, we think about more ways to buy. You might say to me, "Well, Alexa, you guys already have a lot of ways to buy." I think this is really important for us, right? We need to meet our customers where they're at and make sure that they've got very flexible, very low friction ways to onboard onto the platform. If you look at Q2, seven of our 10 largest deals were ELAs. I think as we start to launch Salesforce commit more fully across the team, that's going to be a major driver for revenue acceleration for us as well. On a final note, Patrick, I think, showed you this slide. The premium upgrade motion, I think, is going to be a huge acceleration vector for us. For those who aren't familiar, I'll just show you. You saw this before, so let me orient. We haven't introduced a new value edition SKU in over a decade. In the last, call it, eight quarters, the team's been focused on how do we go take that base of core CRM users and move them up the value chain. For every 1% of the base we move, it's $100 million. More importantly, I think it's an opportunity to push all of our customers to fully leverage the rich capabilities that we're offering in Max Edition, including Headless 360. This is something that every single seller, every single person in the company has been enabled on. They understand this is the call to action. I have not walked into a room at Dreamforce and not asked people to upgrade. If you guys are excited about upgrading your companies, you can scan the QR code and learn more about Max. I think this is going to be really powerful, and we've oriented our partners and our company around driving that upgrade cycle and making sure that we work with customers to make them successful on it. I think just a final note, and you heard me talk about the eight quarters. In the eight quarters with, frankly, I would tell you, partial emphasis on this, we've built out $1 billion of AOV. When you look at the mechanics of it, in the upgrade pattern, you see about a 60%-80% uplift depending on the customer and which edition they are coming from. But when you look at the individual account level data, what we see is a 1.4x expansion of the ARR. I think this is really powerful. We are growing, and that is the key message. But when customers renew, you guys can do the math and map the ARR is slightly less than the upgrade fees. They are remixing the portfolio. They are realigning to where they need to go and fuel their growth or their transformation efforts, or the products that they need to fuel their growth and transformation efforts with. Not only does it lead to top-line revenue expansion for us, but I think it also mitigates any fear of attrition in the future. I think this is really powerful, and we are going to put the whole force of the company from marketing and campaigns through enablement plays, programs, incentives, and calls to actions in the field. This is the execution point. Everyone is going to be focused on monetizing the value addition. I will end there on the monetization note. I think there has been a lot of discussion around Claudeforce at this conference, and I think one of the things I am hungry for is to show you a little bit more about how we are using our own tools, Slack included, powered by Anthropic, but Slack to drive our business. Claire is going to help me here. I was wondering if you were in the back actually building a demo toggle into the Slackforce demo. But before, while she is setting up the demo, a couple of things. We are obviously very focused on driving growth, increasing our sellers, improving their productivity. One of the ways that we do that is through revamping from the ground up our sales processes. Forecasting is one of the processes that we know people spend a ton of time on. We have totally rebuilt that function across the go-to-market organization since the beginning of Q3. We rolled out, and let me know, Claire, when you are I will riff. I will do the Patrick riff, see how long I can do this for. We rolled it out at the beginning of Q3, and this is what we use to run the business now. You are not going to see live data, as you heard Miguel talk about. You are going to see dummy data. But otherwise, this is exactly what we use every Friday when I gather my leaders together to run the business. I think it is really powerful. How many people have seen Slack before? How many are familiar with Okay. All right. See, more, they told me you guys were not going to have seen Slack. Okay. You guys know what you are about to look at. Are we ready to go? Okay. Do you guys mind switching over to the demo? Okay, great. For those of you who haven't seen it, this is the Salesforce in Slack. I think this is one of the most power. I use Slack to do 9 million things. I use Slack to prepare for today. I use Slack to prepare for customer meetings. I use Slack to collaborate with my team. I use Slack to run my global forecast process. I am going to point out a few things here that I think are really important. The first thing that you are looking at is a dashboard. Everyone in this room is familiar, but there is way more to it than a dashboard. I look at this every morning when I start my day. Again, this is not real data. I look at this every morning when I start today, my day, to understand, all right, what's happening in the business? What's changed overnight? What should I spend my time on? There is no more precious commodity than time. I want to know where to orient it. This does a couple of things. It tells me where we are at any given point in time, and it tells me who are the drivers behind it, who are the people who most materially represent the opportunity that we have in any given quarter. You can see that here. It also calls out, look, where might you have some exposure in the business? Where do you need to go pay attention? This is the what to watch. Miguel talked about the fact that our pipeline is up this year. If I looked at this and saw that my coverage was high, I think that's basically driven by momentum, but I am still going to go double-check that to make sure that we are operating with the same quality of pipe that we typically do. This gives me a good orientation for what's going on, what do I need to go focus on. Then I might dive more deeply into the forecast by leader. Well, actually, I will show you. This is just, again, dummy data, so it doesn't necessarily show you a pattern. But I would look at this to say, okay, what's happening? Is there a trend that I need to understand here from a macro perspective? Is Europe doing really well and America is slowing down and Asia -Pacific has a problem? So I can look at this global view. But I tend to spend most of my time in the leader view. I might pick as an example, Lenore Lang. Lenore Lang succeeded me in my previous role, so she runs tech media, telco, and our data foundations business, our largest operating unit by revenue and people. I might pick this business and say, "Okay, tell me about Lenore's business and what's happening." I can see here that Lenore's calling $172 million. Slackbot thinks that's high. In this case, again, not real data. I would be like, "Look, I think Lenore's going to crush it this quarter." But it will give me a view of what Slackbot thinks and why it thinks this is going to happen. This is obviously instructive and helpful, but if you think about it, I have teams of people who spend a lot of time. Forecasting is really important. You depend on me to give you an accurate view of what we are going to do. My team depends on that, too. We spend a lot of time making sure that we deeply understand the numbers, but I think Slack can help us do that better and faster. I can actually dive into, for each of my leaders, but I am going to stick with Lenore here, a CTA. I will tell you, this is a real scenario. It did not happen with Lenore, it happened with somebody else, and it was not this deal that you see here, but it was a real deal that happened last week on the forecast call. I can go through and I can understand, all right, this is Lenore's. The overview of Lenore's business, here are her top three deals. I might see that she has got a big deal at a tech company that is at risk, so we will talk about that on the call, and she may give me some feedback about why that deal is struggling. One of the things that I want the team to do is get Mark involved right now. There is not a deal in tech that should not have Mark connected to the CEO, and they are not eager to do that. They want to be perfect. They want everything buttoned down. I want them to do it fast. I want Mark to reach out to the CEO so I know that if something is wrong. When he executes that reach out, I am either going to get good news or bad news, but I am going to get it fast, and I prefer it fast. I am on this team's case right now to go and get that outreach. I can also look at, hey, what is happening in this deal right now? Are they doing SICs at Dreamforce? What are the exec connects that they have happening? Then I can actually go into it and say, "Hey, team, let us get this done," or, "Let us get this text message set up for Mark, and let us have him reach out to the account really quickly." That is just a very quick run-through of how I am using Slack, powered by Claude, powered by Anthropic, excuse me, to run the business. A final note, this is Miguel's favorite example, so I promised him I would do it. I will be in London later this month, and one of the things as we make these trips into the market that we want to make sure we are doing is spend time with customers. I can ask Slack, "What are the top deals in London, in Q3?" It will go through, and it will search, and you will notice it is going to come back. I did not tell it how many, but it is going to come back to me with, I think, seven deals when I checked it this morning. It is going to say, "Hey, here are the top seven deals in London." Further, I can say, "Look, I want you to send a Slack to every one of the opportunity owners for each of these big deals, copy their entire management team, tell them I am going to be in town, and ask them what I can do to help get this closed in Q3." You will see just down at the bottom here, it comes back and says, "Okay, do you want me to send it as a DM? Do you want me to post it in a channel? Do you want me to curate it so that it is fit for purpose for that individual team?" I say, "Yes, that is what I want you to do." Super quick example, but I think it is indicative of the transformation that we are driving as customer zero of this technology, and I think the opportunity that we have to go help all of our customers transform. With that, I am going to pass it back to Miguel, who is going to share two real-life examples of customers we are transforming right now. A lot from the Salesforce executives, and now we are going to hear from the real heroes that are getting this incredible stack and driving enterprise value in their companies. I am going to start with Adecco. By the way, this has been a little bit impromptu because we saw Adecco many times. We talked about Adecco. The CEO was with us at the keynote, great marketing messages, and then right after the keynote, I met with the working team, and they went through all the progress. I typically meet with them every, what, three, four months. I am like, "Wow, this is even better than I anticipated." I had a good conversation with my friend from many years, Pierre Matuchet, in the IT area, Senior Vice President of IT. Now, Pierre joined me. I think they are going to put a chair for us. Give a round of applause to Pierre Matuchet, Adecco Group. You can sit there. Honestly, the reason, his eyes were on fire when he was telling me the progress that he was driving with Salesforce. I am like, "You know what? What are you doing tomorrow night? Tomorrow afternoon." Actually, tomorrow night also, I invited him today to the concert. "But what are you doing tomorrow afternoon? Because I am meeting a few of my friends, and I would like you to be with me and tell your story." It is funny because Denis, the CEO, arrived to the meeting at the end. I said, "Denis, I need to get your approval to get Pierre to be with me at this meeting." He said, "Yes." Here we are. Thank you so much. Let us take a seat. Adecco, I do not know if you, hopefully you know Adecco, but it is one of the biggest staffing global company in the world and HR services. About 34,000 people in 62 countries, about $25 billion of revenue. We are so grateful that you are here, to your CEO, to the partnership that we have had over many years. The first question, if you remember last year, I always ask the question similarly, what was our relationship between Agentforce? Sorry, before Agentforce. Before Agentforce? Yeah. Okay. We were using your CRM for 15, 10 years. Yeah. It was good. Nothing spectacular. We have a relationship. Okay, I hope you like the interview. Not a strategic relationship, not a strategic partnership. We were a bit stuck from our side with 42 instances of Salesforce, so not easy to manage maintenance cost and so on. We need to build some complex mechanisms to have a view of everything. We get more and more requests from global customer, like Amazon, like Siemens, to have the same process everywhere in the world to be able to give them global reporting. We were in Dreamforce and working with your team, we have decided to implement Data Cloud. This was really, for us, the foundation of the change, because in less than three months, we have been able to put all our data in one layer and to be able to run reports. So that was more or less, what, three, four years ago? 2.5 years. 2.5 years. They were stalled. A little bit of a boring usage of Salesforce. They were a pretty nice sized company. Sorry, customer. They were in the eight-digit business. It was good. 42 instances of Salesforce, but it was a mess. It was a little bit of a mess. We were not growing with them. In fact, we were having conversations of even reducing the fear attrition that some customers, they want to use less. That is where we were. Then you implemented Data Cloud. Yes. You killed it. It was incredible. Yes. Data Cloud, three months, bring us new vision of our business, capacity to implement new processes to better serve our largest customer, which represents 70% of our turnover. A very important moment. Yeah. Okay. The way I looked at it is, that really appeased you. You had now a global view of all your orgs. It sort of stopped the bleeding. Okay? You came to the next Dreamforce, and then you saw Agentforce. Yes. I really would love for you to tell this audience with the same passion that you told me yesterday, what are you doing with Agentforce, what agents are you deploying, at the volumes that you are deploying them, and most importantly, what is the business value that you are driving? Okay. I may be a bit long. Okay. No, it is okay. I will do it in English. Even if Alexa asks me, do we do it in French, I will keep English. We have started in U.K. in May 2025. Six weeks to develop our first agent. It was a pre-screening agent. Today, we have seven agents running in 12 countries, representing 60% of our top line. In U.K., our first agent was what we call a screening agent. It means we need to pre-qualify candidates before a real interview with our recruiters. Year to date, we had 2.7 million conversations with these agents worldwide. For us, the key business impact is a reduction of time to present the candidate to our customer. We reduce it by 40% by the usage of an agent. We were with Parker a few months ago in a branch in the suburb of Paris, and Parker kindly visited the branch and had a discussion with our recruiters. One of our lady, as a recruiter, spoke to Parker. "These agents has changed my life, because at 10:00 P.M. to 6:00 A.M. in the evening, before leaving the office, I launch all my agents. They do the job during the night, and when I come back in the morning, instead of having to call 200 candidates, the agent has already pre-qualified 20 candidates." One of the key advantage of this agent is that it is running seven days a week, 24 hours a day. When our branches are closed, we are still doing business pre-qualifying candidates. In fact, a big percentage of that work for the agent is in after hours, right? Yes. Okay, so that is a pre-screening agent. Agent. The screening agent. We have also the interviewer agent, which makes real interview with voice. We are use— Oh, wait, wait. You have an agent, an AI agent that interviews candidates? Yes. Including voice. We are using Agentforce Voice, last name of it. 20% of our calls are currently done by voice, and we do 20,000 interviews per week with our interviewer agent. Wow. This has a direct impact in terms of business. We increase what we call in the hiring area, fill rate. It means our capacity to answer to the orders of our customer by 10% by using these agents. One second. You place 10% more candidates? Yes. For the orders when we put an agent. With the combined human and agentic workforce that you are putting— Exactly. —recruiters. Wow, 20,000 interviews per week. Yes. Love it. What is quite interesting to see is that the agent allow us to go faster. It take us less time to present candidates to our customer, and we present more candidate to our customer. It is speed and quantity we have. Love it. We have the pre-Agentforce with Data Cloud, made a big difference. Then Agentforce, seven agents already. You talk about two of them, global scale, big numbers. By the way, AWUs in the millions. Thank you very much. Awesome. What is happening now? Tell me what is happening this week. This week. You just made a decision. This week we made a decision. Because we are in the world of AIforce. I remember when we went out of the branch in Paris, Parker told me, "It's nice, your story with agents, but did you notice that this lady has to close 15 windows in Lightning before launching the agent?" Do you remember, Parker? You told me when we went out of the branch. Now we have made the decision to roll out Coworker to our 27,000 users. When we were with Parker in the branch, the lady was a bit stressed. Parker was there and everything, and she missed the pass to go to the right window to show Parker the results of the agent. You remember Parker? Now she just has to type in one command in Coworker to do it. Coworker, you see I have some white hair, so I have launched project, failed some, succeed some. It's the first time that I see such a smooth implementation. We as tech people, we are almost no more involved. We have- Was there an implementation or was it just— No, it's just- —switching it on? We switch on. The user group together, they are writing their prompts. They roll out between themselves prompts to do performance management in term of pipeline, how to do a search and match for certain orders. They have created their library of prompts. Now they share between countries the library of prompts. It's just incredible to see how we have changed the surface of managing our business, it means from a sales of delivery perspective, and it gives really energy and joy to our people to have a new way to interact with the system. I love it. The incredible thing, we presented three new AIforce surfaces yesterday. Coworker is the most basic one because it's already there. It's living there. You just need to click, and then it opens up, and it's like a cowork environment within Lightning. We were not sure how successful that was going to be, but then it took the market by storm. We also announced Claudeforce and Slackforce. This one, when I heard the story, the first thing I thought is, "Great, we're going to have a great deal with them this quarter," because they have to pay for it, right? Coworker, if you saw the SKUs, it's only available to the Max or the A1E. This guy, white hair, very clever. He turned that on because he already bought A1E. He's now enjoying getting the structure, the structured data that sits on Data Cloud for the last three years, and now Coworker is really driving insights and helping everyone. I'm super excited. We've driven a lot of value to you. I mean, 10% more placements. I mean, that's your business. It's pretty impressive. We've gone on a journey. Three years ago, big numbers, but declining. I think in the last two years, we've done a few very The most important thing is we drove a lot of value to you. We've been able to monetize part of that value. That's the trick of AI. Our business with them has significantly scaled. We cannot share all the numbers, but when I say significantly, it's significantly bigger, and we are just getting started. Yes, but we need to renegotiate the new contract. Okay. Don't forget. But he has the best contract possible, right? Yes. He signed an ELA seven months ago. The good news is he signed an ELA, which has unlimited credits for all these use cases. He has A1E, so he can deploy Coworker, he can deploy whatever he wants. That's the good news. That's good. The bad news is the contract is a two-year ELA. Yes. After two years, we need to renegotiate. They are such an incredible customer, and my commitment to him is, if you come here on stage with me, we'll take care of you. We're going to share in the value— Exactly. —that we are driving with you. Listen, you're awesome. Thank you so much, and looking forward to driving more value. Yes. You have one more thing to say? Yes, one more thing to say is that we are only at the first step of the agentification of the companies. Today, we have agentified human processes. It means we have taken human processes, and we have agentified them. Now, we are close to open the second chapter of agentification, which is to redesign our own processes based on agent, then to see where we need human. It will be a big change also for us, and all this agentification, in fact, is a transformation lever for all of us. Love it. Thank you, Miguel. Well, please give a big hand to Pierre, and [Non-English content]. [Non-English content] All right. Now, let me do something before I call the next guest on stage. I have this little thing here. Paul. Okay, I'm doing this for you. I do not know if I can do this, but it is going to be difficult, but I'm going to try to do this. I've known Paul for many years, too many, and he's an amazing friend, and I admire him as an executive. What he's done over the last 15 years since I've known him is short of incredible. In fact, he's done something that nobody ever in the history of any company has ever done. You know the numbers of Anthropic. Super thrilled to invite him on stage. Please join me, Chief Commercial Officer of Anthropic. Paul, awesome. Great to have you here. Thanks, guys. Anthropic is not just a great technology company, it is not just a great partner, but is a high growth. Are we going to put the slide? The next slide? Oh, no, it is me, sorry. Nope. After all that discussion about the slide. Can somebody put the slide? Anyways, it does not matter. But you need to remove that one. Anyways, put the other one. It was there. It is not only a high growth customer of Salesforce, but also very sophisticated, are growing very rapidly to the point that four months ago, one of your sales leaders, Paul, was in a public event and she actually explained, nothing to do with us, we were not invited, she explained how she was running her commercial machine, her commercial engine. Then there was a picture there that had Coworker in the center, obviously, but then it had a bunch of pieces from Salesforce. It had Salesforce, Sales Cloud, it had also Slack, it also had Fin. At the time we did not know what that meant. Now we know that Fin is also part of the family. But it was incredible, and it really inspired us to look how are they. Because they were very successful, they were growing a lot, the speed of their execution. So we went in, we double-clicked, we talked to your team, we talked to you, and then Patrick got involved, Alexa, and we are like, "Why do not we just build this for every customer there?" That was the origin of Claudeforce, our partnership. We announced the product itself, which is Salesforce in Claude, this week. I just wanted to ask you the first question, Paul. What are you hearing from your customers? Yeah. Why is it so cool for your customers, for all our customers? This is one of those wonderful products that your customers kind of organically create, ask for, almost pull it out of our hands in that we were inside, as you said, with, I think it was Kate who was basically doing that at the time. We were using Salesforce in Claude long before Salesforce in Claude was the product that it is today. A lot of our customers jointly were doing the same, and you started to do the same internally inside Salesforce as well. Even before Claudeforce? Yeah. It was clunky and we had to connect. Because intuitively, it just makes sense. It's like if I'm working in something like Claude and Coworker, then I want access to the data that's there. How do I pull it in? How do I analyze it in the way that I want to analyze it? How do I bidirectionally read and write, and use it in a very powerful way and with, as Marc calls it, and as you call it, Claudeforce, as we call it Salesforce Claude, how do you basically produce all of the connectors and the skills to just remove any rough edges and just make that a seamless process? It's how I run the business every single day, and it's how our individual AEs prep for meetings and do all of the things that you would expect them to be doing. It just unlocks a tremendous amount of value. Like you have got decades of sunk value and investment that goes into a Salesforce implementation. This exposes that, it kind of supercharges it, and it allows me to intuitively use it, have a conversation with that data, and use it the way I want. You yourself, by the way, this is off-script, but you yourself have been using Salesforce for many years, then you went dark for four or five years. In the dark, you did not know what you were doing. I was not able to use it for five years. You came back to the light. Okay. It is amazing. Our companies use each other technology. Yeah quite a bit. We are a very proud customer of Anthropic. Our engineers, 15,000 engineers, they use Claude Code. We use your models to power Slackbot, which is transforming Slack and our company. We also use a little bit in Agentforce, and we use Claude Tag in Slack. We power Coworker. You heard Pierre— Yeah. —is over the moon with Coworker. At the end of the day, the reasoning engine is you. You are a great user of our technology. Can you give us a bit more detail— Yeah. —on Slack? I think we are probably, I do not know, we might be neck and neck with Amazon, for example, but I think we are one of the most intense users of Slack in the world in terms of for our head count, just how much we use it. It is kind of like the hive mind of Anthropic and where most work gets done and decisions get made. We use it very intensely. We use Coworker inside of Slack. We launch together as well externally, tag an external Coworker in Slack, and code in Slack as well. We do lots of multichannel coding in Slack and all of these kind of pieces. Outside of that, I think last month we did 1.5 million actions in Salesforce using what is now Salesforce Claude. Our sales team is actually relatively small. Like considering the amount of business and growth that we manage, the go-to-market organization is tripling this year, but it is still coming from a relatively small base versus the amount of business that we run. It is the only way that our go-to-market organization is able to manage the volume of inbound inquiries, to manage the volume of meetings that they have to effectively run the go-to-market business using Salesforce and using CRM and using Salesforce Claude. I wouldn't want to put a number on what level of amplification it is, but it is a very significant amplification that allows us to manage the business. Well, we should have licensed by a percentage of your revenues. We missed that opportunity. Yeah. That contract is not up for renegotiation. It's not up for renegotiation. You might be renegotiating it at Adecco, but not that one. Okay. So trust, Paul. You work with us. Yeah. It is a core value at Salesforce. I know it is also a core value for Anthropic, very close to Dario's heart, your heart. Yes. In the world of Claudeforce or Salesforce and Claude, how do customers stay in control of what you guys see— Yeah. —and do with their Salesforce data? Yeah. Look, it's one of the things we most admire about Salesforce is that continued commitment to trust as the number one value. Honestly, trust is what governs the speed of AI adoption. The more that you trust, the more work you will delegate to AI, and the faster you will go from an adoption perspective. What I love about what we've done with Salesforce Claude is that, effectively, you've got decades of experience in terms of how to manage permissions and hierarchies in an enterprise. What sales team can have access to what data, which individual can have access to which data. Now what we're able to do is apply that to the same thing with Claude. You effectively treat Claude as another employee, and you can determine what permissions you are going to give Claude when it acts on your behalf, what data it has access to, and provide the guardrails. Claude operates within those guardrails that you've defined so that we get basically, safety is our number one focus. Trust is your number one value. The combination of those two things should allow enterprises to comfortably and confidently delegate more work to this. If I take this up a level as well, you at Salesforce were a pioneer with us in terms of what we announced recently around Enterprise Frontier Safeguards, where effectively, customers' data stays as customers' data and never leaves their perimeters. But for our most advanced models like Fable and beyond, how do we give you and your customers the tools to look at how AI is being used within your enterprise to spot for potential misuse and patterns of harm? On various levels, we're partnering together, and I think ultimately it will allow enterprises to go faster. Love it. That was a great partnership, by the way. So really not related to Salesforce, although everything relates when it comes to AI, I am obliged to ask you about the latest essay that Dario published on pacing the frontier. We heard his great answer, I think, at the keynote. Not everybody was here. What do you think it means for enterprises? Yeah. Look, the number one thing, and the first thing that Dario is advocating for, is a greater degree of transparency, a common set of standards, and how do we have more third-party independent insight into the safety standards associated with frontier intelligence? That is the thing that we are focused on primarily first of all, is how do we increase that level of transparency and third-party insight so that there is that clear view of how the frontier safeguards are pacing with frontier capabilities. Now, to be very clear, pacing the frontier is not a pause. We are going to continue to release more capable models. It will still feel like the frontier is moving very fast. But we are very focused on making sure that every time we advance that frontier, that it is paced with the safeguards that go along with the increased capability. Well, please do. All right, so one last one. This is a fun one for you. Okay Paul. So we are here next year. One year from now. How do you think the whole thing is evolving? Also our partnership. Yeah. You know? Yeah. I chuckled when I saw this question, because one year from now, that is amazing. I generally think in hours and days. Maybe occasionally a week out. The mantra at Anthropic is very much like, yes, planning is really important, but the plan is absolutely useless by the time you finish writing it. Now, what I genuinely think though, in one year's time, maybe less, is think about how fast coding moved. Think about how fast when it flipped, it flipped real fast. That is what we see about these different workloads and knowledge work tasks. When it moves, it almost all moves, and it moves very quickly. Nine months ago, we weren't doing fully autonomous coding. Now we are. 5x performance improvement. That is now going to start happening across whole swathes of knowledge work, where the capabilities like we are working on together become good enough that you can effectively delegate a whole series of tasks and then oversee those tasks, and then the whole industry in that particular segment moves. I think we are now going to start seeing that over more and more use cases in knowledge work in general. We will be talking about that next year. I look forward to that. Thank you, Paul. My pleasure. Congrats again. Thank you. Thank you for the partnership. It is amazing. Again, I am insanely excited about this one. It is one our customers are demanding from us. Big hand to my friend Paul. Thank you so much. Thanks, man. Thank you. I am sorry. All right. Let us wrap this up. Thanks, Miguel. Thank you, Paul. To end this middle section on the business and momentum, the three key messages. We see the momentum, we see the momentum. The net new momentum is going to continue. We continue to invest. We are very confident. We have a lot of ways to monetize the AI, and we have all sort of pricing mechanism for customers to buy. Then you are hearing from our customers, please talk to more customers. There are thousands of customers here this week. Thank you so much, and now I am going to hand over to Mark. Thank you so much, Miguel. Be careful. That was amazing. The best is yet to come because we have the world's most incredible President and Chief Operating and Financial Officer, Robin Washington. Robin, welcome to the stage. Thanks, Mark, and welcome. I am sure everybody is ready just to stand up and stretch for a minute. We can all do that while they remove the other chair if you need to. I am. There you go. Well, good afternoon, everyone. It is an exciting time at Salesforce. You heard it from Marc yesterday, you heard it from our wonderful product leaders, and you heard it from our exceptional go-to-market team. What I want to focus on now is the agentic enterprise opportunity in front of us. As we think about that opportunity, I want to share with you the financial framework that we have in place, and importantly, the day-to-day discipline that we have around execution to deliver on it. First, I want to start with a thank you. We know that you have optionality, so we appreciate you investing in us, we appreciate you being here. While you are here, I would encourage you. I had the most phenomenal experience Monday afternoon in Agentic City, and I have to go back because they were not all. Go over. In addition to what you heard today, you can truly see from 20 different companies the way they are leveraging the use cases, the value that we are bringing to them leveraging our platform. So I would encourage you to take a swing through and spend time. Most importantly, we appreciate you being here today, and we are looking forward to answering your questions after this section. Last year, if you remember, we talked about the FY 2030 financial framework, and there were three pillars to that. Growth, and increased it to $63 billion. We talked about operational excellence. Again, a focus on durable, profitable growth. We also talked about our important metric that we look at all the time is free cash flow. I am proud to report, and you heard Miguel talk about it earlier, we are on track. 12- 18 months, we will negotiate. At the end of the day, what we talked about, we are seeing happen. We are on track for organic revenue growth re-acceleration in the second half of FY 2027 and beyond. That is happening because of all the innovation that you have heard about. We are also investing while we are continuing to focus on profitability. I think Q2, we are at 34.1% on track relative to our guide for the full year. We are also investing to scale profitably and to focus on the long-term trajectory that we see, and I will talk a little bit about the opportunity. Importantly, the investments that we are making are translating into momentum. Alexa mentioned the opportunity. It is pretty amazing if you think about what Gartner has laid out as the incremental AI spend from 2025 to 2030. $1.1 trillion. In the slide that Alexa shared on monetization, we talked about the fact that knowledge workers is a brand-new category, and that we expect software spend to literally double by 2030, all within the framework that we outlined. Again, another high level. There is a TAM opportunity out there, and we believe we have the innovation to take advantage of it. Most importantly, we see that innovation already starting to drive our flywheel. We have talked about our platform, we have talked about the great innovation that we have across the various layers, and more importantly, what we see, particularly with AIforce, is the opportunity to unleash or untrap the value within our platform. You saw the excitement in all of the various demos. I am not going to share my COFO center because it does have real numbers looking out, so I will not share it. Ultimately, we really see the future opportunity with the innovation that we have in place today. I am going to click in a little bit on the proof points around that, and I am going to start with the AI-native companies. One just left the stage, and you saw how they are leveraging our platform to drive their business. Importantly, nine out of the 10 top AI companies are building and betting their future on us. That is a huge responsibility, but it is a huge opportunity. You saw it earlier, 5+ clouds per customer, cRPO growth growing 62% year-over-year, and 100% Slack adoption. We had an experience yesterday that I and my team led with COOs and CFOs, and we actually had the CFO of one of these AI-native companies come and speak with us. She talked about the fact that her morning and her evening ends in Slack, very much like mine. You heard Paul talk about it today. It is not just the AI companies where we see this happening. We are seeing agentic enterprise expansion in action across our diversified portfolio. If you think about everyone from automotive to a manufacturing customer, professional services. What we see is that in 80% of our top ARR growth stories, AI shows up. AI is the driver. It is not the only thing, but it allows that expansion to happen. I just want to drill into one example here, public sector. Here, you can see that with Agentforce, the customer enacted the premium upgrade motion. They took on more core and data foundations. They have monetized four of the six pillars that Alexa spoke about, and that is all showing up in a single customer. The results, an expansion across our platform resulted in about a 4x increase in ARR for that particular customer over two years. As you can see, there are many different paths to that monetization or that uplift. One of the things I loved listening to Pierre, he talked about that journey that he is on. What we see as other customers are adopting these AI optionality, we are seeing the monetization of that happen. We are looking at the top 100 AWU customers and we are seeing within 18 months of Agentforce's launch, we are seeing ARR uplift about 2x as to what it was. If we go further into our customer base, we are also seeing ARR meaningfully grow. Again, going back to Pierre's journey, I will go back to a slide slightly formatted a bit differently from last time, but we talked about that journey. It is a multi-year process. Pierre talked about the fact that right now he is adding agents on top. But similar to the transformation we are going on at Salesforce, they still have not necessarily rethought about their processes relative to agentifying. The opportunity is there, and over multiple period of time, we see, as customers become agentic enterprises, a 3x to 4x opportunity for that ARR uplift. That is what we are excited about. Again, proof points of the flywheel continuing in motion. I want to go a little further into our financial performance. Marc shared this slide at the keynote. We have been in the business of helping support customer success with tremendous innovation for over 27 years. That has been a combination of organic and inorganic investments. Last year, I talked about $10 billion or so in R&D investments. You can see the velocity of speed in terms of what we are investing to ensure that we are taking advantage of the AI opportunity. We are also focused on responsible M&A. We closed Informatica in November of last year, and you will remember we talked about our responsible M&A framework and making that transaction accretive within two years. Where similar to what you saw us do with net new AOV, Informatica was accretive in six months. That was along with the fact that we continue to grow the platform. Again, disciplined execution. I want to drill into our biggest acquisition, and I am going to say it very simply. Slack is on fire. 2.5x increase since acquisition in revenue. You see all the innovation from Slack Code to Slackbot and channels, to Slackbot Live. Amazing innovation. Slackbot, which is a true friend to me and many others, 150% usage quarter on quarter. As we have said, all the leading AI companies run their business on Slack. Alexa demoed for you, she runs her business on Slack, and you have seen it work. It is another key growth opportunity for us. This progress that we are seeing from an innovation standpoint to increased ARR, it is underpinned by our profitable growth framework, and it is accelerating. The growth drivers we have talked about, the incremental monetization opportunities Miguel and Alexa spoke of, and some remain the same. Multi-cloud motion, pricing and packaging. You saw from both Patrick and Alexa, the upgrade mega cycle that we see happening given the innovation we have at hand. We have got a pretty diversified portfolio geographically, different lines of business, sizes of business, different industries. The innovation, as you have seen, is pretty incredible. We are investing in the capacity to make our customers successful. On the margin side, 1,500 + basis points improvements between 2022 and 2027. It continues while we invest. We are looking at ways to reduce the cost to serve, which helps our gross margin. We are investing ourselves in our own transformation, Salesforce on Salesforce, or as we call it, Customer Zero, and we are being disciplined. We are funding our best opportunities, but not every opportunity. That is the continued rebalancing and reshaping of our portfolio that we are doing to support our profitable growth framework. What does this all mean? It means we are fueling our future with free cash flow. We estimate that this year it will be about $15 billion. It gives us the flexibility to accelerate our innovation. I want to drill a little bit into that last pillar of that framework, capital allocation. There are two key principles for us. One is responsible M&A and strategic investments, and the other is robust capital returns, which I am sure you as shareholders all care deeply about. Here is the framework I talked about earlier. It is still in play. It is still how we think about the investments, the acquisitions that we do, and those that we walk away from. If we think about it of late, I want to go into a few key focus areas for us. Data, AI accelerators, and a new vector for us, AI Labs. Things that we look at when we are evaluating those opportunities, tech and talent, adjacencies, scalability. In the tech and talent era, I will call out Doti. This was an acquisition that came to us as an opportunity between our M&A team and the Slack team. It was a critical component to some of the innovation that you are seeing in Slack. All the way to the right, we have talked about it, Slack and Informatica, clearly giving us great tailwinds that are helping fuel our growth in our FY 2030 framework. What is AI Labs? AI Labs is a new area of focus for us. It is going to provide us with frontier AI capabilities, it is going to help us accelerate our AI product roadmap, and it is going to help us unlock new opportunities. As you all know, the pace of innovation, the pace of change is rapid. We have got a pulse to the ground, and AI Labs allows us to be nimble, quick and adaptable. Three examples that sit under that umbrella, were Regrello, or as we call it, Agentforce Operations. Fin, which we just welcomed earlier this month, and Qualified. You all saw the demo in the keynote of Piper. If you go to our website right now, you will see Piper. All of this is grounded in us delivering customer success. As you heard from the customers and Miguel and Alexa, everyone is approaching this agentic enterprise journey differently. I want to just drill a little bit more into this ecosystem as how we are thinking about one of our CEO's key priorities, is do we have the right strategic investments to be successful? Salesforce Ventures, amazing investment. You can see them there on the wheel, on the acceleration wheel. I talked about AI Labs building. We are investing internally in incubation opportunities via AI Labs. I talked about the acquisitions that we are making that sit under that. Oh, by the way, you have heard about our partnership today with Anthropic. You heard about our partnership with NVIDIA yesterday on stage, and there are many more to come. I think most importantly, we see this innovation flywheel as critical to our success, and it allows it to stay ahead of the innovation curve. The other component that I mentioned is capital return. We believe the biggest bet that we have made in FY 2027 is on us. We have been buying shares for a long term, $60 billion cumulative, but we launched earlier this year and we will complete in October the largest accelerated share repurchase ever. The return, over 40%. The expected average price, $182 a share. The expected share count reduction, over 14%. Again, that brings value to all of you, our shareholders. That is in addition to the $3 billion in dividends that we have paid out. To conclude, the framework that we talked about last year remains intact. We are very confident with the playbooks that we have talked about with the innovation, with the go-to-market strategy and our path to $63 billion. The confidence is there. The TAM is there. To conclude, so we can go to the Q&A, we believe we are winning at the agentic enterprise opportunity. We are defining the agentic enterprise. The execution is compounding our value. It is unleashing the trapped value. As I said, the opportunity is ours, and we are confident that the innovation that we are bringing will continue to drive the flywheel. Thank you. Thank you. Thank you so much, Robin. Is this on? Yeah. Is this on? I want to thank the whole executive team. We are of course saving the best for last. We have had so many requests. People want to see into the mind of Marc, and Marc is with us, and he has graciously offered to give us his time, to handle solo Q&A from the audience. We would love to. Could we have a chair on stage, please? Here it comes. H ow many people here saw the keynote yesterday? Oh, great. How many people did not make the keynote? Just a couple? Okay, good. Somebody asked me that I am supposed to say thank you to all the people who sold us the stock at $150. I do not know what that means exactly, but thank you to those people. We appreciated the volume there. We appreciated the volume in the stock. Okay, so do we have folks assembled? Do we have someone running a microphone? Yeah. I'm happy to do any questions or take a little bit of time to talk about what's coming. I want to start with Brad in the middle. Can we get a microphone to Brad, please? Brad, do you want to just speak into my- Do you want to speak into my lapel? Speak into it. It's very on. This is interesting. [This is not going well.] This is a little bit different. We're going to do it a little differently this year, Marc. What's that? Brad Zelnick, Deutsche Bank. Thank you again for having all of us. Another spectacular Dreamforce. I think that's a little. Look at the hot swap. Perfect, and the sneakers never disappoint. I wanted to ask about Slack and as well the evolution of the business. If we reflect back five years ago, it was a highly strategic acquisition that you made really. Very well-received acquisition five years ago. At the time, it was a little. I want to appreciate. It was ahead of its time. Everybody's support in the room for the acquisition five years ago. Thank you guys so much for that. Ahead of its time. But owning the interaction layer where customers engage, where there is a lot of rich, valuable data, we saw the opportunity. Some saw the opportunity. Fast-forward to today, we have seen great demos of Slackforce. Alexa, in particular, absolutely crushed it. Yeah. Patrick showed us Claudeforce. As you get pulled where customers take you have always been customer first, built on trust. What does the future mix look like? How should we think about the stickiness and opportunities to monetize, whether the customer comes through your front door or someone else's? Does it even matter? Yeah. I think it is such a great question. I think a lot of people know I am really just back from two months in Europe, and when I was in Europe for the last two months, I literally was with hundreds of customers. It was definitely an awakening for me in many points, but it really resulted in the keynote that you saw yesterday. Number one is this, I would say that something is happening over here to the right. I do not know what it is. What? Oh, okay. I think we are about done. Oh, all right. Great. There we go. Much better. The number one thing is that we saw this incredible thing. It was really one specific seminal moment. I was with this customer in Lausanne, Switzerland. I do not know if any of you have been to Geneva, just outside of Geneva, it is a great area on the lake. With one of our very largest, or maybe it is our largest customer in Europe. It was a long, exhaustive meeting. It was about three hours. We are kind of getting to the end of the meeting. I was with Rami, who is the CEO of our Swiss business. We had already released Claudeforce to our distribution organization and to our operating unit leaders. What we did not realize, and I kind of want to get into this a little bit more, is that the platform itself was so powerful that they were going to start using it and building their own application to run their business. Rami was in front of the CEO of this company and started demonstrating his version of Claudeforce. He had given it a name. He had built this highly customized application to run Salesforce Switzerland. I will never forget this, but the customer's jaw literally dropped open when they saw what was happening, which was that the platform was able to read across our entire database, all of our applications, and build this highly customized application that let Rami run his business. This was kind of an amazing moment. It was only complemented by my own personal experience. We were in the focus groups for the Dreamforce keynote that you saw yesterday. Miguel, who is right here, we were in Beverly Hills, and we are going through, we have customers there, we are presenting to them. I am sure you know what we do. It is very exciting. We are trying to listen to them. I just glance over and I look at Miguel. I see that he has taken Claudeforce and he is building, he is running an application that looked unlike anything I had ever seen. It was incredible, graphical, dynamic, very interactive, very intelligent. He was kind of switching between that and Slack and so forth. It just all of a sudden occurred to me, everything is really changing because of what is happening at the interface level. At this interface layer, we are really seeing this kind of transformational moment. This was that thought that, and I do not know if I am going to be able to express this correctly, but there are certain moments in our industry where everything is changing. This is that moment for enterprise. We saw it when we were doing IBM mainframes. We went into mini computers. All of a sudden we started to go into client-server computing. We saw it when we were moving client-server computing. All of a sudden, we were doing cloud computing. Now we are moving from cloud computing and we are moving into this new platform. That is why yesterday I kind of went through these four strategic layers of how our software is architected. For those of you who have been coming to these Dreamforces and going through these things, you will see we really have not had to kind of spell it out quite like that. The data layer, where the data is integrated and federated and harmonized, the application and semantic layer, which before we were just talking about the applications and the power of the applications, but now we are talking about how the applications and the analytics provide the intelligence for the AI, the agentic layer, which we have been talking about Agentforce, but not as part of the comprehensive platform, and now a transformational interface. That transformational interface, I think, is why I think for a lot of customers, as you kind of travel around, they will say they really have not had their enterprise AI transformation. I do not think most companies feel, and probably a lot of companies are represented in the room, that when you go to work, you feel like, "Oh, yeah, AI has really changed everything in our company." Maybe people are still having their ChatGPT moment at home or on their phones, but when they get to their office, are they feeling like, "Yep, wow, everything is different in our company." It is extremely clear to me, and I am very confident that we are now at that moment where all of a sudden we are going to see a rapid transformation of the enterprise. What we are doing with all of these customers today is showing them how to kind of guide that transformation. We are showing it to them with three different interfaces. One, we are showing it to them with all built on our AIforce framework. We are showing it to them on Claude and Coworker. We are showing it to them with Slack, like you mentioned, and you have seen now Slackforce. We are also showing it to them with Coworker. In all three cases, you can see how the platform is intelligent, it is adaptive, it builds these composite applications, but also that it is very kind of like it is alive or it is a living interface. Only in the movies have we really seen software that looks like this. We have never really seen software in the enterprise that has these characteristics. This is definitely that moment. For these companies and customers who see this experience, they all realize this is now the North Star. While we showed you three of these interfaces, okay? By the time we get back here, or let us say by even as we kind of get into January 1 of next year, I am confident you will have a lot of different interfaces. The interface, customers will be able to choose their religion up here. We are agnostic. That is I think one big advantage we are going to have is the agnostic aspect of the interface, but we are going to give customer choice. I think customers will have different religious preferences up here. There is no question. By the time we get back here to Dreamforce next year, I think we will see a lot of customers who have made a huge transformation. One of the reasons why it is going to go so fast is because those customers, as they start to deploy this interface, the interface is so intelligent, it is helping those customers implement it with them. Rami, they did not have huge tech teams with them to implement this technology. It is not some type of incredible enterprise transformation. You are going to end up with an enterprise transformation, but the interface itself is so smart it can do three critical things. One, it can help administer Salesforce. That is extremely important because there are thousands of different characteristics of Salesforce. That is why these administrators can get in there and they have to kind of work with it in the different administration centers. Two, it is going to let them build these applications. Three, it is going to then let them operate the applications. That is why you can get an operating unit leader or business leader like a Miguel or Rami to all of a sudden have this incredible capability. This is what we are really excited about, and I think we are really uniquely positioned to offer this to customers for one really important reason. I think that you can kind of see how it kind of played out in that I think I did a tweet earlier this year about Salesforce Headless 360, and all of a sudden this headless idea went super viral. While that happened, I was actually kind of shocked because it seemed to me Salesforce has always been headless. People were excited that we had an MCP API. We had had an XML API, a SOAP API, a REST API. It is just a maturation of our API platform. The other key characteristic beside that we are built on a robust API strategy, and we always have, is that our applications, especially the ones that are built in Lightning is not just a runtime environment, it is a design environment. So those customers have designed those applications and have decomposed them into the metadata. The metadata is stored for all those customers in the database. So to your point before, that metadata then is recomposed into browsers today, into HTML browsers, Safari, Chrome, Mozilla, whatever. We do not have a religious choice up there either. Now the browser level is transformed, and instead of having that level, you have Coworker or you are going to have other opportunities up here, quite a few I am sure, that let you build and chat and create and so forth. Now that kind of very, call it an intelligent browser, it can read through that same metadata and then recompose those applications. Because our platform knows what the applications look like, what the data is, the user models, the sharing models, it is informed by the semantic layer as well. Instantly you get that application. That is something I have never seen before in my career. I do not think anybody has ever seen this. I think it is by far the most exciting thing I have ever seen. It is totally unexpected, and the value that customers are going to be able to receive will be incredible. I could not have been more excited to do the presentation yesterday. I think it was like, wow, this is a dramatic moment, and we are uniquely positioned for that moment. I am confident that, and I do not know, how many of your companies today use Salesforce to run your various operations? So there is a few. That is an immediate opportunity for you to turn on. It is not something that you are going to wait for, and you will be living in that environment the way Miguel or Rami are living in that environment today, and soon thousands of customers. Okay, fantastic. Let us stay in the front row and go to Kirk. Yeah. Thanks very much. Kirk Materne with Evercore. Marc, to your point on religious preferences, you guys are agnostic. You had two of the biggest CEOs of AI companies with you yesterday, and I think part of the reason they look to Salesforce— Well, we had also Sam Altman here as well. Oh, I was— There were three. I do not know which three you were saying. Sorry, I was including the AI guys. Oh, okay. All right. I wasn't leaving Jensen out. To the point on the AI models themselves, I think one of the reasons— Okay. I won't tell Jensen that you said that. I'm not tall enough for him to make fun of me. The point I was trying to get at was, I think, whatever your model preference, enterprises in particular are looking for trust, and they need to understand that whatever I do from a model perspective, I need my other enterprise vendors to make sure that my data's safe, the workflows I'm building are safe and are my workflows. Do you think that you all can bring a level of trust to AI that will accelerate this? It seems in the enterprise market, not only have people been waiting for faster time to value, but they're concerned about making a decision today that could backfire on them in a few years. What are you hearing from clients on that front right now? Because I do think it's important that they're watching models jump each other and they're saying, "Well, I don't want to make a big decision on something until I feel comfortable that the entire stack can move forward with me." I was just kind of curious if you could talk about trust, and it goes hand in hand with safety, and then what are clients talking about on that front? Thanks. Okay. I think there's a lot of different questions in there, but I'll try to zero in on one, which is when I'm with customers, like that customer that I was in Lausanne, I'll use that example, they basically say this. They're not shopping around for models. What they say is, "We have three platforms that we run our business on. We have back office, SAP. We have front office, Salesforce, and we have a productivity suite, Microsoft." The vast majority of customers that I met with, for example, in Europe, that is their core architecture. I think we get brainwashed by these podcasts thinking that this is the most important thing. Well, this model now has this characteristic, and that model has that characteristic. That's not where customers' minds are at. Customers' minds are like they're operating their businesses, and they're using our technology to run their sales, their marketing, their service, close their books, provide capability to their employees. That idea that customers are shopping around for different model vendors, I think that that is not where their consciousness is. I think that the vast majority of customers will purchase their AI through packaged software. That's where the value will get provided, through packaged software like ours, not in some bespoke. They don't have the expertise or capability to do that. That is not where customers' heads are at. I think I can speak authoritatively on that at this point. What I would say, though, in regards to trust, when we hear other vendors say, "Well, if you're using such and such model, you're giving them all your intellectual property," that is not true. You're being told something to kind of reset your own frame on how to view that company. That is not true. That is a company that has their own agenda. For the last three years, we've delivered a trust layer so that none of our customers' data has ever gone into a model and never will. We validated that, and we have audited that. We provide a high level of trust. We just re-engineered the trust layer with Anthropic and OpenAI specifically, and it has zero data retention. No customer data goes into that model ever. When you're being told some of these things, you have to remember, people have their agendas that they're trying to get you to act in a certain way. I think that that was kind of, at some level, the core of the SaaSpocalypse. Look, a lot of people made a lot of money on that. There's no question. Okay? We're making some money on the other side of it. Okay? But we didn't create it. I know who created it, how it was managed, but it's like, in the same way other vendors have their specific agendas. When you're being told, "Well, you know that you're trading your intellectual property into a model", you need to realize that is not true. I don't know any example of that happening. What I see is that what customers really want is they want an enterprise AI transformation. They can see that there is technology that could make them radically more productive and more successful. The way they experience it in their individual life, where they can put some of their personal data into these models and then get some kind of an insight, they want that to run their business. We know it's possible because we're living that now. If you go and spend time with Miguel, you'll see, and you should take him aside or any of our executives aside, and you'll see that incredible experience. I'm confident we now have a highly differentiated, okay, experience for the customers based on AI that is at the absolute pinnacle of what is possible. I think we demonstrated it yesterday, and these customers have now an absolute true North Star of how to take their companies forward. In these companies who have spent billions of dollars of investing in Salesforce, like this example I'll give, I'll keep going back and forth to this example in Switzerland. That company has spent billions of dollars putting Salesforce in. It just is going to go to an incredible new level for them, and the only reason that we know that is we've now done it for ourself. I think we have more productivity and more capability because of what we've done with our platform, with the interface, and also with Slack and other things that we're doing as customer zero. We're going to try to do this with every single customer. Does this make sense? I really wanted to directly address the ZDR issue, so I'm glad you set that up for me. Thank you. Thank you, Kirk. Let's go to Alex in the front. Hey, Marc. Alex Zukin with Wolfe Research. Truly inspiring presentation on all fronts. When we talk to customers, and we do a lot of survey work, we do a lot of direct questioning, I think the main question is how much does it cost? From the vantage point of you're putting out a truly differentiated amount of innovation and functionality, you're also being very flexible in how you price it, SKUs, consumption, value-based outcomes. When you think about the distribution of how much value goes to the model versus goes to the harness or the app, in the future, over the course of the next few years, how much of that can you capture, and how do you explain that to customers of what they should be willing to pay for Salesforce? Yeah. I think that one of the most interesting things that's happening, and this is a challenge for Miguel, so he should probably weigh in here, and how I've tried to influence him, I'll tell you my own personal narrative, which is that every customer wants something slightly different on pricing. Some customers want per-user pricing. It gives them predictability. They understand the cost structure. It makes sense to them. Some customers want per-agent pricing. Some customers want consumption pricing. Some customers want usage pricing. Some customers want transaction outcome pricing. That is, I've completed the transaction, therefore, I'm paying for that. Some customers want business outcome pricing, which I have never seen before. But now they're like, "If you save me so much money, I'll give you a percentage of that. If you make this much money, I'll give you a percentage of that." No one majority of customers can you drop in any one of these buckets. So what we've said to our entire sales organization is, "We are giving you ultimate flexibility to write the best deal for that customer." We want Miguel to know that he can go walk into a customer and say, and Miguel has a very large distribution organization, you know the size and scale of it, and basically not be constrained in any way and say, "This is the right price for you." That is the way to get the most value. Over and over again, you have to remember, we have many different ways to get value. One is that agreement that we're writing. Another is also to fundamentally reducing our attrition like we have done also increases our value dramatically to our shareholders. Especially as we kind of cross now into the 50 billions in revenue, which very few software companies have ever done, we have a brand new product line and we have a brand new approach to pricing. You saw in the second quarter, attrition had reached kind of a very low level. Contract length had come to a very high level. Cash flow and margin and revenue levels were very respectable, and we had very clear trajectory going forward where you saw the cRPO growth. All of those things are critical and I think our relevance has never been higher for these companies. Our ability to walk into any customer now and to show them a piece of technology that can radically transform their company very rapidly is unprecedented. And one more thing, it is not going to require a huge amount of people to do it, because the technology is working part and parcel with the user to achieve the result. I only know this because it is happening in my company in a dramatic way. I am not having to wait years for this transformation. I did not have to hire thousands of people to achieve it. That is going to be very exciting for our customers. They still have to deploy Salesforce, but they can also do that in a much more expedited way. They still need to make sure their data is right because if their data is not right, their AI will not be right no matter what they are doing. And they can also deploy a fully integrated agentic environment as part of this. So when you get that working, it is just epic. And like I said, this is like stuff for the movies is what I am seeing. Go back and look at the demos from the keynote. It is on YouTube, whatever. These were not canned demos. Patrick, he has a lot of different versions of the demo because he has a lot of crazy prompts on how the demo is built, different style sheets and all kinds of different. He is laughing because he came up with so many crazy ways to present what he showed yesterday because he is building it. This is really special and I think this is really going to transform computing. Do you want to now address the pricing issue? Yeah. Sorry. Yeah. I do not know if I explained. Did I answer your question? No, no. Very good explanation. Robin, in preparing for this event last year, you introduced a new mantra that we are using in every single conversation, which is, we have to meet customers wherever they are in the journey. We come up, at the time we had three or four ways to monetize pricing commercial frameworks. We have added a bunch of them. Alexa and I, every time that we have a conversation with a customer, we find a new way to price our product. Marc, you will be happy and you will be proud. I mean, your message is very clear. We are now pushing very aggressively outcome-based pricing. Alexa and I meet hundreds of customers every quarter. Today I met two customers. I made two outcome-based proposals. One was a PE firm, and what I agree with the PE firm is, give me one of your portfolio companies that you are going to invest in and flip it after five years. We will put an army of people and technology, and we get a percentage of the value that you drive. At that time, let us say that the percentage is $300 million because they buy it for $2 billion, they sell it for $5 billion. We get $300 million or $400 million ticket and then we create a subscription out of that over five years. We have multiple ways. Adecco was on stage. They were reluctant to sign the first ELA, which took them to a different level of spend with us because they were not absolutely clear. Not even a year into the ELA, we are now discussing, "Okay, we are going to run out of magic. What are we going to do next?" I say, "You know what? Your time to place has been reduced by 40%. Your number of placements have increased by 10%. What if we agree on a couple of metrics and then we share in your success?" The guy wants to do it. Everybody wins here, and just to finish with one comment, Marc. The reason I could not show my Claudeforce, I call it Miguelforce but it is my Claudeforce, is because I run the whole company data and it is very obviously delicate. You know what I did last night? I told a Coworker that put a demo toggle on the top. When I am showing and I have it there and I already offered them to show my whole cockpit of the whole business of the company, I will click the toggle, and then all of a sudden, all the numbers and the text gets blurred. It is the same application, and we have made working with SaaS applications fun again. It is a lot of fun to put your hands in a keyboard and look at. Then, by the way, I am doing the murmur, murmur, and I am doing the "Yeah!" to the teams. Yeah, but we are doing business in the meantime. There will be translation available at the end of the program as well. Yeah. Is that a Spanish sad trombone? Yeah. Something like that. All right. Okay. Let's go to [Carl] back here. I've got to the point in the keynote. Now we get into two different places. One is, I think a lot of you, but I don't know how many, not all of the enterprise applications companies, number one, are API first the way we are, and number two, are not metadata first. There are still quite a few of these software companies that coded their applications. That is, there is still kind of a ghost of client-server past, where the applications are fixed. They don't resolve into full metadata. Some of them are full metadata systems, but some of them are not. We have to kind of then bifurcate into those two worlds. For the ones who do have metadata systems that are API first, you are going to be able to move very rapidly. For the ones that aren't, it's going to look a little bit like, did you see the keynote where we brought up the SAP screens and we're scraping, and then we're working with the agent in the screens? That's a good example of what that's going to look like for companies that have more of that fixed application set. All companies are going to really have to move to what our architecture is. The third piece is that when we're actually building these applications to help you run your business, we believe that the kind of things that the majority of employees in the company want to use, that is, things that are focused on the customers, the products, the competitiveness of the company, its market position, its ability to collaborate, to share, to market itself, those applications are where we command and control the market. That is where we have a very unique and special position, and that our applications are extremely relevant for our customers. In some cases, some of our competitors maybe have niche types of functionality. I don't have to get into all of the details, but some of their applications are not mainstream business data that is appropriate for large groups of users. Ours is. Because ours is for large groups of employees, that's where we're going to offer the most value in this application transformation. I think that it kind of plays out with the customers. I think you'll see it go forward. Obviously, we've seen a couple killer apps so far in AI. One is the ChatGPT moment. The second is the Claude Code moment, where we have the coding agents. Now we have the third one, which is kind of the Coworker area. Anthropic's done a really good idea. That's why we're so proud to be investors in Anthropic. John did a brilliant maneuver by buying hundreds of millions of dollars of Anthropic stock that has turned into probably what will be tens of billions of dollars of Anthropic stock. Obviously, we probably will not hold that stock in the long term. That's not our role. We'll end up probably selling it and paying off our ASR debt. It'll be a good trade for us. We'll be trading our Anthropic stock for the 14% dilution that we gain back on our equity. Not bad trade. I'll take it any day of the week. Thank you, John, for your leadership and great execution. But we, I think, are extremely well-positioned, and I do think that, yes, we will motivate a radical transformation for the industry. We'll get there faster because we command and control the market because of the size and scale of our distribution organization and because we cut across small and medium businesses, large and very large businesses as well, and we are getting to the market faster. You can see that. I think that you'll probably say that maybe we're the first to show you what you saw yesterday. I think that that's extremely important. You follow the market super closely, and I guarantee you that by the end of the year, we will have several other extremely mission-critical, motivating announcements at the interface layer. You can only imagine, I'm sure you could do the strategy at this point yourself, on what all the different opportunities are at the interfaces. Now that we have AIforce, we can slot in every other vendor. Obviously, we had to choose which vendor we were going to prioritize, which we did, and I think we made the correct decision. We met the number one AI with the number one CRM. That was our goal. There is no exclusive deals. We are going to provide a full family of interfaces based on whatever the customer's religion is. Great. Let's go to— Does that make sense? Okay. Let's go to Samik, right here in the front. Hi, Samik from JP Morgan. Thanks for the time. Great event. Maybe if I can get your thoughts on, what is your vision with Koa, the model that you launched yesterday? You talked about training it on synthetic data, but when we think about how does that derive value for the customer, how should I think about that? Clearly with this event, your pace of innovation being ahead of your peers is visible. Does that also then something we expect to see with how you train some of these internally developed models and take that forward in your portfolio? Good. Okay, well, I will have Rohan speak, and is Silvio here also or not? I will have Rohan then fill in the details. I think for a while we have been, you probably know we have a long history of delivering models, about a decade. If you go into Hugging Face, you will see doing prompt engineering itself was built at Salesforce, but models like BLIP and xGen and others. We have always had a vision, though, of actually delivering a CRM model. We think that there are certain things that we could do for customers with a CRM model that would be quite good, but we have not really wanted the price tag. With Nemotron, we now have the ability to fine-tune a model without spending an exorbitant cost. That is the vision for Koa, is to take this vision that we have, which we call CRM verse or customer verse, and apply it to the Koa model, and to use Nemotron as the reference architecture, and I think it will be very exciting. Do you want to fill in the details? Yeah. No, I think, Marc, you captured it really well. There is maybe just one more thing that I will add. Obviously, there are 27 years of product making in CRM, and having those domain-specific models makes a lot of sense. To Marc's point, these open-weight models like Nemotron make the post-training part of it a lot more amenable from a compute cost. That is what we have done. The other part, essentially, is this whole notion of data prep. You can imagine in the future, customers might want to use their own data and their own environment to extend these open-weight models as well. There is an opportunity for us to actually build out that factory, like how do you go create that as a part of the data layer, and make that available to the customers? If the bigger enterprise want to go build that on and they can do it themselves. This is for a really discreet set of customers. As I said, I think most customers are going to want to receive the power of that through the applications themselves, through packaged software. The vast majority of customers in the world receive AI through packaged software companies. They will not be wanting to spin up their own and running their own model. But for some discreet customers who want to have that kind of capability, we want to be able to offer that to them. Yeah. Wonderful. Thank you, Samik. Let's go to John. Thanks, Mark. John DiFucci from Guggenheim. Marc, you and your team, I think, did a great job. I think everybody knows this, at exposing the SaaSpocalypse as a hallucination. But I think that you'd agree with me that your stock is still pretty cheap. When I listened to your whole team today, one question kept coming up in my mind. Is Salesforce trying to become a next-gen CRM solution during the AI era? Or is this opportunity, this technology paradigm shift, an opportunity to become the trusted platform to bring AI across the entire enterprise? I know you always think big, but is that something you aspire to? Well, I think you have to prioritize that. I think you have to realize, number one, the most important thing for our company is we must be the number one CRM. Nothing is more important than that. We have a tremendous position with our customers, as you know. I gave you the example of the three platforms. I think the number of customers that used that analogy with me was exhaustive. We must maintain that position no matter what. Then number two is, if we get there ahead of all the other companies, and we can show that through the flexibility and nimbleness of our platform, we can deliver this total enterprise transformation for you, we will do it. But it has to be a prioritization. You see, in software, if everything is important, nothing is important. You have to choose. You have to decide what you really want. I really believe the revenue opportunity for us, the value opportunity, the differentiation opportunity, and the ability to continue to lead our customers is first and foremost with that CRM opportunity, that we have to continue to control that. I do not know if you saw this morning, I did a discussion with Roland Busch, the CEO of Siemens. Obviously, I visited with him also in his headquarters in Munich. It is a great example. Here is one of the very largest companies in the world, certainly in Europe, and they have been standardized on Salesforce. We must be their CRM standard. That cannot be a discussion. Do you think that there are not other companies in there who would like to have that position? There are. Is it a constant discussion with them? Of course. We are in a highly competitive market, so we have to, number one, make sure that we secure that position. Now, once we have secured that position, can we move on and then offer that capability to others? Absolutely. Do we have that ability? We do. You can see it in the way we have architected our own systems. We are our own enterprise AI standard, right? But we have to be number one, and that is why when you look at the demonstrations that you saw yesterday, they are mostly focused on the customer area, because I believe that is where we have to be number one. If you have a different position or think we should have a different strategy, I am open to the discussion. That was— I've definitely read a lot of what you've written recently. I just think this is the most important thing. Were you surprised when you saw the keynote yesterday? Was there anything that shocked you or is it what you mostly expected? I thought it was impressive, but I've come to expect that kind of stuff from you. Yeah. Your answer is exactly what I hoped you'd say. Oh, okay. All right. Well, there we go. Thank you. Well, that's what I believe. Okay. Actually, right behind you, we have Adam, if you want to hand it to him. Hi. Thank you. It is Adam Wood from Morgan Stanley. Marc, you talked a lot about the tech transformations, delivery of software that has happened. We have seen a lot less innovation on the payment side of how companies pay. Again, you alluded to how that is changing now. When we think about what replaces the seat as the unit of value of software, do you have a vision of that in the midterm of what is the most likely model to replace the seat? Secondly, to the extent that is difficult to call today, how confident are you that the re-acceleration in the organic top line you see for the second half of this year can sustain smoothly rather than being lumpy because of that risk of different pricing models proliferating? Thank you. I really am so optimistic because of the customer response that that is where I am like, "I think we got this really right. I think we are ahead of everyone. I think we reinforced everyone's confidence in the company and our ability to help lead all of these customers en masse." I am shocked that we are there before anyone else. It is hugely surprising. I thought it was a shock that so many people actually pushed back on us, even on the Claudeforce announcement. I do not think they really understand what is going on. I think there is still a lot of confusion. I think there is a lot of people who live in podcast world and do not live with the customers. I think it is a huge mistake. I think what I see is we are so addicted to social media, I am saying collectively. We are on X, we are reading these things, we are watching these podcasts. We do not realize we are all part of a huge psyop and that misinformation is being shot at us constantly. This is where the only way to break all that down is to get out with the customers. That is reality. When you are with the CEO and the CIO or the CRO or the COO or the head of sales and you are actually talking to them, "What do you need to run your business? What do you need to buy from us? What is really important to you? What are my competitors saying?" That is reality, and these other things are not reality. I think this is where we can get really confused, and that is why for the last several years, I just hang it up and I move in with the customers. I think it is so important right now, and I think that that is the way to really maximize the revenue for the company. I think it has been an amazing three years in terms of the way we have transformed the company. You guys have watched it, and the company that we have today is not the company that we had three years ago. Obviously, it is a different management team, but it is a different technology set. It is a fundamentally different position with the customers, and I think this is what the customers wanted. We only did this because it is what the customers wanted us to do. In some case, they had an unarticulated need. They needed this, but they did not know how to say it. They would say they wanted us to transform their company and make them AI first, but they did not know how. They could see the power in the models and the power in the capability, but they did not know what could we do to make it happen. Only when all of a sudden we are like, "Let us show you this," that they said, "This is exactly what we want." That is when we are like, "Now let us hit the gas on this." I was with one specific customer, I will not go through the details. They are a large automotive supplier, and they are based in Milan, Italy. I was with them, and it was fascinating conversation. They are huge customers of us on the front office, but I was with the CEO and the COO, and they were doing supply chain scenario work using Coworker. Every morning they are hand-feeding the supply chain information into Coworker, that is the best they are doing, and then they switch over to Lightning and Slack to run their business. I am like, "I can show you a slightly different way to do this." They knew what they wanted, but they did not know how to get it. It is not their world. They are here, but just by making that slight shift, then now they can go forward and, like I said, they can go forward very fast. That is what is exciting to me. I think we are going to see these incredible transformations. I think it is going to happen over the next 12, no more than 24 months. This should be an opportunity, as I have said, for Miguel. We only had two goals in the keynote. One is to, and you will talk to the team, this was our collective intention. One, we want to motivate the enterprise transformation. Kind of to what John was saying, but on a bigger scale. We want to motivate the enterprise transformation. CRM first, but across the board. Two, we want to motivate the upgrade also. We also want to make it clear that we want them to step into the higher version to be able to get the full value. We know for customers who have already done that, they feel a huge amount of value by stepping into our higher version. This is where we are going strategically. That is why if you take apart our slides, you will see that that was our strategy all the way throughout. Okay, does that answer your question? Okay, Marc, you are on a roll, but technically we are at the end. What would you like? All right. I could do one more question. How is that? Let us do one more. Would you like to choose someone from the audience? Not really. Okay. Then how about I do that? Let's go to Tyler. Hey, thanks for taking the question. Tyler Radke from Citi. You made the comment that you think enterprises are going to buy AI through package software. Obviously, we see the enormous growth that Anthropic, OpenAI are putting up. Given so much focus in recent weeks on trust, is it a strategic bet that makes sense for Salesforce to offer AI reselling or some sort of model routing, just as you're sort of this intermediary between the customer, their data, and the model? All of that is going to be built into everything you saw. The idea that we want to definitely be monetizing the token spend as part of our product line. I think a great example is, I don't know if you've seen what we've done with Slack recently, but not only do you have Slack CRM where you can front-end Salesforce with Slack, not only do you have Slackforce where you have the ability to build a whole new service, but you have Slack Code. I don't know if we demonstrated to you today where you can code in Slack as a multiplayer experience. Today, coding agents are still mostly single player. Slack Code is really the first multiplayer experience where all these companies who are using Slack already can now code in the channels. Our goal is to provide smart routing technology that we will be able to monetize to be able to sell you the tokens as well. You can imagine that is an example of companies want to buy their AI through package software. We should be able to distribute those tokens through Slack. We should be able to distribute those tokens through all of our enterprise applications as well. Initially, it does not have to be step one for what we are doing. The most important thing is to deliver the base functionality that lets customers get the value, and then step two is let them step into the ability for us to distribute the tokens. Does that make sense? Yeah. Okay. It is great. All right. Thanks. Well, I just want to thank you so much for coming to Dreamforce. I am sure you know how grateful we are to all of you for being here. I want to emphasize to you that the customers are untethered to you. We want you to go and talk to them. I know a lot of you do surveys and evaluations of what the customer's responses are. We do not want any constraints on any of the sessions that you can go to or trade shows or spending time with the customers. I am also looking forward to more quality time with everybody. Thank you very much. Thank you so much. How about a big round of applause for Marc? Thank you so much, Marc. Please, if you could remain seated for just a moment. I also just wanted to take a quick moment to say thank you to the IR team. First off, starting with Val right over here. You all know Val. Also Alex, right in the back. Everyone, Alex, raise your hand. Thank you so much. Lauren's in the back. Here's Lauren back here. Sam is probably. Where is Sam? Sam is back here. This way. Is Anna in the room? There she is right there. Thank you, Anna, and everyone else that was related to this event in some way. I just want to thank everyone so kindly. In addition to that, we can now walk outside. We are going to have a networking reception. We have live demos happening out here. Thank you so much for your time and attention.