Agentforce World Tour New York City - Main Keynote | Salesforce

Salesforce. For 25 years, we've been a force for sales, Force for service, a force for marketing, for commerce, for analytics. Well, starting now, we're also your agent force.

Agent Force.

A force for humans with AI agents to drive customer success together.

Agent force Force is not about AI replacing people.

It's about how do we enhance employee.

Experience to deliver better customer experience.

We're not just talking about a business evolution. We're talking about an agent revolution. Agents with the power to act on behalf of you and your business. Agents with context make customer relationships more personal. Agents with the ability to do it all intelligently, accurately and autonomously. Because when you've got trusted AI agents at work, your business can succeed at scale.

AgentForce gives us the ability to deliver that high touch personalized service to everybody.

You can improve the communication between supply and demand, between patients and doctors, employees and employers, clients and customers. You see, this isn't another basic bot. No, this is a bonafide agent force, a team. This is using data to reach every possible customer with exactly the right message, then taking immediate action so they have exactly the right experience. This is augmenting and elevating humans to new heights while always staying grounded in trust.

It will help humans become more human.

Welcome to a force of meaningful and effective intelligence. Welcome to a force for purpose, for trust and for good. Welcome to aging force, to what AI was meant to be.

Please welcome co founder Salesforce and Chief Technology officer Slack Parker Harris.

All right. It was so good to be back here in New York City and I'm so excited to see people still pouring into the room. So for those of you who have seats, good job. Good job getting here early. Well, we have an incredible show today and what I'm so excited to talk about is AgentForce. And I think you've maybe heard a little bit about it. If you haven't, you're gonna hear a lot more about it today. It's really probably the biggest innovation that I've seen at Salesforce in our 25 plus years, building technology. But as we always do at Salesforce, before we do anything, before we do anything, we want to thank you. We want to thank you. There we go. We want to thank each and every one of you because we couldn't do it without you. We have some employees in the room, so, yes, I want to thank my fellow employees that are building the technology, selling, supporting you. But more importantly, I want to thank you, the customers that are here. The MVPs. Do we have some MVPs? I think we do, yeah. We normally do. Wow. We got to get the energy up in the room. MVPs. What happened? The nonprofits, the partners, the ISVs, all of you together, it's our community. Have built something pretty incredible. And I just want to thank you. So what are we doing today? Well, we've got a big keynote. We've got some customer stories from SACS, from Prudential, from Unity, Fisher and Paykel. We've got 150 sessions. You need to go to every single one of them. Maybe have some agents you could send to some of those sessions and they can report back. We've got over 30 demos. We've got a campground. It's very. It's overwhelming. But you know what's cool is we've got an app. We got our events app. Download the events app if you haven't done it and you know what's inside there. Agentforce. Agentforce will help you personalize your journey here at World Tour New York. That's the magic of agentic innovation, and I want you to try it right now. And finally, I wanna thank our sponsors, aws, Deloitte Digital and rytr for sponsoring this conference. We really appreciate your support. Well, over 26 years ago, I met Marc Benioff. And when we met, we talked about starting this incredible company. And when we talked about it, the first thing we said is we need to found the company on a set of values. And I'm so thankful that we have always found, followed our values, especially right now in this world of AI, Trust is our number one value. And I think you're all thinking like, oh, my God, this AI world is incredible. But I'm worried about it. Is my data gonna get sucked up into some LLM and given to my competitor? God forbid? No, not with Salesforce because you could. It's trusted with Salesforce because we want to use that layer of trust to then give you the innovation you need, to give you agent Force so that you can be successful in transforming how you connect with your customers through agent Force. That's really, really cool. And of course, we're always working for more equitable and more sustainable future for everyone, something we believe very deeply in. So based upon these core values, we also realized when we started the company that we could also be a platform for change. It's not just about innovation. Even though that's what I absolutely adore, is innovating, it's not just about innovation. It's also about being a platform for change. And we're doing it here in New York City. We're doing it back in San Francisco, where I'm from, in Paris and Tokyo. Everywhere we have employees, we're driving change. It's called the one one one model. We started it when we started the company. There's no money. The equity was worth nothing. Three people in an apartment. And Mark was a CEO. He wasn't even an employee. At first it was kind of funny. But look at what we've done since then. 750 million, $51 million in all time giving 9.5 million volunteer hours. 59.7 thousand nonprofits around the world are using Salesforce to do good. Yeah. Do we have any nonprofits in the room? We must have. Can you raise your hand or stand up if you're a non profit, yes. Thank you. Right here. And when you see them, you know what they need. They need your help. Don't expect Salesforce to be the only one being a platform for change. Each and every one of you can be a platform for change in your business, in your line of work and in your day to day life, you can actually do good. And it'll actually change your life and your company just as it's changed mine and changed Salesforce. And through those values and through that platform of driving change in the world, we've become an incredible company. I'm very, very proud of that. Number one, CRM. That's pretty cool. Number two, enterprise software. Not cool enough, but not bad. We're going to be number one. Don't worry. We're going to be number one. We're on our way. We're on our way. Most innovative companies. So we're valued for our innovation. We're valued for our philanthropy. Top 100 companies that care ethics. Part of our value system. World's most ethical companies. And we're so excited that we're on our way this year. Guided to 38 billion. 38 billion in revenue. That's really incredible. Really incredible. Now, it's been a journey with AI. So I want to now see this conversation more into what's happening in the world of AI. Salesforce didn't just start doing AI when OpenAI hit the market and everyone's like, whoa, what happened? We have been doing it for a very long time. We did it starting in 2014. We started our research group that does research in artificial intelligence. Some of that research actually led to some of the innovations you're seeing today in marketing. But back then it was about machine learning, doing predictive AI, which many of you probably use. It's all over our products. Who do you know, case routing and send time optimization and marketing. That's predictive AI machine learning. It is still incredibly valuable. It's still incredibly valuable. But then we went from wave one to wave two. Wave two was all about co pilots. These co pilots were sitting beside you and you're saying, well, hey, can it help me write my email a little bit better? You know, I want to have some empathy for that customer when I'm responding to them on that support case. So that's. That was helpful. That was generative and it was, it was good and we were excited about it. And, you know, AI on our platform, we're delivering over 2.2 trillion results per week. That's a lot of AI happening on our platform. So, you know that we know AI. You know that you're doing AI with us. You have been for a long time. But we're moving into another phase, another wave. We were in predictive, as I said then we were in copilots. But the new wave is the gentic AI, and we are succeeding. We are seeing success right now with customers. I was just with, with RBC yesterday at a conference here in New York City, and they were talking about how quickly they were able to be successful with AI with Agent Force, that it makes every advisor at RBC an expert. Pretty cool. Wiley, the bookseller. You know, their peak season just happened when everybody's going back to school and people need to get these textbooks and they get inundated with service requests and they try, how do we scale this Agent Force? And so these are customer stories. You're going to hear more about them today. But we're already seeing these incredible successful customers who are taking Agent Force and amplifying their business. Now we're going to keep going in future waves. I'm not going to talk much more about them. In San Francisco, I finally bit the bullet and I got in one of those automated cars, a Waymox. It's a little bit scary if you know computer science. I'm like, is this thing going to work? But it was incredible. It's the future of robotics. This car just pulled up. There's no one driving it. The steering wheel's moving. And it took me where after about five minutes, it's like, this is kind of boring. This is kind of normal. That's the world we're headed into. And then many believe we're going to hit AGI or artificial General Intelligence. Maybe that'll happen soon, maybe it'll take a while, but it doesn't matter because the AI that we have today can transform you and your business. Now, for 26 years, our number one priority has been to make you successful and to help you connect with your customers in a whole new way. And we like the number one being really tall there. We're not just number one, we're a big number one, but we like that. But our vision has always been to help you connect with your customers in a whole new way. Now, in 1999, connecting with your customers in a whole new way was about like surfing up onto a website and we wanted to let you point, click, close. Anyone remember that? It's like, hey, it shouldn't be that hard. So that's what we were doing 26 years ago. That was 1999, when this thing called the cloud could actually be used not just for buying a book on Amazon.com, but for doing CRM or Salesforce automation. Actually, just Salesforce Automation back then. But as we've moved through these evolutions of technology, a lot has happened since I've been at Salesforce. I mean, we didn't have smartphones 26 years ago. Mobile happened and you're all like, well, man, how do I bring mobility into my enterprise? Well, we took you there because we added mobility. We added the mobile platform to Salesforce's platform. Social happened. It wasn't just meta, it was social within an application. So we added social AI hit and we just talked all about AI. So we brought you into the world of predictive AI data. I'm so happy. We've been investing for many, many years on data with our data cloud because we had that platform of data ready to go when generative AI really hit that tipping point. Because generative AI, as you know, and we'll talk more about it, needs that data to be successful. And now we're bringing you forward into the world of agentic AI with agent force. We're going to take you there. You don't have to worry. We are going to take you there. And when we take you there. Let me just go to this next slide here. You all realize that, you know, it's tough out there. I mean, I don't know about you, but the last few years have been tough. You know, we haven't all been hiring a ton of people. I don't know about you. If anyone's been hiring a ton of people, I want to know who you are. But we have not been hiring a lot of people. But the demands on our businesses haven't changed. So the workforces are feeling overwhelmed. They have all these Low value tasks. Like, oh, my God, it's all repetitive stuff. I need to hire more people, but I'm not productive. People are burning out, but the customers aren't saying to you, it's okay, don't worry. It's fine. Don't worry. We don't mind waiting on hold. I like waiting on hold. Don't you like, totally fine. Don't worry about it. We don't mind if you don't know who I am. No, that's not true. Customer expectations keep rising, so you're feeling this pressure. You're like, oh, my God, I'm overwhelmed. And the customers keep demanding more, more, more, more. So how are we going to solve it? Well, what if workforces had no limits? You say you can't hire a lot of people, but what if workforces had no limit? And maybe you could hire some agents. Maybe those agents could actually help you scale. Maybe those agents could help you both grow your revenue, but also keep your cost lower, even lower your costs at the same time. Both are super important. An agent forest will take you there and it'll take you there safely. Of course, trust, as I said, is our number one value. So we're going to bring you there with trust. We're going to make sure we take care of those hallucinations, that bias. We're going to make sure your data is secure. You're going to use the Salesforce security model, not the LLM, which has no security model. We're going to make it super easy for you to build your own agents. At Dreamforce, customers built over 10,000 agents on site in like 10, 15 minutes on their own. Data wasn't just a sample. It was like, we're going to build one for your website, for your company, for your data. And they're like, whoa, that was fast. And that was easy. That's what we do at Salesforce. We want to make things super easy. And how do we do that? Well, you know how we do that? It's with metadata. It's our platform. It's all integrated and you just configure some metadata and now we have metadata. You're configuring about agents, about AI. And when you configure that metadata for AI, our engineers, I don't know how they did it so quickly. Interpret that AI metadata now, and now, bam, you've got that agent. And if that isn't enough, of course it's built on this one platform. You know about our ecosystem. So the ISVs here in the room are already building their own Agents on our platform that you can use, building skills and actions that you can use in your agents. It's a whole open ecosystem. That's what we do. You know, that's what we do. And this is very familiar to you. We have the Salesforce platform, we have Data Cloud. We have all the customer 360 touch points. But we didn't take Agent Force and go here it is over here, go use it. And that it's separate from everything else. That's not what we do. We want it to be one beautiful integrated whole thing. So that's what we did is we added AgentForce to the integrated platform. You've got that platform for that metadata driven customization for Flow. How many love Are there any flown addicts in the room? That's what we call the people who love automating with flow. Flow can help you in AI and I think Patrick might show you an example of that. You have Data Cloud which I talked about. How does the AI know who you are? Know who the customer is? Know your business, know all your business processes and all of the other data across your enterprise through Zero Copy. That's with Data Cloud. And you still need those touch points. You need to be able to interact in sales and service and marketing and commerce. So you need all those applications. But you know what? You may not in the future interact directly with those applications. It might be the agents actually working with all these services. Those applications get broken down into a bunch of skills, a bunch of actions that these agents know how to use. Just like humans. All these, all of you in the room know how to use our applications. What if these agents are learning how to use our applications for you and taking action on your behalf? That is the magic of Agentforce. Companies like OpenTable have grown so quickly that they're getting inundated with calls. People are calling like, hey, I got a problem. My reservation, I need to cancel it. This isn't working. You know, all of these agents are exhausted. So how do we solve that? Agents agent force 24 7. These agents don't get tired on agent force. They work 24 7. They're empathetic. They know the customer. OpenTable's loving it. Those support agents are getting a little bit more relaxed because agentforce is there helping them. Another customer story of Deco. One of the biggest recruiting firms and job placement firms in the world. They get over 300 million resumes submitted a year. And these are people who want jobs. And so the people who are, you know, the candidates who are saying I need a Job, you know, they want to get an immediate response. They cannot hire at Adeco enough recruiters to answer quickly enough. All of those candidates coming in. So those candidates are getting frustrated. The recruiters are getting tired and frustrated. They're like, oh my God, I can't help. You know, this is not a happy place. Agent Forest comes in and those candidates can be pre screened by the agent, the resumes can be reviewed and actually associated with a job placement. The agent. Agent Forest can even automatically do scheduling for those candidates to actually speed up that process because Adeco knows that the longer it takes to respond to a candidate, the less likely they're going to actually place that candidate, which is not good for the candidate. It's also not good for a decos business. So why should you settle for copilots? You know, we had chatbots and we've had chatbots for a long time and they were kind of okay. And then copilot came along and wow, that's great. But it was kind of fixed and rigid, you know, and it worked, it was helpful. But why, why don't you want to move into the world of Agent Forest where it actually knows your business? It's got all that data and grounding of personalization to know who you are, who your customer is. It can actually kind of think it can plan and reason. And we have something called our Atlas reasoning engine. So it's not just one LLM doing thinking, it's actually a whole agentic reasoning system or loop that actually is reasoning. So it can actually be smart and safely answer your questions and help you or help your customers and then take action based upon that data. And based upon that reasoning, it can actually take action for you or for your customers. And it can do it at scale. That's pretty incredible. And as you know, one integrated platform, but also working in every single industry. So of course Agent Forest works in every industry. Here in New York City we've got a lot of banking customers, insurance customers. I know that. I saw a lot yesterday. So in banking, proactive financing to improve loan terms and insurance, hey, wouldn't it be nice to pay out faster with automatic handling of insurance claims? That'd be pretty cool. Or how about telecom? How many people you know want to call your telecom, hey, my Internet's down, you know, my television's not working. You know, customers hate it and the providers actually don't like it either because it's making for poor customer success. Why not just do that with AgentForce to reduce those wait times? With 247 support working in every industry. And as we know. And I think you, you worry about like, well, will Agent Force be compliant? It's kind of like boring, huh? Compliance. But you worry about that. That's part of what we think of trust. We want you to be able to take Agent Force wherever, in every line of business. And so we of course have 40 compliance certifications that Agent Force inherits because it's part of that integrated platform. It all works together. And bam, we've got an ecosystem. How did we do that so fast? Well, you know how we did it. Agentforce is just part of our platform. Of course we have an ecosystem. We already have partner agents. We have agent actions. Actions are skills or APIs or capabilities that Salesforce has. But look at that. All these partners are giving Agent Force a lot more power by the actions. In aws, on box, on canva, on code science. We have data partners because you need that personalization so you don't have to copy that data. If you've invested, as you know, if you've invested in Snowflake, we love Snowflake. If you've invested in databricks, databricks is great. You don't have to redo it. Data cloud will just connect to it. You got that zero copy data to make those agents smarter with data. And if you need a little bit of help, we got some incredible implementation partners. Accenture, Capgemini, Deloitte Digital, IBM, PwC, Slalom, and yes, even Salesforce too. We can help you and we want to help you. But before we help you do all this, we want to show you some technology. And to do that, I would like to bring up my friend Patrick Stokes, EVP of Product and Industries Marketing. I've lost him. There he is. Patrick, please come up and take it away.

All right, thank you so much, Parker. All right. Good morning, New York. Okay, so autonomous AI agents. That is kind of a doozy. Who the heck knows what these things are? The good news is in like two or three years, our kids are probably going to know everything there is to know about this, right? Maybe an AI agent's going to come over for a play date, play some Fortnite, maybe do some gymnastics in the front lawn, I don't know. But in the meantime, it's our job here to figure out how do we use these agents in the business. And that's exactly what we're here to do this morning. So the good news is these things actually aren't that complicated. When you really start to break them down, there's really Just five key characteristics that we need to think about when we're thinking about AI agents and Agent Force. So the first is the role. What's the job that we want the agent to be able to do? Right? What's the function? The second is the data. What data does it need access to in order to go do that job? The third is the actions. What skill sets does it need? Right? What do you want it to be able to actually physically go out and do and execute? The fourth is the channels, which maybe isn't so obvious, but that's just where do you want to interact with the agent, right? Do you want to talk to it on the phone or in a chat experience? Right. So how do you want to interact with it, if at all? And then the fifth is really, really important, which is the trust and security. So what do you want the agent to be able to do? What do you not want it to be able to do? What guardrails do you want to be able to set up? That's really important. If you're going to put these things running autonomously in your system, you need to be able to trust them. Now, if you tried to wire all five of these things up all by yourself, it would be really, really hard, really expensive. What you want is a platform that can do all of that for you. And that's what we're so excited about. Because with the Agent Force platform, you're getting started really from miles ahead. All of the roles are largely already inside of Salesforce, right? Whether it's your salespeople, service marketers, commerce folks, or people in really specialized industry types of use cases, a lot of the definition of those roles and the data that they need and the job that they do is already in Salesforce. Much of your data is already there as well. Of course your CRM data, your structured data, but not just data inside of Salesforce, but with Data Cloud you can connect data from anywhere, whether it's your data lakes like Snowflake or third party systems like your erp, but also more recently, your unstructured data too, right? Your knowledge articles, your conversations in Slack or your emails. All of that makes up a tremendous amount of knowledge that you'd like your agents to be able to read just like you do. Then your actions. This is where the platform really shines. You've been building workflows with Flow and Apex and Mulesoft for years to kind of define how your business works. All of those are available as actions, right inside of AgentForce. And then your channels, of course, Salesforce brings all this together for you. You can deploy on Your website, in WhatsApp, LINE, Apple Business Manager, on your phone system, or in the very best place to work and collaborate with all of your employees, which is slack. And then finally that trust layer, you've heard about our Einstein trust layer. But let's not forget all of our data permissions built right into the platform, role based access controls, all of that is built right into Agent Force. Now once you've defined these agents, you want to give them a place to actually go out and run. And this is where we're so excited. Because as the world has been enamored with the idea of the LLM itself. And how big is the LLM? How many parameters is it? The LLM itself is a part, it's an important part, but it's not the whole part. The whole part of an agentic system is being able to connect data to an LLM to action. And that's what we've built with our Atlas reasoning engine. And this is a loop system. So as you define these agents, your agent is looking at your data and coming up with a plan. It's reasoning and making a decision and coming up with a plan. And it doesn't just send that plan back to the human beings to go execute, it can actually go out and execute that plan itself. And when it's done, it doesn't stop there, it sends the signals, the outcome of that plan right back into Data cloud. And what does that mean? It means that Agent Force gets better over time as you use it, it's learning your business and it's going to get better and better. It's actually an appreciating technology asset which is pretty incredible when you put all of this together. This is how our customers are getting so much success so quickly out of Agent Force. Instead of trying to build all of this themselves, they're getting to value 39 times faster and they're doing it with better accuracy. AgentForce delivers 33% more accurate answers and they're two times more relevant. This is really incredible. Nobody would have thought just six months ago that you could move this quickly. Now to do this we need to be able to build, right? We need to be able to build and deploy these agents. And that's why everyone in this room, every trailblazer in this room is now an Agent Blazer. Because at Salesforce, what we've been trying to do for 20 years is make the hard things really easy. And one of the core tenants of our platform is this idea of low Code. So we've built our low code agent builder, it's ga. Now this is the place where you can go and build and define and start to play with all of these agents. But we're also today very excited. We just launched this today, our all new Agent Force testing center. You know, one of the things that happens when you start to build these agents and talk to them is you realize you ask it a question and it gives you an answer. But if you ask that question in just a slightly different way, you might get a different answer and you realize, oh my gosh, I've got to generate all sorts of variations of these questions. Well, that's what testing center helps you do. And this means you can deploy agents much, much faster and with the confidence that you can trust them as they go out. Now, as always, we want to tell you a story. We want to tell you a story of an incredible agent Blazer. And that's the story of Saks. Now Saks is delivering luxury experiences for every one of their customers with AgentForce. In just over a week, they built a brand new customer service agent on top of AgentForce. And I don't want to tell you the story myself. I want you to hear it right from them. So let's go ahead and roll the video. We believe there's going to be a fundamental shift in the way that you interact with humans. At Sachs, that's really going to be enabled by Agent Force.

At Saks, we deliver a dream. We sell things that people want to love. The emotional connection you have with finding that one thing you want.

There are lots of new changes happening across the technology ecosystem. You need to have the best technology.

We saw the luxury consumer beginning to move to E commerce. We said we gotta pivot.

Really important for us to meet the customer where they want to be and service them in the best ways.

AgentForce offers personalized service to customers like Maria. In this case, she has a birthday coming up.

If you have millions of customers and you want to create millions of different experiences, it's not scalable. But AgentForce gives us that ability.

AgentForce will enable us to service customers in ways we couldn't imagine before. It will recognize photos and understand text and make personalized recommendations to customers like Maria.

We really believe there is an immense opportunity for AgentForce to allow for our service agents to become stylists, really focus on clientele with our customers. We are recommending things for you that are personal to you, that are authentic to you. AgentForce is really allowing our humans to have a deeper, more impactful interaction with our customers.

It gives us the ability to continue to offer a very high touch luxury experience that people expect from a Saxon. And I know it sounds simple, but that full 360 degree view of the consumer, everything they're doing, from how they're browsing, from how they're shopping, from what they return, from what they call the call center about, from how they pay, from everything really understanding them, we're going to give them that comfort that they're the most important to us, which they are.

When Maria contacts us, it's intelligently routed to a customer representative based on the nature of her question.

Agent Force is going to free up our people to work in a different way with their clients. It's not going to replace, it's going to augment.

Here we have Agent Force making a recommended response based on customer data, previous cases as well as knowledge articles. All we have to do is hit post.

We believe that data cloud is going to be the platform for us to activate that data through servicing, through commerce, through order management.

If you can get people comfortable and if you can work with them on an individual basis, a personalized basis, the sky's the limit on what you can do with them.

I don't believe that the experience that we are delivering would be possible without Salesforce.

It goes back to the belief that humans with agents drive customer success together.

Together.

That's how we're going to.

All right, so that was the incredible story of Saks. And we're going to show you their new agent in just a moment. But first, what I want to do is I want to share a little bit of my own experience with this. So we're approaching the holiday season. Thanksgiving is next week and we're going to be in full swing any minute now. It's probably going to get cold in New York. Who knows? It's been like summer the whole time. But I needed to order a new outfit because I've got some holiday parties coming up. In fact, I've got an early one starting right this week, which is kind of crazy. So I went on Saks.com and I ordered a new sweater and it came to my house just a little bit earlier this week and it didn't quite fit. It was a little bit too small. So I thought it would be really fun to stand up in the middle of a room with, I don't know, a couple thousand people and call customer service together. Sounds fun, right? So let's go ahead and do that. So here we go.

Hello and thank you for calling Customer service. If you know the extension of the party you are trying to reach, you may dial it at any time. To hear our store hours, please press 1. To start a return, please press 2. For product inquiries, please press 3. If you would like to speak to a customer service representative, please press.

Okay, I don't know about you guys, but I don't want to do any of that. What I really want to do is actually just start talking. I want to describe what my problem is, and I want to get some help really, really quickly. I think we actually all know where that's going to go. I'm just going to go to option four and ask for an agent. Anyway. The irony of this thing is there's a whole kind of technique in the customer service industry for this. It's called case deflection. They're just trying to deflect you from the more expensive channel of actually talking to a human being. And the result is that you kind of, most of the time, don't actually get the help that you need. And that's really not great. That's not what we want as consumers. What we really want is we want help, we want solutions. We want resolution. Well, the good news is it does not have to be that way anymore. That experience that I just had doesn't have to be that way anymore. And it doesn't have to be that way anymore because of Agent Force. Now, earlier I mentioned that Sax used AgentForce to build a new AI agent, and they did that in just a little bit over a week. And so they call this agent Sophie. What I want to do now is give Sophie a call and see if the experience is any different. Hopefully a little bit better. So let's do that. All right, there's Sophie.

Hi, I'm Sophie, your SACS AI assistant. How can I help you today?

Yeah, hey, Sophie, this is Patrick. I'm wondering if you can help me with my most recent order. I think I might have gotten the wrong size.

I'm sorry to hear that, Patrick. I'm happy to help. Is this regarding the Saks Collection seed stitch crewneck sweater you purchased last Saturday?

Yeah, it sure is. I think it might be just a little bit too small.

I'm sorry the sizing didn't work out. Based on your purchase history, a size medium should provide a relaxed fit. How does that sound?

That sounds pretty good. One question, though. Is it going to shrink?

This sweater is 100% fine Italian wool, so we recommend dry cleaning only to preserve the integrity of the fibers and avoid any risks of shrinking Would you like to go with a medium?

Yeah, fine Italian wool? That sounds great. Yeah, let's do the medium.

Great. Based on your shipping address, you should receive it within three to five business days. Does that work?

Ooh, no. Actually, I've got a party coming up in just a couple days that I was hoping to wear it to. Is there any way that we could get it to me a little bit faster?

Unfortunately, that's the fastest shipping available for this item. Would you like me to transfer you to someone who can assist you further?

No, that's okay for now, Sophie. Thanks. Okay. Gotta hang up on Sophie. There we go. Okay. So much, much better. Experience. The thing that I like most about it is that I was able to just start talking and describe my problem. I didn't have to, like, listen and interpret a menu. I just was able to start describing my problem. And Sophie knew exactly who I was. This is one of the cool things about agentforce is agentforce knows who your customers are. And I didn't have to give an order number. She was able to just run all the queries and find my order and immediately start getting me help. That was a really awesome experience.

Experience.

But you may have also noticed there was one thing there at the end that she couldn't help me with, which is she couldn't come up with an option for getting the item to me, the sweater to me a little bit quicker. But Saks actually does have a way to do that, which is they've got a store right down the street about a half a mile away from here. Right. And so imagine if Sophie could actually identify that there's a store nearby. And then imagine if Sophie could look into the real time inventory of that store, see if the sweater is there. If she knew that the sweater was there and knew that the store was close by, she might be able to offer me a new option to go to the store and pick it up, and then I'd have it in time. Now that sounds kind of crazy. It sounds like that might take a long time to build, but it really doesn't with AgentForce, and that's because of our low code tool, Agent Builder. I want to show you just how easy it is to configure these agents to do exactly that. Okay, so we're going to go to the demo here and no tricks, no magic. I love our demo team, but I wanted to do this demo myself right here in front of all of you. Although, to be fair, they're there in case I screw it up. So here we go. So Here we are in Agent Builder. You can see we've got Sophie here and we've got a little bit of a definition of what her job is and the channels that she interacts on. But what I really want to look here at is our topics. Now, our topics are just kind of groups of knowledge, the things that Sophie can actually go and do. And you'll see we've got an order management topic here. And if I look inside of order management, it's just got a description and a couple things. See, this is how the AI is connecting what I was asking about. I was asking about an order and so Sophie was able to kind of narrow in on this topic and follow these instructions. There's no code, she's just doing it with reasoning. Within this topic is a whole bunch of actions. And I can see, in fact some of the actions if you recognize these icons here. A lot of these are just flows. These are actions that we actually just saw Sophie perform. She looked up my order, right? She checked on the size. She even modified the order for me to get me a medium. But you'll notice that there's a few missing actions here. There's nothing about identifying nearby stores or the inventory. So if I wanted to give Sophie the ability to do that, actually all I'd have to do is add some new actions. And I've got some actions here that look like they might be helpful, like change delivery method, get nearby stores, which you can See is a MuleSoft API schedule an in store pickup. But I don't have anything to check to see if I've actually got the sweater in the store. So to do that, what I need to do is add a new Agent Force Action. So I'm going to go over here to setup and I'm going to click Add New Agent Force Action. And this is where you just expose all of the mulesoft APIs and flows that you've built to Agent Force. And you can see we've got flow here. All of the flows that I've already built in my system are available to me. With one click. I could make them available to agentforce. But in this case I want to add a mulesoft API because I happen to have a store inventory API actually already all set up for my stores. So I can do that. I'll click next. I can change the inputs and outputs if I need to. The good news is we don't need to. We're just going to go ahead and hit next and I can jump back over here to Agent Builder. And now when I go in and if I refresh these actions, you'll see I've got a new one here. So let's add a couple. Let's add store inventory, let's add schedule in store pickup. We're going to need to see if we've got a store nearby. So we're going to add that API and then we're going to add change delivery method and I'm going to click finish. And this is where something really magical happens. I don't have to give Sophie anything else, I don't have to write any code, I don't have to write any more instructions. I just have to provide the ability to look at those actions and identify what they are, which Sophie can do because they've got descriptions now to prove that, let's actually chat with Sophie right here in the chat interface and see if this all works. So I'm going to put my name in and I'm confident enough to do a demo on stage, but not type on stage. So I'm cutting and pasting. So, hi, my name is Patrick Stokes, customer id, yada yada. And we're going to see Sophie work here. And what's so cool inside of Agent Builder is I can actually see Sophie thinking. So she selected that topic based on my question. I mentioned the word order, so she went into order management. She's finding my order number. This is where she's querying against the flow to get my order number and she's got a response here. So it looks like you still need to select a delivery method, but there's something new here. She's saying that now I can pick it up in store. That is pretty incredible. How did she figure this out? Well, let's look. She checked the order status. She looked at my question, which is can I get it there sooner? She realized that the order status and sooner doesn't quite match up. So she's looking now to see if there's nearby stores. She found a nearby store and now she's looking into the store inventory to see if the thing is actually there, the sweater, but it's not quite done. Now she realizes she's got to come back to me and ask me if I would prefer an in store pickup. I sure would. We're going to select pickup and we're going to see the rest of the process unfold here. She's now changing the delivery message, running the schedule in store pickup flow and giving me my response. Now, we just tested this inside of Agent Builder, but let's see if this has actually propagated out to our Sophie customer service call as well. So let's go back and call Sophie one more time and see if this works.

Hi, I'm Sophie, your SACS AI assistant. How can I help you today?

Yeah, hey, Sophie, it's Patrick again. I just wanted to see if I could get an update on the delivery time of my most recent order.

Is this regarding the Saks collection seed stitch crewneck sweater?

Yep, that's the one.

We have two delivery options available. I can have it delivered within three to five business days or it can be picked up as soon as today at Saks New York in midtown Manhattan. Which option suits you better?

Yeah, let's do. Let's do midtown Manhattan. I don't know how I'm going to get across town that quick, but let's do that. Sounds great.

Great.

I've placed the order and notified the in store client advisor that you will pick up the item. They will have it ready for you within the next three hours. Is there anything else I can help you with?

Nope. Sophie, you have been great. That was very helpful. Thank you so much. I always forget to hang up on Sophie. I hope she doesn't mind. Okay. All right. So you can see just with a few clicks inside of Agent Builder, we've given Sophie a whole new ability. She actually just reasoned her way through that and figured out that there's a nearby store and there's a way to get me that item sooner. And so you can really see how this is what AI was meant to be, how agentforce is what AI was meant to be. Think about the ways that this can augment all of your employees. Think about a customer service rep actually solving problems so that they don't have to go to that live person all the time. Think about what this means for the customer, experience for the experience that I just had. And most importantly, think about what this can mean for your margins and ultimately for your revenue. But to really make all of this work, we have to understand how do we get the data to these agents, to AgentForce? How do we bring that data together in a way that they can actually use it? And the good news is we've got the world's best person here to explain that to us and walk us through it. Please. Welcome to Talk about Data Cloud, our VP of Product Marketing, Sanjna Parlekar. Sanjna, welcome.

All right, thank you so much, Patrick. Now, you've seen Agent Force in action, but data is really the beating heart of how Agent Force does all of that cool stuff you just saw Sophie do in that interaction with Patrick. But in order to fully understand its power, I want to debunk a little myth here for everyone today on how AI can work for our business. Now, what a lot of folks think is that I need to train an LLM with all of my business's data in order for AI to work for me. And that's just simply not true. It's costly, it's time intensive, it requires specialized developers and data scientists. And more importantly, as your data changes and as dynamic as your customers are, the AI doesn't change with it without retraining. So this really isn't the way that we're going to get AI to work for our business. Instead, we're going to flip the script here and put the power inside of our prompt. Now, a prompt is nothing but a set of instructions and questions that we send to a large language model to teach it about our business. So everything you need for an LLM to know about your business can reside within a prompt. But what we also don't want is a prompt that's hundreds and hundreds of pages long, because it has all of that context that we want to give back to the LLMs. So what we want to employ here is a new technique called Retrieval Augmented Generation, or rag. Now, what RAG does is it enables us to put a ton of context into that prompt that searches through all of the data that I have available to me and retrieve that data into the prompt and teach our LLM about our business. This is how we get AI to work for us and for our customers. So you see here that we don't need to do any DIY projects to get AI to work for us, Right? But I know what you're thinking. It sounds great to get all of this data into an agent, but my data's sitting in totally different systems. We know that all of our customers have islands of disconnected data sitting everywhere. Whether that's in an external data lake, several different Salesforce clouds, or even some legacy systems that might not even have an API. Or we understand this pain very, very well. And it's actually the inspiration behind why we created Data Cloud in the first place. And it's our hyperscale data engine that resides deeply inside of the Salesforce platform. And the mission we had in mind with Data Cloud was really simple. We wanna enable you to put all of your data to work. No matter what kind of data it is. Telemetry data, healthcare data, website engagement data. We want you to put that data to work for A better customer experience. Now, to really understand the magic of Data Cloud, we got to talk about how it works under the hood too. And we make it really easy to connect to any of these systems. And we have a few of these logos here. Whether it's your Salesforce Clouds or different Salesforce Orgs that you have for different regions. It could be external applications, it could be external data lakes like Snowflake or Databricks, or it could even be systems that are storing your unstructured Data, like your PDFs, your voice data, audio files, video files, anything you can think of. Now, once you've connected to this data, we do this in a really special way using our zero copy integration, because we don't want all of you to incur the cost of moving your data every time you want to use it inside of Salesforce. We want to make it easy. And so what Data Cloud does is we virtualize that data inside of Salesforce so you can use it like any other object and activate it across the customer. 360. Now, another vital part of Data Cloud is harmonization, because once you've connected to your data, you still have different versions of the same customer residing in those systems. All of your data systems speak different languages. And what Data Cloud does is it enables them to all speak the same language. So you have that central unified view of every single customer that you can activate in any experience that you choose. You can govern this data, you can govern these profiles with defined policies inside of Data Cloud. And you can activate this data, of course, inside of an agent or any other actions that you want to drive for a better customer experience. Now, Patrick mentioned the Atlas reasoning engine, and Data Cloud is really at the heart of the way that agents reason and plan with Atlas and retrieval. Augmented generation is such a vital part of this. And we're going to show you this in action in just a couple minutes here. Now, Data Cloud really is at the heart of what makes Agent Force better. And I think the easiest way to think about it is that so many of these capabilities around personalization, cross sell, upsell, or even just closing deals faster with the right information for your reps at the right time, it wouldn't be possible without connecting to all of those systems with Data Cloud. So I want to show you this in action in a demo. And I'm going to have my friends Claire and Rebecca behind the demo desk help me out. Let's give them a hand. All right. Now, Patrick had his story with Sophie and his Saks shopping experience, but I got a Story of my own, and I think it's a pretty relatable one. I think we can all relate to that feeling when you buy an expensive item and then it immediately goes on sale and you want your money back. A price adjustment workflow. Now, that type of question, if I ask it to an agent here, it might take a service rep at Saks several hours to solve this case. They'd have to know the return policy practically by heart to figure out how to process my refund. But the great thing about AgentForce is that a task that's really complicated for a service rep is a perfect task for AgentForce. So why don't we go ahead and see how we can enable Sophie with this new ability to handle this customer question. Now, our journey here starts of course, in Data Cloud, in connecting to the right data that we want to empower Sophie with to solve this question. Now, it looks like we've already gotten a head start here. We've connected to our CRM data, which is awesome. But in order to really answer this question, I need my order management system data that sits inside of Snowflake. So I'm going to go ahead and create a new data stream. And Data Cloud makes this really simple with all of these out of the box connectors for any data system you can practically imagine here. So I'm going to go ahead and select Snowflake and create this new data stream with my order management system data. And what you're going to see here is it's automatically creating this data graph and it shows a visual representation of all of the relationships across my different data systems to that individual that we want to solve this query for. Our next step here is going to pop back into Agent Builder. Now, Patrick showed you this. Agent Builder is where we give our agent force new abilities through topics, actions and instructions. So we already have a topic here around pricing questions and we've actually drafted an action as well on price adjustment. And this action is a prompt, right? I told you before, the power is in the prompt. So why don't we go ahead and open up Prompt Builder and make this prompt a little bit more powerful. Now, Prompt Builder has been available to our agent blazers for a year now and they're absolutely loving it. And they're loving it for a couple of different reasons. The first is that we enable you to select any model you want to use under the hood with a simple dropdown. You don't need to write any code or figure out a complex evaluation. All you have to do is test it inside of Prompt builder. Now, the second reason that our agent blazers love this is because this is prompt engineering the Salesforce way. It's completely low code, so you can create and revise these prompts in natural language. So we've already gotten a head start here and pasted in the draft of our prompt, and I want to make it a little bit more intelligent with some data that I connected to with data consciousness now with you all. So I'm going to go ahead and drag in the name of the contact to really ground that prompt and the information about my customer, as well as some of that order management data that we just connected to inside of Snowflake. So when I drag all this data in, I can also test this on a contact record. So I'm going to test it on my own contact record here and see what the response could look like from AgentForce. So I want to call your attention to the resolution here, because I can actually see how the prompt is thinking and retrieving the right data to create that response you see on the right. And I'd say I give this response like a B. It's okay. It's giving me some context, it's giving me the amount of the refund, it's addressing me by first name. But I think we can do a little bit better, and we can do better with retrieval augmented generation. So what I've done previously is I've created what's called a retriever. Now, all a retriever does is it kind of does what it sounds like it does, which is retrieve the right data into the prompt from what I specify. So I'm going to drag in my retriever for my return policy in here. And when I drag that in, I also want to give this retriever some parameters because I don't want the LLM to waste time searching through every single document every time I run this prompt right. I want to give it some specifications. So I wanted to specifically look at price adjustment eligibility. Now let's go ahead and save this and preview it again and see how we did. Okay. If we look in the resolution, we're going to see exactly where this prompt is looking for the right context and grounding our prompt with it. And our response is much better. So why don't we see it actually inside of the experience that we started out with? So I'm going to ask my question to Sophie. I want this price adjustment. I'm going to confirm which product it is, because I've been shopping a lot. So we want to make sure it's the Right product for the price adjustment. And immediately what you're going to see here is that Sophie can not only adjust the price here, give me the amount, all the context that I need, but can process that refund for me in a matter of seconds. This is the power of data cloud under the hood, empowering us with the right data for AgentForce to really take action for the customer. And Sacks was able to do all of this quickly with Agent Force. They were able to ground their prompts, empower Sophie with new abilities, and do all of this on the platform without training a single model. So now that we've shown you how the platform works, the power of Agent Force, all of this really does come to life when you see it across the customer. 360. And to do that, I want to invite our SVP of Trailblazer Community, Leah McGowan here.

All right, New York. It's always great to be back at my own stopping ground. Brooklyn in the house. Oh, things have changed. All right. Well, as Parker said, if you've been rocking with us since 1999, you know that our mission, our vision has always been to help you connect with your customer in new ways. And this has not changed. If anything, we have doubled down on this. And we do this by helping our customers build their customer360 by pulling in their service, sales, marketing, commerce all into one tightly integrated platform. And now we're bringing Agent Force to every one of these applications. And we want you all, everybody here to meet their Agent Force. Today we're talking one Agent Force on one trusted platform. And what this is going to allow you to do is it's going to allow you to create a seamless experience for your customers across all lines of business. So let's look at this for each application, shall we? Let's kick it off with sales. So Agent Force for Sales acts as your sdr, helping your sales team convert and increase their pipeline, as well as provide coaching to all of their sellers. And then there's Agent Force for Service. And here they're working with your service reps to help close cases faster as well as give proactive and personalized service 24 7. And I know what you're thinking, but what about marketing, Leah? Well, Agent Force for Marketing works with your marketers to help them create and deploy highly personalized and super precise campaigns at record speed. And then Agent Force, Agent Force for Commerce. Now, this is really amazing because what it does is it's going to work with your merchandising, your buying and your personal shoppers. All to help your customers find the items that they're looking for. And then I know, what about revenue and orders, Leah? Well, we didn't forget about them either. With Agent Force we have automated the revenue life cycle from quotes to contract to billing. And this is super powerful. And with AgentForce and Tableau, we are bringing AI to analytics. Now those are two powerful words and bringing those together, mind blowing. And what this allows you to do is to see your data easier so that you can move from insight to action on one platform. And lastly, but definitely not least is AgentForce in Slack. And you're going to see how you can collaborate not just with your fellow colleagues, but you're going to collaborate with agents as well, right in the flow of work. Now we're going to bring this in. Oh, and let's not forget our industries. Now we understand that each industry is unique. So we have over 100 industry specific actions for Agent Force available right out of the box. Now we're going to see this innovation all come together through the lens of Fisher and Paykel, which is a premier brand, premier brand in appliances. And this is really timely because we're talking about holidays, everybody's cooking. So we're going to look at this and we're going to have a lot of great innovation that we're going to see through four mini demos, or as I like to call them, minnows. I just made that up, four mini demos. So we're going to see lots of innovation through four demos. Let's kick it off with our first one with Agent Force and Field Service. So here we are. Now, a customer's refrigerator has been beeping. Now we've all been there, maybe you haven't, but I know I have. And you kind of keep pushing through and you sort of ignore it. Well, you know who is not ignoring it? Agent Force. Agent Force sends the customer a text and is like, hey, you know what we're noticing and does say that. It says, hey, you know what? Hey, we noticed that your freezer temperatures are high and we want to send a technician out there to check out your freezer. Well, it's the holidays. We don't need anything defrosting unnecessarily. So, so they come to to a date, they go back and forth with the customer finding a date that works for the customer and voila, it's settled. Now this is all proactive with AgentForce and now we want to fast forward to the day that the technician is coming out. So when the technician comes out, they receive a brief of everything. A pre brief of the work. Now what's really cool about this is they're not just getting a brief about the work they have to do, they also know about the customer. Now I know I've had technicians come to my house and they didn't even know my name. But having here, this technician knows who the customer is, knows about past incidents, all of that information. And what this is doing is Agent force is preparing that technician to provide excellent customer service, personalized customer service. And the technician knows all of the items that they need to fix the problem. Now by show of hands, how many people have had a technician come to their house, they get there, work on something, then go, oh, my bad, you know what, I'm going to have to reschedule because I'm missing a part. How many people have experienced that? Okay, but guess what? Not on Agent Force's watch. Because in the past, the technicians had to manually check on the truck, make sure they had everything, match up all of their jobs with the inventory. Now with AgentForce, Agent Force automatically identifies every item that is needed for that technician on their truck for the entire week. And what that means is they show up to the job ready and able with all of the tools. So once the job is successful here, AgentForce automatically writes a summary up, removing that admin task from the technician so that they can start prepping for their next job. But this is even powerful because inside of this summary here, it actually triggers a workflow that then goes and adds the customer to any follow up visits or any checkups that they might need to know or any notifications. That's the power of being in an integrated platform, being able to leverage those workflows, those mulesoft APIs, all of the validation rules. All right, that was Minnow number one. We ready for Minnow number two. Mini demo, Remember mini demo number two? Let's jump into number two with Slack. So welcome to Agent force. In Slack here we have an army of agents ready to go. So we're going to go ahead, let's check out the inventory agent profile. Now earlier we saw Patrick show us how these agents are built. Right here we have the inventory agent with the skills, all their skills, their topics and the knowledge based articles that power this agent. But let's see all of this come in action. So we're going to go to the channel here. Excuse me, the American Amer east distribution channel. Now in Here we have 119 employees collaborating in there. But I want you to notice right next to to it, you see that Five. That means we have five agents in there working alongside the employees as well. So let's see what this looks like. The inventory manager asks the agent, hey, how are our inventory levels looking for the rest of the year? Well, check this out. The inventory agent comes back with information, but they have receipts for that information in the form of tableau dashboard right there. So here's the thing. This, this agent has the CRM skills, but it also has tableau skills. And this inventory agent is able to use predictive analytics because it says, we notice that 17% of jobs are scheduled within two days of their incidents. And this is also a really busy time of year. So all that to say you need to order some more inventory, but all of that predictive built right into that agent. And here's the thing. The agent doesn't just give insights, it also takes action because it's on the integrated platform. It has access to all of your flows, all of your apex, all your validation rules. In here. It kicks off the order process, which is an actual flow. So here, this is super integrated right here. This inventory agent is kicking off the order process. Awesome. Let's jump into vignette or menu number two, three when we're going to look at agent force and marketing. So here we have agent force and marketing, which is going to help your marketers create and deploy very personalized campaigns with great precisions. This is an existing campaign, but AgentForce notices this campaign is missing a segment. If you look on the right here, it's saying you're missing a segment of customers that only have one one connected appliance. Now I want to pause here for a minute. Marketers know identifying segments is difficult unless you got like a ride or die data scientist with you 24 7. These things take while. And even if you do have a data scientist, no shade data scientist, but this would have took days, weeks or days to figure this out. Agent force figures this out in seconds. So here agent force not only identifies the segment, but also identifies the attributes to complete this segment. So when we go in and look at the attributes, we can see the first attribute is pulling back all of the individuals that have one connected appliance and then the second segment attribute. Now this is where it gets really interesting. Here we're using Predictive analytics because AgentForce identified that customers typically go into a showroom when they want to purchase an oven. They want to touch it, they want to see it. They, you know, you're not going to just purchase it online and not look at it. So this attribute is Going to find folks that are close to the Fisher and Paykel showrooms. So we are all good with this segment. We want to go ahead and create the segment. And now as we're doing this, Agent Force is still at work. It's like, how can we help you move inventory faster? Well, Agent Force comes back and says, you know what, you should also offer a promotion to this segment. You should give a 20% off to help move this inventory faster. Well, I'm like, if I'm a marketer, I could definitely use a partner that's going to help me sell my inventory a lot faster. And that's exactly what Agent Force is doing right here. So let's see what this all looks like when it comes together in the ad. Now here we can see the lovely ad. 20% off that oven is beautiful. Now, Patrick Assange and I had their shopping moment. I would like to have my shopping moment and purchase this oven. But then that means I need to cook. That's a whole nother thing. But we're going to go ahead and book that. That looks great. That's the power of agent force in marketing. Now let's wrap it up with Minnow number four. We're going to look at Agent Force in sales. Now, in here, you're going to see how an SDR agent helps sellers qualify prospects. Now, a customer has received this highly personalized email telling them about a promo for oven. The customer is very much interested in it and has some questions and wants to go back and forth. Now, listen, it's Q4. Sellers are out there trying to close deal, hit their numbers, going back and forth and trying to figure out this person's really serious about oven takes a lot of time. Well, this is where agent Force comes in and lightens the load for the sellers. So agent Force goes back and forth answering the question. And when the customer is serious about purchase, it has moved from the looky loo stage into I really want to purchase this oven. We can go ahead and schedule the appointment. Agentforce schedules the appointment to bring them into the showroom. That's awesome. So now if we fast forward to the day they're coming in, the seller can get fully briefed on everything that the SDR agent has said or the conversation has had with the customer. All the things the customer's looking for. Right there in the middle is the conversation. And if the seller's short on time, they can see right there on the right hand, there's a summary that Agent Force also put together for the seller. So the customer so the seller is fully briefed on who the customer is. And what you're seeing here is agentforce is really lightening the load so that the seller can use. Can work with all of their customers and they can have qualified quantity time, quality time with quality customers. Now, before I close this out, I need New York to help me out. Can you guys help me out? All right. Can you help me out? All right. So when I do this, I need you all to say, agent Force. Are you ready? Let me test it. I need you to say it with conviction.

Agent Force.

All right. So that's how humans with agents drive customer success. With Agent Force. Thank you. Back to you, Parker.

All right. Great job, Leah. You're a hard act to follow. All right, well, Patrick took us through how easy and also powerful agentforce is. And you can build them too, if you go out into the room over here just after the show, but don't leave yet. But Agent Force is super easy. Powered by data cloud. Sajana showed you the power of data cloud to personalize those agents. And Leah just knocked it out of the park to show you how those agents can appear throughout the customer. Customer. 360. All those touch points. So all of you want this, right? You want to get to the world of AI customer success. I want it. You want it. That's what we want. We want to help, you know, you connect with your customers with these. These agents. But we've all been trying to do this for probably the last couple years, and it's not easy. You might have been training some models, building your own custom models, retraining because you want to keep them up to date with the latest data. You might have data that you don't have access to. It's trapped. You might be disconnected from all those applications you've been trying to. How to. How do I hook up the skills at all those applications? You're like, wait, these LLMs have no security model.

Oh, no.

My data is all in this LLM and I have no security model. You're hiring specialized AI engineers scaling rapid change. This is hard stuff, people. So don't do it yourself. You know, 26 years ago we said, why are you trying to build and run your own Salesforce Automation? This is crazy. Why are you buying computers? Why are you hiring people? We are doing the same thing today with AgentForce. Don't do it yourself. Use AgentForce. It's right there. You have it. You have the platform. You have data cloud. You have the customer360. You have agent Force. And you Might be saying to me, parker, I don't have this. Oh, no, I don't have this. Oh, well, you do. We have Salesforce foundations for enterprise customers and above. You just upgrade for free and you get sales, you get marketing, you get service, you get commerce, you get data cloud and you get agentforce with 2000 conversations built in to get started for free. We want you to understand the power of AgentForce. We want you to understand that today. But before you leave the room and go out. Yesterday I had the pleasure of going to this thing we call a hackathon. So we had a bunch of people coming and hacking Agent Force, trying to build agents all over the place. Kristof Kohenratz here ran that. Christoph. Come. Come on up, Kristof. You know, I walked into the room, normally I like people to say hi to me when I come into the room and I came in and everyone's like, heads down and they're like working hard and I'm like, what's going on? Like, don't they want to say hi to me? What were they doing, Parker? They were hacking. We in fact had 45 teams competing for a $20,000 grand prize. And all these teams built amazing agents with Agent Force. But we have a winner. And the winner built an incredible event coordinator agent. So please give it up for the winner of the Agent Force Hackathon. Team 4DS. All right. Team 4DS. All right. Congratulations. You don't. You can't get this yet? Sorry. Don't try to take the check. Do not try to take this check. I hope you're not flying anywhere because this check may not fit in the overhead compartment, but $20,000, that's pretty cool. What are you gonna do with $20,000? You don't have a mic, but I'll tell them what you said. Build more agents. Build more agents. Actually, he said buy more agent for us is what he said. He's going to build more agents. Well, congratulations. And I love that it's an employee facing agent. And I don't know if you noticed, you can actually light that up in Slack. Did you see that demo earlier? Okay, so I want you to light it up in Slack. Congratulations. It's incredible. Were you up till late hours? Midnight? No, no. It was easy, huh? Easy peasy. All right, well, we're going to let you take this check. Why don't we get a picture? Yeah, we need a picture. Kristoff, you go on the other side because this is pretty cool. This is a big memory for you guys. All right, Big, big shout out to the team. 4Ds, winner of the hackathon. This is pretty cool. All right, guys. Congratulations. Yeah. All right, well, thank you so much for being here. Agent Forest World Tour. Thank you. For everyone online who's been online this whole time. I forgot to give a shout out to you. Thank you for being here. There's more ahead. There's a talk by Sanjay Gupta. Future of health and technology. You can build your first agent. Go out and build an agent right now. Please download the app and please give us feedback on the keynote. We love feedback. And thank you very much. World 2 New York.