Welcome back to Jefferies AI Week. We are on day three now and looking forward to the conversation with Parker Harris, who is with us. He's a Founder, Co-Founder, and CTO, among many other titles inside Salesforce. Parker, really good to have you. We got Mike Spencer as well on as well, so any questions for Mike, he can take. Parker, again, was one of the Co-Founders of the company. He's been there for over, well, over two decades, helping lead the company through many technology shifts. Parker, great to have you here. You've helped steer the company through many of these different technology shifts over the last couple of decades. Many are asking about the AI era. Is this different, how you're embracing it? Maybe kick off just from your overall thoughts as we enter this new era. Yeah, yeah, of course. I feel lucky to have been part of so many things. We took advantage of the internet as a different way to deliver software, and that was 26 years ago. I thought that was a big deal. We rode through the iPhone coming out. I think that was, what, 2007? That has changed how we use software. In 2014, I think we started doing a lot around machine learning and AI. I had to admit, during that time, machine learning was great, predictive AI was great, but some of the early LLM work, I was a little bit skeptical, like, would it really move the needle? When all of this hit that tipping point a few years ago, I think we were a little surprised, which was interesting because our research group had actually participated in a number of papers that contributed, including prompt engineering, by the way. We pivoted the whole company, and I think AI right now could very well be bigger than what the internet has done to e-commerce and software. I think we took that very seriously and have pivoted the entire company, which, you know, Brent, you've seen all the work we've done around Agent Force in particular. It's still super early days, and I'm not sure I'm a believer in AGI is going to happen tomorrow, but I am a believer in the power of AI for productivity in the enterprise space. Back to what's most exciting for you in Gen AI, could this be bigger than the shift to cloud and SaaS? When you think about what's driving this overall excitement across the industry, maybe if you can peel back one layer about what you're seeing and why this can be so much more incremental from your perspective. Yeah, I mean, if you think about the internet, it was a different, different delivery model. We could, you know, give actually a far better service to our customers at a far lower cost, not just our licensing costs, but all the costs around it. They didn't have to buy computers, they didn't have to hire all the people to run them, we did all that for them. It was really an economic shift of, you know, you could argue in pricing and the quality of the service we delivered. I think with AI, the power of AI is, it's now doing the work beside you and for you. I'd say we're still early, so I believe it's more, you know, augmenting humans very strongly. We're seeing success within Salesforce, so we're being very aggressive, we call it customer zero, and really pushing hard to make sure that we're using this technology first, and we're seeing amazing results internally. We're seeing a lot of results in our customer base. We just launched Agent Force literally a year ago. It started out with some simple use cases of like, hey, come to your website instead of a chatbot, you have a powerful agent that can really answer customer problems. Initially it's kind of customer, you know, the deflection of those tickets or those problems to the AI versus the human. It's rapidly evolved to much more sophisticated use cases. You'll see a lot of that at Dreamforce at the big conference coming up. I know we'll see you there, Brent, and others. In October, we'll have a lot more customer stories. That's really been our focus, is customer success in the market now with AI. The big debate we're having is SaaS, you know, going through a transformation. What ultimately happens, and I know you have a lot of thoughts on this, is this rule of applications. If you look at all the application stocks we cover, they're all down year to date. Everything infrastructure is off. Simplistically, I think everyone feels like, you know, is the, for lack of better terms, this Salesforce transition, everyone says, are we going from Salesforce to an XYZ transition now? Yeah, I think Satya Nadella's comment that SaaS is dead, everyone's kind of internalized a little too much. I don't believe that AI is going to replace SaaS. I think it's changing SaaS dramatically. You think about the IP that our customers have that they've built on Salesforce, the data that they manage in Salesforce, the customer data. Now, obviously, with Data Cloud, it's far more data, the business processes that they've crafted and that they run their businesses on, the call centers that we run, the marketing campaigns, the amount of all of that. You're not going to take an LLM and say, great, just code all of that up for me and run it. I think what is changing is the interface to that technology. It's not that the technology goes away, it's that it's going to be rethought in the era of AI. What I'm excited about is that it's going to be a lot more flexible. You can imagine that everything a customer has in Salesforce, all of those, the user experience, the business logic, the data, imagine that getting broken down into parts that AI can leverage. As a human, or even as an agent, you're starting to take advantage of that. All of the business logic and the workflow that exists in corporations can now be leveraged as skills and tools from an AI, from an Agent Force agent, or from a third-party agent, from agents in Slack, where I spend a lot of my time right now. The UI is going to change. Maybe instead of logging into Salesforce and you're looking at Salesforce, you're going to be talking to AI. I think it's going to be more and more within Slack, and that UI is going to be coming to you. The AI is going to be poking on those workflows and firing them off, and workflows are going to run. They're going to be running on the Salesforce platform and all that IP, all that workflow that customers have built, they're going to unlock more capabilities in that. We, in a way, are disintermediating ourselves in terms of what does it mean to be a SaaS provider before anyone else is going to. A lot of what we talk about now, actually, in 2019, we bought Slack. I know that you and others were very angry with us that we had bought it because, you know, hopefully you can explain why you were so angry. I think it's probably one of the most valuable assets that we have now. Because if you think about, you know, when you're talking to AI right now, you're talking a lot in text. You're having a chat interface that's evolving to richer experiences where UI is coming back from AI. You're also moving into the world of voice. You're going to see voice at Dreamforce and you're talking to AI. Slack as a front end to enterprise software, to enterprise productivity, a lot of which is in Salesforce, but by the way, it can also connect to all the other applications in enterprise, leveraging all the data that Data Cloud has connected. If you think about our Data Cloud, Data Cloud is connecting all data in enterprise. MuleSoft is then connecting all the APIs, all the workflows in Salesforce and across. Slack's connecting all the interfaces to all of that and connecting, yeah, and talking to Agent Force, which is orchestrating it. I think we have a huge advantage because all of this is one integrated platform. We're not like trying to piece these things together separately. I don't think AI is magically going to come in and, you know, all of a sudden, like, wire all of that up together. These are hard problems. Some of it, you know, like a lot of what you'll see in the market now is people are using AI more prescriptively, and then they're using predictive logic, which is, you know, state machines workflow for things that are, you know, like this is just like, I know what I want to do. I don't need the LLM to think. You can think about that combination. That's where we're going with our integrated platform. Yeah, I don't think anyone was against the Slack technology. It was more probably the close to $30 billion purchase price. That was the only thing I hear in terms of. I know, I know, the value to us is huge right now. You know. Yeah, no, and I mean, just to kind of expand on that, when you think about this world that Slack's going to play, and I know we're going to hear more from you at Dreamforce, how long will this take to get rolled out to customers? When can they start to utilize that as the UI layer? Maybe it's today. How do you think about kind of the timing and how this can impact their, because this to me seems like a really easy way. We use Microsoft Teams internally. Sorry, I'm mandated to use it. It has really become the layer where we interact with everyone. How long will this take? Yeah, I think it's happening now. I think it's happening now. You know, Teams is great for video. It's great for direct messaging. Hey, you know, Brent, you know, I got something to ask you. It's not really a place where people do work. That's really what Slack is. We see a lot of coexistence actually in our customer base where they're like, great, yeah, I got Teams that was bundling fine. You can now launch Teams meetings from Slack, you know, or Zoom or whatever you're talking on. Slack's where work is happening. You know, to go talk to any of the major AI providers, you ask them, you know, what are they using most? They're using Slack and they're using, you know, an OpenAI. It runs on Slack and they're using AI through Slack because Slack is where humans are working together and it's where humans are also connecting to AI. You'll see definitely at Dreamforce, but it's happening now. You're going to see Slack as a place where Agent Force agents are the best place to be. It's the best place where a human is going to work with an agent unless they're on your website, for example. We put on help.salesforce.com, we launched that as customer zero. If you go to help.salesforce.com, you can use Agent Force and talk to AI. That's more of a self-service customer-facing, but if employees are working with AI, it's going to be in Slack. You're going to see Agent Force there. You're going to see native AI in Slack that's just like right there in the flow of work. You're also going to see, you know, we're releasing more on our third-party platform, meaning when OpenAI wants to plug into Slack or Anthropic or Perplexity, or think about all the do-it-yourself AI that has kind of been a failure to me, but there's a lot of AI out there that corporations have built. We're going to make it easy for them to leverage that for now, and they can use it within Slack as an interface and then also have access to the Slack data where they can, you know, search it. Also, Data Cloud and Agent Force, and it all plugs together. Our vision is Slack is where humans and AI come together, regardless of what AI that is. Obviously, Agent Force for the enterprise is going to be a huge productivity lift. We're also an open platform. We want to also allow you to plug in other AI. Slack will be the predominant platform. We win because that's where the action is. That's where the activity is. We can use that more and more to drive value to the customer base, value to the end user, and capture more value over time for what we've delivered. Back on the application concerns, one of the concerns is if this actually works the way you think, are there going to be as many employees to sell to? Workday CEO said, look, they're still seeing their employee count expand. Recently, Carl mentioned that. I think everyone would kind of love to hear your thoughts on that. I think simplistically, everyone says, if Agent Force works and I have 100 call center agents, maybe I go to 90. Is this going to be incremental to my budget? Can Salesforce grow the budget? If you can maybe unpack some of those broader concerns, it would be helpful from your perspective. Yeah, I mean, you know, we grew up on, you know, licensed revenue. You know, we started the company. We're like, well, I think it's $50 a month before we wrote a line of code, you know, and it turned out that that worked for quite a long time. I think there's still a lot of value in per user pricing for certain types of functionality. Thankfully, we worked on our Data Cloud even before this LLM, you know, generative AI revolution really hit. That is a usage-based pricing model. That was our first step. Actually, it wasn't our first step because Marketing Cloud is a usage-based model. Our e-commerce is also usage-based pricing. More classic, you know, similar to the hyperscalers' usage-based pricing of like, hey, I'm using credits for processing data in Data Cloud. We've released that a few years ago. We have what we call our digital wallet. This is kind of like when Amazon started. We're doing it for SaaS now, where we're teaching our customers, hey, I know you like licensed revenue, you like predictability. We're going to give you that, but we're also going to give you predictability because on more usage-based pricing, because customers have asked us to move to that for a while. You can't price, like if you're going to get rid of a number of people in customer service, or they're going to move to higher level jobs because they don't need to do the jobs they were doing, and if AI is doing that work, I don't think you can price it and say, all right, we're going to price per human credit, you know, like replace that seat. Some things are very simple. Hey, I need to, you know, for Salesforce, hey, I need to change my password. Okay, yeah, sure. That's, you know, actually a lot of our support tickets are like, hey, I don't know how to, you know, update my password. It's a very simple problem. AI can, you know, solve that for you. Or if you're, you know, going to Williams-Sonoma, you'll see a story of Williams-Sonoma at, hopefully at Dreamforce. You wanted to return, you know, some pans you bought. AI can do that for you. Depending on the complexity of that transaction, the value to the customer is different and also, you know, the value that they should be paying us. That's really where we get into usage-based pricing. You need that predictability. That's where we have a lot of calculators, digital wallets that the customers can start to understand, where is that cost going? That was kind of what Amazon went through when they launched, you know, usage-based pricing for Amazon. I think it's early in the market. Customers are like, hey, you know, I want to pay you by the drink, but I want perfect predictability. We're giving them that. There is this trust layer that they need to start to see empirical evidence. Okay, I can see that. That's also why you're seeing us going into our customers with, you know, four deployed engineers on Agent Force. We're working on very specific use cases and jobs to be done and making them successful, then showing the customer, okay, for this, this is what this transaction is costing you. We're growing those deals. It's a little bit of a different motion with Agent Force and Data Cloud where we're going in and going fast, proving success quickly. Customers are coming back and saying, that was great. I'd like to buy more. I want to buy more credits because I want to get more value. That's that trust layer, that momentum of that. Over time we get that recurring revenue of that usage-based stream. Salesforce doesn't pay by the drink to Amazon. You can get very big deals over time as you get that trust because we know for all that we run on AWS, we can kind of predict here is what we think we are going to use in the basic compute and storage and everything that Amazon would charge us. We'll do a multi-year deal. We're going to get to that as well where customers say, yeah, it's a little bit more expensive for me to just have that predictability and pay you, you know, as you go. We can all use discounting and say, fine, you know, you want to sign up for a bigger deal. Sign up for a bigger deal, a bigger discount, you know. We're headed in that direction, but still early. In the future, it's a world of seats and usage-based model. It's going to be a total mix. Think about what's happening in corporations, like you said, where humans in some areas of the business may do less and hand it off more to AI. We want to give our customers the ability to move that spend, so they're like, great, you want to leverage more usage of AI, of Agent Force, more usage of Data Cloud. That's fine. You're going to be able to move some of that spend around to basically help our customers. We want to help our customers move into this agentic world. We want them to be agentic enterprises. The way to do that is to give them the right technology, which is our platform with Data Cloud, Agent Force, Slack First, Analytics Everywhere, by the way, is another part of that, and giving them the ability to evolve where they've been in the past. I'm moving from all licensed revenue to a mix. We want to help them make that shift. We want to be in the customer, proving that out really quickly so that they can gain that trust and move with us into this future. This is scary for everybody. It's like, wow, AI, it's taking jobs, or will it be successful? I launched into AI in my do-it-yourself mode, and I have it all over the place, and it hasn't been entirely successful. That's where we're going in and saying, we have a platform, we built it, we've tested it, we have the predictability. Let us prove that to you. It's kind of like, think about 26 years ago, I'd come to you and say, hey, Brent, do you want to run your sales automation on the internet? People were like, I don't want my contact list on the internet. They didn't trust us, right? Or IT was like, I don't trust that you're going to make it available or that it's going to be secure. You can't do that. I'd do that. We're just in this new world of, do I trust that the AI is going to work? Is my data going to be there? Will it be predictable? Will it be secure? We're just in that mode again where we're proving it to customers. We're going fast. It's all about those customer stories. Dreamforce, that's the whole point this year, is let us tell you the customer stories of success, of moving into the agentic world and becoming agentic enterprises. Just on Agent Force, it's been a quick ramp, 5,000 - 8,000 to over 12,000 deals in the last quarter. It's a really nice progression. Many have asked us, you've got over 150,000 customers. Why aren't customers stamping even faster? When you think about this ramp and your ability to get them onboarded, maybe just talk through what you're seeing, the number of go lives. We'll hear more at Dreamforce, but it seems like this is one of the fastest ramps of the new product you've seen in a while. Help us understand the trajectory. I think, you know, there's two things. One is, you know, the technology is moving really fast. We're, you know, when you think about, we used to call it force.com, you know, where our platform is called force.com, and you would use our platform to customize it to do what you needed to do. Early on, we did more hand-holding of our customers to make sure that they got the most out of it. As we perfected the platform, you know, we created, you know, more ease of use of the platform, more predictability, now in AI. It became more self-service where customers and our SI partners were doing more of that. I'd say right now, we're our customers directly. You know, you'll see a lot of the stories that we'll tell. We're in there with those customers, and we're proving success. We, you know, we have a, in the staff meeting that we have that Mike Spencer and myself and the rest of the team with Marc, we're looking at what we call the Agent Force funnel, which is not just like, okay, what are our leads? What's our pipeline? We always do that. What are we closing? Great. We're going all the way down to implementation and looking at that every single week because we want to know, and not just implementation, it's not, you know, we used to call it conversations. If you remember, you know, pricing a year ago, now we're looking at actions. It's fine to have a conversation, but is it driving action? Is it driving outcomes? We're looking at measuring those actions. That's how attentive we are as a management team on driving this momentum. I think that is fueling that customers. It's the same thing we did 26 years ago. Make customers successful, tell their stories, you know, market the hell out of that, get more customers, make them successful, and, you know, turn that flywheel. It's early, and we want to make sure that we're really paying a lot of attention to every single customer, especially because this technology is brand new. You know, everyone's saying like, oh, I love AI, but it's non-deterministic. You know, it can hallucinate. You know, I don't have the right data, you know, my data is a mess. We have to make sure that all the customers know, like this, and there's new roles in corporations that you need. We're in there, working with our customers. We're also working with our partners to scale them up so that they're doing what I'm, what we're doing and being in there with our customers. If I said anything, it's that this is all about a customer success war in the market. It's getting this technology in customers as fast as possible and getting them successful. Yes, we have 150,000 customers. You're going to see a lot more coming, but they're all coming off this do-it-yourself hangover where they're like, oh my God, I've done so much with AI. They're fighting with their CIOs. The CIOs don't want to tell the CEO, yeah, what we have been working on is not totally working, because I went and I did it all myself. It's kind of working sometimes, but I really believe they need an integrated platform like Salesforce has to offer because it's not just about, hey, I want to automate sales, and I want to automate lead nurturing. We have something called, we hire people, we used to hire people called sales development reps, and they would do outbound calling into customers and say, hey, would you like to buy some Salesforce automations, some marketing automations, some e-commerce, customer service? They still do that, but we have a lot of leads that we couldn't work on because we didn't think they were high value enough. Now we have an agent that's going out, it's called an SDR agent, and it is sending emails out to customers. It is receiving the responses, processing those responses, and actually nurturing those leads. We have AI doing that. Is that just a sales use case? Not really, because it's also a marketing use case, because those emails are about how do we market to the customer our products. When you think about, well, I'm not just automating sales, I'm automating sales and marketing, and I need to flip between sales and marketing and then service, and I need to do that fluidly, and I need to have access to all the data across all those touch points, that's where Data Cloud comes in. I think people don't really understand how much technology we have and how integrated it is and how much work we've been doing over the past five years plus. The power right now of that in this agentic world and Slack, let's keep talking about Slack as the way to pull it all together as that interface. We have those assets, we've got to prove that out in the market, and really fight to get to all those customers. Maybe, maybe to add one thing to what Parker was saying, if folks are interested, the funnel he was talking about that we review on a regular basis, we did a deep dive with a number of the product leadership underneath Parker and team right after earnings, and it's available on our website. If folks are interested, they want to see a visual of it, they want to hear our team talk through the process that Parker's talking about and what customers are going through. It's a pretty good, it's about 45 minutes long, but it's a pretty good walkthrough of what we're seeing. Parker, just on Data Cloud, you know, 120% growth, billion tune rev, you know, really, really impressive trajectory. Everyone kind of asks like, what's next here? I think one of the biggest concerns or limitations we hear of getting AI going is how do you get your data state ready? How do you, yeah, effectively, you know, get it set? There are a lot of questions in the question hotline we're getting about, maybe this is the big issue for the industry, is data readiness really improving? Or are we at a spot where companies have the right data? It seems like in many, many situations, the answer is no. How can you help with that? Yeah, I mean, that's the first realization everyone has is like, you know, they plug an LLM in and they started doing work and they're like, wait, this is, you know, the data is not right or I don't have access to the data. That's where our data, I mean, I'm so happy that we had been building our integrated data lake, integrated, you know, data activation platform that's kind of used in multiple ways. It was already well on its way and successful when we started building Agent Force. Yes, data is super important. I think what customers found is historically they'd go off and they were building their data platforms with Snowflake, with Databricks, maybe on Azure or Google or GCP, or AWS with some of the native tools, which is great. They get the data all in one place and then they tell their employees, okay, the data's here, come get it. Usually what that meant is, okay, I'm going to go do analytics and look at history because it was locked up, it wasn't really tied back to the active work of the corporation, like selling, like doing customer service, like marketing to the customers, or e-commerce, all the capabilities we have. You know, Data Cloud in the market is super valuable right now, certainly as a role of a CDP or a customer data platform for marketing automation. That's where we see a lot of success. More and more, it's about unlocking all the data in enterprise. I think we need to explain that clearly to the market, to the customers, that it's both. It's both a data platform and resident data that you can use natively to clean up your data in place. It's also an activation platform to activate your previous efforts that, you know, you got the data in one place, but you didn't complete that last mile and turn it back into value. It's just sitting there. I didn't think this was possible that technology moved ahead of me and we were able to do what's called federation or zero copy where we can unlock that data that's sitting in Snowflake, that's sitting in Databricks, that's sitting on GCP and GQuery, sitting in any of your data platforms and bring it back into the flow of work, bring it back into like, how do I have that personalized email or marketing campaign out to my customers? How do I understand who that customer is right now from a customer service perspective? You're like, are they on my website? Are they trying to return something and struggling? Then they call the call center and the call center agent needs to know right then what's going on with this customer. We need to connect all those sources. That's where Data Cloud comes in. That's where MuleSoft comes in, connecting to all those different platforms and data sources. That's where Agent Force comes in because Agent Force looks at not a database, it looks at a logical data model of your corporation. You can think about this virtual data model of my corporation and a virtual, a logical data model of my customer. That data could be coming from all kinds of places, but Agent Force doesn't know that. It doesn't care. It just sees Data Cloud as this logical schema. The data's rationalized from all these places and processed, and you get the single view of the customer. I can use it when I'm selling, when I'm servicing, when I'm marketing. That's kind of the magic of getting that value out of your data. The customers that have been investing in this are going quickly with AI. Customers who haven't, we're in there with them and helping them connect all those data sources, clean out their data, and move quickly. Also, by the way, why we're so excited about bringing in Informatica as an asset. Yeah, that'll be a good thread to pull later. One of the key questions we're getting is, you know, Mark kind of highlighted Dreamforce and said, you know, we're jumping in the IT Service Management market. Many listeners have asked me, you know, why did they wait so long? You know, ServiceNow got to almost a $200 billion market cap. Why now? I think it's about focus, Brent. You know, like, I mean, there are so many things we could do. If you could imagine internally, like, why don't we do this? Why don't we do this? We could do this. We have to focus. I think we stayed focused on our core market and service, and move further into CCaaS, move further into the contact center, move further into automation, connected Slack for case swarming. I want to bring in all the right people to help me solve customer use cases. You know, then we looked at it like, that is a market we should have too. It's also like, you know, we also see ServiceNow trying to come in our direction, you know, and we're going to go, you know, every customer, a lot of customers use ServiceNow for ITSM, and I'm like, I'm sure I'll use it. It's not the best experience. It's not connected to their customer service. It's not, not well connected to Slack, by the way. When you think about our entry into ITSM, it's a Slack-first ITSM model where the employee, hey, I need my new laptop or my phone broke or what's going on with my systems, like something broke, I need to do resolution management. Where are you going to do that? You're going to have people working together. You're not going to do it over email. You're going to do it over Slack. Oh, I need it to be connected to all my data sources. Slack's connected through Salesforce, through Agent Force, through Data Cloud. You think about all the assets we have, and our platform. I mean, you know, ServiceNow basically built a baby version of our platform. It's fine, but we have a better platform. You think about the assets we have. We just have to add a few things. I need to understand what the assets are in the IT system in my corporation. We're taking a lot of our existing IP and putting it together for that use case. I think that's the power, you know, and it's one system, and it's Slack-first. I don't have to swivel chair between Workday and Salesforce and ServiceNow. I just am living in Slack. I'm using Slack to do my work. I'm using it for collaboration. I'm using it to do my customer service work. I'm using it to do my ITSM work, which is a different use case. I think you'll see ITSM is kind of one of our first use cases of a Slack-first foray that's adjacent to where we are. I think we can do others. Yeah, there are a lot of questions from investors in our hotline queue about agents. There are a lot of agents that are out there, and many are asking, you know, OpenAI is going to have their agent, you know, others are going to have agents. What gives you that inherent advantage for Agent Force to be the standard? We have the users starting to plan. We have the data, and we can take that advantage, and we have all the implementations of business logic, everything I was talking about before. We're taking all of the advantages we currently have and then applying them in an AI-first, Slack-first, Agent-first world. It's an open platform. Agent Force is going to be there, and it's going to be the best at helping you do your sales, helping you do your customer service, marketing, e-commerce. It will help you build agents for employee productivity. If you want to plug in OpenAI in your corporation and also use it for some other research or something, God bless you, go ahead and do that and use it from Slack. You're going to be using a lot of different agents. That's why I think having the user base and having the attention, because you're going to be using it from within Slack, I think definitely you're going to be using it there. You're not going to be using it from email. You're not going to be using it from Microsoft's products to work with all the different enterprise tools, I think. That's the advantage we have, that we're going to capitalize on. We're going to listen to our users, and we're going to watch them. Are they being productive in those use cases? Is Agent Force working well for them? Really augmenting the humans, doing the work on behalf of the humans when it's appropriate, like that SDR agent example or like at help.salesforce.com. We're going to keep evolving technology driven by our customers and customer success. That's what we've been doing for 26 years. I think as long as we stay true to our values, that, yeah, it's trusted. We're focused on customer success before we're focused on innovation. Like with AI, we're all getting mesmerized by the demonstrations, and in the market, you're seeing it. Companies are using an LLM to do some really cool stuff, and they're selling these little companies after six months or a year. There's some interesting IP out there. We can get mesmerized by demonstrations. It's really about customer success first before you get lost in the world of all this magic that, you know, it is magic until it's not. It's wonderful. Like when you, if I demo, you're like, oh my God, that's amazing. But does it work every time? Is it really, can I trust it, and am I being successful with it? Those have been the values we've had all along, and we're still guided by those values. Yeah, Parker, maybe to close out the chat, and thanks again for being part of this. When you look at the internal team and the technology and everything you're building, and you know, we all sit on the outside, but the question is, when you think about what's the most underappreciated thing we can't see that you see, what are we all missing? What are you all missing? I think you're missing the impact AI is having right now in the simple use cases, that it's having a big impact on productivity. You know, AI right now is probably the best in the enterprise at coding. The reason for that is because there's so much IP out there of code that these models have been trained on. We're seeing upwards of 30% productivity in our engineers because of AI. What you're missing is the AI is not taking over. It's not replacing those jobs. It's just making the engineers we have that much more productive and making them more predictable, like not creating bugs. I can't demonstrate that to you. Like, check this out. Isn't this the most amazing demonstration? What you want to see is the AI writing all the code, writing the spec, and doing it all for me. Then I don't need those engineers. What I think the world is missing is focus on the simple stuff right now and appreciate the productivity of automating the simple things and making them more predictable and the productivity gains that you get in the enterprise. We're going to evolve really fast as that matures and gets, you know, solve more complex tasks. The productivity gains right now of just focusing on helping me get my work done is transforming a lot of enterprises. I think the other thing you're missing is thinking about human capital in that way. Our Head of Employee Success or HR, Nathalie Scardino, has worked with our President of Engineering, Srinivas Tallapragada, and they've looked at, as Srini took over customer support and services, they looked at the job roles and there were so many different titles. They were both looking like, well, these are all the same job function. They looked at like, let's break that down and like, what are the job functions? What are the skills? What are the human skills? What are the AI skills? I think the other thing that people are missing is thinking about where is human capital going and not just like, what are we going to replace? What are we not? How do you think about how to evolve human capital and think about it at the skill level, at the role level, and not making it overcomplex? You know, you actually, there's only a certain number of job functions and skills that people do in a corporation. We just give them lots of different names. If we look at it simply and we look at how AI can help, we're going to see a lot more productivity gains in every corporation. Do you feel that the claims that the founders of OpenAI and many of the other LLMs have put some pretty big numbers out there in terms of the job losses? Most at AI Week have said that they don't believe that's more headline grabbing than actual reality. What are your thoughts? I think there's definitely a lot of hype in the market. I mean, if you look at, just look at the capital spend that's going on. I mean, it's like, we're all watching it. You know, the spend that Meta, that OpenAI are spending, that has been, you know, NVIDIA, it's also a good bit of ancestors that NVIDIA is giving money to OpenAI. They're buying the chips from NVIDIA. Oracle's giving, you know, but there's a lot of money. With all that money, all that investment, it comes a lot of hype too, like, you got to justify where that's all going. It's got to be big. I do think there is a lot of hype. That being said, I think we should think less about job replacement and more that jobs are changing and how fast are they changing and how do we retrain workers. You know, like that sales development rep example, like maybe over time, Salesforce won't hire any humans to do that job. That's fine. The people that are doing that are going to do higher level sales jobs. I'm going to have AI doing the more basic stuff. I do think some of what we call entry-level functions in corporations, that's changing. I don't think it's this job replacement where jobs are going away. Just as like in the industrial revolution, jobs didn't go away. We have far more jobs now. When the computer came out, the personal computer didn't replace jobs. We have way more jobs now. It's just we have new jobs, different jobs, ones that we don't even know of yet. I'm an optimist. I think the world's getting better, and it's going to be good. If people don't learn to use these tools and they don't get retrained, we are going to have people get left behind. We're going to have more partisanship in the world. It's going to be big issues. I think it's on educators, on corporations, on governments to figure out how are we going to move everyone into this new agentic future. Parker, real pleasure having you. Looking forward to seeing you at Dreamforce. Mike, thanks again to your team for pulling us together and being part of Jefferies AI Week. Thanks again. We'll see you soon. Brent, thanks for having us. Thanks, Brent. Take care.