EP 149: Marc Benioff (CEO, Salesforce) Predicts Half of Conversations Will be With AI Agents Next Year

Speaker A: There were more than 100 million leads that we have not called back at Salesforce in the last 26 years because we have not had enough people. So we just couldn't call them back. But we have now an agentic sales just for our own company. More than 10,000 leads a week right now. Having conversations, turning them into pipeline. Our pipelines have never been more full and a lot of it has to do with that. We're feeding them with this agentic capability. And so our salespeople are also now part and parcel in partnership with these agents as well.

Speaker B: Mark, thank you for doing this.

Speaker C: Oh yeah, it's great to be with you, Logan.

Speaker B: So I think, uh, it's been eight months or so since we had the last conversation. I think we're seeing a lot of um, at least I'm seeing a lot of end of software. This is the end of application software as we know it going on. I guess. What's your perspective over the last eight months and some of the rhetoric about this that we know we're no longer going to see the commercial opportunity for software that we've seen in the past?

Speaker C: Well, I think there's two things, you know, you look at the uh, last eight months, I mean it's been eight of the most exciting months I think of my career. When you look at what's happened with applications and with software, it's pretty awesome. If you remember, our conversation was all about AgentForce and we were getting ready to deploy Agent Force on our support we layer. And now uh, we have, and I just tell you like, we're customer zero for our new agentic service and support product at Salesforce. So we have uh, now done about a million and a half conversations with customers. And at the same time that's the agentic layer speaking to the customers. A million and a half conversations also happened through our support agents during that same period. And the CSAT scores were about the same like, which was stunning. And also I was able to rebalance my head count on my support. I've reduced it from 9,000 heads to about 5,000 because I need less heads. But there's also an omnichannel supervisor now that's kind of helping those agents and those humans work together. And this is the most exciting thing that's happened, you know, in the last nine months for Salesforce. And we also are deploying thousands of customers with the same vision.

Speaker B: I want to dive into, uh, some of those things that you brought up in a bit, but I guess I'm curious, uh, the agent Force and you mentioned uh, the cost reduction or the ability to kind of manage costs within customer support and I think engineering as well, you guys have been able to manage what the headcount and scalability of that looks like. Do you think the biggest benefit of AI is going to be cost optimization for organizations or do you think that ultimately we're going to have revenue uplift as well?

Speaker A: No, definitely not. I think that you know we are all on our path and I feel like I um, have to pioneer this as my, as I said my own customer zero and I just gave you the support example. But I have to tell you a good story which is that and something we did not talk about nine months ago, which is that there were more than 100 million leads that we have not called back at Salesforce in the last 26 years because we have not had enough people. So we just couldn't call them back. But we have now an agentix Sales uh, that is calling back every person that contacts us in our company and we're doing about, just for our own company, more than 10,000 leads a week right now, having conversations, turning them into pipeline. Uh, our pipelines have never been more full and a lot of it has to do with that. We're feeding them with this agenta uh, capability. And so our salespeople are also now part and parcel in partnership with these agents as well. So just in the way that the support people, nine months ago I said we were about to do that, we now have also done that in sales

Speaker C: and I have other examples I can give you because I am on a mission to make Salesforce an agentic enterprise.

Speaker A: And I think that this is what can really transform every company.

Speaker C: As uh, you can see I've rebalanced my support headcount as I said so

Speaker A: I can now put those heads into sales.

Speaker C: So I've increased my distribution capacity and now I'm also making sure that I

Speaker A: have much more efficiency and productivity in

Speaker C: my lead generation and in the ability to actually work with customers that are contacting me. Even in my website I have deployed uh, an agent on the front of it. So if you go to our website you'll see we've taken all of our data from our website, put it into our data cloud, put an agent on the front of our website. Now you can talk to our website right through our agent as well. And so that just makes the marketing so much more efficient. This is really the beginning of every part of the company having this kind of agentic augmentation. It's A force multiplier. It's a synergistic effect between me and the agents and we're proving it out first at Salesforce, but we also have thousands of companies that are also deploying this.

Speaker B: You talk to a lot of investors and you've seen a bunch of technological trends, I guess. Do you think public market investors or investors at large are sort of waiting to see this come to fruition either in the growth rate, acceleration or profitability before they really lean in on the themes or what's been the sentiment as you sort of talk to people in the public markets on the investment side?

Speaker C: Well, I think you definitely see a lot of confusion with customers or with investors on what does it mean that we're moving into an agentic era? Does it mean that software and applications go away completely? I mean that isn't true for me. I don't know if it is true for you, but I'm using applications on my own.

Speaker B: I will say. I mean this exercise I was having the other day and I'm curious your thoughts on it is like, you know, I've been long, my career's been sort of predicated on investing in software, broadly speaking. Right. Uh, but I'm definitely going to websites less like in using OpenAI or Claude as the portal of accessibility in some ways. And so I was thinking like will I ultimately use some similar interface? And not to say that that's going to capture value that you wouldn't otherwise capture, but I do wonder about the interface element and the usability changing.

Speaker C: Well, I think at Salesforce what we have really seen is that in the type of applications that we're deploying and the automation that we provide to enterprise professionals. So I kind of gave you the example of, you know, our support center where we have an omnichannel supervisor that's

Speaker A: managing humans and agents together.

Speaker C: There's no better interface that I've seen or I would use it on top of our data foundation. You know, our data foundation is our data cloud, Mulesoft, Tableau and Informatica. That's the core of our company. And we're, we have a huge amount of data ourself in there, but we also manage 230 petabytes of that information for our customers all over the world. The second layer is the application foundation and some of these areas like support or sales are highly specialized applications and require, you know, incredible, you know, powerful user interfaces. And by the way, it's not that I don't have like a slack user interface for service and support or a Slack user interface, uh, for sales. But then, you know, I still have to branch out because all of a sudden I've got a lot more data I need to consume and humans are not going away. We are working in partnership with these, with these agents and that's how I look at it. And then when it comes to Slack, like for example, since I talked to you nine months ago, I now have, you know, a couple dozen agents running inside Slack on my behalf, doing renewals, you know, doing support, but also like doing my wellness benefits, doing, you know, all kinds of interactions with my employees. They operate in, inside the Slack application. You can see in the Slack marketplace all kinds of new agentic apps and ISVs that are running inside there. That's amazing. So that is probably the most exciting, most thriving ecosystem in tech for the enterprise right now is inside Slack. So I think we're really have a good solid look at that every single day.

Speaker B: Do you think, and this is maybe tied into my job in some ways, but do you think. I don't know what percentage you guys have of the CRM market. I used Claude before this and it said uh, 26% was the number I got and ServiceNow was 44% of ITSM or something. One question we've been wrestling with is like, do you think we're going to see just much more federation and like this generation of companies that are being founded right now might pick off a percentage point or two here or there and the market overall will grow. And so it's, you know, a rising tide for everyone. But it's going to be really hard for net new businesses to have that level of penetration that you guys and ServiceNow and Workday and whoever, ever, whoever else have been able to achieve.

Speaker A: Well, I hope you'll come to Dreamforce and you'll see. Actually we have a, we've never been

Speaker C: in the itsm, um, market before.

Speaker A: So we're entering and we're building on Slack, you know, so It's a Slack first app. It's Agentic also. So it's Agentic, it's Slack first. And I mean ServiceNow is a great company. They, you know, I think they automate like 9,000 companies. I don't know what the number is that they have. But Slack is on a million companies and those million companies, they're, you know, small and medium and large and extra large. Just because all, you know, Salesforce sells to the five major segments of business, uh, that the all of the IT

Speaker C: world and Slack is one of those products that we do that with and

Speaker A: that idea that we're entering the market for itsm. But it's, you know, a whole different kind of architecture. But it's the architecture that we're talking

Speaker C: about which is we have to have

Speaker A: humans and agents working together. And that when we're, you know, managing, you know, our assets in our company or you know, really kind of providing that kind of, you know, database to really understand the change configuration, you know, agentic capability is very powerful. And then if you can provide it right on your phone in Slack, that's really a next generation ui.

Speaker C: And we're doing that with all of our products. So all of our products.

Speaker A: So like our sales cloud, which we've talked about, you know, for decades, it's becoming agentic sales.

Speaker C: Our service cloud is agentic service.

Speaker A: Even our marketing cloud where, you know, we do 11 trillion emails every single year. Those are all one way conversations.

Speaker C: Today, you know, you're going to see a dreamforce.

Speaker A: Those are all going to become two way conversations. And uh, it's because you're going to

Speaker C: have an agentic on the end of that, having a conversation with those customers. And I'll tell you, like even, you

Speaker A: know, in my home I have an Airstream trailer outside and it's hooked onto

Speaker C: the power grid, you know, with this device from a company called Eaton.

Speaker A: And they've been a customer of ours for years.

Speaker C: They've done, you know, their sales and service on us. But we have this field service product that we also now have made AgentIQ. And so when the field service agent from Eaton shows up, not only are they like on their phone, you can see the app by the way, it's on the app store. Not only are they looking at all my information, oh, it's Mark Benioff. Here's his home, you know, here's his Airstream. We got this working or I don't understand why this is not working. He's not by himself, he's with the agent. He can interact with the agent and the user interface. Exactly as you're kind of describing that kind of, you know, large language model interface and trying to figure out what's going to work, what's not going to work. And then all of that is going to get stored into the system of record so that when the next agent comes out to fix my, you know, power system again, it's all right there in front of them because that's going to be the nature of field service. You know, even like when we work with PG&E on their wildfire prevention they're out there with our field service app where they're looking at every power pole and every branch and every piece of. But they're not alone. The agentic layer is with them. It's humans and agents working together. But the system of record, the uh, agentic layer, the LLM, all have to be integrated together. You know, it's that we talked about this actually nine months ago. I remember the data layer, the data foundation, the application layer and the agentic layer are uh, the three core layers of how applications are working going forward. And that's at least that's how I use them every single day. And maybe you have a different way. Even when I'm using. For example, like last night I was shopping for ties. So I was, you know, on an LLM and I'm looking for the right tie and this kind of thing. It wasn't one of the two that you mentioned, it was a different one. And then it brings me in there. It's kind of a super search. You know, it's like helping me search to find the website. And then I'm, now I'm on the website, but I still had to go to the website to complete the transaction to identify, you know, who I was, complete the commerce. Will that maybe get more refined? It probably will. But when it comes to the fundamental trust, security and information sharing in an enterprise, that is a different ballgame right there.

Speaker B: What is managing agents and managing workers entail? You guys have gone through this transition on the support side a little bit and um, increasingly maybe on the R and D and development side and now on the sales side as well? Well, I guess what, how do you think about if you're a leader in trying to figure out how to deal with both the change management process associated with going through that, but then also like how do you actually organize and design the business such that KPIs and accountability is actually roiling through the organization?

Speaker A: Well, we talked about that too nine months ago, which was. I really felt I was going to be the last CEO who's only managing teams. Remember that?

Speaker B: Yes, I do think, and I still haven't come up with a better term of like managing agent workers or something. For some reason that feels a little dystopian to me. Uh, but it's clearly headed down that path in some way, shape or form.

Speaker A: No, I don't think it's dystopian at all. I think that this is reality, at least for me. But I'm managing agents and humans and that means my agents, when they show up to a customer, like I told you of that salesperson, now that's calling back all my leads. And that sales agent, there has to be a certain kind of set of guardrails, a certain personality, a certain kind of tone, the ability to know when it needs to escalate immediately to a human being. Because these large language models can do a lot of things, but they cannot do everything. And you know that.

Speaker C: So.

Speaker A: And that we're kind of hitting in some ways, you know, a high evolution of the large language model as we

Speaker C: can kind of see as we got into GPT5 looks a lot like GPT4.

Speaker A: It's more evolutionary than revolutionary. So we're seeing a maturation of that type of technology right now.

Speaker C: That deeply integrated into the tech, into the application layer.

Speaker A: That's where I'm getting the most value.

Speaker C: And that idea that those agents then

Speaker A: when they're directly talking to the customer

Speaker C: or directly talking to the employee, they

Speaker A: need to be, you know, managed through those guardrails, they need to be managed through that structure. And that's incredibly important for us as

Speaker C: the tech vendor to be able to provide that to the customer.

Speaker B: When, when you say 30 to 50% of work is being done by agents today, I guess how do you think about the, the unit of work being done? How do you assess that at an organizational level to try to figure out where the balance is of who's doing what?

Speaker C: Well, I think we kind of lay it out like in that support example, which is really, I think, uh, the best example, right, that if we were having this conversation a year ago and you were calling Salesforce, there would be 9,000 people that you would be interacting with globally on our service cloud, and they would be managing, creating, reading, updating, deleting data. We called CRUD database with an app of very powerful interface, you know, with lightning in some cases, if there's a case, maybe it gets swarmed onto Slack. But this is what they're doing. Maybe they're checking the analytics in Tableau, maybe they're over here, you know, doing, doing some other kind of sentiment analysis. Now it's a different system now all of a sudden, here we are a year later, and the million and a half conversations that are happening going forward over the next year, and a million and a half human conversations that are going forward over the next year have now bifurcated. 50% are with agents, 50% are with humans. And there needs to be also technology and people who are managing. How are these working together? And because all of a sudden, like the Agent will scale out and say whoa, I can't handle this, I need to, you got to go help handle, have the human work on that. It's not any different than have you been like in your Tesla and all of a sudden it's self driving. It goes, oh, I don't know actually now what's happening, you take over and that's kind of the same thing but on a very complex, you know, you're working with a very complex customer. You know, in a support environment. That is really the magic going forward. You know, how do we get these two. And so that idea of the 50, 50, I think that's definitely where we're going in sales, in service, in marketing, in field service, in the fundamental collaboration of our employees. Um, all, all of, all of these pieces are going to have that kind of balance.

Speaker B: I don't know if you've reported since May on numbers related to this. What I had down was 8,000 deals and generating over 100 million. Ah, for Agent Force. I don't know if there's newer numbers out there, if that's the latest.

Speaker C: Well, you'll, you'll hear those when we do earnings next.

Speaker B: Okay, great. Okay, so, so earnings, we'll wait in bated breath for that. I assume they're higher than they were in the past. What, um, what was counterintuitive or as this has ramped up, what's been unexpected in the response of actually seeing this out in the wild and in production?

Speaker C: Well, you can see that our AI and data product line is the fastest growing product line we've ever had. It's, you know, it's over a billion dollars now. And uh, that a huge shock that we've been able to scale it as fast. I mean we've seen the, these great startup companies like Databricks and Snowflake. You know, we've been investors in both of those companies. Uh, we helped bring Snowflake, uh, public or investors in databricks as well. And you know, and then you know, we look at other companies that are doing data foundations or data foundries and others, it's like, wow, this is a big category and these companies are all like 3 to 4 billion dollars in revenue and now all of a sudden, well, we're $1 billion and we're fast tracking to 2 billion in revenue on that product. So that's very exciting. I think that, that idea that the Data foundation product line, the data cloud, the uh, you could even say Agent Force at some level though I wouldn't put it at that stratification mulesoft, which also provides the integration capabilities as well as Informatica, which you know, as we've announced we're going to acquire as part of our data foundation and um, getting all of that working to really get our customers to harmonize all their data because if you don't have that data together you can't have the accuracy with the AI. This is really a huge category uh, for customers and I think that this category will radically expand or it has been expanding, will continue to expand for us.

Speaker B: Have you guys not closed Informatica yet? These big regulators, man, uh, it's crazy how long these deals take to close.

Speaker C: I guess you've never acquired a company before.

Speaker B: Not at the scale, not at whatever your guys valuation is.

Speaker C: We've done quite a few acquisitions, I think maybe more than 60. So I'll just tell you that, you know, we just let everyone work at their own pace.

Speaker B: Yes, yes, I uh, that's very diplomatic of you.

Speaker C: I have a lot of respect for everyone. There are a lot of hard workers out there.

Speaker B: Yes, yes, exactly. Uh, that's very diplomatic. They talk about a place we could use some agents. I guess, um, I guess one of the things we touched on last time that I'm very curious about is like the, the per seat pricing which you guys were a pioneer in and then the shift to more agentic pricing I guess. Any updated observations, thoughts, perspectives on like what's going to be maybe cannibalistic as you don't need as many seats to do it, but might increase overall dollars that a uh, customer spends. How do you think about that now with a little bit more data?

Speaker A: I, I've been on the road for two months with customers and so I'm just back now in my office. So you know, my view of that really continues to evolve which is of course with perceived pricing we've always had consumption pricing also which is like we saw in our commerce cloud or even on email or our data cloud is consumption pricing. Per seat pricing is like the sales cloud, the service cloud, slack. You even see per seat pricing like on ChatGPT that you mentioned or you know, these kinds of products. Um, so per se pricing, consumption pricing and then conversational pricing or this kind of idea that maybe you have a certain amount of conversations or certain kind of flex credits and one more category which is customers want kind of the ability to buy all of it as one big package way more uh, aggressively than I realized. They want kind of a complete uh, agentic enterprise license agreement. Every company is really on a path to become an agentic enterprise. I've articulated us as customer zero. Like I gave you the story now of service and sales or what I'm doing in Slack where I have a dozen agents and I'm renewing customers. You know, nine months ago, I had no agents deployed in my company. When we talked before, you know, now I have lots of agents and I think every company is going to when they see what we've done. And when you get to Dreamforce and see my keynote, I'm going to have a 12 Fortune 100 companies there, you know, all showing you how to build an agentic enterprise. Different shapes and sizes, different ways to do it, ranging from Pfizer to FedEx to OpenAI Anthropic. They're all going to be at Dreamforce, really showing customers how to do that. That's October, you know, 14th, um, through

Speaker C: 16th in San Francisco.

Speaker A: And I think that will be a very critical thing that I don't just articulate, hey, here's our great new product. Here's, like I said, the new ITSM product or this new product or that new product, but here is customers being successful, becoming agentic enterprises. Last year we were just talking about Agent Force. You know, we've talked about that. Here's Agent Force. You can deploy this.

Speaker C: Go.

Speaker A: Now we're saying, no, actually, this is a huge enterprise transformation for you. And in every category, we're going to transform that function. And we've had to rebuild every single one of our products to not only be the application layer where you're creating, reading, updating deleting the data, but also working hand in hand with the agents as well. And that is, I think, really exciting. I think for a lot of customers, they haven't been able to see it yet, and they want to see what other customers are doing and how to make it work and how to deploy it. And that, I think, will be probably my greatest pleasure at Dreamforce is to see customers show other customers how they're doing it.

Speaker B: You mentioned OpenAI and Anthropic there, and we touched on a little bit of the scaling elements of the model today. I'm sure you get to see a lot of stuff in preview or get to have conversations that, uh, a lot of people aren't privy to? Um, do you think we're increasingly moving to, like, an absorption and digestion phase where we just try to take advantage of all the value that we've already presented or those model companies have already presented for enterprises to take advantage of? Or do you think we're still on a fairly steep slope. And it's a little bit of ways from the harvesting stage.

Speaker C: It depends what category of the market we're talking about. You know, the market is really in five segments. You have the small and medium business, you know, the, you know, call it a couple hundred employees, you have the medium businesses, call it a couple hundred to few thousand employees. You know, you have the large businesses, call them like four or five thousand employees. Then you of course have the very large fortune businesses and you have the government. And these five segments of the market each need a slightly different version of the product. They need something with a slightly ui, they consume it a little differently and the speed of their deployment is different because their architectures are deployment are different. And also AI is going to dramatically change, you know, small businesses. There's going to be a radical explosion of the number of small businesses because AI is going to make entrepreneurs so much more, you know, capable and probably a media business too. And of course in large business like mine, it's happening. But not everyone is probably as committed to deploying the technology rapidly and at the bleeding edge as I am. So those five segments will all adopt the technology slightly differently. And that's my observation of technology over 40 years.

Speaker B: And so where do you think we are on that? Uh, do you think we're at the absorption stage for the mainstream enterprises?

Speaker C: We're at the beginning of the beginning. A lot of for big enterprises, let's call them the uh, big extra large enterprises. You know, they've a lot of them have tried things out. Some of them like in the Dreamforce keynote, Pfizer will be there. They've deployed agent force to 20,000, you know, their sales professionals. They use our life sciences cloud, which is now also a gentic that idea that we're able to kind of, you know, work with a company like that to kind of give them much more capability for their professionals, that it's a force multiplier for their employees that is very powerful and for their customers as well. And other customers need to see that. In the pharmaceutical industry, it's a great example. It's a variation of companies who are willing to try technology to companies like Pfizer who are always the leaders in deploying that technology. So I called Albert Borla, CEO of Pfizer. Please come be part of my keynote. That's very important for me because they are pioneers. They're really doing an incredible job, you know, really delivering this next generation of AI.

Speaker B: One of the things we're seeing in the private Markets for startups, I guess. Is this maybe a overused terminology but adopting some of the um, nomenclature from the Palantir world of like forward deployed engineering, which I think is being purpose filled, purpose fit a little bit differently than what Palantir intends it to, to be. And maybe it's a little bit more of um, I saw someone call it sparkling sales engineering or something versus in the past. But I guess do you, are you seeing more consultative relationships with customers that are helping or that are looking to you to help them, um, more map the journey than you have in the past? And therefore does that require like different staffing or different utilization of resources?

Speaker A: Internally I'm very inspired by Palantir. You know, uh, they, they sell in, they sell in parts of the market that I have not traditionally sold in and they also sell at prices that I've never seen enterprise software being sold at.

Speaker C: So I have various multiples that uh,

Speaker B: you know, rarely are seen as well.

Speaker A: Right, yeah. And I mean yes, the federal, US Federal government, Salesforce's largest customer and you know we run all the major, you

Speaker C: know, civilian agencies like the Veterans Administration, fully automated on Salesforce. And I would say that now, you

Speaker A: know, when we look, you know, certain

Speaker C: parts of the government we haven't sold

Speaker A: into but in some areas, you know

Speaker C: we are, you know, selling. And, and uh, the U.S. army we just beat, you know, Palantir was publicly

Speaker A: announced, you know, on a, on a new deployment.

Speaker C: And I would say that we're going to do that because our prices are so much better at lower cost and

Speaker A: our technology is probably so much easier to use to deploy. But when it comes to, for deployed engineers, this idea that we had salespeople and system engineers on the front lines, that was always true. We had professional services.

Speaker C: That was always true.

Speaker A: But early deployment engineers are for deployed

Speaker C: engineers where you're starting to build the application before the deal is signed. That isn't something you know, that we've really ever done before. And I find that very inspiring and I'm definitely trying that out and seeing

Speaker A: if that will help me m. You

Speaker C: know, accelerate, you know, customer acquisition. I think it's a really cool idea and I, I'm very inspired not just by you know, the hundred times revenue multiple.

Speaker B: That's inspiring too though.

Speaker C: That's inspiring.

Speaker B: Yeah.

Speaker C: But I'm also, I'm inspired. Look, you know, I've been a um, 4 million dollar company, a uh, 40 million dollar company, a 400 million dollar company. I've also been a 4 billion dollar company like Palantir.

Speaker A: And now I'm a 41 billion dollar company company.

Speaker C: So I've been all of those stages and each stage is a little bit different. But I can be inspired by everyone and anyone.

Speaker B: Are there, are there unique pockets that you think are advantage to be a startup, um, these days versus an incumbent in the market? And you would say, hey, here's the opportunity for investment that might exist outside of the core advantages that incumbency has.

Speaker C: Well, I mean, Salesforce has been a very active investor. You know, we run our Salesforce Ventures. You know, we own 1% of anthropic.

Speaker A: We just were part of selling Wiz to Google, you know, which was a

Speaker C: huge, you know, outcome for us. I think more than a billion dollars. And um, you know, we helped, you know, we took Snowplake public. That was more than a billion, A billion and a half. Both of those, I think were billion and a half. I would say that I don't know what the IR exactly is in Salesforce Ventures. I think it's like 33%, something like that. When we're looking at these companies today. And I just met with two entrepreneurs myself yesterday. They're both 18 years old, they're both in Y Combinator, they're both building on Anthropic cloud, they're both addicted to it because anthropic gave them $30,000 of free credits. They're using their new Harmony API. They're doing all of these things. And I'm like, whoa, innovation is alive and well in Silicon Valley. And every time you hear that, uh, you know, San Francisco is dead or something, I'm like, don't worry, another gold rush is coming. And then people never go, oh, Mark, you don't know what you're talking about. And then, oh, yeah, here we are, it's a gold rush. And look at people are coming in from all over the world with their pans and their shovels and their picks and they're got their blue jeans and they're panning. And I would say that it's a very exciting moment where you can see all these new technologies, new ideas, incredible innovation and things are moving fast. And as evidence that I'm going to go back and watch what we said nine months ago and see how much of it has iterated, evolved and changed, and how much we've actually been able to get done. Because usually it's not. These enterprise deployments are, uh, not done, Logan, in nine months, it's like, whoa, I've got this. Oh, yeah, hey, Logan, this is my actual result here's. The KPIs. Here we go. And that's why I'm super motivated and excited. I'm super energized. And when you get to Dreamforce, this needs to be like a big message that I have, which is, hey, you need to become an agentic enterprise. Here's the products. Every app is now agentic. Here's the data foundation, here's all these pieces. But I don't think customers care that much about what I have to say about the new products. I think what they want to know is, hey, what did that person do? What did FedEx did? This. And here's, you know, the CEO of FedEx explaining exactly what they did here. You know, OpenAI did this and this is exactly how they did it. And that, I think is cool. And that I think is another level of kind of capability that we have to be able to show. And I'm, uh, going to pivot. You know, how I present my keynote based on that feeling I have, which is that, you know, these customers, like, I'm built these big customers in Europe and they're like, whoa, I want to become an agentic enterprise. These are customers that I've had for like one or two decades now. I'm like, hey, we're going to move your whole infrastructure forward, rebalance your headcount the way I'm rebalancing mine, change your business KPIs, and you're going to come out the other side as an agentic enterprise.

Speaker B: We kind of touched on it there. And also when you were talking about the startups or the young kids going through YC these days. But it does seem as a private investor, there is a different rhythm or cadence that it seems the AI first companies are operating under. And I think to some extent, when your world around you is changing so quickly, it forces, uh, an internal culture of change to be much more material in a meaningful way than like, more traditional businesses. I guess, outside of adopting agent force in mass and all the good stuff that you guys bring to bear up and down the stack, are there things you've learned about how to change the speed of moving a bigger organization that's gone through changes in the past, but now has to operate at the speed of the competitors that were founded in the last couple years?

Speaker A: Yeah, I mean, before talking to you, I actually spoke, uh, to a company that I helped start in the AI world. Richard Socher used to run Salesforce Research, you know, has this incredible company called view.com and it's an AI first search company. It's amazing. It's scaling incredibly well. It's does incredibly accurate search based capability. You probably have it on your phone. If you don't, it's pretty awesome. They also provide an API approach which is widely consumed by some incredible companies, gives them a search infrastructure, you know, uh, powerful. And another example is I have another company called Artera, which is an AI first company and that company is doing prostate cancer diagnostics, just got an FDA clearance, it's about to do breast cancers, do other ones. And these are in my private venture portfolio, you know, which is Time Ventures. So when I look at what Salesforce is doing, what I'm looking, what m I'm doing, I would just say it's very similar. You know, you have a great entrepreneur, you know, so you have Andre Esteva who's running Arterra, you have Richard Socer who's running um, u dot com. They're visionaries, they're experts. By the way, both of them used

Speaker C: to work, both of them are in

Speaker A: Salesforce, both of them used to work together in the AI world. They have a clear vision of what they're trying to accomplish. One is doing, you know, next generation search through an API. The other one is, you know, trying to provide democratizing high quality healthcare globally through AI. It's leadership, it's vision. You know, what do you really want? What is your outcome? Where are you totally passionate and totally focused about what you're doing? Nothing is going to replace that. And then the core values that they're building their companies on, you know, is it about trust? Is it about customer success? Is it about a vision, um, and innovation? I would say that when you're running something like how Andre is running, which is you're in like the most sensitive aspects of somebody's life, you know, which is their cancer diagnosis, I would say that that's something where all of a sudden, you know, you better have be completely buttoned up as a company and have the highest level of trust and capability. And so your values matter. So your vision matters, your values matter. And then your execution matters, the quality of your team matters, how you're actually making things happen day to day matters. And also are you rapidly resolving obstacles? And what are your KPIs, are you scaling your revenue? Both of those companies are scaling their revenue really aggressively. Like uh, you need to scale your revenue and go because others will come for you. Well, this has always been true. And you know, I've been in Silicon Valley my whole life. I was born in San Francisco, I grew up in The Peninsula in Hillsborough. My whole life has been in Silicon Valley and all the great entrepreneurs and

Speaker C: all the great venture capitalists that preceded

Speaker A: us, you know, from the era of Arthur Rock and Sandy Robertson, who was one of my mentors, you know, to the great investors and entrepreneurs of today. You know, they have more things in common than different and one of them

Speaker C: is, you know, you better go and you better go faster and you better go now.

Speaker B: I guess, uh, as we wrap, one thing that I get asked a lot and I'm curious, your perspective on this is like if you're a young person, if you're 22 years old, graduating college or whatever, interested in entering a field in some way, shape or form and AI's changing so much. Eight years ago I would have said just go get, five years ago I would have said go get a CS degree and you know, that'll benefit you no matter what you go do. And now I'm not sure my counsel would be the, would be the same. Anything you would give to someone that's maybe in the early part of their career and trying to figure out.

Speaker C: Absolutely. Well, I told you, I just met with this cool startup that's in YC with these two 18 year old founders, you know, that is amazing. And um, and then I have two, ah, two interns from Stanford, uh, working in my office for the summer and hey, create value, Create value and deliver. Deliver something different and create something amazing. And these kids, I don't know, you know, these kids, they're a, they're AI natives, they're authentic natives, they're not digital natives, you know, like they are, they know intuitively what's possible and where this can go. And then they're looking at my business process, my product lines, my capabilities and saying actually here's your gap and this is what can get filled in. So that's very powerful. And we need these people and I really, these studies. Well, we're not sure if we're going to hire these kids from college. I mean what a mistake for companies not hiring people from college or bringing in new talent or bringing people in at that age. I mean that is where the real value and the insights and the energy is going to come from.

Speaker B: I guess one last one before we hop. So You've been the CEO now of Salesforce for 25, 26 years. You've seen every cycle that at least in my lifetime, from dot com to mobile to cloud to AI. Um, do you have a contrarian bet that maybe people believe about AI today that we're going to look back on in five years and it's just going to be patently false.

Speaker A: Well, I think that there's, you know, unfortunately we have this kind of Klarna, you know, I would say reality distortion field that got created, uh, around the time we talked about a year ago, where all of a sudden the CEO of Klarna seems like a very new sky. I've never met him, I've had him

Speaker B: on the pod, seem wonderful, but his

Speaker A: message has changed like 10 times in, um, 10 months. And the stuff that he said was true. He's kind of walked back. Is not true. I see on the other side, there's people in my industry, even some of my peers, who talk about the end of apps or the end of crud, you know, that enterprise apps are just CRUD databases. It's like, whoa. I just think that there's a lot of kind of crazy things. I mean, I think even some of the talk about AGI may be, uh, uh, too augmented, that these large language models are really amazing, but they're not AGI. And I was like this, this weekend, I was like, figuring out how might communicate this to people because we forget these large language models. These are relatively finite algorithm sets with regular, relatively finite data sets. And those two things provide you some functionality, but not all functionality. And as evidence of that, there's this really cool medical study now that our brains start to create immune cells when we're near sick people. And I was joking on Twitter. Well, I kind of missed that feature on GPT5. I don't think it does that quite yet. So we still have an advantage. But I think at some level, because you're talking about these finite algorithms and finite data sets, which is kind of what all the AI is built on, the same data set. These, uh, LLMs, which is why they're all kind of. Seems like they're hitting this upper limit where you can see GTP3 or 4 might have been more revolutionary. Maybe GTP5 is more evolutionary. You know, that there's still some cool things happening, but it's not these big transformational leaps. I think that we could kind of then make a statement of, you know, we're going to need another set of models and another set of capabilities before we get that next set. And that when you're dealing in the finite, like the finite data and the finite algorithms, we're infinite, you know, we're infinite beings. We have the ability to have a level of creativity and inspiration and insights that's beyond that. That's why that example of like, hey, we're creating immunes.

Speaker C: We have an immune system.

Speaker A: You know, we're creating immune cells. We don't even realize we're creating immune cells. We're tapped it into a level of energy and capability that's beyond the finite data set. So, um, I think we have to keep that front of mind that I

Speaker C: think we still, uh, are an important part of this, uh, world that we're in.

Speaker B: That's an optimistic note to end on. Mark, thank you for doing this.

Speaker C: It's great to see you again, Logan. I hope you're coming to Dreamforce now that I'm invited.

Speaker B: Uh, I was waiting.

Speaker C: You are invited. I'm happy to have you and it's going to be awesome. You're going to love it. And, uh, do you like Metallica or do you like Benson Boone? It seems like it's an a B test.

Speaker B: That's interesting. Uh, I guess if those are the two extremes, I would put myself a Metallica.

Speaker C: I thought. Yeah, I thought so. Yeah. Well, there's a whole group of folks who are Benson Boone people. We're got both. And maybe Stevie Wonder might make an appearance.

Speaker B: Are you going to do the Benson Boone outfit? I hear big CEOs dress up.

Speaker C: Oh, and I will not be doing the backflip either. But I do like the music. But I, of course, Lars, I clip very close with, as you know.

Speaker B: Yeah.

Speaker C: Metallica does a lot with Salesforce, so we love, uh, working with them.

Speaker B: Oh, okay. I will see you at Dreamforce. Great to see you, Mark.

Speaker C: It's great to see again.