We have the OG. We have We have Mark Beni off today. >> Mark Beni off. >> Mark Beni off. Mark Beni off. >> Mark Beni off. Co-founder and CEO of Salesforce. Absolute legend in tech. >> Thank you. >> I feel like I'm becoming the bottleneck. I still have to >> You probably are. I don't think most people still really understand what is going on. >> If you were to give advice to somebody fresh out of college >> and she's asking me if she should change majors, so I'm trying to recruit her. >> All right. Welcome everybody. Welcome. I'm Matt Berman. Uh, and of course we have here Mark Beni off, co-founder and CEO of Salesforce, absolute legend in tech. >> Thank you. >> Lately, one of the loudest voices talking about agents, how they're going to transform work, how they're going to transform communication, and I'm so excited to talk to you today, Mark. Thank you for joining. >> Well, I'm so happy to be here. Thank you. And we're so happy to have everybody here for this incredible event. We just had a great program downstairs um here at the St. Regious and uh it's been an awesome day. >> Yeah. A lot of features launched

Slackbot. We're going to talk a ton about that. >> A lot of happy customers and partners. >> That's right. I am especially excited to talk to you because I think about a lot of these questions all the time. And now I get to sit across from you and actually ask the man himself about how he thinks about the future. So let's start out with the AI interface. Salesforce acquired Slack and it is increasingly obvious that agents should be everywhere that work happens, not trapped in a single interface and Slack >> seems like the perfect place to do that over time. How do you think about the tension between Slack being the primary interface and then also Slackbot needing to live everywhere? >> All credit really goes to Peter Schwarz on our team who's our chief futurist at Salesforce. A lot of people know Peter who wrote or co-wrote or participated in the development of movies like The Minority Report, uh War Games, Deep Impact, and other things. Um you know, you universally regarded uh in our

industry as a being incredible futurist. Well, he came to us uh now almost 10 years ago and said the number one thing that we should focus on is acquiring Slack. At the time, no one in the company really agreed with him and no one in the company really understood why that would be. Um, but his number one focus was that the world would go to AI and the world would go to agents and it was his words exactly at that time. what he foresaw correctly was that we were going to get breakthroughs in the models that we were seeing being pioneered in Silicon Valley that we would um need an interface to those models, something that is conversational, something that is open, something that has a broad ecosystem. I think what no one could have seen though is not only that Slack has persisted at a great user interface to AI, but also this ecosystem is so rich. The ecosystem of Slack is beyond any of our expectations. It was never kind of foreshadowed that this would be

one of the great parts of Slack and it has become that way. And also Slack has become a great interface not only to the AI community, not only to all these companies including the AI companies, but also to Salesforce itself that all of our applications are becoming Slack first. >> I mean, let's continue on that thread. So, your co-founder Parker hinted at this or kind of spoke about it during the keynote today. Do you see a world in which the traditional Salesforce interface almost fades away a bit and and people are really just interacting with their agents, their their Slackbot and then kind of sitting on top of your data layer. Is that the future you see? There's no question we we've said this to our whole company now several times that we really over time you know really want to kind of position lightning in where it amp gets amplified where it's strongest but at the same time lightning has a role but slack has a role and I slack slack as a conversational interface is just a great place for Salesforce users to live not just

Salesforce users even Tableau users other other and of course the users of all these ecosystem products as well. In fact, I just had a great, you know, demonstration of writer AI, which is this amazing new, you know, AI tool a lot of folks are using in the marketing community. It was 100% in Slack. So, that idea that products are coming along to be 100% Slack first, we are completely behind that. >> And then are you comfortable with people taking their Slackbot off of Slack wherever else they may be working? Do you see a future in which that's going to happen? huge part of it that I think that Slackbot should be kind of a highly composable object that can be dropped into every capability and we're committed to working deeply with Teams from Microsoft or every other collaboration tool like Workspace from Google. >> But in addition to that, the idea that it can get dropped into every Salesforce app as well. So when you're in SalesCloud, you know, which is our number one, you know, namesake product or a service cloud, the Slackbot is with you as well.

>> Yeah. Okay. I mean that makes a lot of sense. I want to talk about how this transition >> good. Will you communicate that to my product people as well? >> Uh yeah I just >> nervous laughter from the nervous laughter from the audience. >> So so I want to I want to actually continue on that thought because all of these changes really change how work happens. They change how companies are structured. How do you think team structures change from here? Do you think we're going to see fewer or sorry more smaller teams? Do you think we're going to have bigger, more ambitious companies? Uh do you see like a SEAL team being the the the best uh application of the human team inside of a company? What do you think is the right way to think about this? >> All of the above plus a huge explosion of agents that you know are getting coordinated and commanded either through the AI or by humans. As we've been saying for the last two dream forces and I think we got this right, humans and agents are working together. This idea

that we have a role and the agents have a role. When you look at the power inside of a company for the agentic layer to become an agentic enterprise is what we say. That idea that all of a sudden now I have my agents who can help me service my customers, sell to my customers, qualify my customers, market to my customers, have conversations with the customers because agents are built on large language models. The key word is language. It's good at speaking language. So things that are basically impacted by language like a like a service conversation are going to be dramatically better using these tools. Uh even coding coding has now become a language. When I was coding it was not a language. We were down to the machine level you know and we're doing 68,000 assembly language you know at Apple in 1984 that was not about language that was about you know a whole different kind of mathematical construct. Now coding is language and so these tools are very good abstracted at that moment.

>> Yeah. And so I I'm facing this in my company. So I want to ask you agents are getting better. They're producing more work. they're able to almost anticipate what I need. I feel like I'm becoming the bottleneck. I still have to I certainly am. Right. >> I am definitely >> is I wanted to see if you felt that way and like what is the solution there because we're still having to prompt and we're still having to verify which is incredibly important to human in the loop. But >> over time the human also is the bottleneck and I'm already feeling that. Are you >> it's fine with the human is the bottleneck because these large language models are still you know wildly inaccurate at times. All of us have had the experience where all of a sudden we're using a large language model and it gets totally confused and it's taken a right turn and it doesn't know what we're talking about. So it's very critical that human beings at least at this stage of AI stay in the loop. Maybe not forever but right now I think it is extremely important and we can see that because the accuracy levels are just not there. So having that ability to really kind of go as far as you can go. A good

example is if you go to help.salesforce.com salesforce.com right now you know that you're working with agentforce to resolve your customer service issue but for about half the calls it hits a moment where that customer is like I need to speak to somebody and the agent goes you're right and boom through our omni channel supervisor goes to a human who then gets a screen in front of them and that screen it could be in Slack it could be in lightning then is looking at all the conversations all of the information and humans are really good at that moment looking at the screen and going actually the problem needs to be this. We're just very good at synthesis and that human even will be 100% accurate but the large language model is still needed a a very high percentage of the time. >> Is is there still a set of tooling to be built to help humans verify at a higher scale? it like I don't like being the bottleneck and I'm wondering >> well one thing is yes and then the second thing is new models that'll be more accurate over time as we have new

AI baked for this remember we are in a continuum of models you know starting for decades we've had more and more models and then now we're in the large language model stage and we'll move to world models but we're going to move to other kinds of models that we can't even describe yet that will just inc over over time radically increase the accuracy and uh our you know uh chief scientist D Silvio Savarasi basically has the vision of you know that we're moving into multiensory models. We haven't really seen them yet but the reason why it's important is the model just has a lot more data to be able to make a decision not just language but all this other kinds of sensory data that we have like we have our eyes and ears and our brain and our memories and all these things and we're able to kind of make these decisions. Eventually the models will get to that point. >> Interesting. And and so let's continue on the human in the loop. For a long time to rise up in a company as an individual contributor, you needed to specialize. But it seems like we're

having a renaissance of the generalist. Are you seeing that inside Salesforce? What do you think about generalist versus specialist in the age of artificial intelligence? >> Well, I think this is especially true in software engineering. Obviously, we have 15,000 software engineers at Salesforce. Each one of them is an A player. And the key thing about these 15,000 engineers, they're all out there all over the world. All of them can now be hugely augmented with these coding models. It could be Enthropic 46, it could be open AI codeex, it could be cursor, it could be others. But when they start to use these models, they're now working not only with the AI but agents to help them code. And they can even become somewhat supervisory over these agents. But still those engineers are needed. the the model still cannot operate autonomously. We're we're not at that level yet of AI. So, it's really critical. So, our engineering organization is probably more than 30% more productive, but I wouldn't call it 100% more productive. And that's why even in the top AI

companies, if you go to their job boards, you'll see they are hiring a lot of engineers. They're hiring a lot of everybody because they have to build companies of humans. Even though these top AI companies, we can go through the list of them again, have these unbelievable models, they need a lot of humans. And that's probably that's the canary in the coal mine that we know that the models are not at that level yet. >> So I I know you're a big believer in humans will be much more productive. You will still need to hire a lot of humans. We're seeing that in companies like Anthropic, like OpenAI. But there is the flip side where there are other companies and a diversions of opinions here that they're cutting and like what what do you think about the reason might be for that kind of split opinion and different approach? Well, Salesforce right now has a you know hit a new record number of employees which is more than 83,000 and but it the balance of those employees and where they are placed is different than where it was 5 years ago

because we went through an uncomfortable period ourselves over the last 5 years of rebalancing our workforce. That's just a difficult thing for any company. In some cases, these companies are cutting because their costs are just too high. In other cases, these companies are cutting because they've made financial commitments specifically to data centers that they have to pay for. And in other cases, these companies are cutting because they need to rebalance their workforce to reflect the changes in artificial intelligence. These are different reasons. So, you cannot bucket all these companies together. If you do, you're making a fundamental mistake, I think, in business. And even though I've spoken about this, I think somewhat aggressively, I don't think most people still really understand what is going on. And it's too easy, you know, to kind of basically take the make AI and make it the scapegoat. And I think for some CEOs, it's the lazy way out. That that's up to them. I think it's better just to say, here's what's really going on and trying to be specific as you can. You're going to take bullets no matter what because

that's your role as CEO. and then you have to kind of get go forward and you know put everything back together. >> Yeah. I mean the CEOs that I'm talking to they're doubling down on the teams that are leveraging artificial intelligence. They are investing more in them. They're hiring more. As you if you were to give advice to somebody fresh out of college uh you said that you know maybe you are rebalancing or had rebalanced inside Salesforce. What organizations should people skill up to? This is a very very good question and I am very worried about this actually because I was just at several universities just last week including MIT in Boston and I sat with an incredible woman who's a junior at MIT top computer scientist in her class and she's asking me if she should change majors and I walk through with her the realities of AI and the models just to remind her of her own technology you know strengths of what you know where the technology actually is and the reality is I'm trying to recruit her, try to bring her, but all of her colleagues, you know, should come to

Salesforce. We're hiring interns. We're hiring that freshman class. We want to send our recruiters out to those top 25 high academic threshold universities like MIT and bring those top computer scientists and others to Salesforce because we badly need that talent. And that idea that those people are so critical for a company like ours, that is really part and parcel for what I think the discussion is because for a lot of them, they've been told, well, there might be a difficult you getting a job for the summer or even getting a job when you graduate. But the reality is is that companies like ours badly need these people. And we need to kind of put two and two together to really show, you know, that this is still going to be a critical part of our workforce and a lot of work forces going forward. >> Besides for engineering, which makes a ton of sense, what other parts of your organization are you most excited about being transformed by artificial intelligence? >> Well, I think number one is sales. I

mean, you know, you can do more as a salesperson. We have more salespeople than we ever have. We're selling across all of our core segments. that is from the very smallest companies in the world to the very largest to the largest governments. That idea that doing what we're doing right now that is face-toface communication that idea that I'm still having to sell you communicate to you or to your audience exactly the vision for Salesforce. This is still very much a critical thing that happens in our whole company. We have about 15,000 sales people. We also have about 15,000 engineers and those 15,000 salespeople, they all need to get out there with our customers because we have hundreds of thousands of customers on Salesforce's core products, but we have more than a million companies, you know, using Slack and each one of them needs that conversation to be able to kind of have that vision painted for them of what's possible. That is what is exciting right now for Salesforce and for salespeople. And you know, that's not the only exciting part of the organization. I think for engineering, you can do more

as an engineering uh executive now than you could ever do because as an engineering exe executive coupled with this large language model, you're not just the engineering executive, you're also the product executive, the design p executive, the marketing executive, you're all of the executives. And in reverse, the marketing executive is now also the engineering executive. You know, these things are starting to meld together, which is great. And so we need to like slightly again slightly adjust our structure really looked at how do we reflect you know the changes in technology to do one thing which is to maximize our customer success. Boom. We have to do that. Nothing is more important for Salesforce than maximizing customer success. When we talk about agent force nothing is more important than agent force adoption. So that idea that we are seeking customer success and adoption and making every single customer successful right now. How do we do that? How do we make that happen? How do what are the actions that we have to

take at Salesforce to do those things? That is something not something that we can just turn over to a large language model. That is really the kind of brute force tackling that you're going to really have to get out there, get into the trenches, work with the customers and make that happen. And I think it's extremely exciting moment. And it means that a salesperson can do it. A systems engineer can implement software today. You don't have to wait for professional services to roll in. You can do it now locally on the ground. Okay? And and you a marketing executive doesn't have to wait for engineering to build the product. they can start building the product right now. So that is a huge breakthrough in our industry and every company needs to start slightly realigning around that idea. >> Yeah, I love that. I mean it speaks to the generalist versus specialist argument and the fact that anybody who has that tenacity and the persistence can just go and get something started even if it's not necessarily directly

within their role. It it is a very exciting time to build a company right now. >> That idea it means that you can change, you can transform, you can evolve, you can go forward right now because the technology is empowering you and enabling you to do something that before just was not possible. So now that it is possible, it means you might not have been a coder. You might have just had an idea for a great product. Well, now you can start building the product. You may need an engineer to finish the product. You may need someone to come in, but you're going to get a lot farther along than you would have before these models. >> Yeah. I I think I've heard no more presentations, just demos, right? So, I think that attitude is great. >> That is a very interesting point because then people see the demos and they think, "Oh, this is a product." There is a big leap at that point from demo to product. >> Yeah. >> So, we sometimes we see demos and we go, "Oh, that means that you know, this is now done." Well, rapid prototyping also means that you can only go so far. You

have to all of a sudden say, "We need to fill in the rest." >> Yeah. So, this is kind of a personal question to me, but I I wanted to ask you, um, there are a lot of people in San Francisco, including myself, that are weirdly obsessed with artificial intelligence, maybe some of the folks in this room. And I haven't seen that really with many other technologies. I do truly think about it all the time. It's just it feels very special. Um, why do you think this hits people so much different? Are and are you feeling the same way and will you be my therapist? >> No, I think that, you know, you have to realize whatever geography you're in, you're feeling the the spirit and the energy of the of the location. And I think for San Francisco, you know, this is the home of the summer of love. This is the home of, you know, gay rights. This is the home of many great companies like Levi Strauss, uh, GAP, Salesforce even, you know, it's the home of a lot of innovation. It's where the we started

with the gold rush, you know, and all of that ideas, the spirit of transformation and innovation all started in San Francisco. And that kind of idea is still present here because it's about the energy uh, that's present here in the city. So when you're still walking down Hate Ashbury Street, you're still going to get that vibe. And so it's going to you're looking into the future of what's happening and what's possible. And I'm sure when you go to different places in the world, you tap into those energies and it's slightly different as well. >> Are you feeling that? Are you feeling uh like you're thinking about AI all the time now? Agents all the time? You do talk about it all the time, so I have to assume it's uh on your mind. Well, I had my big AI freakout moment around 201 or 13 when I started to see these incredible models come out of Stanford and that was really how we ended up with Einstein because we ended up acquiring companies bringing engineers together and we ended up you know in that period of that first generation of deep learning with Einstein and then you know as we contributed to those models even

prompt engineering itself was invented at Salesforce and our research team you know then we had the breakthrough now in large language models. I think it's one of the reasons that Salesforce has ended up owning 1% of Enthropic, you know, because we, you know, were really, you know, cap cap captivated with AI for a long time. And I'm excited to see us get to the next level. We're obviously going to keep going. You know, when we watch the Peter Schwarz's movie, Minority Report, you know, I wouldn't say that we're exactly there today, you know, but there's pieces of it that we can resonate with and go, okay, that's kind of happening, that's kind of happening. But that idea that we're in an AI society, we're still a long way away from that. Maybe other countries and other nation states, I could give you some examples, are farther along. You know, there's definitely some places in the world that you step off the the plane and you realize, wow, I'm in a little bit more of an AI society, a little bit more about facial recognition, surveillance, even, you know, where AI is going really wrong, where it's going really right, how it's

moving people in certain directions. We're not at that. We're still at a very kind of, you know, we're still at a very much a a beginning stage in all of this. >> So, I want to get to back to that in a second, but you mentioned Anthropic. You own 1%. Congratulations. Incredible company. Uh, talk a little bit about the birth of that partnership and then how they're powering Slackbot today and what the current manifestation of that partnership looks like. Well, that was a very easy thing because what had happened is we were really pining after investing in Open AI. And no matter what we did in Open AI, they kind of refused to let us invest in OpenAI because Microsoft blocked us. So, because we were feeling so down about Microsoft blocking us even though we knew OpenAI was a great company and we wanted to invest in OpenAI and we like the OpenAI team and the leaders and friends with them and so forth and they wanted us to even invest personally but not professionally. We felt very conflicted with that and so we were looking for more opportunities. So we invested in a series of AI companies you know

including cohhere and mistral and also anthropic you know because we just wanted to be part of this next generation of models and that's how we ended up investing about $330 million so far into anthropic. So that's been uh very exciting for us. >> Yeah that's incredible. Talk a little bit about how they are powering Slack today. how they're powering your AI products today. >> Well, I think one of the great things about Slackbot and and Agent Force 2 is that the different model companies, including Enthropic and also OpenAI, are all part of our ecosystem. And all of those model companies, we want to have a home in Salesforce's architecture. We believe at the very base of the stack is the large language model. It's an incredibly new but exciting part of our architecture and call it that's the beginning of our architecture. And then the next stage of it is really data itself. That data that is federated. That means you know connected to other data sources that is integrated that is harmonized. That all of that data together we call it data 360. We just

bought Informatica M you know Muleoft that that data layer is critical to getting your AI right. If you don't have your data right your AI is not going to be as strong as it could be. And then the application layer which includes you know not just Slack but sales and service and marketing and all of our incredible applications Tableau and the ability for those to then be connected to that data lever to be able to create value. And then the third part that people have seen us really start to deliver is uh agent force and the agentic layer and the power to start to form agents out of that data and out of those applications that can serve those applications. Like in the example of uh customer service, the application is now has an agentic layer. The agents are working with customers, not just humans, but humans and agents are also working together in all cases. And then of course, not just that, we then go to the customer, the employee agent like we saw with Slackbot that you just referenced

or other kinds of local agents like we see with OpenClaw. and then maybe more of a supervisory layer or a control layer even maybe slack at that level that's looking across that whole architecture helping the system uh to come together and that idea that these all these layers are critical including the fundamental ecosystem itself means that you're able to deliver a very compelling new solution for companies to automate themselves and that's where the world is today and we're trying to deliver you know our our capabilities in in that environment. >> So, you mentioned OpenClaw. I I've been a big fan. I just want to ask you, did you install it yourself? >> I did. >> Yeah. Did And what did you >> I had to buy a separate Mac Mini? >> No, I did an iMac because I wanted the screen. >> Okay. Do you like it? >> Good. >> I think it's great, but it's not enterprise grade. So I think you know at Salesforce we have a research project underway called Albert and that idea is how could we build an open claw and we have some great architects who are

working on this that could be enterprisegrade that is trusted that is secure that is reliable that is available and that can work within Slack but also in all of our applications. I think we have to deliver local agent capability. We have to deliver customer capability like we have with agent force. We have to deliver employee capability like we've done with Slackbot. We have to deliver the whole cornucopia. And by the way, if we don't have a not invented here syndrome, that's why we also bought qualified which has its own paper agent architecture called Piper because we want to make all of that work together. >> I want to know, you talked a little bit about how different countries may feel more AI forward, more futuristic. Some of them might be getting it wrong. We're kind of still figuring it out. uh in the US. What version of the AI future worries you the most? Is it bad automation? Is it concentration of power surveillance? What are you feeling is the the the risk that we should really be wary of today? >> I think it's really the number one risk remains the number one risk that we've seen in social media probably remember

in 2018 I kind of was calling out social media is the new cigarettes that when we look at what was going on with section 230 that you know social media was becoming addictive. it wasn't good for you. It was kind of they were trying to bring your children in. I think a lot of children were harmed through social media, especially in other countries, we saw social media being misused um by other governments, you know, to do kind of almost nefarious things. I would say that in the same way that we just saw social media, you know, have a lack of safety, uh we're kind of starting to see that with AI. And we saw this year a number of situations and we saw this profiled on 60 Minutes where large language models became suicide coaches for children and they just did not have the safety built in. And that at this point there's no excuse for that. And every company needs to double down on safety on trust. And if you're a core infrastructure provider you have to take that very seriously and act faster and really speak out about that and call for safety. Not just call for growth, but

safety and growth are two sides of the same coin because we won't have a successful product line or successful ecosystem or even a successful industry unless we have safety and growth together. >> Yeah. And I think that goes handinhand with the overall sentiment in the US towards artificial intelligence which tends to skew negative overall outside of this little San Francisco bubble that we're in. How do you think we address that? Well, I think it has to be through, you know, aggressive action and I think in some cases maybe uh aggressive regulation. You've already seen it now with social media that finally countries are coming along and saying if you are under 16 or you are under 17, you just cannot use this technology. You go to Singapore, your children are not going to be using social media the way they are here in the United States. And in the same way, we're going to need that same kind of action to really people are going to need kind of controls, guard rails if you will. And look, we everyone understands technology needs guardrails.

Our whole world is built on technology with guardrails. So having technology and guardrails, whether it's created by the industry or created by the government itself, is critical. Nobody wants anything to be overregulated, but at the same time, people do want to have a safe environment. Yeah. Well, Mark, I want to thank you so much for chatting with me. >> Thanks so much for coming. >> Everybody give it up for Mark. >> Thanks a lot, Mark. Good.