Guy Raz & Parker Harris: Building Salesforce

Beautiful. It is a beautiful day. Yeah, it is a beautiful day.

Well, I will start by saying one of the luckiest moments in my life was when I met Marc Benioff. Myself and a couple of co-founders had been at a small startup for many years. We were doing Salesforce automation. And it was Salesforce automation on a laptop. You know, it was early, early days. It was not cloud computing. And we left that company and we did some early cloud computing work as consultants. And we met Marc Benioff through one of those jobs that we were doing. And Marc had taken a sabbatical from Oracle Corporation where he was an early executive and very, very successful there. And he had this idea. He's watching like Amazon.com as a bookseller and at Oracle they were doing the network computer. This was if you remember client-server went to thin client and Netscape Navigator was out. And so there's two ideas in his head when he was on sabbatical. He had this idea, you know, what if selling software was as easy as buying a book on Amazon.com? You didn't have to buy the computers. You didn't have to install the software. We had the background in Salesforce automation. We had the background and early like what does it mean to build something for the cloud and it was just this magical meeting where the CEO of this company we're working at introduced us. Marc was an investor. We were consultants. It was down in Burlingame. And we had lunch and Marc said, 'I want to start this company' and we were looking for our next thing and we just hit the ground running and we built the prototype very quickly. This was in the dot-com, remember the dot-com? And here in the city every company was growing and they were, you know, and these dot-coms were our first customers and they were totally willing to take a chance on this startup. They're like, 'Great, you know, love to use you.' And working in the cloud, awesome. And you know, and the bigger customers were not ready. They were like, 'Oh, you want me to put my customer list on the internet? I don't think I'm going to do that.' And so we started with these little customers, boom, and just grew from there.

Well, I think the first was, you know, every corporation was saying, 'Look, I can run this better than you.' Like the IT departments were about security. They were about performance. You know, when we launched the company one of our metrics was fast at 56k. That was a modem. People were still like using software on the internet with dial-up modems and we had to think about well what is performance, you know, at that kind of low baud rate. And so performance, security, you know, and trust. You know, like look, we understand you're giving us a lot of control and we're going to run it for you, but what we're going to give you in return is we're going to give you that trust. That's why when we talk about our corporate values, trust has always been our top value because when we started, people were still not sure they could trust their credit cards on the internet. Right. They were like, 'I don't know if I want to put my credit.' Now we're like, credit card here, credit card there. Buy this service. It's like everywhere, much less your customer. And you know, what if you lost your customer list? What if there was a hack? What if it's not available and I need to sell? But actually one of those startups in the dot-com, it was a great moment for us. Well, not for them because they had their company broken into and all their computers were stolen. Every and these were desktops. These were not like laptops and big screens. Everything was stolen. And they were very upset. But then they were like, 'Well, it's actually not terrible because Salesforce still is running my service for me. They still have my contacts and they still have my deals and I can just get a different computer and use that.' And I know that's kind of obvious today, but back in the day that was revolutionary.

How much do you want me to be a marketer versus reality right now? Just kidding. You know, one of the things we did is we really started with the word co-pilot and there's a company that we compete with that's very focused on co-pilots and we wanted to really differentiate ourselves. So, let's just start by like we definitely need to lead with, you know, how we position ourselves and so we really went forward and talked about agents and agentic AI. And if you really take the literal definition of that, agentic AI means it's an agent that can do things on your behalf. It's agentic. You can say, 'Please go off and research this company for me or go off and create a briefing for my next meeting or prep me for this talk today.' And it goes off and does that work for you. I think that is the future. And I think there's a lot of examples we have. Salesforce has something called a sales development rep. It's a human being we hire and they dial for dollars into our accounts. And now we have a digital one and it'll automatically, autonomously go and email customers that leads we weren't sure we're going to close and if the customer responds that agent will have an agentic response. But I still think we're early days. I still think that yes, there is autonomy. There's great examples of autonomy, but we need to be successful with AI right now. And some of it is just like, let's augment ourselves. Let's just become more productive and, you know, let me have this expert right there with me. I'm in a call center. It's helping me understand who this customer is and I can work with it. Or, you know, I'm a developer. You're seeing, I mean development is an amazing place of productivity and I have AI there to say like don't check that in because there's a bug there. And how amazing is that?

Well, there's actually a company that's just above me, a company called Adecco and they created a separate company called Our Potential and I just had a brief talk with their CEO and they provide human capital. They provide, you know, you need employees, they will source those employees for you or those consultants, contractors, and they'll do their work for you. And they had this big idea, well, what if you wanted to hire an agent, an AI? And so they're building AI employees basically that you can go hire and that will do different jobs for you. And so that's kind of the far out like, wow, that's a big, big idea and they have like a potential agent that's going to go and look for opportunities in your enterprise. But then you just look at like Williams Sonoma and you just like I really believe in simplicity and let's just start simple and they have Chloe who is, you know, and you can go into the Agentforce and check out a lot of these examples. But you know, my sous chef and help me think about like a recipe and you saw it in the keynote. And so we're starting out simple where, you know, Chloe maybe doesn't know me yet, but it does know recipes. It does know the product line of Williams Sonoma. It will help me know like, okay, I have this pot. What's the right recipe? But then we can go from that. We can be like, oh, well, now it knows me. Not only does it have an expert in cooking and an expert in the product line of Williams Sonoma, but it also has deep knowledge of me as a customer and then it can say, well, I know everything you've bought and, you know, here's some new things that we have or new recipes based upon all the things that you have in your kitchen. And I think that's where every customer is going is, you know, they're starting simple kind of expert knowledge agents through to highly personalized interactions that are leveraging all the data across the enterprise about the customer or the consumer and giving those incredible interactions.

Well, I think, you know, customer service is the first place where I think every company has gone. Whether, you know, it's examples on your website, if you go to help.salesforce.com, we're trying to be the first to use all of this AI. You can see we went from using a chatbot to using an agent built on Agentforce and we're showing you the statistics. And so, you know, that's a good starting point. We're now using them in the call center as well. And so I think you need to look at customer service as the first place of disruption because we need less humans to do some of those, you know, basic interactions and it's creating a lot more productivity in the enterprise. Now, a corporation that's thinking about, you know, expenses could just say, 'Oh, that's great. I'm just going to cut my workforce entirely.' But you can't cut yourself to growth. So you need to think about okay well that's an opportunity so we can take that capacity and we can retrain them and they can do higher level, you know, complicated support tasks, they could be in the field with your customers. We're taking a lot of people and retraining them and they're in with our customers as forward-deployed engineers. And so I think you need to think about where are the first opportunities, what is it going to do to your workforce, how do you bring your workforce forward and transform them because we all don't have enough workers, human and digital, and we need to move our humans forward and their potential and retrain them and then we need to add that infinite, almost infinite capacity of AI. And the final thing I'll say is keep it simple and iterate and test and know that you're successful. And I think you can get carried away like we have amazing marketing here at Dreamforce and, you know, kudos to our entire team for the show that they put on. We want to show you a vision of where we can go and where you can go with us. But where are you going to start? And where are you going to know that that starting point was successful? And what's the next thing and the next thing and the next thing? And so you need to hold that grand vision in your head and inspire your employees and your customers. This is where I'm going to transform my company. But then how do you break it down into things that break that risk down that let you get there? And it's not a straight line to get there, but how are you going to get there iteratively and successfully?

Well, I think you said two things. When will they be strategic? When will they make decisions? And then when will they be autonomous? And I think it's two different things because I think we can start, you know, Marc as an example, and I think we need to change how we work by the way, you know, how many of you are still, you know, just searching for answers versus talking to AI to get those answers and it's a very different mindset. I've watched Marc really lean in hard on, you know, how can he transform and he, I mean to a fault, you know, we're uploading or he's uploading to AI our business plans, our strategy, you know, the earnings script, you know, of the next, you know, these highly confidential things, and he's talking to his friend, his friend is AI and he's asking, you know, he's building the business plan and he's got a small team of like two people and an AI working with him and that AI is making decisions. It is, you know, but he's translating that. He's taking that and thinking about do I agree with it or do I not just as he would any top employee who is advising him. It's just another input. And I think we all need to start there. Change how we're working. Trust the AI with, you know, a lot of this information, and use platforms like Agentforce that have these trust layers that secure the information and go outside your comfort zone. You know, are you asking AI the same thing you're asking the top expert in your company? And ask them both and have them work together and start to transform how you're working in the enterprise. And I do think AI will help us make the decision. It's not going to make the decision for us, but it's going to say, 'I think you should do this. I think this is the right answer. I think this is the right strategy.' We still need CEOs. We still need to make decisions. We do not want to like cut the cord and go like, 'Yeah, run my company for me. I'm going to go play golf.' You know, have the AI CEO, but imagine if you have an expert next to you who's helping you as one of your additional advisers and then maybe in some cases you do want to say, 'Okay, yeah, go do this autonomously.' But I think it's two levels of complexity. Yes, I trust AI to have an email conversation with a potential customer and go back and forth and then when it looks like it's a deal that would close that SDR agent will hand it off to one of our best salespeople and they'll close it. But for our top customers here, I want to talk to them. I don't want to send them over to the AI and go talk to the AI and the AI will summarize and tell me. You know, I believe in the human potential and I think we're all rising because of AI. And so I think the AI can help us make decisions. It can also be autonomous, but it's two different things at this moment in time.

Well, I think one of the first challenges is, you know, you go to ChatGPT, you go to Anthropic, you go to Perplexity, they've trained these models on all of this public data. Maybe not all public, but they've trained it on a lot of data and you can ask it things and they will answer. But for our customers, it doesn't have your data. It doesn't know your customers. It doesn't really know deeply your products. And so the first problem is have you unlocked all the potential of all the data assets you have in your corporation? And many people when I say that will think about all your structured data, all your databases like my contact lists and the activities of my interactions and my invoices, the payments, that's all structured data in CRM and ERP. But what I've discovered is the power of unstructured data. This conversation, the text on your iPad, the voice conversations, the Slack messages, the emails, all of the documents that are being written, there's a wealth of information there that we couldn't tap before and now with LLMs and generative AI technology we can unlock that and it's almost like there's more value in that data because it has all of these human interaction. It has much deeper knowledge and we can now tap that. And so the first problem is have you unlocked all your data and have you unlocked it in a secure way. It doesn't mean take it all and throw it in an open database because, you know, I have access to data at Salesforce that I don't think every employee should have access to. I'm on the board of directors. I report to Marc Benioff. I need access to a lot more information. So I need a whole security model around it. And then beyond data, does the AI have access to the APIs, to the skills, to the tools? Can it go and create a briefing document for me? So does it have an API for that? Can it check on the shipping for a customer? Can it see if the customer paid their bills? These are all different systems, so it's reaching in through APIs to do work on your behalf. And then are you testing it? Do you have the data and analytics every day that are knowing that the AI is working?