Unsupervised Learning with Jacob Effron
Hosted by Jacob Effron
7,455 words · 3 speakers
Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
This is Jacob Effron, one of the co-hosts of Unsupervised Learning. And today, we're running a really fun crossover episode we did with another Redpoint podcast, The Logan Bartlett Show. Logan and I talked with Salesforce CEO Marc Benioff. We had a really interesting conversation. We hit on how he thinks about balancing the here and now capabilities of AI with where the technology is going in the future. We talked about the incredible market pull he's seeing for agent force and kind of the impact agents are having in the enterprise in general. And we also talked about why he thinks Microsoft's failing in AI, as well as his reaction to Satya's take that progress in AI agents might obviate the need for kind of core SaaS tools. Overall, just a fascinating conversation with the absolute legend in the SaaS space. I think folks will really enjoy this one.
Well, Marc, thank you for joining. Appreciate having you on.
It's great to be with you always.
So one question, I guess, we're going to talk about the commercial applications of AI and how Salesforce is using it externally to your end customers. I'm curious, I heard you say something on a podcast recently about maybe not hiring more engineers this year, keeping that flattish and maybe customer support going down over time. Can you talk about how it's actually impacted the business of Salesforce?
Oh, yeah. Let's just talk about that because I just think it's such an exciting moment. For the last 25 years at Salesforce, you know, we're really all about helping our customers to connect with their customers in new ways. We automate all these customer touchpoints. We're helping them manage and share information and manage data. And we're a huge database of 230 petabytes of information. It's awesome. And all of a sudden, and that's a huge TAM, by the way, all of its own. I know you guys are venture capitalists, so you like to talk about TAMS. So the TAM world is, you look at like, just like, we'll just take one, like, call it Slack, the Slack world that we're in, hopefully you guys are on Slack. It's like 100 billion TAM, the collaboration world.
Then you've got, you look at the sales and service and marketing, the kind of the traditional CRM world. Maybe that's a multi-100 billion dollar TAM. The analytics world, we own Tableau, that's like a 100 billion dollar TAM. But we're kind of in the hundreds of billions of dollars TAM. But I think we're in a new world and this new world is the world that, you know, That has been in before, but we're all about to go into, which is the world of digital labor. And this idea of digital labor, this is a trillion dollar TAM or multi trillion dollar TAM. This idea that we're not just supplying information management tools to our customers anymore to help them manage and share their information, but we're now providing digital workers, you know, digital labor.
And that is like the huge awakening that this is a new, exciting world. That is what's really transforming. And I think as we've moved into these different levels of AI from kind of the predictive world where, you know, we kind of started 10 years ago with Einstein, which was this world of, you know, it's, it's about machine intelligence, machine learning, predictive intelligence. And then we moved a couple of years ago, two or three years ago into generative. And where generative AI was really cool and we're all on there and doing our search and saying, hey, what I'm looking at buying this new camera and which, which one, oh, the Sony camera could do that. Oh, I had no idea, you know, and then listen, it's like, how is it doing this?
And then now we're though moving into the agentic world. And the agentic world is this exciting world, and then we're moving into the robotic world. And I'm sure you guys are making investments in that category, you know, in the agentic category. And you probably were in the degenerative category and I know you were in the predictive category. And when you look at these four areas and how it's played out, it's awesome. But this third chapter has started and we're all in it and customers are really excited. I mean, we've signed thousands of customers now with, on our agent force platform. And I've never seen anything go faster.
Yeah, no, I'm curious. I feel like a question a lot of folks are asking is, is just the timeline toward, you know, some of this agentic revenue and then kind of that larger TAM that you talk about. I'm curious, as you look, as you think about like a few years out, you know, two, three years from now, like, what do you think the relative split ends up being of kind of this digital labor revenue versus, you know, different types of traditional software revenue? And then, you know, even looking at a decade from now, where, where do you think that goes?
Wow. Well, those are like three or four questions. So. Let's try to take it apart one by one and then if I've missed one, let's go back and kind of close the door. So when we were getting ready to talk about this at Dreamforce, I thought the most important thing for us is to start talking about how it's humans with agents driving customer success together and that, you know, at some point, these agents are not, like our agents are 85 to 95% accurate right now. Talk about that with you and what we're seeing. But at some point, the customer says, actually, I want to talk to a person and bam, you're back in the customer support world with a human and that whole screen in front of you is filled with the whole agentic conversation.
And you see everything playing out dynamically from what happened in the agent and now I'm seeing what's going on with the humans. So that is very powerful. And that is the deep integration between the two worlds. Is that we're not in a pure agent world, maybe we, you know, I don't know if you're talking to her every night, you know, from the movie and on your way home, you're having a relationship with a digital agent, but I'm not. You know, but if you do go to help.salesforce.com, you'll see that I'm trying to be customer zero and I took our stuff and, you know, we have 9,000 employees doing support at Salesforce.
And we basically put an agentic layer on our whole system. And you're, you log in and we ground you, that means connect into your Salesforce data. So we know what products and all your cases and everything. And you're working with the agent and why that's important is we do about 35,000 of those customer support inquiries every single week. And a month ago, 10,000 of the 35,000 have to go to humans. So you think kind of they're on there working with the bot or something, you know. You know, trying to kind of work inside the electronic world and then they eventually got ejected into the human world. Well, now only 5,000 are not resolved by the agent.
So we've gone from 26,000 resolved to 31,000 are resolved by the agent. So there's still 5,000, but we just need less support people because of that. So that is a big thought where all of a sudden, wow, we're getting a lot more automation, a lot more capability, but there's still a deep integration required between the agentic layer and the software layer and connecting humans and agents is extremely important to deliver customer success. So that that's certainly how we see it right now.
And you have these great case studies. I mean, similar to what you've done internally. I feel like you've published with like Disney and Wiley and all these folks, some really impressive outcomes of
We have signed now thousands of customers with revenue relationship. That is incredible. And these deals are from very small deals to deals that are as big as eight digits just for agent force. In addition to all the other products that they're then, you know, buying as well. So that is very exciting. And, you know, we can see, you know, you know, when we do a deal with a customer, if we're talking about a large customer, like let's say a large, I'll give you an example, our telecom customer deal we recently did, it's a large deal, you know, it's a nine digit deal and it's very significant and it's multi-year and so forth and so on. And the total, we call
the total contract value or the TCB is this long, this big. And then in that deal, we saw like an eight digit agent force deal. So that is very exciting and it pulled also all the other products along with it because it makes all the other, we don't just have a service cloud. Like you know, we are the number one service cloud in the world. If you look at the Gartner magic quadrant on service cloud, we're up and to the right. Oh, by the way, that's all pre-agentic. Now, we're the first agent-first service cloud in the world. And we have a complete agentic platform around our service cloud. And for all those customers who have service cloud, who are about to buy service cloud, it's all going to be agent-first. So that is very cool.
And it's not just the only agent-first service cloud. Our sales cloud is now agent-first, our marketing cloud, our commerce cloud. Even if you go to our website, you'll see that we took, you know, WordPress, and we have built an agentic layer on the front of it, ingested our website into our data cloud, and then built an agentic layer on the top of it. It's an experiment that we're running, but I think it's a very neat idea that agents can be, you know, front-ends to websites as well. So we're in a new world. I don't think all of us understand where we are. It happened so fast. I don't think we had time to all really debate it and discuss it like we normally like. Oh, hey, this is what's going to happen. Like, boom, it just happens. And so now we're all just trying to go as fast as we possibly can.
I'm curious, like, as you think about that example with the telecom and the service cloud revenue and the agentic revenue, just from a proportionality standpoint, I guess, as we sort of internalize some of these use cases, does it end up being, you said, an eight-figure deal for the agentic? Is that ballpark? Does that end up being like 10%, 20%, 30%? Like, we're just trying to quantify, as a venture capitalist, how to even think about, you know, the incremental opportunity for some of these things.
Every single customer is going to be different. And I think that it's impossible to say exactly what that's going to be. In that case, the customer was about a third agentic and two-thirds traditional. If, I can't tell you yet exactly. I just don't have enough, you know, examples to be able to say, oh, this is exactly how it's going to play out. But in that case, that customer was about a third agentic. And that was a very exciting, you know, transaction. And very exciting for us to take this very good-sized telecom company. Here is the platform to automate them. Let's get them to another level. We're able to paint a vision of what the future is for these customers. That is incredible.
And also help them show they're going to lower their costs with the agentic layer, but radically increase their customer intimacy and their capabilities to be able to deliver value to those customers as well. So it's a tremendous use case, and it's just awesome opportunity.
CEO of this upstart business, Microsoft, Satya Nadella, said recently on a podcast, something to the effect, let me read it for you, and I want to get your reaction to it. He said, "Business applications will collapse in the agent layer. They are essentially crud databases with essentially a bunch of business logic. And once the AI tier becomes the place all the logic is, they will start replacing the backend." I'm curious, it felt like that was maybe a veiled or a direct shot at Salesforce in some ways. I'm curious your thoughts.
It was unveiled. And I think that I had to watch it and then try to, I'm glad you wrote it down, because I think for a lot of people, they're trying to figure out what is he exactly saying. And this is what he's basically saying. Microsoft has disappointed everybody with, you know, how they've approached this kind of AI world. And, you know, today, you know, when we look at Copilot and what they've done, they've kind of repackaged OpenAI and like, dropped it into like Excel or something and say, oh, yeah, now here, now you can, you know, you can try to do this, do something. But customers are not finding themselves transformed with this Copilot technology. I mean, I've spoken to these customers. They, I mean,
they barely use it. And that's only if they don't have, you know, a ChatGPT license or something that like that in front of them. So it's not at all what we're talking about. And I think that, you know, we're delivering an agentic platform in production today to our customers. And we're already the largest enterprise AI provider in the world. We'll deliver 2 trillion enterprise AI transactions this week to our customers. Now we're delivering not just predictive and generative, but also agentic AI. And we're delivering this at scale globally to our customers. And this is what customers really want. Look, Microsoft's a very good company. They're the number one software company in the world. We're the number two software company
in the world in the enterprise and they're very good fast followers. I'm sure they will try to copy our stuff like they usually do and try to move our, copy our language and move towards us. But we're out there right now in production with thousands of customers and they're, they're just not at that level. And I think this copilot thing has been a huge disaster for them from a branding and kind of validation standpoint. Customers don't look at them and don't take them seriously in AI, nor should they because they're not even making the AI themselves.
One of the debates we've had internally on this is as we move to more of a UI-less world and we're, we're interacting more and more with some, some chat-based system, does that remove some of the incumbency advantages that a system of record has? And it could be Salesforce, it could be Workday, it could be whatever, we can come down to ServiceNow.
Let's take that head on because I think that if you kind of heard what he said and kind of what you're saying, which is we're moving into the environment of her. So if we haven't watched the movie, this is what you're saying, right? You're like, well, listen, um, I just talked to, hey, how's my, how's my sales forecast? And by the way, I'm trying to close a deal with these guys, you know, at their venture firm and want to make sure they're using our products. So let's make sure we follow up and get that on my calendar and let's do this. And that's not how I'm, I don't know what you guys, how you operate every day, but I have this thing called a phone, which is this really cool invention that I will be on like when I'm done with the podcast, checking my text
messages, my emails, my Slack messages, working on my forecast. You guys may not use it anymore because you're way out in advanced and venture capital world, but how I operate is like I have a phone, I have a computer, I have a, I have a, I do Zoom. I have a lot of things, these tools that I use and I don't know what world that he's in where, um, you know, these SaaS applications are only cred databases, but.
The funny thing is, it's a mishmash of words because SaaS applications are cred databases. Cred is create, read, update, delete. So yes, we are creating, reading, updating, deleting, sales information, service information. And kind of the example of if you go to help.salesforce.com and hopefully your portfolio companies are all using our service cloud and our sales cloud. And they get on there. And they are having a great experience and resolving 90% of their things on the agentic layer. And then they go, no, I need to talk to a Salesforce employee now. And then boom. That person comes on the screen and then that everything flips.
And what happens for the Salesforce employee is a huge screen of all the information appears in front of them and they're looking at the screen and they can see exactly what the agent has been doing with you and looking at the case information and looking at your company and your, all your agreements with us and all the products and every interaction that you've ever had with Salesforce is right there on the screen. Okay. That world is not the world that you are describing. You're describing the post PC, post phone, post Zoom, post Slack, post email world. And I'm not in that world. I'm in the current reality. It's 2025. Here is my desk. I'm in the now.
So I know what I could do for people. Oh, and by the way, the AI is not 100% perfect. I don't know if you've tried it, but these things are good, but not great. And you know, AGI is not here quite yet. I know you may have heard some, read some blogs this weekend, but I don't know what AGI they're using, but it's not the one I have at least.
I'm trying to make good of some very good AI that's a lot better than what we've had. But, you know, we can do a lot for customers, but we can do not everything, but we can do some things. I mean, I think what you're saying makes total sense. I don't know what I'm saying. I haven't really had the chance to respond to that, so I appreciate it.
We're happy to provide the forum for it. I, uh, yeah. Listen, it's, it's a, it's a question that we've, we've debated internally, even outside of that clip itself. We've, you know, we thought about the UI-less world.
It's a spectrum. It's like this. Did you ever see the movie Space Odyssey, I think it was called?
I did.
And there's the moment in Space Odyssey where he says, "Open the door." The computer says, "No." Remember that moment?
Yes, yeah, yeah.
That isn't how I go into my house today, you know? Maybe one day it will be that I'll be able to, you know, open my doors with my voice and every... We're just not in that. Look, there's a spectrum of, you know, technology is a continuum. It's constantly getting lower cost and easier to use. And we can see where we are and where we're going. And it's great to have like a marker in the future. Yeah, we're all heading to her. But then to say that that's where we are now, I think is a deception to customers and to people like you, good, hardworking investors who are trying to figure out what companies should they invest in to actually make money for your, you know, LPs in the next five years or the life of your fund.
And that is not, I think, useful right now, which is that the reality is we do have a world where humans and agents are going to have to work together for probably the short term. And at some point, if we move into the computerless, you know, world, let me know, because that will be very exciting, but that's not where we are right now, is it?
I appreciate you looking out for lowly venture capitalists, Mark. I, uh, you know, all this, all this FUD and crud out there, it's making it hard for us to do our jobs.
Hey, I'm an investor too, and I, you know, we have a little thing, Time Ventures, you know, or an angel investor, please include us on your deals. And, you know, we're investing in agentic, robotic, you know, world, you know, regenerative biology. You know, these things are exciting, but... We have to kind of operate in the here and now, otherwise we get too far out there. It was probably not a great situation.
I mean, it makes total sense, the human support rep that, you know, is going to take the handoff from the AI agent certainly needs, you know, like something like Service Cloud to be able to navigate this. How do you think about like the, you know, as more and more just AI agents are doing some of this work? And maybe, you know, at some point we get, you know, companies that outsource all of support to AI agents. What do those agents themselves need? I mean, do they, you know, does the tools that they need to like to log into or get access to or be able to, you know, get the information they need, does that look like, you know, Service Cloud or is that something different? I'm sure it's something you've thought about a lot.
Well, I think that, you know, our fundamental architecture has had to change in the last couple of years. And it's kind of happenstance how it's kind of started to line up with what we've had to deliver in the agentic world. So I think the big change that we've made is, and I think you understand how Salesforce has architected, which is our sales and service and marketing and commerce and even our analytics. It's all one platform now. It's one code base. It's one sharing model. It's one user model and it's all amalgamated. So all the workflow and all of the capabilities where we had separate workflows because we acquired companies. We've really united them into one workflow that we have called Flow.
One user interface, which we have called Lightning. And then you're able to basically bring in the functionality you need to have that application. And then we've also added a data cloud on top of that, which helps you amalgamate all of the data and federate that, which means connect off to the snowflakes and the data bricks of the world and do all of those things. And that idea of an application layer and a data layer are extremely important. And that's what we thought two years ago, pre-agentic, because we didn't really think that we'd go into agentic as fast as we have. And now that we're in the agentic world and we're shipping an agentic platform on top of that is layer three.
So that third agentic layer is also part of a single code base. So the agentic layer, the data cloud and every customer touchpoint at Salesforce is one code base and one piece of code and one data model. And why that is important is because the AI. Needs data to make the right decision. So it needs to have the seamless understanding of the data and the metadata. You know, the data is my phone number. The metadata is it's a phone number. So that idea that the metadata, the data, the apps, the workflow, the data cloud and the agentic layer are one code base is kind of Salesforce's unfair advantage because it makes our AI more accurate.
And that's how we look at it. And I think that's why customers are, you know, going so fast with our platform. You probably saw we deployed because we kind of released it nascently into 135,000 customers. And now they just have to turn it on and then they can turn on and build within the platform their agents. So we should get to our goal of a billion agents. That that is very exciting for us. And I think this is an exciting moment. And I do not think that, you know, this is just a crud database. I think it's a misunderstanding of the vast power of the platform of Salesforce and what you can do with it. And don't ask me, ask the customers because they're the ones who are going to really
be able to deliver that, you know, value.
I guess I'm curious, like, as you kind of zoom into the future a little bit, you know, it seems like today, you know, there's a bunch of enterprises that are adopting these support agents and they're talking directly with customers. You know, in the future, not to beat the her analogy to death, but I imagine, you know, consumers may have their own AI agents that are talking back and interacting with that. And, you know, where does this all go? And what does that mean for like the agents that we actually build?
I don't know. I mean, it's probably a really good lunch at the Village Pub, you know, where we like everybody's talking about this conversation, really. Like everybody, I think, all of a sudden has gotten thrust into this, you know, in a way, because you can see like, whoa, this is going faster than we all anticipated. And I think that's the cool part about our industry right now. And this is a moment where we are all like sitting there going, when are we all just going to be in the her world? And I think it's a totally fair question. And then I think it's a it's a it's a continuum. So where are we? I think it's a good point. Like, where are we in this moment? Because I don't think we can exactly predict when it will happen. Maybe there's people out there that could say, well, yes, in 2029,
all phones will shut off and we will just talk into the microphone. But watch this. Hey, what is my schedule today? Oh, nothing happened, by the way. So what is Logan's schedule today? Siri, what is Jacob's schedule today?
Well, given that we're VCs, a blank calendar might be the right answer there anyway. So I'm clear if that was correct.
Tweeting, you know, podcasting, everything VCs do.
So that is the amazing thing, which is like, it's not quite there yet. And I think that that is the Turing test for her. We just did it.
One of the things I've heard you've been thinking about is just global labor shortages and some of the economic outlook or implications for this AI agentic layer that we're we're moving into. Can you maybe elaborate on some of your thoughts around that?
I think that this is a big moment for our customers to be able to transform themselves to become agent first. And it's kind of a leads into your next world, which is we are going through a global labor shortage where we see all these declining birth rates. We understand that it is harder to hire, especially people here, right? In the United States and sales and service, you can see it. And this is going to give us the ability to do more. And as an example of that, look at engineering. I think in engineering this year at Salesforce, we're seriously debating, maybe we aren't going to hire anybody this year because we have seen such incredible productivity gains because of the agents that work side by side with our engineers and making them more productive.
And we can all agree that software engineering has become a lot more productive in the last two years with these, basically, these new models. And this idea that there is somebody who's kind of along the ride with us and kind of having this incredible experience. Help making our engineering teams even more successful. That has not been true in our sales and service and marketing teams. I mean, maybe it isn't content. I think that's one of the reasons that Adobe is struggling right now is because you can see what's happened in the content world. Like I watched that Jensen Wong keynote last night in Las Vegas, which was epic.
And that keynote, almost every example is a content example, except for the robots and the driver driverless cars. And like the examples were awesome on all the content that was being built. But in all those cases, I would have been using Adobe products before to generate a lot of those movies or to do a lot of those images. And then I'm like, whoa, this is like really powerful that there is just a huge ecosystem of companies. You know, that are doing these amazing products that are competing against Adobe in incredible ways. But even just the generic models are able to do incredible. You know, I'm sure we've all had the experience like, hey, draw me this and that's so good.
I can now just put this on a T-shirt and you could not do that two years ago. So that has definitely changed. So there's no question the world is changing. When it gets down to labor and delivering the next generation of labor. This idea that we can start to provide these digital workers to our, you know, customers. That is the big thought that we've only been a software company up to this point. We've only been, yeah, we've only been a database company with apps. Okay. Yes. I think even Slack, it's a database and apps. You know, Tableau, it's a database and app, Salesforce is a database and apps. And now though, agents, yeah, that's different.
It's we've created a new TAM and that TAM is this multi-trillion dollar TAM of digital labor. That is going to supplement the human labor that we can't really get.
You've been very thoughtful about how business can make social impact as well. From the founding days of the of the company with the 111 program. I'm curious, the industrial revolution happened over 100 years, 120 years, 140 years, depending on how you you size it or scope it. And I'm curious, as you think about the like retraining. And maybe we'll take within Salesforce just because it's, you know, it's within your purview. I'm curious how you think about like the reskilling of your own workforce and the ability to move someone from customer support where maybe it's going to be declining over time to sales,
which maybe will be increasing over time. Do you think it's on the onus of companies to move people around and provide the learning opportunities for them to stay within an existing organization as roles maybe get cut?
Well, you're right. You know, before I started Salesforce 25 years ago, I was at Oracle for 13 years and I loved being at Oracle and I loved my boss Larry Ellison. But one of the things that I realized when I was at Oracle, because I was trying to create it was it could have had a more philanthropic culture, especially in really powerful moments. And so I just committed to myself at that, you know, when I started Salesforce, that I would take 1% of our equity, 1% of our profit and 1% of all of our employees' time and put it into a 501(c)(3) foundation. And it worked out really well. You know, this 1-1-1 model, we've been able to give away about a billion dollars. We've done about 10 million hours
of volunteerism and we run about 50,000 nonprofits and NGOs for free on our platform. It's pretty awesome. And almost 20,000 companies have joined pledge1percent.org, which is our 1-1-1 model. And it's a pretty big contribution to the theory of business that business can be the greatest platform for change. And I really encourage every entrepreneur that I invest in, and I hope you will too, to think about this, especially at the beginning, because it really shows how you can use your business to do something good in the world through your product, through your people and through your money, you know, as you get forward and how, what those things are will be completely, you know, at your discretion.
So that's a really cool part of, I think, you know, starting and running and building and scaling a business.
And so do you think that like within that now the retraining is a is an onus that come or is is an impetus as leaders? Do we have some moral obligation to try to repurpose the existing talent we have versus just hiring the net new person? Or is it we live in a capitalistic society? And so, you know, if you can hire someone better externally, you're you should just do so.
Well, I think that there's a debate in Silicon Valley about exactly as you just said it, like, do we have any moral obligations at all? But also, and then what is the point of capitalism and its level of purity? But I actually think they're the same thing, because I think you actually will do better and create a better economy if you actually, you know, accept some of those moral obligations. And we've been doing AI for a long time. And we do a lot of retraining. We have our own retraining platform, Trailhead. We invest a lot in AI. You may know that we've given more than $150 million to the San Francisco and Oakland Public Schools, not just because of the moral obligation. It's very practical. Our employees, this is where
they have their kids. And we've put a lot of AI education into the schools as well, a lot of math education, a lot of things to increase attendance in the schools, especially in the middle schools. And that's been very valuable, and I think very important for us. And I think that each one of us probably has a great idea on how to make our schools better, how to make our hospitals better, how to make our communities better, especially in the way that AI is moving, including retraining and reskilling. And I think all of us should do it because it's going to make all of our businesses much better.
Yeah, one thing, you know, I was struck by when you were talking about, you know, watching Jensen's keynote was, you know, you mentioned kind of these these different products that like were kind of in the world of Adobe and how there's all these startups doing that. And I feel like in the VC world, you know, we obviously see a bunch of like upstart competitors in, you know, we'll take customer support, for example, and, you know, there's your former coworker, Brent Taylor's company, Sierra, there's Decagon, Maven, you know, folks that are kind of focused singularly on this agentic problem. You know, how do you think about that and where that space evolves?
Well, it's a powerful moment, you know, in technology, in I think everyone has been inspired by this next generation of AI. And then everybody has their vision of where it's going to go. And of course, the vast majority of them will be wrong. And that's just the nature of our industry. And that's the cool part. And then a few of them are going to get it really right. And each one of us hopes that either Salesforce Ventures is invested in that right one. You know, like hopefully it will be Typeface, you know, which is one of our big, you know, investments in the content world or Time Ventures will, you know, get one of these things really right.
Like ZipLine is one of our, you know, investments like in the drone world or, you know, and you guys, I'm sure have your list of, hey, I hope these are going to be really right on. And, you know, it's a little bit of we're at the, you know, we're, it's, we're making our bets to see, you know, which way the future is going to go. And then we have as many failures as the successes, as I'm sure you have, you know, we're just writing these and go, well, that one did not work. Boom, that was a bad idea. And it was just not happening. And I think that that's what makes our industry fun and enjoyable and exciting and that nobody gets it exactly right. Everybody has a success and everybody has a failure.
And hopefully we're learning from our failures and turning it into our next success story.
And do you think some of these other folks are maybe betting that this like her moment is sooner than it sounds like you think it is?
I just look at what our customers need right now and I'm working with our customers. So I'm talking to customers and delivering product. I expect, you know, to be the first to deliver a billion dollars in agentic revenue in enterprise software. That's my goal. And when I deliver that, hopefully in the short term, that I'll be able to say, whoa, that's because we understand the current product requirements. And I think that being out with the customers, talking to them, helping them to understand where they are and where they want to go, while also looking at the technology, all has to kind of work together. These companies have spent Trillions of dollars, you know, putting in
in very advanced systems to run their businesses, governments, organizations of all types all over the world. And those things aren't just going to turn off. I'm sure you probably know, we go into a lot of banks and they're still running IBM mainframes, you know, that they started putting in decades ago. So, technology tends to coexist and not just all of a sudden replace, you know, itself. And when we look at our data cloud today, not only is the data cloud connecting to Snowflake and Databricks and Redshift and on and on and on and on, but it also connects to IBM mainframes as well because a lot of the data is there. So, it's important for us to be able to bring all the data in, to get the agentic layer on top of it.
These architectures, these enterprise software architectures, you know, this, these are going to last for decades. This isn't just something like, you know, I'm going to change my phone or I'm decided to move from iPhone to Android SIM and that's my, how I've changed my software. That's not how company enterprise software works.
Mark, last one and then we'll let you go. I guess I'm curious, uh, what role you think, um, uh, the government and regulatory maybe plays in AI as we're looking forward in it? Do you think we're in too embryonic of a state for anyone to actually get involved and try to come up with terms or structures? Or do you think it's such a powerful technology, we need to get out in front of, of how we work with it?
Well, I think it's going to be a balance. And I think that you can see that because, look, uh, everybody kind of is looking at Elon Musk right now and what he's doing with Doji, but I think pre-Doji, um, he did something very interesting. He supported the regulatory bill that, uh, California was considering for AI. And everybody was looking at that bill, which was, you know, very significant. It didn't pass, it got vetoed by the governor. But before it got vetoed by the governor, it was supported by Elon Musk. And you all, everyone remembers when Elon tweeted, "Hey, I'm supporting this regulatory moment," and yet he's very anti-regulation.
So there's gonna be a balance and I bet that we're all gonna be switching back and forth a little bit because I think in this technology, a lot of us still are trying of wrestling and grappling with what is really happening, how far are we? One of the reasons that I, and I mentioned the Jensen keynote a couple of times, that I liked it was, it was very practical, it was very specific, it was very actionable, you knew what products you could buy from him, you knew what he was building, you could see where he was going. And I think in a lot of cases, AI leaders are doing keynotes and you're gonna hear, one of the things I really loved about the keynote is he didn't use these three initials that are, get everybody like head spinning, AGI.
And of course, AGI is getting reframed, it's not the AGI that your father knew, it's a new AGI, it's like, well, it's not AGI, what we were talking about two years ago, we're talking about it now is this, it's like, he didn't mention AGI. You know, he mentioned basically, here are the four layers of AI today that he can see, that he's building products for, that he's able to deliver today to customers, that he thinks customers are gonna get value from. I think that's where CEOs need to be, it needs to be, here's my solution, here's the product I'm building, here's how it's priced, and I'm gonna deliver success for you when you implement this, and I'm gonna lower your costs, improve your customer relationships,
improve your business KPIs. That's the power of AI today. And I think if we get too into these other worlds, it becomes very, it becomes very, I would say conflicting, and I think in the regulatory world is where you can see that conflict expressed, as I think this example that I just gave was, which is, in some cases you may say, I'm pro-regulation, and in other cases you may say, I'm against it. And so, it's gonna be, it's not gonna be a black and white issue, there's gonna be some gray areas and regulation with AI, and I'll tell you, nobody wants a Hiroshima moment with AI. Nobody wants to see that kind of experience. I watched this movie.
Over the weekend, Creator, I think it's called Creator. It's an AI movie. If you haven't seen it, it's it's worth watching. It's about robots and agents and humans all coexisting together. But there's a Hiroshima moment with AI that they talk about. We don't want to get there. We want to have, you know, an AI world that we, you know, have a safe AI and an AI that's that we work with and that and that's productive for society and that doesn't do all these terrible things that we know AI can do. So there's probably a balance and hopefully we'll find that balance and that we'll all be more successful for it.
Well, Mark, thank you very much for doing this. We'll we'll take you up on the we'll take you up on the Village Pub at some point here. But maybe maybe we can run it back in some period of time and and see how all this stuff is played out if we're in this her moment finally. But thank you for coming on and doing this.
It's great to be with you guys. Thanks for asking me to come on. I really appreciate it.
Yeah, of course. Thanks for listening to that really fun episode with Mark. We've got an incredible lineup of guests coming up for unsupervised learning this year. So definitely stay tuned next week. We'll have another amazing founder, operator, researcher in the AI space. See you then.
Page updated October 26, 2026 · transcript and summary are machine-generated
