The Rise of the AI Economy and Digital Labor with Salesforce CEO Marc Benioff

Summary

Highlights

• AI's transformation from traditional enterprise software to digital labor signifies a substantial market opportunity, valued at trillions. 📊
• Open-source innovation has been a catalyst for the speedy development in AI technology, enabling rapid advancements and commoditization. 🌐
• Salesforce's AI applications, like Einstein and Agent Force, enhance customer interactions and operational efficiencies for major clients. 🎯
• Marc Benioff discusses the integration of AI reasoning models with LLMs to boost accuracy and decision-making capabilities. 🧠
• Benioff envisions an 'unlimited age' of AI, urging awareness of potential ethical and practical challenges in the future. ⚖️

Key Takeaways

• The AI revolution is accelerating faster than any previous technological wave due to open-source innovation and rapid developments. 🚀
• AI is pushing industries towards digital labor, offering a 3 to 12 trillion dollar market opportunity. 💰
• Salesforce utilizes AI for customer success, helping companies like OpenTable and Singapore Airlines enhance consumer experiences. ✈️
• AI's pace is transforming enterprise software by integrating with large datasets and reasoning models, increasing efficiency and productivity. 💾
• Marc Benioff highlights the potential of a future 'unlimited age' where AI becomes autonomous, prompting caution and excitement. 🤖

Overview

Chapters

• 00:00 - 00:30: Introduction and Overview of AI Transformation The chapter begins with a reflection on the significant transformation brought about by AI, describing it as the most exciting change we've experienced, while emphasizing that we are merely at its inception. Moving beyond enterprise software, the narrative explores the rise of digital labor and its potentials. The chapter highlights a massive market opportunity, possibly ranging from 3 to 12 trillion or even larger, likening the advent of AI to introducing a 'new species,' and noting the parallels previously only seen in science fiction.
• 00:30 - 01:00: Speed and Innovation in AI The chapter titled 'Speed and Innovation in AI' discusses the rapid pace of development in artificial intelligence compared to previous technological waves. The speaker emphasizes that AI is evolving much faster, with significant innovation occurring in the open-source space. They note that what was considered true in AI even a few months ago may no longer be valid, highlighting the necessity for companies and individuals to stay attentive to avoid falling behind. The chapter concludes with a reflection on the transformative impact AI will have on our world, suggesting a shift into new, uncharted territories.
• 01:00 - 01:30: Marc Benioff's Tech Journey and AI Hype The chapter discusses Marc Benioff's extensive career in technology, including his founding of Salesforce 25 years ago after his tenure at Oracle. It highlights his experience witnessing various tech trends such as the.com bubble, the rise of cloud computing, and the emergence of cryptocurrencies. The conversation turns to the current hype around AI, questioning whether it is justified or if there's excessive enthusiasm surrounding it.
• 01:30 - 02:00: AI's Financial Impact and Market Opportunity The chapter discusses the financial impact and market opportunity brought by AI transformation, which is considered the largest ever encountered. It compares the shift from traditional enterprise software to digital labor, projecting a market opportunity ranging from 3 to 12 trillion dollars or perhaps even more. The transformation requires companies and individuals alike to adapt to this new world.
• 02:00 - 02:30: Rapid Advancements in AI and Open Source Contributions The chapter discusses the rapid advancements in AI and highlights how it's significantly faster compared to previous technological waves. The conversation reflects on what sets the current AI wave apart, particularly focusing on its speed and the role of open source contributions in accelerating AI development.
• 02:30 - 03:00: Evolution of AI Models and Open Source Impact The evolution of AI models has accelerated significantly over the past decade, transitioning from deep learning and predictive models to the era of prompt engineering, generative AI, and now advancing into agentics and robotics. This chapter delves into how these shifts have been pivotal in the rapid development and deployment of advanced AI systems. The discussion also highlights the potential impact of open source contributions in propelling this evolution.
• 03:00 - 03:30: Agentic Layer and AI Integration in Salesforce The chapter discusses the rapid advancements and integration of large language models and new reasoning models in Salesforce over the last 12 months. It highlights the emergence of world models that incorporate new sensory technologies, which are significantly accelerating the pace of developments in AI within the platform. The reasons for the swift progress compared to previous innovations are also explored.
• 03:30 - 04:00: Salesforce Customer Success Stories with AI The chapter titled 'Salesforce Customer Success Stories with AI' examines the widespread influence and innovation that AI has brought across various industries. The discussion highlights how sectors such as technology and biomedicine, including pharmaceutical companies, have experienced significant transformations due to AI. It emphasizes the pivotal role of open-source development in AI, which has particularly accelerated since the emergence of deep learning from major academic institutions. This transparency and availability of information have enhanced the industry's understanding and capabilities in AI technologies.
• 04:00 - 04:30: Tableau Integration with Data Cloud and LLMs This chapter discusses the rapid evolution in the realm of Artificial Intelligence, particularly focusing on integration and development within Tableau, Data Cloud, and Large Language Models (LLMs). The open-source nature of current AI technologies has accelerated progress, significantly transforming truths from the past year or even six months. It's highlighted how staying informed is vital to avoid falling behind in this rapidly evolving field.
• 04:30 - 05:00: Salesforce's Agile Approach to AI Adoption The chapter discusses Salesforce's agile approach to AI adoption, emphasizing the rapid pace of AI innovation driven by open source contributions. It highlights that many AI researchers come from academic backgrounds and are contributing to open source projects, accelerating the development and dissemination of AI technologies. This open-source phenomenon is a key factor in the fast-paced evolution of AI.
• 05:00 - 05:30: Unlimited Age and AI's Potential for the Future The chapter discusses the commoditization of technologies and trends in the Learning Management Systems (LMS) space over the past four years, noting that many systems have similar features, making the industry highly competitive. However, breakthroughs like the development of DeepSeek signal significant shifts, showcasing advancements from traditional transformer models to more cost-effective and deployable alternatives, which hold the potential to bring about substantial change.
• 05:30 - 06:00: Salesforce's Strategic Use of AI in Business The chapter discusses Salesforce's innovative approach to integrating AI into their business operations. By leveraging AI technologies, Salesforce has managed to significantly reduce deployment costs by 90%. Initially met with skepticism, the initiative proved successful as the team managed to efficiently utilize open-source resources under an MIT license, allowing wide accessibility and use. This strategy stands out as unique compared to traditional software development practices seen in recent years.
• 06:00 - 06:30: Managing AI Teams and AI's Role in Business Planning The chapter discusses the rapid pace of development in AI technology compared to the relatively slower evolution of other technologies like smartphones. It highlights the open-source nature of AI models, encouraging collaborative advancements, unlike proprietary technologies. This collaborative approach results in faster innovation and integration in AI, contrasting with the slower, more incremental updates seen with products like the iPhone.
• 06:30 - 07:00: AI's Influence on Media and Time Magazine's Role The chapter discusses the rapid advancement of AI research, particularly in Canadian universities like the University of Toronto, where significant developments occur every few months. The speakers note the increasing pace of AI advancements and reflect on their experiences interacting with AI researchers and graduates.
• 07:00 - 07:30: Personal Use of AI and Future Prospects The chapter 'Personal Use of AI and Future Prospects' discusses the innovations in AI coming out of Canada, humorously referring to Canada as the 51st state. The mention of 'Carney' highlights a significant figure in AI, possibly referring to Mark Carney, a notable public servant. The chapter expresses amazement at Canada's leadership in the field.
• 07:30 - 08:00: Conclusion and Reflecting on AI’s Future The chapter begins by reflecting on a surprising election outcome that no one anticipated. The conversation then shifts to Salesforce's AI advancements, notably mentioning Einstein and Agent Force as key AI products. The speaker is prompted to elaborate on Salesforce's AI developments and what customers can look forward to in the future.

The Rise of the AI Economy and Digital Labor with Salesforce CEO Marc Benioff Transcription

• 00:00 - 00:30 This is the biggest most exciting transformation that any of us have ever gone through and we are just at the beginning of it. It's a step out of enterprise software and the traditional applications world and into digital labor. You're really looking at 3 to 12 trillion market opportunity, maybe bigger. We've given birth to some new species. It's kind of a scary thing. You've only seen it sci-fi.
• 00:30 - 01:00 When you look back at previous technological waves, what feels different about AI? Speed. This is happening much, much faster. The huge amount of innovation in AI has been open source. Everything that was true in AI a year ago or 6 months ago is not true today. If you weren't paying attention, you got left behind already. Every company and all of us are all going to have to shift into an incredible new world and it's wide open.
• 01:00 - 01:30 Mark, welcome to the show. Thank you so much for being here. Oh, yeah. It's great to be with you guys. It's great to see you again. Yeah. First question we have is, you know, you've been in uh in tech for a long time and you've seen a few big tech waves. You know, you've been uh Salesforce you founded over 25 years ago. Before that, you were at Oracle. you've seen the, you know, rise and fall of the sort of.com bubble. Uh, you've seen cloud, you've seen crypto, now you're seeing AI. Uh, do you think the hype around AI is justified at the moment or do you think we're maybe getting a little carried away? I don't know. This is the biggest, most exciting
• 01:30 - 02:00 transformation that any of us have ever gone through and we are just at the beginning of it. And when you look at it on a financial basis, it's a step out of enterprise software and the traditional applications world and into digital labor where you're really looking at 3 to 12 trillion market opportunity, maybe bigger. And this is just an opportunity where every company and all of us are all going to have to shift into an incredible new world. And yes, it's all
• 02:00 - 02:30 driven by AI and what the future of AI looks like. And it's wide open. Yeah. Yeah. When you look at look back at previous technological waves, what feels different about AI? Speed. This is happening much much faster. And that's always been true for AI. And I can kind of give you my assessment of why that is. Yeah. Please. So I think when you look at the last few decades of AI, things have gone very fast and we're moving into this incredible technology
• 02:30 - 03:00 and where AI is right now is is amazing. But one of the reasons that it is going fast and has gone fast and especially in the last call it 10 years is we kind of shifted from deep learning and these predictive models and machine intelligence models and then we kind of crossed into prompt engineering and then generative AI and now we're moving into agentics and soon robotics that that moment of you know that we're have all these next generation models we call
• 03:00 - 03:30 them large language models how but of course we've always had models and then we also have new reasoning models as well. So that's a huge breakthrough that's really come together in the last 12 months in a huge incredible new way and we're also all anticipating these kind of world models which are the ones where we're going to have all this kind of incredible new sensory stuff. So it's going fast. Why is it going so fast? One of the reasons why it's going fast versus things that we've seen like in
• 03:30 - 04:00 other industries like you look at maybe other technology companies or even biomed companies or pharmaceutical companies is because the huge amount of innovation in AI is been open source and we've really seen that especially starting with deep learning and as that came out of a lot of the big universities all of a sudden it was like very clear to everybody exactly what was going on and what we could do. the
• 04:00 - 04:30 vision the early vision models the these kind of very beginning just as we kind of stepped into prompt engineering as we stepped into the LMS that this opensource phenomenon this is really different and so it lets us go much much faster and even in the reasoning models it's just letting us go faster like everything that was true in AI a year ago or six months ago is not true today it's like if you weren't paying attention you got left behind already. So, it's like, oh, you have to
• 04:30 - 05:00 really pay attention to what's going on. And there's a lot of nuances, but it's going fast because it's all open source. And a lot of these AI researchers are really into the open-source phenomenon. You know, they were in universities, they were they were professors, they were postgrads, they were, you know, coming into this and posting their research. And it's out there. And that is what is cool. And so you have speed. You have a lot of speed.
• 05:00 - 05:30 And it's also turning a lot of these things into commodities. So, you know, as we're going up the chain, and you can see it for sure in the LMS in the last 48 months that it's kind of they're all one feature or two features ahead of each other, but they're all about at the same level. And it's a big commodity. Or then you can have a big breakthrough like we saw with DeepSeek where all of a sudden, oh, this is a real change from the traditional transformer model to a new kind of model that's much cheaper to deploy and all of a sudden I'm like
• 05:30 - 06:00 deploying at 90% less cost and then my friends were very competent initially are like this isn't true and then oh no it's actually true and we didn't realize you know what they had done but they open sourced the whole thing into an MIT license which means everybody can just use it. really cool and that is not how any other software has really come along in the last call it you know three
• 06:00 - 06:30 four five decades and you could see like on your phone it's not like iOS and you know is an open-source model that everyone is like working on it's like proprietary and proprietary teams that are working in those things the technology is just going to go slower so you know the iPhone still kind of looks like it did when we got our first iPhone, you know, and you know, that's not true on AI. So, we're going faster. Yeah. No, we
• 06:30 - 07:00 couldn't agree more. On the research side, Hust and I both used to live like one street down from the University of Toronto, which is where a lot of the big AI research happened. And like every 3 months, like, you know, we'd meet these grads and researchers, and Hust was working at at a tech incubator at the Toron at the University of Toronto. Every 3 to six months, you were just seeing something completely massive. and and I think the pace is like not just kept up, it's like feels like it's going up significantly right now. So couldn't agree more with you on on that assessment. Yeah, these Canadian universities have also added a huge
• 07:00 - 07:30 amount to the AI uh set water all these places like you can really see like it's incredible what came out of Canada and um yeah I heard it's the 51st state now. Is that true? Okay. I think let's see like the carney Carney for a long time. I'm like it's like amazing to see him like is now the head of Canada. It's incredible. Yeah.
• 07:30 - 08:00 Crazy election. It's It was a crazy election. We did We did not see that coming. For sure. Yeah. I don't Nobody did. Yeah. He didn't for sure. He didn't see it. Yeah. Yeah. Absolutely. Absolutely. So Salesforce has been building with AI for quite a while. Uh Einstein's been around for a few years. Uh we have Agent Force now. Can you tell us and the listeners a little bit about what Salesforce is building with AI and what customers should be excited about? Right. There's a lot to be excited about, but mostly right now what I'm
• 08:00 - 08:30 excited about is the customer success. So when we look at what's really going on with customers and what we're getting excited about, we're looking at some of these stories that are coming out. This product's been kind of out there now for five or six months. And so we're really starting to start to see these scaled stories. And one of the first stories which continues to unfold is Open Table where it was augmenting their employees and now it's like extending to their consumer experiences.
• 08:30 - 09:00 And this idea, you can even see it at Salesforce, you know, we have help.salesforce.com. um that instead of speaking directly to a customer service rep or trying to deal with FAQs that I'm interacting kind of how I did with a large language model but with my customer support department and I can ask it questions and help resolve issues maybe increase my licenses or you know change my
• 09:00 - 09:30 subscriptions and it's amazing. So for Salesforce for example, we've already done more than 500,000 conversations with customers directly on help.salesforce.com and that has been very exciting. And then we have um customers who are deploying this not just open table but other amazing customers like one really cool story is probably a product you know smart sheet which is this kind of cool cloud blaze spreadsheet and they've put it right
• 09:30 - 10:00 inside their product. So not only are the the end users getting support and help but you can increase and decrease your licenses and all of this. Another really great story is remarkable. You know, the pad that you can draw on, you know, you can go there, you can start to work with the agent to get help. Like I did it myself. Like I need to replace my stylists. How do I do that? Um and airlines, you know, I just got back from a trip to Singapore, Singapore Air,
• 10:00 - 10:30 who we've worked with for like eight years on working on their sales or on their service or on their marketing org. They're building an agentic layer over the whole company. And you know that's going to let people get a level of service and support that and even sales that they were not able to do it before and thin air who has 11 million consumers is also deploying. So that's cool. These are stories that are happening much faster than I would have anticipated. I feel I'm much more in a race. I think that you know we have
• 10:30 - 11:00 these things happening all over the world. This is technology that requires you know a level still a level of implementation. They're using our data cloud. They have to get their data right. You know they're shaping the responses of these agents. They're installing these guard rails. There's a semantic layer. There's an action layer. There's a data layer. And we're super inspired by it. And we even introduced you probably don't follow what's going on with Tableau which is one of our products in data analytics and business
• 11:00 - 11:30 intelligence. It's a company we bought like eight years ago, but we have completely rebuilt the product. Last week at the Tableau User Conference in San Diego, we launched the new version and it's a big deal and I want I'll explain to you why. because it's not only the Tableau that everybody loves, the familiarity, the kind of functionality. Um, but we put it on top of our data cloud, which you know, when we bought the company, they never had
• 11:30 - 12:00 that idea that there was a kind of a client server almost relationship where you had the shared data repository. So that's awesome because you're getting all the data from your company and all of our apps are in that data cloud and it's federated out to all these other data repositories in your company like a snowflake or a data bricks or a red shift or a big query or something like that. But then not only do you have the Tableau that you love the data cloud integration there's also an agentic layer on Tableau and agent forces there. So you have a triad or a trinity. You
• 12:00 - 12:30 have the app, the data and the agent. And why that's important is I was with a customer yesterday who's using a large language model to do some very sophisticated simulations. I won't go into the technical details, but it was like really fascinating and cool and you'd relate to it. But then I was like saying to myself, this isn't exactly what they want to be doing because what they're doing is where they're working with this large language model which is kind of like a text in and text out and maybe some all right let's say it's
• 12:30 - 13:00 multimodal and they're like throwing stuff into it and then there's stuff coming out and they're so excited about the output and they can't believe it and they've had these wow moments and then you know there's a hype cycle with you know you're in this exercise and of course you're getting these amazing things and at some moment you'll be deflated and going well that answer isn't very good. Ask another get tune your prompt. But here's the thing with Tableau though as the front end to the large language model and you're interfacing you're also seeing the
• 13:00 - 13:30 visualizations with it and that is really cool and I think like for this one specific customer I was saying to myself they would be going faster and getting more excited and they were super excited about what they were doing large language model if they were using this this Tableau we call it Tableau next because the repository would be getting filled with the data and instead they're having to load all the stuff into the large language model. And then the second piece is the visualizations are happening. If you know how Tableau
• 13:30 - 14:00 works, these kind of visualizations that can come out of it are amazing. So then the combination of these two things, you're just going to go faster because the reality is that you know we're still the ones writing the prompts at least for now and we're still the ones who are like asking the questions at least for now. So, we're like saying, "Hey, I'm running my business and here's my quarter and here's my products and here's my geos and how's my business
• 14:00 - 14:30 doing and where should I focus and what should I do and all of these things, but just having that then stream of text back or even a couple of whatever images isn't what I want. What I really want is I want that incredible visualization." So, that idea and we just crossed a lot of bridges, right? which is that yes, I have conversational capabilities in my business. I can have digital labor. I can augment my employees. I can have more productivity. But in this case, I'm kind
• 14:30 - 15:00 of doing something where I'm getting a level of enlightenment I cannot really get with any other capability. So all of these things are important. It's not like just one is important. Number one is employees do want to be augmented with these things. It's like we're augmenting our stuff personally and we want to augment ourel professionally. Two is we want more productivity where hey the computer's just resolving some of the stuff on its own. The person wants to change their password improve their subscription
• 15:00 - 15:30 rate. We don't need a human and in the loop on that. And then the third piece is I'm running something managing something that's incredibly sophisticated. I have a huge management team. We're on this. I really want the software to be running side by side with me and I need a lot of information visually in text and images and video in every possible way and I need real enterprise software expertise security
• 15:30 - 16:00 sharing. So all of these things are important and can work. So this is a really cool moment in enterprise software as we kind of start to come out with the next you know iteration. It's awesome, Mark, right? Like the day like I worked at Snowflake like early on a few years ago and like you know just like the data app and the agent force combination you're talking about like that just sounds phenomenal and if you can with the real time visualizations it just I think makes the life of an enterprise user so much easier if you
• 16:00 - 16:30 can see that impact the data feeding in and like that's amazing to hear like the changes like you've made at the tableau and like how it's kind of like refining. Yeah, we probably ingested about one and a half trillion records from Snowflake last week. You probably remember in the early days of Snowflake, we kind of provided our API outs. Yeah, I worked on the I worked on the integration with your Salesforce team early on actually. Yeah. And that was an incredible investment we made. I think we made 1.6 billion on our Snowflake investment when it went public. And that idea was we helped Snowflake get going by bringing
• 16:30 - 17:00 data into the platform. But today, Snowflake is giving us way more data back because they've been able to aggregate data from so many different data sources. And now our data cloud is federated to Snowflake. So our apps are able to benefit from that integration birectional integration and then um you know when we're running Tableau right so here we're running Tableau on our data cloud but it's federated off to Snowflake and grabbing that stuff and dropping it back in. So that's different than where we were wouldn't you say like
• 17:00 - 17:30 even just two or three years ago. And that's a whole different It's not that people weren't using Tableau on top of Snowflake before. Yeah. But this is a much more sophisticated and much more exciting, you know, next generation of enterprise software. 100%. I was looking at like one of your release notes from the spring 25 and I saw you guys released this reasoning engine called the Atlas reasoning engine and some a library of pre-built skills. I thought that's like really cool, very powerful and we're just curious to know like any
• 17:30 - 18:00 customer success stories of folks who are already using it or like what powers that gives like an enterprise user on day one if they just like open up their Salesforce and they're like, "Holy we have this reasoning engine now available." Reasoning is the path to accuracy. So in large language models, we realize that because they're word models, they inherently have some level of inaccuracy or I guess well, you know, we've called them hallucinations or where things just don't really make sense because it's this word, that word, this word and then
• 18:00 - 18:30 you get your answer and sometimes it works and then sometimes it does not work and we've all had that experience, right? Is that a fair characterization? Now we couple the large language model the reasoning model. reasoning model is different. As the reasoning model is kind of takes on the prompt and then gets the answer from the LLM, then it starts to try to diagnose and figure out exactly what it it its answer is going to be. And then as it comes up with its answer, it then keeps that knowledge and it doesn't have some static data set that's driving it
• 18:30 - 19:00 like an LLM. It has something that's constantly improving. Now, I don't know if that's the path to AGI or not. Some people think it is that these reasoning models are now running and they're stacking and building their own kind of, you know, almost like synthetic data sources. It's not exactly a synthetic data source, but it kind of, you know, you're stacking each answer up. So, you're getting more and more knowledge. These two things together, the LLM with its kind of its data set combined with
• 19:00 - 19:30 the reasoning model with its data set that's more dynamic, this is giving us a much higher level of accuracy. So when we work with a large like we're working with a large healthcare company or I could we're largely working with a large media company actually the large media company's right here it's Disney so with Disney you know we're seeing very good accuracy rates like in the '9s because we're also coupling it with the with the reasoning model and before that I would say that the accuracy rates were more in
• 19:30 - 20:00 the 60s so it's a big leap in terms of capability when you couple LMS and reasoning models together. That's amazing. Uh Mark, I was reading one of your opeds in the Time magazine and I think you coined this term the unlimited age. Uh and in your like minds, I'm curious to know like what do you think like with this new LLM wave, what feels unlimited? Is that is that like it's unlocking new creativity for us? It's unlocked more bandwidth, compassion,
• 20:00 - 20:30 just productivity. What feels unlimited? like I'm sure like the the readers like our our listeners would love to hear that it's not compassion because you know computers don't suffer so they can't really be compassionate. So if they don't suffer they're not going to have really have compassion. Um I heard that from a friend of mine many years ago and I would say that when we talk about the unlimited age it's kind of a scary idea. Um at least it's scary to me. Maybe it's not scary to a lot of
• 20:30 - 21:00 people, but the idea that the computer and you know the intelligence gets more and more and we move into these worlds where you know more and more of the coding maybe even all the coding is being done simultaneously by the computer and then all of a sudden you know the computer is able to interface with robotic systems or manufacturing systems and can make its own robots and rockets and goes into space and is self-replicating and building its own
• 21:00 - 21:30 worlds, you know, in the future. And it's like some AI is out there now, you know, running some factory on some planet building some robots and maybe we're tapped into it somehow through some brain machine interface and it's like that's the unlimited age where it's just like it's gone. Yeah. That we've given birth to some new species. It's kind of a scary thing. I think it's like it's we've only seen it sci-fi, you know, and is that what's really
• 21:30 - 22:00 happening right now? I think that there's a lot of people who think that our futurist is sitting over here on this couch. He was involved in writing these movies like Majority Report and War Games or we saw the movie like Her Terminator. That's the unlimited age. And I don't know if I'm ready for it or not, but it does seem like we should talk about it because it seems like we're all starting to experience what could be about to happen. I think the conversation conversation is so critical, right? Like helps us understand and prepare like Well, we
• 22:00 - 22:30 know we're not there completely because did you realize that Zayn said, "Oh, I'm going to start the recording now." Yeah. Yeah. Exactly. Like still asked you to the click. There was no AI that said, "I'm going to start the recording now." Oh, I see Mark is here. I'm gonna start the recording now. No, we still need Zayn. Zayn still has a role. He goes, "No, I'm gonna start the recording now." So, that's how we know we're not quite there yet, right? That's not the unlimited age because we're limited still by Zane. He's one of the limits.
• 22:30 - 23:00 But when we don't have Zay, then we become unlimited. Unlimited age. No. So Mark like I think one thing you had mentioned uh and as you kind of talk about this unlimited age and the coding changing I think in uh in your recent uh uh quarterly uh uh financial results that Salesforce you talked about like you're seeing significant productivity gain at an engineering level and Salesforce may not hire significant amount of engineers this year or the next year. I just curious to know like
• 23:00 - 23:30 is that just you're implementing now LLMs uh across the board in your product or engineering and that's where like the gains are coming and that's where you see agents becoming a key part of your organization now as a as an internal teams as as well right so this is the CEO mark now is uh you know number one saying hey did you see cursor did you see wind surf like um we did it oursel you probably know one of the first coding engines was ours codegen which was an LLM just doing coding. So I would
• 23:30 - 24:00 say number one we have our own internal products called code genie. I would say that um number one is yeah these engineers should be getting more productive right now. This is a moment of productivity. So we were really saying 30% our head engineering came to me said he wants 50% more engineering capability this year. Um there's a you know it's an organizational issue. We're not running it's not five people in a startup. We're like a big organization. It's it's going
• 24:00 - 24:30 to require some management change management and um yeah we want to target 50% productivity this year and not just there but in support we talked about also right and services that we provide professional services for our our uh customers. So all of these things together, we want all of these things to have more productivity, but where you also know that I'm hiring more salespeople this year because I still need to get to more customers and that
• 24:30 - 25:00 this level like think about the kind of explanations and capabilities that we're really talking about, the nuances and the newness of all of these things. There's still a lot of face to face in the B2B software world that I'm in. Yeah. Mark, you've also talked about um you know, as a CEO learning how to manage AI, like it's not it's no longer just about managing employees. You have to learn how to manage a team of AIS going forward. Can you maybe give us a little bit of color around that as well?
• 25:00 - 25:30 Yeah, there's no question that that's true. And we already talked about help.salesforce.com is a critical part of my support organization. I was just managing our our sales team in Sales and we're talking about our sales agents and our SDR capabilities as well. And another thing is like when I'm writing the business plan myself for the fiscal year, you know, you should know that this is the third year in a row that I'm not only just sitting with another executive writing the business plan for the year, but I'm also using an AI. So,
• 25:30 - 26:00 it's the three of us. It's me, this other executive, and the AI. And I will ask the AI questions like, "Hey, com how does this compare to what my competitor is doing? Give me a letter grade on this idea." you know, am I considering all aspects of this, you know, market? Where am I missing out? And in some areas, even it doesn't know or isn't able to put things together. But in a lot of areas, it is like I'll tell you that because I've been using the AI for the
• 26:00 - 26:30 last three years. There's definitely things that I found that I would not have found. But even like yesterday, I came up with something where I'm like, "This is interesting. I hadn't really thought about this before. this is a good idea. We should be focused on this. And it was not in any of the AI responses. I went back and looked and I'm like, the AI still doesn't it knows what it knows, but it doesn't completely know what it doesn't know. And coming up with something completely new or totally
• 26:30 - 27:00 out of the box, it's it's good in some of those areas. I'm sure you've done it. But in some of those areas, luckily, we still have a role. So Zayn, you're still hired. And Hassan and I are still like, you know, absolutely still adding value to society for now. So that's good news. I just have one final quick question. So Hassan and I know we're at the intersection of of, you know, tech and media. You are at a very unique place because obviously, you know, uh, you founded Salesforce, but you also own Time magazine. With the amount of AI
• 27:00 - 27:30 generated content that's going to be out there, it looks like, you know, very soon there's going to be more AI generated content on the internet than human generated content. How do you think about the future of media and what our relationship as humans to to media is going to look like? Well, I think it's changing a lot and then at some level it's not changing. You know, last I own Time magazine a Tuesday or last week about one week ago, you know, we got a call, you know, urgent call, please come to the Oval Office. President wants to talk Time magazine.
• 27:30 - 28:00 Oh, wow. So, our editors and our photographers and our videographers all got on the plane from New York, flew down there to Washington DC, rolled into the Oval Office, you know, and we had the photographer who did the 2015 cover and took a picture, did a long interview, long form interview on Friday, published the cover on Friday, published the long form
• 28:00 - 28:30 interview and there's nothing else like it in media last week. No, there's no other press conference or anything else that's at all like what we produced. It was not AI produced. Yeah. Yeah. And it was important piece of journalism. If you didn't read it, you should read it. It's like this is worthwhile. And that's important that there is that level of transparency that we're doing the long form that we wrote an article about it, but we also did the long form interview
• 28:30 - 29:00 and it AI was not on this one. Yeah. You know, I don't know if we used AI to touch up the photo or not. I don't think so. I think we just ran the photo as is. And I think it was just like here we go, you know. So that's it. I think in putting together big lists like the time 100 and all those things, you know, we can put together our list and then say, did we forget somebody? Who else would you put on that list? How would
• 29:00 - 29:30 you look at this? Is this comprehensive? Those are things the AI can is very good at, right? Yeah. because the AI is able to look at the whole world and maybe our writers who are kind of in their own New York world, you know, don't know about something that's happening in Canada. Yeah. Or India or some other country. And they might say, "Hey, did you know Mark Carney is not on your Time 100 list?" He wasn't, by the way. So the time 100 most influential
• 29:30 - 30:00 event which was you know last week Thursday in New York and a big time 100 summit and we published the time 100 list and now Mark Carney is the head of Canada. He's not on the list. He should be on that list. Maybe the time 100 maybe the AI would have seen it. I don't know. Yeah. Absolutely kind of funny. It's two funny stories, right? Yeah. So it's new ways to look at these things. So Mark, like two more questions and we can wrap up like where you always
• 30:00 - 30:30 you're always very curious to know like like we get a lot of folks uh on the podcast and want to know like how do you use AI on a day-to-day basis considering you're like CEO of like one of the most well-known company of our of our age, current age, like how do you kind of use AI on a day-to-day basis? What are some of your favorite apps uh which you're using? Well, I have all of the AI apps on my phone. So, and I'm going between all of them. I don't know what your experience is, but my experience is
• 30:30 - 31:00 they're all actually a little bit different. Some have different strengths and some have different weaknesses. And you know where I'm using it is asking questions about my business like we talked about. But even like I have a friend of mine who just had surgery on her hand two weeks ago and I can see that her healing is not going as well as it should be going and I was wondering it's an older woman. and she's in her mid to late 70s. And I'm like, well, should she be using the hyperbaric
• 31:00 - 31:30 chamber because that can provide a lot of healing in this environment, you know, and postsurgically and what are the studies on that and what are the rates and how often and yeah, I'm using it like that. I'm using it to ask questions. I'm also just asking it a lot of basic questions. I'm probably going to it maybe more than I am going to a normal search engine. So, that's important. And I'm using it for the kind of things that I'm sure a lot of people use it for like editing and for um
• 31:30 - 32:00 summarization y or if I get a huge amount of content and I want to have something a little summarized that's important to me but I noticed that it's still you know there's there's gaps and I'll give you one of the areas is Apple has CarPlay. I use it a lot and it has a summarization of like text messages now and it's just uh not as good as it could be. So I think there's there there's still gaps and I think that where we'll be this isn't a very aggressive
• 32:00 - 32:30 statement but where we'll be even just two or three years from now are going to be light years away from where we are now. That this thing is really moving with speed. And I went to a conference last week with a lot of AI folks and wow they have all have a lot of anxiety around where AI is going. So that was extremely interesting. So maybe that could be like one one thing we can wrap up with like what are some things that you are very excited about which considering you also went to this conference you think are coming up in
• 32:30 - 33:00 the next 12 months. Well, I think it's kind of what we talked about the unlimited age. Like we can talk about augmenting our employees, making them more productive, providing new levels of enlightened with new next generation tools, but when some button when we do get to that moment where Zayn is not telling it to start at the recording, but it knows, it's guiding us, it's maybe prompting us, it's giving us subtitles on the bottom of the screen, it's telling you to ask these questions based on what I'm saying, which is
• 33:00 - 33:30 what's not happening right now. I don't think you have it set up like that, you know, and AI is more pervasive. You know, I'm in my office here and there is no robots running around. I have no AGI here. I, you know, we're still kind of in the un We're still in the limited age. Yeah. Still in a co-pilot. We're not in the unlimited age. What's that? Like a co-pilot age right now. It's like an assistant to us. Oh god. That's the clippy age. the
• 33:30 - 34:00 co-pilot age. We're out of that age. We're in the agentic age. We're definitely into the agentic age. So, thank God we left that co-pilot clippy age behind. Nice. That's That's the eentic age. I like I like that. Yeah, we're in the agentic age. And we'll move into the robotic age at some point. You've all seen like there's hundreds of companies working on these humanoid robots and those those potentially could be very cool with the models that they're building. And you've probably seen like the Aloha model out
• 34:00 - 34:30 of Stanford and others and this idea that they can do like, hey, you're getting home and your dinner's going to be made by, you know, this humanoid robot before you get there and um house will be clean and Yeah. your laundry will be folded. Yeah. Absolutely. Not yet though. I guarantee neither one of you all your laundry is going to be folded when you get home tonight, right? So Yep. Yeah. We still got to go do that 100%. See, we're still in the limited age, but I hope that we move into the unlimited age. It'll be extremely I
• 34:30 - 35:00 mean, it's going to be different. Yeah, absolutely. Like, you know, we're we're we're looking at this stuff every single day and the pace of progress is is pretty crazy. I don't know if you saw the AI 2027 paper. I was reading that, you know, about how AI can unfold over, you know, like the next 10 years and how it's looking with, you know, the US, the China, the arms race and having like an unaligned AI and so on. So, I think it's an incredibly both exciting and and scary time to be in. Uh, with that, Mark, thank you so much. This has been incredibly informative and educational for us. Any any last words before we
• 35:00 - 35:30 wrap this up? Yeah. Well, we don't want to move into the unlimited unaligned age like you just opened that door just briefly when you you're looking at that paper and you're talking about oh unaligned AI. Yeah. Unaligned AI and an unlimited age may not be the best possible combination for humanity. Yeah. No, absolutely. I I I couldn't agree with uh more with that. Uh thank you Mark so much for this. really appreciate this. Great to see you guys. Thank you so much as well. Thank you so much for this. Okay. All the best. Byebye. Thank you so much, Mark.