Steven Wolfe Pereira: How Can You Govern Something That You Don't Understand?

Welcome to the Boardroom Governance Podcast.

I'm your host, Evan Epstein.

In this episode, I talk with Steven Wolfe Pereira, the founder and CEO of Alpha, a premier global leadership community and AI-powered ecosystem designed to equip board directors and C-suite executives with actionable governance frameworks. Steven has been at the intersection of technology, media, and data for over 2 decades. We discuss the rapid evolution of the AI market and how it's reshaping the boardroom. Steven shares his perspective on the need for tech-savvy directors, the importance of data governance, and how boards can responsibly engage with AI tools, particularly in sensitive and highly regulated industries. We also explore the future of agentic AI, geopolitical tensions surrounding AI leadership, and the critical role of events and forums in educating and preparing board members for this next wave of Steven offers his take on private versus public governance dynamics, the strategic importance of data as an asset, and closes with reflections on mentorship, attention, and leadership. If you enjoy this episode, please consider subscribing, leaving a review, or sharing this podcast on social media. You can also support the podcast by subscribing to the Boardroom Governance newsletter at evanepstein.substack.com. The Boardroom Governance Podcast is sponsored by the American College of Governance Council.

The ACGC is a professional association of lawyers and academics in the US and Canada, widely recognized for the expertise and achievements in the field of corporate governance. The ACGC was founded by some of the most prominent US corporate governance lawyers, and today the organization includes over 150 practitioners and academics. The ACGC's mission is to promote a high level of professional standards among governance lawyers, along with a better understanding and broader adoption of best practices within business organizations. You should check out their website at amgovcollege.org. That is amgovcollege.org. Steven, it is so good to see you in the Boardroom Governance Podcast. We have got to know each other through many different venues, particularly the LCDA, the Latino Corporate Directors Association, but others. You have attended the VCBA, the Venture Backed Board Academy that I do at UC Los Angeles with Cooley and Nasdaq.

Which is excellent. Which is excellent.

Well, thank you. And that's going to happen again in New York on October 28th, the 4th event. But you are also doing many things in governance, so I thought, Steven, let's talk about what's going on in the market. You're very focused on AI. So thank you very much for doing this, and I'm looking forward to our conversation.

No, well, thank you for having me, and congrats on your 5-year anniversary.

Woo-hoo!

First-time caller, longtime listener, but it's great to be on.

Love it. Okay, so you know the drill. Let's start from the beginning. Where were you born? Where you grew up? And then we'll go through your many different ventures around the world and items that you've done in marketing, governance, all that drill.

Happy to. Well, I am a proud son of immigrants. My mother is from the Dominican Republic, from Santiago de los Caballeros, came to New York in the '60s. And my father was from Ukrainian-Russian immigrants and was born in the Bronx. So I am a born and raised Bronx boy from Mount Vernon, New York.

All right. Well, there we go. And then tell us a little bit about your professional background and what did you focus your, at least your executive career on?

Sure. Well, you know, it definitely has been a long, strange journey, but when I was graduating in 1995 from Tufts University, I believe, uh, our senior class was the first class to get an email address. Wow. This new technology called email.

Uh, I think the year of the Netscape IPO.

Exactly. And so this was, you know, kind of, um, You know, I think it was a Pine address actually. But we, you know, we were exposed, I think, early on. You know, both my parents were teachers and my dad specifically was a math teacher. And I think that was always kind of in the back of my head, which I just love to tinker and love math. And I think if I knew at the time, I probably would have majored in computer science, but I ended up doing economic development. And I think the whole advent of what was happening with the internet, with technology, it was so kind of exciting and it just attracted me in such a powerful way that I started to get involved in initially in finance and investment banking, in technology, media, and telecom. And I was assigned to do telecom very early in my career, and that kind of exposed me to really the underpinnings of the internet, internet infrastructure. IP addresses, you know, domain name systems. And that kind of led me to this incredible startup that came out of MIT called Akamai Technologies, which was founded by the head for the Lab for Computer Science at MIT, Dr. Tom Leighton. And I joined the engineering group. And so in 1999, when things were just kind of really getting crazy—

Crazy.

With the dot-com bubble. But it was exciting 'cause I was actually in charge of network infrastructure for Latin America. And Southern Europe. So I built out our platform, our infrastructure for that region. And that, I really think that that began this incredible 25-year trajectory around data, machine learning, and now what everyone is really obsessed with, AI.

Hmm.

Yeah. And so there is a lot happening in the AI world and everybody's talking about it like this is the new platform that is way bigger than what internet was, what mobile was, what SaaS was. Like, this is a new paradigm shift. It seems to be backed by numbers, right? Like, the number of investments that companies are doing is just over the roof. And tell us about your point of view there and how and when did you start focusing on AI? But there's a lot of playing around the name as well, right? AI is kind of the new thing. And, you know, when I talked to Joe Grundfest 100 episodes ago— —he called this the pixie dust. And I just recorded an episode with Eric Goerding, who used to be the Director of Corporate Finance at the SEC, and we talked about AI washing and how the SEC is going after companies that are just putting AI on everything. And you gotta be really careful using that. It's kind of the next greenwashing term.

Absolutely.

And that's part of it. But give us your take and maybe tell us what you're doing now because I wanna talk about your new company, Alpha. I can see it in your shirt. And, you know, I'm very excited to talk about your new venture because It's all about AI, right?

Yeah, I mean, look, well, let's take it back. And I think it's probably been covered for folks that are exposed to technology, but again, AI is not new. And the category of machine learning really dates back to, you know, kind of the mid-1950s, but really back to Alan Turing, right? If you think about it, you know, kind of the father of modern computing. But I think when you fast forward, a lot of people have been using machine learning inside of the enterprise. And AI was kind of viewed as a marketing term. It was kind of almost derogatory. And so everyone really wanted to show their technical chops, and so they would talk about machine learning. And if you really think of kind of the trajectory that we've had, you know, kind of 2012 was really the major breakthrough when you had AlexNet, and you really had the godfather of AI, Dr. Geoffrey Hinton, kind of make that major breakthrough with Ilya Sutskevich, who, you know, was one of the co-founders for OpenAI. Mm-hmm. Being able to kind of use a machine to recognize all the patterns of what we lovingly call catness. And they basically trained a model using YouTube data to identify what is a cat, but that's not like what a cat looks like, just catness in general. And that major breakthrough kind of led to a lot of innovation to the 2017 Transformer paper, which was really released by a bunch of Google engineers. And that has now set off this new wave around AI which has been generative, not kind of the deterministic that, hey, 1 1 absolutely always equals 2, but probabilistic where you are now leveraging all of this data, you kind of ingest it, you actually, you know, kind of prompt it in some way, shape, or form, and then you get an output that is generative, probabilistic in nature. Yeah. And so when you kind of see that all of this has really been building on every single previous generation, but what is unique about this is, Whereas the internet was incredible, but it was a network of networks versus this is actual intelligence. And I don't think what people really process is that this has now mastered human language and all of the modalities, whether it's audio or video or image or all these different ways to kind of understand human language. And so when you actually have intelligence really being at the heart of this, This now means that it is much larger and much more impactful than just the internet. And when you hear that, it feels like hyperbolic. And I'm sure a lot of, you know, directors that are, that are your listeners, they're like, oh, eyes rolling. Yeah, it's bigger than the internet. No, it actually is because this is on the scale of understanding electricity, the transistor, like these major technological breakthroughs that then permeate and radically transform every aspect of society.

Hmm.

I truly believe that AI is gonna become the operating system for society as we know it.

Hmm. All right, so there's a lot to unpack there, but let's dive first into Alpha and what your company is, what inspired you to do this new venture, and what it is that you do.

Sure. So, you know, I've been involved really with kind of data and machine learning, but you could package it all as AI, right? 'Cause you cannot do machine learning without data. And so those are really, you know, kind of the, you know, key ingredients But dating back to kind of really 1999 with Akamai and then pull the way all the way through, you know, we've been working on ways to apply machine learning and leverage data to lots of different industries. And so I started kind of in tech, then, you know, a lot of telecom, made my way into media. And then in 2010, I kind of ended up in advertising. I was at the Publicis Groupe. I was running the Walmart media business, which was basically $1 billion of media spend. But that's where we were really seeing the advent of, you know, kind of data-driven marketing and these new social platforms like Facebook and, you know, kind of YouTube. All these things were really starting to rise. So we were applying kind of all of that science to advertising. And that really led to the whole field of advertising technology.

Mm-hmm.

And then in 2013, I became the chief marketing officer for a data technology company called Datalogix, where we were using machine learning and first-party purchase data to basically do predictive analytics. And that's where we were saying, hey, if you saw an online ad, would that lead to an offline sale? And that was working with folks like Coke or Heineken or Walmart or whoever. So that company, we were going to go public. We ended up getting acquired by Oracle, and that led to the creation of the Oracle Data Cloud. And that's where I was, you know, CMO for that. And then after a year and change, I became the CMO for a public company called Neustar, which again, using machine learning now around identity, but that was applied to security and telecommunications and finance as well as marketing. And then I did one more stint at an AI behavioral analytics company. And then I started an edtech company in 2019. So you can see the through line here. It's always been data and machine learning. And it's been an incredible wild ride. But in 2022, specifically November 30th, 2022, we have the ChatGPT moment.

Mm-hmm.

And that for me was, you know, such a revelation because we've been talking about ways to apply machine learning to businesses, to brands, to consumers, for well over 2+ decades. But now you have the first true mainstream application of AI and just took off like a rocket ship. And we don't need to kind of repeat all the numbers, but, you know, kind of 100 million users in 2 months. You've never seen that type of adoption. And it really was this watershed moment. And I call that the equivalent of the Netscape Navigator moment back in 1994.

Hmm.

Right? So now you actually have all this incredible momentum and now everyone's trying to figure out, wow, what do I do with this thing? It's like this incredible magical experience. And I was like, wow, it's finally here. And literally, I remember, you know, meeting with, you know, CEOs, meeting with C-suites, you know, in 2013, 2016, 2019, talking about AI. It just wouldn't land.

Mm-hmm.

Now all of a sudden everyone was calling me saying, hey, can you help teach me about this AI thing?

Mm-hmm.

And because I just know lots of folks, I've been in lots of industries, I started going to boardrooms and C-suites and just kind of doing my, you know, kind of state of AI presentation. What I effectively call is, you know, wake the hell up, but maybe with an F-word presentation. And that kind of led to lots of folks saying, hey, I really don't know anything about this stuff. How can I really learn? There's so much noise. And you start connecting the dots. And, you know, we all know a lot of folks on boards today. So that really led to the creation of this idea of how do you kind of create something that is going to be of substance where directors can have a safe space and place to really learn, not from consultants, not Not from charlatans, because now everyone and their mother is, you know, an AI expert on LinkedIn, but actually go to the source, go to the technologists, go to the practitioners, go to the operators, and also go to actual directors. And so that was really the spirit of creating the first kind of leg, which was the Alpha Council, which is kind of for directors by directors. Think of it as kind of like a YPO-style network organization where members get to learn, you know, from each other, but they also get to learn from actual technologists and practitioners. And it's invite only, kind of like an Amex Black Card kind of vibe. And that led to creating the Alpha Institute where we started to do research and kind of help, you know, organizations understand, you know, the policy and, you know, the regulatory aspect. And again, really, how do you actually have this neutral third party? Because we're not doing consulting, we're not doing any of that kind of stuff. Like we're really this neutral Switzerland where we work with everyone, but we're really trying to super serve directors. And then the third leg of the stool was really kind of helping to really create this type of purpose-built governance intelligence platform to really help directors learn all this kind of stuff, but in a bespoke way. So that was kind of like the 3 legs of the stool. We have, you know, the council, we have the institute, and now we have Alpha AI.

Yeah. And you got events, right? You did the board forum in LA on May 21st, which was, I think, a few days after the VCBA. Tell us about that forum and And you're based in LA?

Yeah. I mean, born and raised New Yorker, but my wife, the amazing Nuria Santamaría, she was originally from El Salvador but came to LA when she was 3. So LA is home. And as I learned very early, Evan, happy wife, happy life. Also turns out that after, you know, a lifetime in New York, living around the world, but 6 years in the Bay, my 2 kids being born in the Bay, we moved to LA.

Oh, I didn't realize it. Well, I guess Oracle time. Yeah, yeah, yeah.

Okay. Well, and again, you know, my wife was early Twitter and, you know, she went to Stanford for undergrad. And so kind of, you know, the great, you know, kind of technology connections there as well. But yeah, but we moved here in 2019. And so this is home base. But again, basically a Delta seat, you know, somewhere in the sky is the other home. But yeah, we got all this kind of requests from a lot of our members saying, hey, it'd be really great because we do a lot of these, you know, member meetings virtually every month. You know, we just had a cybersecurity expert talk to our members. Last week, but they were really clamoring to kind of meet in person so they could actually not just ask questions to kind of subject matter experts, but also just to kind of connect in real life. And I think you're going to see a premium on IRL really moving forward because the bar is going to be so high. There's going to be so much AI slop everywhere. But for you to kind of get out of your house, get out of your office, and actually meet with people in real life, that's going to be incredibly valuable. And so we started to do these intimate Alpha Board forums. We did one in New York in Q1. We did one in LA in Q2. And now And now we're gearing towards— we did a partnership with NASDAQ. So we're going to be doing an AI governance summit at the NASDAQ on November 19th.

That's great. I will have to get some of your advice because I'm doing the Boardroom Governance Summit, right? I was planning on doing it this fall, but I got tapped to teach a corporate governance class at the GSB. And I had to do a lot of work. And when you have 100 students, 100 MBAs, You gotta put—

You're in demand, Evan. People wanna hear from you. Yeah. Maybe they fill your pod.

Full-time. So, but I, I do think that that's a great venue to get IRL, talk about these matters in governance, AI, and other stuff. And—

Yeah. And, and specifically, it's like a technology conference for directors.

Right.

And, you know, and other types of executives, but really from this technology lens. 'Cause, you know, we've had 30 years where it's all been about, you know, kind of, financial qualified experts, you know, kind of all the emphasis on audit and, you know, you kind of, of course, have to get, you know, your financials. That's, you know, table stakes.

Mm-hmm.

But I feel like we're now at this really important moment, this incredible tipping point where you need to actually have directors become technology qualified experts. It's no longer okay that you do not understand key components of technology, which involve data, which involve AI, which involve all of this, you know, kind of area which involves cyber. Like, we've been dealing with the data and cyber issues for 2+ decades, and people still don't understand these issues. And it's because they're constantly changing, evolving, growing, and it's exponential. And now you bring in the AI layer on top of all of it. I just feel like we're at a moment where you need to have every single director really become conversant in these issues.

Yeah, I think I love this. And clearly, This has become number 1, 2, and 3 item in the agenda of any board, particularly because we've talked about disruption and innovation for many years, but now it's in overdrive. And since you've done a lot of—

This is overdrive? We haven't even started it.

We haven't.

That's the scary part.

Right.

I don't think people can process this is not linear. This is literally exponential. Again, it's not the internet. You're dealing with intelligence.

Yeah.

And so what happens when this continues to grow? If we're at 150 IQ points today with all the different LLMs and this continues to grow on average every 6 months, it's getting smarter. So it doubles in 6 months' time, much faster than Moore's Law. Where is this gonna be in 12 months' time, in 24 months' time, by 2030? That's the exponential nature of this.

So you've obviously done a lot of state-of-the-art? What is the state of AI for directors? And I suppose this is a great forum for you to also talk about directors that are listening, not only in the US. I have a lot primarily in California, but also outside of the United States. Maybe give us a little bit of what are your top 3 talking points for directors? What should they think about and resources? And maybe to ground them because there's a lot of noise out there. And maybe you've done so many of these that you can have a few pointers here.

Yeah, look, I think it's a great question and it's an important question. One, anyone that says they're an AI expert is a liar. And I think it's really important to realize that this is all what I affectionately call wet cement. And so you're dealing at a stage where it's so embryonic, but it's moving so quickly. And so it's really hard to wrap your head around that. I mean, just over the past 6 months, from January 2025 to June 30th, 2025, we had over 30 major model, large language model releases. 30. And they continued to kind of one-up each other. Literally last week, Grok-4 just dropped, right? So for your listeners, Grok-4, which is part of Elon Musk's xAI, You know, that is now the most intelligent model out there. And so you see this kind of ones-upmanship that's happening. And it's important to understand that there's 4 forces that are driving this incredible exponential wave.

Mm-hmm.

The first one is compute. And I think that is the most important building block because understanding why Nvidia just hit $4 trillion in market cap, the first company to ever achieve that, And again, I—

more than Google and Meta combined.

More than them combined. But when you understand that Nvidia is not a chip maker— I mean, of course they make chips, right? They're a software company, and they actually have this software lock-in with their platform called CUDA, and that's what every single GPU is using to kind of build these types of AI models on top of. So understanding the compute layer is going to become critical, but you're seeing this rapid improvement in terms of the way that the GPUs are being designed and implemented and then clustered together and then the cost of it coming down. So there's this kind of compute, you know, lane that's improving exponentially. Then you have the data lane. And again, every single piece of kind of public, you know, data on the public internet, all that stuff has been ingested into the models. And again, we're gonna have years of copyright suits and, you know, the New York Times versus OpenAI, like all these things.

Yeah.

Again, You and other lawyers are going to be very, very busy for a long time. But the algorithms and the data, you know, that's kind of like 2 and 3. Those things are also increasing exponentially. So all the kind of public market data on the public internet, that continues to increase. Again, one of the genius, you know, moves by Elon, that was one of the reasons why he bought Twitter/X in the first place, to get this steady stream of data coming in.

Mm-hmm.

Who else has that data? Well, Google has that data. Meta has that data. And again, that's why OpenAI is racing to kind of get that steady stream of data. So this is a complete war for data.

Hmm.

And the last bastion of data is really probably in 2 places. One, it's inside the enterprise. So all that first-party data. And so please, everyone that's listening, protect your first-party data. Don't give it to other folks 'cause that is gold. And then it's really data in the physical world, right? Like what you see and observe and everything's changing. And then, you know, so you have compute, you have data, then you have the third, you know, kind of pillar, which is really the algorithms. And those are the designs that's leveraging, again, the transistor model. What are new ways, new methods? And we had kind of the first major breakthrough with, you know, ChatGPT. But then you saw the next major breakthrough, which was chain-of-thought reasoning. And now giving your, you know, kind of model the ability to actually not just take 1 step or 3 steps, but now think about it as a recipe. You can now have 10 steps in that recipe. You could actually have 100 steps. You could have a million steps. It could go on indefinitely. So the ability to do reasoning that you now can actually have your LLM start to do actions, that's a major breakthrough, but you'll continue to see innovation of the algorithms. And then the last kind of final frontier is really robotics or what they're calling physical AI. And I know that really sounds preposterous, you know, it sounds science fiction, but like we're all gonna have a robot. We're all gonna have an R2-D2, a C-3PO, like, Rosie the robot from The Jetsons. You pick the robot, but the robots are coming. They're not here today, but they are very, very soon going to be a part of this factor. Those 4 forces of compute, data, algorithms, and robotics coming together, think about how that is going to radically change how every single enterprise, how every single board is going to be operating. Literally, this is a reset of how every single business, how every single brand, how every single consumer, how every single government— like, that's why you're seeing this geopolitical race around AI. And it really is going to be these 2 superpowers of the United States and China. So the geopolitical down to the consumer, you know, kind of implications of where this is, it requires every director to get smart about it.

Yeah. And so what is your first recommendation to directors on, on where to get smart on these matters? How to get educated? Not get drowned in all the noise? Uh, do you have any resources that you point to?

Yeah. I mean, look, obviously it's, it's a, it's, it's an easy plug for the Alpha Council because I think that we need to learn from each other. But, you know, putting Alpha aside, I think it's critical to actually, one, start to use these tools. I mean, I, I tell, you know, kind of directors, I'm, I'm basically presenting, you know, at this point, you know, 2, 3 times a week, every week to some subset of board or C-suite or, or whatever. But, You can't learn how to surf through PowerPoint, right? You never are going to learn how to ride a bicycle by reading the manual. Like, you have to do it. You have to use these tools. And so one of the questions that I always ask is like, how many of you are actually using it? And, you know, maybe half say they're kind of using ChatGPT, but they're using it the way they think of like Google, right? Like they're using it kind of like for a search. And that's not what it is.

Hmm.

Right? It's a fundamentally different application. So for example, I ask everyone, have you actually set up your own GPT? Like, have you actually set up your own environment and you're starting to train this model in the things that you care about in a privacy-secure way so that you're not training those models? It's actually— there's a way to kind of make sure that it doesn't kind of go into the larger pool of data, that it's actually just locally on your machine. But there's all these things for you to start using And there's lots of exciting tools just to kind of understand what's possible. But getting your hands dirty with these tools, I would say, is step one.

Let's talk about the personal ChatGPT, taking it out of the online format, because I think there is a lot of concern from users of putting personal and certainly professional and confidential data out there. And there are services— and I was talking to Jack Lazar, who's a director at Box and—

He's awesome.

Right. And he was telling me that he uses a lot of the Box AI private enterprise version to do a lot of stuff. So like board minutes and other stuff that is confidential, there's an environment where it doesn't get into the internet. How can people adapt these new AI models that are off the grid that can allow you to use some power AI that is more secure? And I think that's an important vehicle to start experimenting and helping you in your personal decisions, you know, maybe 10, 20, 30% more productive? What is your benchmark there and how more productive you are these days than you were pre-AI?

Totally. So I would say break these into different segments, right? So you as a consumer, right? So let's say board director XYZ, he or she, just your daily activities, right? So nothing to do with the company, nothing to do with the board. You're not putting board decks into this stuff, just you as a consumer. How are you using this? You know, Menlo Ventures came out with a great article. I'll share it with you, Evan, if you want to kind of, you know, put it in the—

Show notes. Yeah.

You know, kind of, yeah, in the show notes. But they talk about the 5 categories of daily life, like routine tasks, learning and development, physical and mental health, connection, and then creative expression. And so just understanding how using not just one, I think it's very important that you start to view these as a symphony, right? Like, understanding all these different tools, they each serve a different purpose. Now, again, maybe you're not gonna wanna do all that, so that's fine, but at least use more than one, right? Obviously so many people are using ChatGPT. They're the largest, they're the 800-pound gorilla. But, you know, Claude is one of my favorites, right? Like Claude is incredible for writing. Or definitely try Grok, you know, understand the differences between that and then something like Perplexity.

Yeah.

And then of course there's Gemini, you know, from Google. So, Each one has their own kind of flavor and their own kind of strengths and weaknesses. So just understanding, hey, these tools all serve a different purpose and actually combining some of them is really powerful. Like you, maybe you do something in Claude, then you kind of put it back into ChatGPT to see, hey, does that, you know, kind of sound good? And then maybe I put it into Perplexity.

What is your actual spend on these? Like, you know, how do you decide to pay, you know, ChatGPT $20 a month? And then the other one, I think there are some that are research-oriented that you pay $300 a month or stuff like that?

So I really think it depends on the needs. And we're just talking about as a consumer now. We haven't spoken about anything business, right? But even as a consumer, some of them offer basic, you know, kind of features and functionality for free. So you don't have to pay anything. But holy cow, like this is again, intelligence. This isn't a parlor trick. This is truly understanding that you now have the equivalent of PhD-level scientists mathematicians, you know, your McKinsey consultant, your doctor, your therapist, you know, your best friend. I mean, just understanding all the different dimensions to this. And why wouldn't you want to just start to build a profile? And these things are now starting to have infinite memory, so they remember every conversation.

Mm-hmm.

So again, making sure that it is private as a consumer, that it's not sharing data with the larger model, But there's ways that you could just start to use these tools to benefit you. But why wouldn't you wanna, you know, sign up for the pro tools, get even more advanced features? And, and what you're referring to is like the deep research. So, right. For some, you know, you get some functionality at $20 a month. That seems to be like the entry-level price. And then some are really giving you the ability to do kind of like the deep McKinsey-style research or PhD-level research. And that's like $200 a month. Mm-hmm. And again, they'll continue to have different tiers. Eventually enterprise, I think, will be even more expensive. But I would say just figure out what your sweet spot is. And again, you could just start for free, but you have to start using these tools. Absolutely.

Yeah. And I remember talking in my past episode about complexities for boards on deciding how much should they spend on cybersecurity, right? So you've got your CISO that comes in and says, you know, it's always been a hard thing for boards that are non-tech literate, right, to understand what the CISO is saying. This is a new version. Right, with AI and how should boards approach this AI function and manage this? Because as you say, it's exponential. So how would you structure it from a board perspective? Where does this fit in a board committee? Do you like a board committee to be tech or to be cybersecurity or to have a different cross-function there? And how do you correlate that with management and who in management is in charge? And how do you pull it up into the board?

So all the easy questions, Evan.

Okay, great. Good, good, good.

How much time do you have? I mean, all joking aside, this is truly the key issue. How can you govern something that you don't understand? And that's the existential question. And I think we need to start with the end in mind. This is about governance. Your fiduciary obligation to shareholders. And you are now a part of the greatest technological transformation in history, in human history. And so when you put that in perspective, when literally everything that has been produced online has been done by humans to date, plus or minus maybe, you know, a couple basis points. And moving forward, 99.9% of every single thing that you see online will be made by a machine. What do you know is real when you actually— you saw the impersonation of Marco Rubio, right? Where there was actually a deepfake and it sounded just like Marco Rubio. And, you know, all these kind of things are going to only start to happen more and more and more. And so you're seeing this gap you know, we call it the governance gap between traditional governance and we're moving to this new world of AI governance. And I would say there's kind of 2 dimensions to it, right? There's operational AI, which is absolutely like in the weeds. How are these things architected? You know, what data's feeding what? Those are all technical things that I would say are traditionally kind of like, you know, the way the CISO is talking about all the cyber stuff. And then there's strategic AI.

Hmm.

And so I feel like You need to really be up to speed so that you could ask the right questions in your duty of care and your duty of loyalty and all the responsibilities as a director. But if you don't start to do this, we've already seen now ISS has been publishing for a while now, for the past, what, 18 months about AI governance.

Hmm.

They're starting to identify which directors are actually fluent, conversant in these issues, and how are companies doing when it comes to AI governance? Who else has been talking about this? BlackRock, State Street, Vanguard. So all of those institutional investors are now looking at AI governance as well. And what do you think's going to happen when you actually see the new 2, 3-person startup in the Bay with not 100 people, but with 100 AI agents?

Hmm.

And they launch a product or a service that competes with your company that you sit on the board of. And maybe they take 10, 20, 30% share. You're a public company, your stock drops, and what's going to happen? An activist investor is gonna come after using their universal proxy card, the individual director that was negligent, that did not know anything about AI. And they're gonna be like, why is that person on the board? Let me offer a slate that actually has folks that are AI literate. That scenario is going to happen. Last year was what, the 2nd highest activity of activist campaigns in history? 264, I think, was the stat coming from the Director's College that we had a couple weeks ago at Stanford. So, you know, I just really can't emphasize enough getting up to speed, you know, taking this seriously. It's not optional. Like, it is actually your fiduciary obligation to become AI literate. And then understanding how are we preparing for the strategic questions. You could actually have someone just go very deep on the technical side, and we could talk about like where this sits. But I think it's actually, I think it's a major problem that we continue to cram all of these technology, and, you know, I'm doing the air quotes, issues into the audit committee or into the risk committee. This is bigger.

Hmm.

And, you know, it's so funny to see the pushback from, you know, maybe more traditional boards. I don't want another committee. That's lots of work. It doesn't warrant that. I think it does. And I would argue that it probably should not be led by a technologist solely. I think there's probably gonna be much more power to have a 2-in-a-box approach. You need a business person and you need a technical person because this is fundamentally rewriting the game of what industry and the way you go to market. And the funny thing is the private equity companies are already racing to do this.

Hmm.

because they don't have to deal with a lot of the hoops of a public company and they could just jam it in. They could say, you are gonna be using AI all across the company, period, full stop. And they're looking for the, not just the efficiencies, right? We talk about a 2x2 matrix. One of the frameworks that we have at Alpha is, you know, on the x-axis is internal and external, and on the y-axis it's your risks and opportunities. And so on average when it comes to AI, but you could apply it to other things as well, Where does a board spend the majority of their time? 90-plus percent, it's on internal and risks. Well, guess what? If you're not talking about the opportunities that are external or the risks that, you know, are— I mean, you know, the opportunity is internal, like, you're gonna be missing the boat if you just obsess about, oh, we have to keep our, you know, head in the ground. We can't do anything. It's too dangerous. Like, you know, there's ways to kind of Really start to implement this in ways that aren't just like pilots for vanity's sake. You know, everyone's questioning the ROI, but you have to figure out what the plan is. And that comes back full circle to the strategic implications of AI on your business and working 3 to 5 years out to stand in the future. 5 years from now, how is your business gonna be radically transformed by AI? And then you work backwards.

Yeah, and it makes me think of the other framework, which is, you know, typically boards have traditionally focused on hindsight or oversight and not so much on foresight, right?

Right.

Which is the same idea of strategic thinking and spending time, and now AI is there. Look, I think that it's hard to believe that all the directors today— public directors, I don't know, I think there is 40,000 public directors in the United States, but I'm not clear that all those people are going to be up to date on AI, and there's going to be a new Entrants and people. If you think of board composition, you know at least what they're going to try to do is to have one or two or three people that are more conversant, and there's going to be a shift that's going to take some time. But let me ask you another topic which is related because it's very alive in Silicon Valley, which is this idea of staying private and going public. And people say, well, you know, maybe we should just stay private. As you said, private equity is pushing an agenda. The VCs are pushing an agenda as a private company, you have much more freedom to design your board as you wish. You don't have the pressures of ISS, Glass-Steagall. You don't have the pressures from BlackRock, Vanguard, State Street. You don't have the pressures from the activist investors. You don't have any pressure from outside. You can kind of manage this. And some people like that, right? Now, there is a distinction on liquidity. You know, maybe there is a value on having liquid markets, raising money, And, you know, people have done it through dual-class share structures or other vehicles to avoid all this other pressure. But some people say, well, look, the private markets are vibrant. We've got 50,000 venture-backed companies. We've got 13,000 private equity-backed companies. Public companies is only 4,000, right? Or give or take.

And by the way, that's down almost 50% from 1995.

Exactly.

Down from 8,000+ public companies down to like 4,200 or something.

Right. And we've got new vehicles like secondary markets, NASDAQ Private Market, that now you can provide liquidity through tender offers and others. And there is a discussion here. And I think, you know, the SEC will have to weigh this in. The SEC has kind of started looking at this, and they've been talking about this probably since the JOBS Act. But let me ask you about this, because AI brings this new hyper-scalable technology that will change And even Warren Buffett, who's probably the most structured person thinking about companies, you know, in, in, I think one of the annual shareholder meetings, maybe in '23, '24, said if you looked at the top 20 S&P 500 companies from 1985 and then you take it 20 years, there's none left. And a lot of them were from Japan. And, and so the— what are the odds that this current group stays 20 years? And You know, it's hard to think that the current companies, the Nvidias, the Googles, the Metas are going to go away. But there's been discussion about even Google for the first time feels a threat from these newcomers.

Absolutely.

And the odds are that innovation and what's happening is very important. So how do you think about this stay private versus go public? Because AI has been driving every— like 50 to 70% of all venture financings have been in AI. So it's dominating this space.

So I do want to come back to talking about like how to think of the board structure and kind of the committees, because I feel like that's where the real work needs to happen.

Yeah.

Because it really is, you know, kind of a code red. And I think directors really need to understand just how to start. But when you're a private company, especially a technology-backed company or technology-focused company, VC-backed, You know, it's just different. You, you, you just live in a different world. You breathe different air. And, and we know that, right? Like, I, I've worked for 4 different venture-backed technology companies and then I started my own and I raised, you know, $16 million in capital for, for, you know, my edtech company. So it, it's just a different universe.

Mm-hmm.

And they just have options, you know? And so when you're a venture-backed tech company focused on AI, you know, the world's kind of your oyster. And so you don't have to go public. But again, it's not just, you know, kind of understanding that it's only AI. I mean, look at all the fintech companies. Again, look at Stripe.

And by the way, now they're public benefit corporations.

Absolutely.

And they've got all these like crazy—

Actually, just for the record, Encantos, my edtech company, was a PBC.

Wow.

We did that back in 2016, so.

I can't believe that. Wow. You were ahead of the game.

Again, I love the whole B Corp structure. But, you know, specifically, there are ways to kind of get liquidity. Obviously, you wanna make sure that your employees that are working hard, they have all these unvested options. How do you give them some liquidity so they kind of stay there? And then you see the poaching game that is happening right now. I mean, the crazy reports of Meta hiring folks for $100 million, you know, signing bonus and all-in comp. So $300 million. I mean, it's just, it's insane. But there is value in having a public currency, a publicly traded currency. And so you will see, I think, the large firms like the OpenAIs of the world go public. Or you'll start to see the large tech firms that really are kind of caught a little bit flat-footed. I mean, why do you think Meta's going all in trying to acquire all this talent? Because, you know, they just kind of hit a wall. You know, they didn't have the talent and, you know, like now we need to hit the reset button. So let's go kind of circumvent, you know, the rules and buy 49% stake in Scale. Right.

These acquihires or whatever they call them.

Yeah, acquihire. I mean, it's, it's, it's It's the worst known loophole in the Valley. But, you know, they need to kind of bulk up on the talent. And eventually, I think the large tech companies will be buying, you know, some of the most innovative companies because they need to bring that talent as well as the technology in-house. I mean, just look at Apple. Like, it is shocking how behind they are when it comes to AI. I mean, Siri still sucks. So, like, what are they gonna do? They have capital. So I think people are still trying to wait and see because it is still so early. Mm-hmm. But I do feel that the large companies that are going to want to have the currencies so they could acquire, so they could do stuff, and then they really do have global aspirations. I do think those companies will go public at some point. You know, just the question is, when is the right time? And they want to have as many ducks in a row because again, once you're public, that scrutiny—you have to be prepared for everything that comes along with it.

Yeah. So at the top of the show, you were talking about geopolitical tension, which is another big story where today. I mean, we probably lived through a globalization where it was great to have operations globally. Now it's, you know, people are talking about uncoupling from China or de-risking from China. It seems to be a very different environment. There's all these tariffs that are being implemented. There's all this discussion around this. The boards are under pressure, right? And how do you think, particularly on the AI race, like, do you think China is A little bit behind, a little bit ahead. Where do we actually fall in this idea? And clearly, the elephant in the room is energy, right? And all these graphics that China is building nuclear plants, they're in the energy component, are way ahead of the United States. But what is your take when you have these discussions on geopolitics on boards, and how should they address this matter?

Yeah, I mean, I remember vividly, you know, I go to Fortune Brainstorm Tech every year. Um, you know, they, they do kind of great stuff. They had Kai-Fu Lee, who is the, you know, one of the leading kind of AI technologists. He's been at big companies. Um, he was at Baidu. Um, but he in 2018 came out with a great book. I don't know if you recall it, that was called AI Superpowers.

Yeah, yeah, I got it.

China, Silicon Valley, and the New World Order. Um, and then he came out with another book, uh, in 2021 called AI 2041, kind of showing visions of the future. And so it really was painting this world where China would be in the lead because they have all of the ingredients to go and far surpass the United States when it comes to the workforce of just STEM talent, you know, just all their engineers, the, you know, lack of regulations because they could just like jam stuff through, their ability to build data centers and energy, nuclear, um, you know, solar, wind, but just being able to really have the energy to kind of really power all the compute. And then, you know, really understanding that they are far in the lead when it comes to robotics.

Hmm.

And so back to the 4 forces of compute, data, algorithms, and robotics, they kind of check all the boxes and they're just racing ahead. And they now are really neck and neck with where the United States is. And so certainly you had the DeepSeek, you know, kind of freakout back in January. But again, if you're a part of the AI community, everyone in the Bay, we knew about this. This wasn't new news because again, it is a community. So even though it is, you know, radically competitive between the United States and China, the research community, they all share that, and the open source community is following all the latest innovations. So the kind of freakout was overblown from one perspective, but it really was a wake-up call showing the way that they can innovate and that innovation doesn't only apply to the United States. Other countries can innovate. And it really is going to be this kind of two-horse race. I would say that we are definitely not guaranteed to win this, but what does win actually mean in geopolitical terms? I kind of see, and I have a closing slide towards the end of my presentation talking about, you know, kind of the 3 universes or the 3 kind of options. And so the first one is The Empire Strikes Back, and that is kind of the China model, which is really kind of the state controls everything. You're living in surveillance capitalism. I mean, they've— they have for a long time, but the Empire struck back, won, and this is kind of like the China worldview. Then you have Star Trek, and that is the EU model where like there is going to be, you know, everyone trying to get along. You're going to have privacy, you know, really, um, you know, kind of being the pillar, and you're going to be able to have all of your rights and that AI will be held in check, but you're going to have this peaceful, peaceful, harmonious world where everyone gets along. And that's the Star Trek path. And then—

I don't see that one, but okay.

I know that one doesn't have a lot of fans right now. And then you have good old America, and that is capitalist version of Mad Max. And it's just everyone out for themselves. If you could afford it, you get to win. If not, you're out of luck. And we're kind of really spearheading this Mad Max approach. You could see all the dismantling of regulations and just go, go, go. Again, cutting safety nets. Again, that's, that's another pod we could have.

Right, right.

But how does that impact a company and a board? And so what I would say is you're now reaching this point where, you know, from call it November '22, call it to today, but be generous, call it to the end of the year. So '22 to '25 was really the first wave of this new kind of AI era, this intelligence era. And it was really all about the chatbot functionality of an LLM. You know, the parlor trick. Wow, wow, I'm talking with an LLM and it's actually smart, getting smarter. Oh, I could do images. You know, we'll do, you know, kind of all the different pictures and stuff, video. So that kind of multimodal LLM was wave 1. We're now getting ready for the next wave, which is agentic AI.

Hmm.

AI agents. And this is now chain of thought reasoning and moving from a prompt to an action. And now all bets are off because when you actually have an agent, and it will be adopted by consumers first, as all the technology waves have actually happened, led by consumer adoption, because consumers care about convenience over privacy. That's been proven for 25 years. So I'm gonna have an agent And that agent is gonna schedule my travel. I'm just gonna say, hey, find this price. I fly Delta, do this and that. I want to go to New York, I want to go to London, whatever it is, an agent will do that. Then I'll have another agent for my food and maybe another agent for this and that. And then I'll have an orchestration agent to kind of orchestrate all of my agents. Well, what does a company do when you can't actually talk to the consumer? You have to talk to my agent. Well, now the company's gonna need an agent. And that agent will become more important than the company's website, more important than the app. And so that agent, and again, it's not just one agent, it's gonna be multiple agents that are talking with the consumer. And then you'll have a whole host of agents that are gonna be internal-facing for the company. Do you think that going forward, a new employee is not gonna be onboarded by an agent? Like, that will happen.

Mm-hmm.

So now you're gonna start to look in your workforce and be like, okay, how do I manage a hybrid human AI agent workforce. Marc Benioff has been very public about this. This is the last generation of CEOs that will ever manage a 100% human workforce. You will have digital labor. So what does that look like when you now, as a public company, everyone else is saying, hey, we're cutting heads because we've applied AI agents across the board and look at all of our efficiencies, look at our profit margin grow, and you're the outlier that's actually adding human labor? You're gonna stick out like a sore thumb. Hedge funds are gonna be like, why is that company actually hiring more headcount? Is hiring headcount gonna become a red flag as a public company? So already, you know, Andy Jassy from Amazon is saying that it's gonna happen. You literally had the CEO of Ford Motor Company saying 50% of all white-collar jobs are gonna go away because of AI.

Hmm.

So we're just at this really precarious point. Where we don't know what's going to happen. It's early innings, but understand that agentic AI is the next wave. It will probably really start to take off in earnest next year. And again, every major big tech company is putting billions and billions of dollars to make agents a thing. So it will happen. The question is if and when, not if, but when. And then how does this radically transform the way the board governs? What are the questions that they need to be asking? And again, can you even do anything in AI when you don't even have your data house in order? So this goes back to how is the board asking the right questions right now? You have a window, you have a moment in time right now as a fiduciary. Get your data house in order. What are the questions that you need to be asking and how do you actually get conversant in this so that you could truly start to not just kind of play defense, but really go on the offense? And understand how you could be leveraging these tools, not in, you know, a bunch of pilots. You know, a friend of mine is a C-suite exec at a major tech company, and he talks about how there's so many pilots up in the air. He says it's like we have the Royal Air Force, you know, like too many pilots. You don't need to have 1,000 pilots.

Mm-hmm.

You need to have the few that are actually gonna move the needle on the business so you could see the business outcomes. Right? So I feel like this is where we're gonna start to move to. We've done with the novelty phase. Now people are trying to figure out, okay, how do I implement this? How does it actually really have business impact and outcomes? And then how does the board really start to not just hold management accountable, but really start to rethink everything when it comes to compensation? Like, are you, as a CEO, you need to be the one driving AI adoption across the org. Does comp now need to change for that CEO? How do you think about the talent that you have? Is everyone conversant? Again, you don't need to be the technical expert. You don't need to be in the weeds and know literally how a neural network is actually architected. That is not the job for everyone. But as a non-technical person, you need to know how this is gonna reshape your business. And I feel like that's, again, the operational AI and the strategic AI.

Yeah, I mean, it's really interesting and I think there's gonna be so much happening at a higher pace When you describe your 3 scenarios, and let's talk about the US capitalism and overdrive gone wild, I do believe in accountability. And this is where at least maybe my lawyer hat comes in and thinking, you know, you can't just do anything and anything for profit and anything that is going to maximize your own personal return, damn everybody else. And I think this is where Uh, the US system will be tested, right? Uh, maybe this is why there is concern about companies leaving Delaware and going to Nevada and Texas. And, you know, how are you going to make sure that you—

But which companies are that? Those are tech companies, right? Yeah. And largely tech companies that are leaving. So I think that's— that bodes a question. Are they leaving because they want the flexibility and the convenience so they could go faster? And then what happens to everyone that doesn't leave or everyone that's playing the traditional rules of the game?

Yeah. And that's scary because you do want to have a certain amount of accountability. And that's the board, right? Like you have to play according to the rules of the game. You know, even if you go Milton Friedman is, you know, it's okay to have profits, but as long as you play along the rules of the game and starting—

But Adam, what if the game has changed and we don't even recognize that it's changed. Literally right now, every single major company is playing by the traditional rules of the game, which was search engine optimization. Guess what? SEO is dead. It is broken. People aren't going to Google to search for something and get 50 answers. They just want one answer. That is answer engine optimization.

So how do you—

So you have no ability to figure out How is your company, if you are, you know, you make the company a retailer, a financial services product, you know, credit card, um, you know, uh, consumer electronics company, how does your brand show up in an answer engine optimization environment, whether it's Claude, ChatGPT, Perplexity, Gemini, Grok? How do you make sure that you don't get 20 answers?

Mm-hmm.

You just get the answer and that my product is the answer.

Mm-hmm.

That is gonna be a huge challenge for companies. And you already see traffic dropping off.

No, I get it. And that is the business side. But I'm putting, let's say, the director hat, right? And you, you're like, okay, the CEO wants to do XYZ and he wants to build and this is going to drive 1,000x whatever returns, but we're going to damn everybody else and we're going to create externalities, negative externalities. And at least you want to make sure that your fiduciary duties are respected. And that is being tested and will be tested in this model where you say, look, the US has to win. And it's like, damn, if we don't do this, the Chinese are going to take over, right? That's been a traditional response to whatever people are doing. And it's interesting because it's capitalism gone rampant. Can we hold that back? And how? To make sure that we're still competing and we don't take over by the other 2. And I think it's going to be really interesting because it puts again at the core what is governance. How do you govern this? How do you govern this, you know, monster growth in a proper way?

And what happens if you're on the opposite side of that growth, if you're on the losing end of it, right? And how do you actually take action? Is it too late? Yeah, you know, do you want to become another Kodak?

You know, well, unfortunately, you know, you know, these are the things.

And again, I don't want to lead with fear because I feel like so many consultants are doing that. I want to lead with options. How do you deal with solutions? And I feel like part of this is understanding, look, my parents taught me you control the controllables, right? And so come back to first principles and first principles of governance, right?

Mm-hmm.

What are you doing to make sure the long-term viability of the company Yeah. And really going back to, okay, in the next 3 to 5 years, how will our company be transformed because of AI? And do all the different stakeholders, right? Because you will have internal and external stakeholders, your employees, your C-suite, your board, your supply partners, right? You know, certainly shareholders, you know, institutional investors. You know, certainly all your different customers and channel partners, like just every single vector of your stakeholder community, how do you really envision it being transformed with this technology?

Mm-hmm.

And I would start there and really have a robust conversation because in the boardroom, you know, if you are meeting every 4 to 6, you know, times a year, whatever it is, again, you have your audit committee meeting and you're literally getting through, you know, 800 pages of an audit presentation, whatever it is, you know, for global companies and all the different divisions. It's, it's complex. And then you're supposed to shoehorn in cyber, which by the way, we haven't even spoke— that's a whole nother pod.

Right.

The amplification of cyber in an AI environment. I don't think people even understand the threats that are gonna be able to come from that. But that's again, a whole nother pod. So what time do you really have to strategically think about the business? Where does that happen? 'Cause it's not gonna happen in the comp. It's definitely not happening in audit. Risk is always going to focus on the downside. And then non-gov, you know, you're really not having that conversation the way that you should.

Mm-hmm.

And so how can you really create the space to really— and, you know, maybe it needs to be some, you know, business transformation or innovation subcommittee. And, you know, you could have it be a subcommittee led by, you know, kind of a 2-in-a-box, a business leader and a technical leader. But I think this is all hands on deck.

Yeah.

And again, I think people have just been getting, you know, kind of accustomed to, you know, the bombardment, all the noise. You read the articles and a lot of scare tactics, and then a lot of pilots. And then my concern is, oh, these pilots aren't working. Oh, these models hallucinate. It's not real. That's my concern, that that becomes the takeaway, as opposed to, no, this is happening. Not a question of if or when, and what are we doing to prepare, and what does good governance in an AI era look like?

So before jumping into the rapid-fire questions, is there any other topic that we haven't talked about that you think is important to highlight for directors on this topic of AI or others that is in your personal radar?

You know, I, I would say the AI noise that people are seeing every single day, how do you kind of strip that onion and get to the core? At the core of this is data. And if we're really being honest, we have been struggling with data for the past 25 years. Every single company that I talk to, undoubtedly they offer up, it almost becomes like a therapy session. My data house is not in order.

Hmm.

I have data over here, I have data over there. I have data, like I have my loyalty card. Like none of this stuff is connected. And so as a director, you know, with our favorite, you know, kind of noses in, fingers out, you gotta put that nose in really far and really sniff out, okay, what does our data infrastructure look like? If there's one key thing that I would implore for every director that's listening, How can you reimagine what your balance sheet looks like? And this intangible asset, which is your data, how does that show up? Do you really understand this is your most important asset, bar none? First-party data. And you need to protect that as if your company's life depends on it, because it does. And my fear is that all the big tech companies come and we make all the same mistakes that we've made for the past 25 years. You know, Google, Meta, Amazon, you name it. Again, all great companies. Salesforce. They're all gonna come. They're gonna be like, hey, give us all your data. We'll make this easy for you. And that scares the bejesus outta me because you need to figure out how to really bring some of these tools in-house? How do you have your own platform? You could leverage certainly one of the large language models to kind of build your own GPT internally, but you need to protect that data. And that is an asset on the balance sheet. And it's probably not connected, it's probably not curated, it's probably not synthesized. And how do you start to play the games that the big tech company players have been doing with synthetic data, which is like a whole nother conversation. But understanding a lot of the tricks of the trade. I mean, do you not remember not too long ago, the only true regulator that Meta has ever had was Apple? And when Apple released that new version of iOS that kind of cut off their access to all of the consumer data, and it was like, oh, um, you now get to opt in if you want to share your data as a consumer with these companies. And most people opted not to.

Hmm.

What happened? Meta figured out a solve, and that was using synthetic data to build out the cohorts and the profiles and all this other great stuff. And those kind of tricks of the trade are used by tech companies. How can we get the non-tech companies to do those kind of things so that you could actually get in the game? Again, that goes back to understanding what questions to ask when you're in the boardroom. But if there's one key takeaway, Your data needs to be viewed as an asset on the balance sheet, and you need to be asking questions about it because that will power your AI future.

All right, love it. Okay, let's move into the rapid-fire questions. What are the one to three books that have greatly influenced your life?

I'll give you three. I will start off with just one of my absolute favorites that was foundational to me growing up: Meditations by Marcus Aurelius. It's a classic, but that becomes kind of. your mindset and just a way to live your life.

Mm-hmm.

Then early on in my career in business, I loved the book Start with Why from Simon Sinek. As an operator, but also as a director, I think it's a really great framework where, you know, you could focus on the what you do, how you do it, but why you do something really matters. And people are gonna care about the why, 'cause that is what's going to move hearts and minds. And so, as a director, kind of think about starting with why as you go on this whole AI journey. Like, really use that high, you know, how and what framework. It could be very powerful. And then a recent favorite book that I recommend to everyone is The Coming Wave by Mustafa Suleyman, which, you know, I have right here behind me. It's a great overview. It kind of puts in perspective a lot of, you know, important themes that have to do with the AI era. And it's It's, you know, great plain English. He's a great storyteller. But I feel like if you wanted one book to kind of really get up to speed on kind of where things are going with AI, that would be a great place to start.

All right, great. Who are your mentors and what did you learn from them?

Oh geez. Again, that's another very long pod, but I feel that I started my career very early in finance and in private equity. There was a gentleman when I was an intern at newly formed private equity firm in 1994 called the Blackstone Group. And my mentor was this guy, Chin Chu. And so he kind of taught me the ropes of finance along with another woman, Viola McCausland, Latina, Colombiana, who was at JPMorgan for many years and then had her own firm. So that's kind of where I learned, I would say, the foundations of business, just, you know, kind of P&L, building financial models. Then I got to work with this incredible technologist and operator, Paul Sagan, who was the, at the time, president of Akamai, but he became CEO of Akamai. He's been on many, many boards. He's on the board of Moderna now, I believe. He was on the board of Dow Jones. You know, I just learned so much from him, and that was a very kind of critical phase of my career in my late 20s when I was at Akamai. But I just learned so much and he's now a general partner at General Catalyst. And then when I was at Publicis, I got to work for David Kenny, who is just genius. He's just brilliant. And he most recently was the CEO, now executive chairman at Nielsen, and he's the lead independent director at Best Buy. But I've learned so much from him. And then I really got to work very closely with this incredible woman, Lisa Hook. Lisa Hook. Who was the CEO of Newstar. She kind of courted me outside of— to leave Oracle to join Newstar as a public company. But I learned so much from her. And, you know, she actually started her career as a corporate lawyer. And she's on many, many boards. She's the lead independent director at Philip Morris. She's on the board of FIS and on the board of Nokia. And again, understanding kind of the needs from the EU and now the EU AI Act and how that impacts, you know, kind of all directors in the EU. You know, just learning a lot from her. All right.

Well, that's a great list. Are there any quotes you think of often or live your life by?

So I grew up as a huge fan of Greco-Roman mythology. I just loved all the, all the stories. And now my son's reading Percy Jackson, so it's a lot of fun. But one of my absolute favorites that I have on my wall is from Epictetus: you become what you give your attention to. And the full quote is, you become what you give your attention to. If you yourself don't choose what thoughts and images you expose yourself to, someone else will, and their motives may not be the highest. So your attention creates reality.

Very appropriate for the AI world that we're living in. What is an unusual habit or absurd thing that you love?

So I don't know if it's an unusual habit because billions of people share it. Around the world, but I am football obsessed. Okay. So soccer for our American friends, but football, the beautiful game. I am a hardcore Arsenal fan in the Premier League and Real Madrid in La Liga in Spain. And my son who's turning 10 this weekend, he is also, you know, an avid footballer. And so I just think that it's an incredible metaphor for life, just understanding How to kind of play on the pitch and really working with a team.

What about Chelsea 3-0 PSG, right? In the final.

You know, I I can't even begin to tell you the astonishment because PSG dominated so much, and then for them to lose to Chelsea. But full disclosure, a dear friend of mine, Jose Feliciano, actually acquired Chelsea from Capital. So kudos to Jose and the team over there for for the win. Yeah, amazing.

All right, final question: Which living person do you most admire?

Oh, wow. That's such a great question. Living person, I mean, obviously a lot of my mentors, uh, you know, my wife who is, uh, just an incredible tour de force. But I'll, I'll give you a name from like a business context. And, you know, if there's an entrepreneur that I truly admire and just kind of the values and the way that they've, um, built something and operated, I'd say it's probably Reid Hoffman.

Hmm. Okay.

I think what Reid has built, LinkedIn, is by far my favorite social platform. But just the way that he's kind of really been outspoken, he's really viewed technology and now specifically AI as a force for good. And he's very, you know, sober about it. He doesn't have kind of rose-tinted glasses. He understands the threats, but he really does view around the ethics, around the ways that technology can improve humanity. He thinks a lot about the human connection, hence, you know, the way that he thought about building LinkedIn. But he's been a real inspiration.

All right. On that note, Steven, thank you so much for your time. This was a great discussion. I feel we just scratched the surface on everything that's going on, but I'm sure directors got a lot out of it. So hopefully I'll see you soon in San Francisco, New York, LA, wherever we end up.

Very much so. Thank you so much, Evan, for what you do.

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