https://www.youtube.com/watch?v=N8q9CNojc8c

Hi everyone, I'm Mandy and I'm the course assistant for Ms. And E472 and I'd like to welcome you to the Entrepreneurial Thought Leaders series presented by the Stanford Technology Ventures Program, the STVP and Bases the the Business association of Stanford Entrepreneurial students. Today I'm delighted to welcome Anna Pinole to etl. Anna is a partner at an effects investing in the AI applications transforming how we work, live and play. She's a former founder and operator with deep experience in marketplaces and AI and one of the current leading experts in AI agents. Anna began her career at Amazon where she helped launch Amazon in Spain in 2013 and and became one of the youngest managers in Europe. After earning her MBA at Stanford and Co founding Jupiter, she joined NFX's investment team. Originally from Barcelona. Her journey as an immigrant founder shapes her belief that building a startup is as much about personal transformation as company success. Thank you so much for being with us today, Anna.

Thank you Mandy. Is this working well? Hi everyone. I just learned this is the last class of the year. What an honor to be here. So who is about to graduate this year? Well, many of you. And who here is thinking of going like starting a company, joining a startup. Okay, anyone thinking of going into vc? Awesome. So there are many possible career paths and thinking what's next is probably top of mind. When I was in your shoes, about to graduate from college in Spain, I didn't even know what VC was. It was literally not a thing at that time there. But like you, I knew I wanted to work on something important, something that I could feel proud of. I wanted to find success and be able to build the life I wanted. Fast forward to today I can say that I personally found in VCE and NFX in particular the perfect match for me. A few months after I joined this job and this team, everything felt so different to anything that I had done before. Suddenly I was in flow. Nothing felt hard, I was obsessed. I just wanted to learn, get better. I found myself working on weekends just because I loved it, not because I had to. And you know, it's very hard to stop someone having fun. So after two years I quickly got good at it and I got promoted to partner at nfx. First time in the history of the fund. For those who don't know, NFX is an early stage VC fund run by ex founders including myself. We've invested in 25 unicorns and we manage 1.6 billion in assets across four funds. And our mission is to be the best partners to founders, from seed to ipo. A work that I feel extremely privileged to be able to do. It took me 15 years to find my calling. Some people find it earlier, but most people never do. Doing work that matters with people you admire while affording the life you want. That's what I want for you. So let's talk about how to get you there. Today I plan to share a little bit about myself and the pivotal moments that shaped my story, which may also apply to yours. I'll talk about how the moment in history in which you graduate influences your career and related to that, where I'm seeing the world going today and some of the things that I'm seeing in AI. I grew up in Barcelona as the oldest of four. My mom comes from a long line of entrepreneurs and my dad started his business out of our apartment when I was a kid. I remember watching him work super long hours. Clients and partners coming in and out of our apartment at all times. Like you all here. I excelled in high school and I got accepted into a select college program in which they were taking 20 people per year and it was known to be a funnel into all these consulting law firms and top banking institutions in Europe. That was the path I was supposed to take at the time and the path that most of my other classmates took. But I went into another direction. I ended up joining a tiny startup and then Amazon in Spain when at the time most people didn't know what Amazon was. It was 2013 and I was part of this team tasked with expanding Amazon in Spain. And I took the only available position that existed at the time for someone my age was which happened to be in sales. The four years I spent there were full of ups and downs and I doubted myself a lot. I watched my classmates fly business class and build all these fancy Excel models where I was literally calling up stores trying to convince them to sell on this website called Amazon. But a few things kept me going. First, I felt that I was living in the future, that I was doing something important. I also looked around and I saw a lot of smart people, people that were incredibly intense and very demanding, but whom I really enjoyed working with and I also enjoyed spending time with. They felt like my kind of people. And finally I had an intuition that sales was a very important skill to master. I wasn't sure it was going to be my thing forever, but I thought it was important and I poured myself into it. After a couple of years, I became one of the youngest people managers in Europe. And at 25 I was leading a team and we accomplished incredible things. So what does it mean for you? What it means is as you start thinking about your career, you should also think about what really matters. And it's not obvious. Always choose curiosity and passion over status and expectations. Joining Amazon at that time was unexpected, but I had a strong intuition and it ended up being one of the best decisions of my life. Know that the people and the network you choose is actually the most important thing. When people think about careers, they usually think about how much I'm going to make, the brand, the role, the skills, and usually they forget about the people. For me, joining Amazon and not Goldman, for example, set me into a completely different direction. It influenced the people I got to meet, my values even, and also the decisions that I've made after. And by the way, for the people dating here, the same thing applies to marriage. This is not romantic, but you're going to join their network and that's going to inevitably impact who you'll become. But marriage is a topic for another day. So back to today. I would say always prioritize learning and strive to be the best at whatever you're doing, even if it's something that you don't think you're going to be doing long term, especially at the beginning of your career. It builds character and your reputation. So it was the reputation I built and the people I met that brought me to Stanford eight years ago today. I actually took this class eight years ago. I was sitting where you're sitting. Growing up, I had never heard of the gsb. None of my family members or friends had taken this path. But back to the people. There were people at Amazon who had in big part, thanks to them, in 2017, I landed on this campus, new to the U.S. fresh off the boat, as they say. Who here is not from the US Originally? Wow. Lots of you. Okay, so you know what I mean. After a period of adaptation, I quickly met my co founders. We got into Y Combinator and I set out to build my company, Jupiter. We graduated as one of the top companies in our batch. We raised from nfx. Where am I today? Then? Khosla. Everything was going great. From the outside, from the inside. After a few years running the company, something wasn't feeling right and it was deeply unsettling. This was what I thought I was supposed to do. I thought it was my destiny, like my dad, my extended family and. But yeah, despite that, I was feeling these doubts. But the fear was too big. So I did what any founder is trying to do. Push harder. I told myself this is supposed to be hard. That's what we're always told, right? I kept trying, but my body kept voting no. I wasn't sleeping well, I lost a lot of weight and I was having trouble with simple things like hanging out with friends. I became a different person. If I was to leave my company, I would risk my visa status and my reputation. Would people think that I was too soft? Or worse, that I was fired from my own company? Eventually, despite all these fears, I opened up to my co founders. We agreed to a five month transition period and terrifyingly, I stepped away with no plan B. Surprisingly, after I made the decision, I felt extreme peace, which then turned into confidence. When your inside voice and your outside actions finally match, there is a magic that happens. You feel a sense of self alignment which shows up as strength and confidence and people take notice. So I jumped into my job search and surprisingly, the people that I had feared that would blacklist me were surprisingly welcoming. In a few months, I had offers from three different VC firms including NFX and you know the rest of the story. That scary choice was the gateway to the work that I love today. It turned out that my mission was not to be a founder myself, but support others in doing so. Others like my dad. As you go about your careers, always have the courage at any time to pivot and rewrite your story. Persistence is a virtue until it's self betrayal. When you act from a place of fear, and you might be doing this today, you're telling yourself subconsciously you are not enough. When you act from a place of alignment, instead you tell yourself, I trust you, you can do hard things and you'll accomplish whatever you want. And you should always change that mindset. Okay, we covered a lot and I hope these stories reflections stay with you as you face important life and career decisions. But I want you to know this is not all. There's another major force that shapes every career and it's completely outside our control. And that's the moment in history in which we're born and we graduate into. Every technology or sector has a limited open window. So if you join the plastics industry between 56 and 73, you are the mover and shaker. A plastics entrepreneur at the time looked like an absolute rockstar because the world was suddenly buying plastics for the first time. By around 78, the industry matured and if you joined, you were joining a slow growing industry where people weren't at the cutting edge anymore. When the demand curve is exploding in a sector, the rising tide leaves Almost everyone who's competent. Once it matures, there's suddenly less career opportunity. You work harder for smaller gains. And this applies to both starting companies in that sector or joining companies in that sector. So when I joined Amazon in 2013, it wasn't the most obvious thing to do in Spain, but the Internet wave was absolutely exploding. People and businesses were moving frantically online. I worked really hard, but to be honest, that wave did 80% of the work. The responsibility and opportunities that I was given at 25 would not have been possible had I joined a more mature industry. And you need to know it always works like that. You need to work hard, you need to have the right mindset, but it's still very important to be at the right place at the right time. I like this analogy. Think of surfing. There's three elements. First, there's the board. This is probably a lot of the things that you are learning here at Stanford. Your hard skills. It might be engineering, math, negotiations, writing. Then there's the surfer. Some of the things I just talked about, your mindset, your frameworks, your attitude, your soft skills. But there's a third element which is very important. You can have the best board in the world, be the best surfer in the world, and still you will go nowhere on a flat ocean. So where am I going with this? The AI wave, of course. And I know you're probably hearing about AI all day, so I'm curious in this room, who's thinking of starting an AI company or joining an AI company? Okay, what about doing something completely different? Cool. So for the most part, we're sold, we're early, we're at the center of it. It's awesome. But is every AI company going to succeed? Absolutely. No. Absolutely not. We've seen this story before. Thousands of Internet companies were started between the 90s and the 2000s. Some of them became monsters. Many went nowhere. My job as a VC is to figure out who's going to lead this AI revolution. I get to meet the best AI founders early, sometimes when there's just an idea or a pitch deck. So I get a front row seat on what's happening in AI today. So I want to share a few observations that will help you navigate what's ahead. First thing to know is some things are harder today than they were 10 years ago. If you join a job today, know that you don't just need to know your function, you'll probably need to know adjacent ones. Marketers who can code engineers who can sell the market rewards, people that can connect the dots. Generalists are winning in this era. And the reason is that a lot of the basic, well defined positions, entry level positions, are shrinking. Some of that work is being automated. Know that the first job you have is probably going to require more breadth, more autonomy and more judgment from day one. So you should get ready for it. There's a big flip side though, which is there has never been a best time for a small smart team to build something massive. For the first time ever, we're seeing teams build unicorn companies. Teams that are like 12 to 20 people build unicorn companies super fast. It's a mix of, obviously the market is buying AI a lot, but also AI is providing huge leverage. It's not just software, it's a teammate. It may be that your first hire is an agent and people are taking advantage of that. There's also a great reset happening in AI in general. Well, a great reset happening, which is no one has 20 years of experience in AI. It's very new. So being early in your careers is a huge advantage. You're learning this from scratch. You are not just unlearning other stuff. Finally, there are many more non traditional paths. Startups used to be a weird thing to do and today they're mass market. I mean, particularly here. But there are many other things. Solopreneurship, people buying old businesses, transforming them, people working on projects on weekends that suddenly become companies. It's a very exciting time. If you go into entrepreneurship though, know that the playbook is changing in real time. The old way used to be you have an idea, you build it, you ship it, you learn, you repeat. If it starts working, you might raise money. You build up the team so you can have more people to build more features. The new way though, it's you think of something on Friday, you build it on the weekend, on Monday you launch and on Wednesday you're already like rethinking it. With the current tools, MVPs take hours. Today instead of months, teams stay lean for longer and features can be built in parallel. This is very new. What it means is that execution risk has gone down a lot. It has become easier than ever to build something impressive. The flip side though, is that it has also become easier to drown in noise. There's a lot of competition today from other startups, but also from incumbents. The incumbents of today are smarter and faster than the ones of prior waves. I'm talking about Google, Meta, OpenAI. They all want to win in AI as well. They have massive distribution and they're smart. So you need to choose a Real problem for real people in a big enough market. In other words, choosing the right idea is paramount. So I'm going to share a few of the thesis that I'm excited about today. I wrote about a few of those. If you want to get the deep dives, you can go on nfx.com but I will boil them down in four big breakthroughs that I think are very important to understand as we get into this new era. The first one is that AI is turning software into labor. A lot of the work that you used to need a human to do, it's now possible to do with a computer. Computers do work. Not only that, they do it at a fraction of the cost, at 100 times the speed, and sometimes with higher quality. Imagine what this means in terms of what you can build, but also what it means for humanity as a whole. As the cost of intelligence and labor goes down close to zero, what are the things that we'll be able to accomplish we cannot even comprehend right now. Another interesting trend is that AI can deliver humanness at scale. What do I mean by humanness? I mean those scarce traits like patience, empathy, the perfect recall, things that we used to think as inherently human. Now they can also be delivered by an AI. And not only that, they, they can be delivered like software. We're turning atoms into bit, and we are able to program, price, and distribute these amazing qualities. Related to that, I'm observing a rise on what I personally call the clone economy. It might sound scary, but it's also very interesting. As AI voice phase models are advancing rapidly, individuals are increasingly able to replicate themselves and scale themselves. Imagine being home, working, I don't know, cooking, while you send your clone to a meeting to represent you. This is very close to be a reality, and yeah, it will bring a lot of transformation. And finally, voice AI is becoming the next interface. The mic is becoming the new mouse. Conversation is how humans are naturally wired to interact with each other. It's humanity's default AI, ui, latency, quality and cost are now enabling computers to keep up and to meet us where we are. We're increasingly going to be able to talk directly to those computers instead of typing on them. So these are four major waves that I think it's very important to keep in mind as you build and think about the world that we're living. If I was to summarize them all in one thing, I would say we are approaching the era of infinite leverage, cost of labor, and intelligence dropping to zero. AI that can think and act, emotional bandwidth suddenly abundant AI that understands us, our presence, being able to be cloned and distributed as if it was software. And finally interfaces as natural as speaking. We're entering a new paradigm of human computer interaction. These are some of the ingredients that you can use to build things that we've never seen before. Personally, I think we live in a very unique moment and we're very lucky to be at the right time, at the right place, and frankly, at the center of it. By being here in Silicon Valley. This is where I'm personally spending my time, my capital, and my curiosity. So if anyone is as excited as I am about these things or building in these areas or similar, please reach out. Let's talk about it. And with that, thank you so much everyone for listening. And now I'm excited to hear your questions. Thank you so much. What was the toughest point as an entrepreneur? What was your darkest hour? And how did you. How did you actually pivot at that point of time? So the question is, what was my darkest moment as an entrepreneur and how I navigated that? So it was a lot of what I shared today, it was like a lot of doubts, feeling. I mean, I think the worst feeling in the world is realizing that you are not doing what you're supposed to do. And then also if you paired it with having done a commitment and having to break it, to be able to honor that voice that is telling you the opposite, that's very hard. So it took me a long time to make that decision and a lot of people helped along the way. But yeah, it was a tough journey to get there. Thank you. You're welcome.

Here is the next. Holaesta.

Hola. Hola. Hola.

I got an MBA from the uem, the University of Barcelona.

Oh, really? Wow.

Like, my question is like, I got like, kind of like same mission like yours. Like, I've been to AM for PhD communication, but my mom got. My mom got lung cancer, so I came back to, to mainland China and I bring something like, I've been educated from taxonomy for business and also for communication. And I want to bring a healthy lifestyle within the marketplace. And now after learning from you about how to leveraging the resources we have as female entrepreneurs here in the states and also to get more resources as female. That's the question.

More resources as female in particular, I'm not sure. I mean, you're obviously studying at Stanford, right? Right now, or Arizona State. Okay, Arizona State. I mean, I think there are a lot of resources. I wouldn't. I mean, a lot of them are dedicated to Female founders. And I'm happy to go back to some resources that I might have and share with you. Yeah, I mean sadly women are still like a small percentage of the founder population, but there's also a lot of efforts trying to promote female entrepreneurship. So I'm happy to share those with you after the talk.

Hi, I'm Dhaval, I'm a computer science alumni here. I wanted to ask, and I work in machine learning AI. I wanted to ask you about. So you are focused on funding AI companies right now and that's the way you see right now for the next few years. But at the same time are you also as a vc looking into the next thing after that, like Quantum or something like that? And the second question I had was about ups and downs. So you said your main ups and downs were when you did the startup and stuff and the transition was a big thing for you. What are some of the ups and downs you went through when you became the vc?

Good question. So these days I'm spending a lot of time just in AI. I think there's also like something to say about being very focused on one thing when you're investing and when I say one thing, AI is so broad, I think it's so hard even to keep up with the pace of changes and everything that's happening. So I'm trying to spend, I would say 80% of my time there. That said, I don't think I would be a good VC in particular early stage VC if I wasn't keeping an eye on what's next. Because a big part of being successful in this job is to be able to spot trends before their consensus. Sometimes people talk about contrarian and non consensus. I think for me, the way I understand it is you have to be pre consensus to be able to do good. Something needs to become consensus at some point, but you need to see it before anyone else. So that's why I'm always like so at nfx we write a lot about our thoughts, our thesis, but at the core we remain very open minded and very driven by what we learn from founders. Because at the end of the day founders are the ones that are on the ground and sometimes they come to us with ideas that you are like, wow, literally this is the first time I hear about this. This makes so much sense. Actually some of the best investments that we've done in application layer AI were investments that we did four years ago. @ the time we were not able to put them on a box of like, oh, this is a vertical AI investment. But it just made sense logically over the years. Suddenly it became a thing. And you were able to place them on this thesis with this in mind. We're always open minded. To be honest, one of the biggest checks for me when I'm evaluating a company or a founder is did I learn something new from my conversation with this person? Do I feel this person is living in the future? It's a high bar because as VCs, we're always talking to people living in the future. But when you suddenly talk to someone and you're like, wow, this person is talking about something completely new, you really need to pay attention. I'm sure in this room there are many people actually fitting that. That said, I still think AI has a lot of potential and we're very early, so there's value in doubling down there. That's what I'm doing. And ups and downs is a vc? Yeah, great question. I always say when I think about the difference between being a founder and being a vc, I always define it as a founder. The highs are higher and the lows are lower. By design, as a vc, some days one company is doing really well. Sorry, one company might be doing bad, but at the same time another might be doing well. So your emotional range is always a little bit more constant. But it's not like, I mean, I love my job and I think it's a great job, not for everyone and we can talk about that, but it's not free of doubts and ups and downs. At the end, we have a huge responsibility to the RLPs that are the people that trust us with their money and sometimes they're organizations that you really want to do well for them. There are institutions like Stanford or NGOs. We have that responsibility. So we need to be very careful with what we do. And we also want our founders to succeed. Not just for the company to do well, but you build a very close relationship with a founder and sometimes the market or something changes and that impacts that founder and it's very hard to navigate, but worth it in my opinion.

Hi, thank you so much for the presentation. Oh, sorry. Thank you so much for the presentation. You mentioned that in each cycle there's, you know, a rise of different startups and then as it matures, some fall off. So some startups are much more generational than others. But then at the same time AI has very different sort of defining characteristics. As you mentioned, there's smarter incumbents, et cetera, besides the typical, like looking at mission aligned founders or even for example My personal thesis is like virtually integrated startups are much more of a stronger moat than horizontally aligned. What are the other factors you believe are unique about the businesses that are being built now that we can think about when we look at what to like, what startup to join so that we can optimize which startups will actually still be at the end of this wave?

Yeah, great question, great question. First of all, I would say I really agree with you. So I'm also spending a lot of time looking at vertical solutions. I think there's a reality which is a lot of the horizontal solutions will probably be owned by the big players. So I think there's a lot of opportunity in going deep in a particular industry and really customize everything to that industry and make the effort to do so, that probably it won't be worth the time of one of these big players and it still will be like a huge thing. Because one thing with AI is that you can maybe in the past you would look at an industry and the time would seem small because at the end there was, I mean, you could just charge a certain amount, but AI is multiplying the value that you're creating for your customers in that industry. So even an industry that is not as big could be a very big opportunity. So I think vertical solutions are more protected in general. That said, something that we always think about when we are looking at these vertical solutions is we want to understand who is the incumbent in that specific vertical. So on one hand you have the general incumbents, which in my opinion are going to own those horizontal applications. But within the verticals there's usually sometimes a pretty big company. Then the question becomes, do we trust this big company to also add AI and thus benefit from distribution? Sometimes the answer is I don't because I think this company is very old, they're going to move very slow. But other times the answer is yes and then it becomes a harder decision to invest in the startup trying to disrupt tax sector. Because at the end it's always a game of what do you think is going to be more likely or faster? The incumbent using their distribution and building AI features or the company that is fast at building features getting to that massive distribution. Incumbents can also use these AI tools. So it's a little tricky sometimes.

Hi, completely agree with what you're talking about in terms of speech to text. Plus the humanness of AI being like a huge unlock that we previously couldn't do for processing qualitative data. My question is if you foresee privacy concerns and trust being a barrier to wide scale consumer adoption of voice, given that it is eliciting more personal data as a result, or if it's just going to be so useful that people aren't going to mind so much.

Great question. I think privacy concerns are going to be a huge challenge and that's one of the reasons why I think this particular area, while having a little bit more of like horizontal characteristics, might actually be a fertile area for startups. But I think it's going to be so hard for a big company to put their feet into something so sensitive. That said, yeah, there are going to be a lot of concerns. I think as we've seen with prior waves, usually utility ends up winning. But I think as a whole, as a society, we're going to have to be responsible and figure out ways to control all this. Actually, the flip side of this global economy, other types of opportunities that I'm looking at is what are the tools to protect us from the misuse of these technologies. We're starting to see very sophisticated hacks today that for example, use voice cloning to call people and try to pretend that they are other person. Creativity from these hackers is very high. So there needs to be another type of industry developed to protect us from that. It's going to be a joint effort of all society on how we deal with these things. I think they're going to bring a lot of good, but as always, there's going to be also downsides. Hi, Anna here.

Hi, thank you so much for coming. I wanted to ask. You were talking about how the playbook for founders is changing and how small team of five people can maybe be profitable over a weekend. And what I was wondering is how do you think it challenges or changes the place of VC in this? And would founders have the same incentives to want to raise money in this world?

Amazing question, Very top of mind. I think. Like to be honest, I think it's increasingly possible to bootstrap your company and do really well. It's fine with me. I think at the end I want great things to be built, but it's increasingly possible. The flip side though is that usually when something works, people notice and people start copying very fast. So this is happening. But at the same time there's also a very high incentives to move very fast and sometimes raising capital is what enables you to do that. So I think they're both things, kind of like coexisting. But yeah, I mean something that I'm wondering lately is like maybe I have less of a belief that VC is going to disappear completely. But what I'm wondering is, is it going to be needed like so much money or companies are going to be able to do much more with less and maybe the rounds. It's not what we're seeing in the market. We're seeing the opposite that we're seeing massive rounds. But the reality is people can do much less today, much more today with less money. Again, it's not showing up on the data, but it's a reality. It's one of the things that we'll figure out over the next few years. But great observation. Hi.

Hi Anna. Thanks for clear perspectives. My name is Shekhar. I wanted your take on the AI in education paradox.

The AI what?

AI in education paradox. Either it can be seen as that the AI is the next wave of tech which will transform it, or it can be seen as yet another technology which will not, which maybe fail because education is already in its optimal mode.

You said the AI education product?

Yeah. AI application in education and learning.

Oh, okay. I mean, when I think about the intersection of AI and education, personally, what I'm most excited about is about this idea of one tutor for one person at the end. One of the most exciting things is how AI changes the unit economics of work. As I shared, if you think about education, it's one of the best examples. I think the way we understand education is usually one teacher for a class of. I'm talking more like a young education, 30 people and same content for people that might be at very different levels or might learn differently. And today we are able to manufacture this education for every person and be super tailored, following their style, following where in the process of learning they are. And we're able to do it at a super low cost. So I think that's very exciting. Yeah. And a lot of solutions are being built.

Thank you.

Hi.

So I see a lot of AI startups building really cool things, but many of them get wiped out overnight when the big doors like OpenAI or Google take out some new feature someone trying to build in this space. How do you decide what's worth investing time in and how do you protect against being outpaced by the foundational model players? Do you go about building a new model or do you just use existing models to create some application in a specific industry? Sort of for an approach to this question.

Yeah. Personally I think that there's much more opportunity on the application layer than in the foundation layer. Obviously there are always exceptions and there are teams that are incredible and can build things and compete. But I Feel like at this point of the cycle, that market has already been said and we already know what are the emerging winners there. I think the biggest opportunity is on the application layer and in bringing your unique insight, or it could be like you have it already or something that you really dedicate yourself to learn to a very niche problem. But that feels niche, but it's actually not that niche. I think it's increasingly common to see these, what we call compound startups. Inevitably, we're going to start. Inevitably. The world in which we just launch one feature and it's massive is a little harder today. So I think founders need to learn about how they pick a wedge into an industry and then what are the next features that they launch to increasingly get deeper in that industry. And, yeah, the more vertical, the more specific, the more protected from the big guys. Yeah. Honestly, this cycle, the last three years, have been pretty disconcerting for VCs as well. I mean, there were so many companies that we got very close to investing. We finally didn't invest, and I was like, oh, we made a huge mistake. But then a year after OpenAI launches something, and you're like, oh, great. I'm glad that you know. So I think, honestly, thinking about incumbents, both these big models and the incumbents on the industry you're looking is key. It's literally like a book check that you need to do. Okay, last question.

Hi, thank you very much, Anna. I think. I hope this is a good one to end on. So from this talk, I know it's been very much about catching the right wave and stuff like that. So I'm interested, what are your thoughts on the AI wave right now? Where do you think we are in IT and where do you think we're going? What do you think the potential Pat's present and future are will be is?

So I think we're very, very early, and it might not feel like that sometimes given where we live. I think if you live in the Bay Area, sometimes you feel like you're late to this, but then you go outside the Bay Area and you're like, wow. I don't want to say people are behind, but definitely they don't see things as clearly as we see when it comes to AI. An example is, I think a few weeks ago, I was talking to an investor that was not in the US and they asked me, so who in your fund is covering AI? And I was like, what do you mean? We're all like, there's no one single expert. We see AI as this kind of Thing across. I see it as who's covering the Internet when we were in the 90s. So first question, I think we're very early where we're going. It's a little hard to say. I think I shared a little bit of the four things that I think are the things that are going to move the needle the most. They're more kind of like high level things on how the world is changing. I think the biggest thing again is we're just all going to have a lot of leverage. So what does this mean once we're all putting out products in the world? I think one big thing maybe I missed is that there's going to be a lot of noise. So whoever can figure out ways to stand out. I think, for example, I'm not seeing so much innovation in marketing or ways to stand out. Everything is feeling very clogged and nothing is new there. So maybe that's an interesting area for you to build. But what I would say is I know I said it's very important to choose the right company and there will be many that won't succeed. Something to add there is that even if you go on an AI company, it ends up not being the one. Just having spent time on AI will give you a lot. A lot of people start businesses that didn't go well but they gained a lot of that expertise and maybe they ended up joining the winner later and doing incredibly well as well. Obviously you try to make the right decision. If you hit it, great. But I think there's going to be also a lot of benefits just by like for spending time in the industry and being like an expert. Like again, there's a lot of opportunity. They are not experts in AI yet and it can be you.

So this is a great note to end on. Thank you so much, Anna, for a fascinating discussion. This is our last class of the quarter and what a great note to end on. Thank you everyone for joining us.

Sam.