Debbie:
[0:00] Welcome to Skin in The Game with Debbie Go, the show where we go beyond the success stories to explore the real decision, risk, and values behind leadership.

Debbie:
[0:11] Today, I'm joined by Anupriya Ramraj, CEO and co-founder of Vaultzy Inc., where she's building AI-powered technology to help individuals and families securely access the records they need when life gets complicated. Anu brings more than 25 years of experience leading cloud, data, and AI transformation at companies including HP, Unisys, DXC Technology, and PwC. She's also the co-author with her daughter Avanti of When AI Robots Knock, exploring how AI is reshaping work across industries and generations. Today, we're going to talk about what happens when technology becomes deeply personal, when it touches identity, health care, family, work, and the moments in life when people are most vulnerable. Anu, welcome to Skin in the Game. It's wonderful to have you here.

Anupriya:
[1:14] Thank you, Debbie. I'm super excited to be part of your podcast, Skin in The Game. And it's amazing what you're doing here, talking to founders around the globe. So super excited and thank you for the opportunity.

Debbie:
[1:28] Love to have you here. Anu, you've spent more than 25 years leading cloud data and AI transformation. Now you're founding Vaultzy. So looking back, when did technology stop being just about business results and become something more deeply personal for you?

Anupriya:
[1:47] Debbie, the two of us met as part of Stanford's Graduate School of Business's LEAD program. And I think one of the questions that LEAD actually... Pushed us to ask is, what problem is really worth solving? That was the whole core behind design thinking, for example. For about two decades of my career, I had corporate roles, global leadership roles. I was advising Fortune 500 companies modernize billions of dollars of technology through their cloud and then their AI transformations. And then I heard the story of foster kids. This was brought to me by California state leadership around how they have several programs for foster kids in the U.S. Here and how these foster kids sometimes go from one home to one home just with a pillowcase of their belongings. And even though there's been several government programs to help them get to college, a very small portion of these foster kids, less than 10 percent, go on to actually graduate from college. And then when we looked at the problems that these kids were facing, it really became evident that.

Anupriya:
[3:01] Having documentation, having the, think about birth certificates, immunization records, think about all the things that you need to go enroll in a school or a college, for example, or to get your first job. And having access to that and then having the guidance around that to say what to do when, that is so important, right? Like we all take that for granted. And so these foster kids didn't have it. And that's what got me thinking. And then I realized this problem is even broader. The people that lose all of their identity and documents and wildfires to when people are facing medical emergencies and don't have access to documentation.

Anupriya:
[3:40] So that's when I realized that, OK, this is the one that I wanted to tackle. And the timing was right. Technologies like Agent TKI and blockchain maturing to bring it together in Wallzee. And I know like Singapore already has solutions like SyncPass, other countries do. And sometimes you have to learn from the globe. And that was part of the Stanford LEAD program that we went to as well, Debbie, to bring it all together into Wallzee.

Debbie:
[4:06] That's a great insight, Anu. Was there a moment when you thought, oh, this is bigger than technology because it affects people's lives?

Debbie:
[4:14] And when did you realize you had real skin in the game?

Anupriya:
[4:18] That is such a profound question, Debbie, and there's so many stories around this, right? And we ran a pilot with a school here that is called Miracle University, and they helped dropout kids. And looking at what these kids were doing with this technology, we realized then, God, there's real skin in the game here because what we bring to them makes a difference between whether these kids go down a life or it's these dropout kids in the U.S. Especially there's what's known as the prison pipeline because they don't get the educational skills. They don't get the jobs. And then these other kids then get into trouble and land up in prison. So it's called the prison pipeline. And here by giving them the right guidance, by making sure that they had the right reminders, the right coaching on what to apply, when to apply with all the documentation, I realized that was real skin in the name. That was real impact. And then the other side of it is like, this data is so valuable and the folks trust us with it. So there's also skin in the game from our side to make sure that we really secure that data as well.

Debbie:
[5:30] Because Vaultzy is addressing a problem many of us don't think about until something goes wrong. And we know that life can change in an instant, like you said, when you lose your identity or perhaps like a flood, a medical emergency, or suddenly needing a proof of who you are. Can you share a moment when you've seen or experienced where having or not having

Debbie:
[5:54] an important record made a real difference in someone's life?

Anupriya:
[5:57] This one is a little bit of a sad story, Debbie, and it happens way too often with the wildfires we've been seeing here in California. So this happened in the Paradise Fire. The town is called Paradise, and it is the most beautiful town on the banks of a lake. But they had a very, very destructive wildfire. And so many folks lost their homes, and unfortunately, some of them lost their lives as well, fleeing this fire. This particular town was so constructed such that there was only one escape route out of that town. And so a lot of the people were stuck and had to leave so quickly and had to leave all of their stuff behind. So I was speaking to one of the survivors and she mentioned, I just didn't lose my home. She was super grateful that nobody in her family had lost their lives. But what she was saying is that I just didn't lose my home. I lost proof that, my home and even me ever existed.

Anupriya:
[6:59] That was a very profound statement when I replayed it back because she left in such a hurry other than like her driver's license. She literally had nothing with her and she had to rebuild everything back from start. Luckily, she had some online information and then quickly was able to reconstruct portions of it back. But it took a while to replace, right? Don't think about what certificate. So that's when I realized like what this could be.

Anupriya:
[7:28] That brought home the significance of this problem for me.

Debbie:
[7:32] That really gets to the heart of Vaultzy. On the surface, it seems like a technology platform, but underneath, there's much more human problem. So at Vaultzy, you're building a secure AI-powered digital vault so individuals and families can safely store, access, and share the most important records anytime, anywhere. You touched upon it earlier, but maybe you can flesh out the human problem you're trying to solve.

Anupriya:
[8:00] Absolutely, Debbie. There's access to your most vital documents, and these could be your identity documents, your medical, your legal, your financial. But it goes beyond just access, right? What we're really trying to solve with the use of Agentic AI is just have a trusted life assistant. All of us could use that. And it could be simple things that this life assistant, could help us and remind us with. For example, things like, hey, Anu, your passport is expiring and you travel internationally and you need to renew it six months before. Right. Like I've missed that before. So things like that. Or it could be something, more involved like, Anu, you're about 50 and you're supposed to do a mammogram. And by looking at your medical records, I don't see you've done one in the last two years. So everybody needs a life assistant. And because Vaultzy, knows about the person and where they are in life, what milestones they are working towards, whether it is getting a college degree or whether it is graduating or buying a house or staying healthy, it is able to coach you and serve as that assistant. So I think that is the biggest life problem that we are trying to solve here. My husband calls it the nag, right? I like to call it the friendly assistant or mentor.

Debbie:
[9:21] I would love to have that.

Anupriya:
[9:23] Yeah. Everybody needs a nag to keep us on track.

Anupriya::
[9:28] Another problem that's related is the fact that because of AI, Debbie, there's also the thing that people are losing trust in identity. It's so hard to prove identity and establish trusted documentation because I can take your degree certificate and I can replace my name on your degree certificate saying I went to the same university as you did, Debbie, I did not. And it takes me literally 30 seconds on my favorite LLM tool. So then how do you trust these? Documents, right? The other problem that we're trying to solve is bringing in blockchain so that when documentation is anchored to blockchain, because somebody issued a document and we immediately put it on blockchain and anybody can verify that it was issued on this date by this person. Or if somebody notarizes the document, we put that on blockchain and then people can say, others can verify that the notary has verified this document. So we're trying to bring in trust in there as well. So we're trying to solve the challenge of the documents, also make sure they are trusted, and make sure that we have that nag or assistant helping people.

Debbie:
[10:34] I love the fact that you can actually authenticate the document through blockchain. I have instances where I have a lot of documents in different places. So having that prompt every now and then, especially when your driver's license is up for renewals, is really great. And what have the people using Vaultzy taught you about trust, vulnerability, and the responsibility that comes with handling something so personal.

Anupriya:
[11:01] That is so fundamental to what we are building here, because people are putting a lot of trust in the system by uploading their documents. And so we really have to earn their trust and keep their trust, right? So which involves multiple aspects. One is making sure that the user data, we guarantee that the user's data is their data and nobody else's unless they explicitly share, The platform has ways of sharing the data with trusted people for different purposes, for purposes of the application, for example. Unless they do that or they name a delegate that can come in and access the data, we do not sell or share the data with anybody. That is so fundamental to establish trust. And the second aspect of it is data security, right? So we bring in the best-in-breed cloud security guardrails, and we're going through audits right now. we'll go through periodic audits to make sure that we are compliant with all the security standards, NIST, SOC, HIPAA. HIPAA is the U.S. healthcare privacy standard, so that we can really hold this, really ensure that we serve as that trustworthy platform for individuals. And we take that really seriously.

Debbie:
[12:21] Building and using AI responsibly is very important. You mentioned earlier about foster youth and people facing disaster. So through Volsi's work with foster youth, perhaps seniors or disaster survivors, maybe people facing housing instability, what have you learned about dignity and agency? And what does it mean to give someone back a little bit of control when so much of their life may feel uncertain at that moment in time?

Anupriya:
[12:50] Debbie, at Vaultzy, we are very mission-driven and definitely we believe that restoring the documents is restoring dignity. Access to documents is fundamental to have human dignity. And one story, especially near and dear to my heart, and this is with homeless populations in the U.S., they are often subject to police sweeps because there are certain locations where the homeless can, stay, some locations they cannot. And when those happen, they lose all of their documentation. So fundamentally, the homeless are already on the streets, and now their identity and documentation is also more at risk than all of the others, right? We've found ways to get these folks onboarded onto Walsy so that we can restore some semblance of dignity. Sometimes when they need to seek legal help, because some of those folks need that for pending cases, etc., that is so important to have all their documentation, prior legal paperwork, etc.

Anupriya:
[13:50] So yes, as in this case, human dignity is so much tied to your identity or digital documents as well.

Debbie:
[14:00] You've also written about how AI can improve healthcare. There's a lot of excitement and a lot of hype around AI in medicine right now. What's one application you've seen that you believe is genuinely improving patient care? And why do you think it stands out for you?

Anupriya:
[14:20] My daughter Avanti and me, we interviewed experts around the globe as we wrote our book, When AI Robots Knock. And healthcare was one of the industry is that we really dived into. I think we had four expert interviews for that particular chapter alone. Because there were so many diverse perspectives we wanted to bring in. And what was interesting to observe is that this industry is probably the one that is going to go through the most transformation because there's such a need for that.

Anupriya:
[14:50] Medical expertise, right? There are parts of the world where still people travel several hundred miles to just get to a healthcare professional, right? So just think about that and think about how maybe an AI primary care physician might be able to at least do a first level of triage and really bring medicine out there for all of those folks. So I think that is going to be fundamentally a big step forward across the globe, especially in parts of the globe where the access to healthcare is limited.

Anupriya:
[15:26] Here in the U.S., one of the struggles that many physicians have, and my sister is a surgeon, Debbie, and when she comes home after having a hard day of doing multiple hours of surgery, then there's so much paperwork to catch up on. She's putting in notes about what patients she saw, what did she speak to them about. They had to manually put all of that into the systems, even though those systems were online. But now with AI coming in, we've had these, especially with generative AI, it's making a huge difference. These patient-doctor conversations can now be transcribed. There's also ways to input them into the system. So literally the doctors can like one click just approve all of them, right? So what this does, I believe, is it fundamentally makes the doctors spend more time with their patients rather than with the systems capturing the data. I think it really improves that patient and doctor relationships further as well. So we're already seeing that, the effects of that with the AI. There's multiple technologies out there where AI can transcribe and input it directly into the systems. And that is one that I'm really pleased to see the progress there.

Debbie:
[16:38] Because it frees up the admin work from the doctor and actually improve a patient's experience.

Anupriya:
[16:43] Absolutely.

Debbie:
[16:44] I'm curious, when you're building AI for sensitive areas like healthcare or personal records, what are the guardrails you believe have to be there from day one? And just as important, who needs to be part of that conversation when you're building that?

Anupriya:
[17:01] This is so fundamental, Debbie, but I have to put that out there, is that there's got to be a human in the loop.

Anupriya:
[17:08] And this is so important from multiple aspects, including who is ultimately accountable, right? Because especially when it comes to industries like healthcare, it could be a life or death kind of a decision there. Let's take, for example, like we're getting pretty close to medical decision-making systems, right? So these systems are able to analyze vast amounts of data, look at the patient's symptoms, look at the patient's medical record, the past history, look at the lab results, look at imaging, and even recommend certain things. But I firmly believe that what the agents and the systems can do should always be overseen by humans, especially when it comes to medical decision-making. Humans have to always be in the control and be the final decision-makers in there. So I think that is like the number one core principle. And then the second biggest thing for me is that every recommendation should be explainable, right? We need to be able to stay accountable to decisions being made. Imagine a CEO going into a board meeting and saying, the AI agent made all the wrong decisions, so we've been not treating our patients correctly or not making the right insurance decisions or whatever, right? So you cannot blame AI. Every recommendation should be explainable. So the humans have to be in control and everything that was done by AI has to be explainable. Not the least is that...

Anupriya:
[18:38] There should not be any kind of a bias, like unconscious bias creeps into the system. It could be because of the data that I was trained on, right? And so we got to make sure that biases don't creep into the system and cloud everything that's going on in terms of the decision-making.

Debbie:
[18:55] So one is humans should be in the loop. Second is the conclusion needs to be explainable. And the third is there should be no bias introduced into the system.

Debbie:
[19:07] I think those are great guardrails. Many senior leaders are trying to move from what you might call random acts of digitization to a more focused AI strategy. So what are the two or three questions you ask to tell whether an AI project is actually creating value or is mostly hype?

Anupriya:
[19:27] It's a great question, And Debbie, I think the way you called it is absolutely right, random acts of digitization, especially as I was advising fortune finder companies with their AI strategy. In my prior roles, we saw a lot of that happened. So November 2022 is when Generative AI, starting with ChatGPT, came on the scene. And then what happened is that all the C-suite was under pressure. They were all under pressure to basically say, hey, what are you doing with AI? And sometimes even their annual reports had to have whole sections around what they were doing with AI. Otherwise, the company was getting dinged. And so what happened was that led to pressure from the top for everybody to do something with AI. And rather than have a coherent AI strategy, these random acts of digitization, as you rightfully call them, started happening. The wrong way to do it is, I would say, people tend to create like a backlog, which is perfectly fine. You do need those backlogs, right? So they tend to create a backlog. And I've helped advise many companies to do that. They go from division to division to see what are the pain points and how do we put them together, right? And this creates like a huge backlog for what do we want to solve with AI. But when it actually comes to picking what you want to solve from the backlog.

Anupriya:
[20:49] That's when I think, to your point, then the right decisions have to be made so that you don't end up with these random acts of digitization. And some of the cardrails would be asking fundamental questions around, is this something that will genuinely solve the problem or make a big impact, right? So rather than just doing something to do that AI checkbox, is this really going to make a big impact from a business perspective. It could be from an employee experience perspective. It could even be an efficiency perspective. But is that really going to make a big impact? And what is it? Making sure that you really understand the impact, right? We worked with a couple of drug discovery companies. And for them, it was about things like, will this make my clinical trials go faster? Yes, that's a big impact. And then walking backwards from there. So sometimes you even want to codify what's the impact that you want to make. Before you pick out what you want to do from your backlog, so get that straight first.

Anupriya:
[21:46] And I think the second big one is people are used to doing like the cost-benefit analysis, Debbie. You've seen that like in your senior leadership roles. People always say, okay, what's the cost of doing it? What's the budget you need? And then tell me the benefits. And then they'll put those two together, weigh them up and say whether this project gets funded or not. Especially when it comes to AI, there's a third vector in there, which is the risk factor. And it's more than the risk. It's about asking a fundamental thing about, should this always be done by humans or do we really want some aspects of this to be done by the machine? And you have to ask that question. And if it is done by the machine, what are the risks that you have to watch out for? And making sure you are looking at it from that cost-benefit and then AI risk vector so it becomes a three-pronged analysis, not just a cost-benefit analysis is so important. So definitely think about the big picture impact. And as you pointed out, don't do those random acts of digitization.

Debbie:
[22:45] There has to be a cohesive strategy behind that decision, as you said.

Anupriya:
[22:50] Right. Yeah. What do you really want to get at, right?

Debbie:
[22:53] Now, that brings me naturally to your book, When AI Robots Knock, which brings us much closer to home. When you wrote that book with your daughter, Avanti, that grew out of your late night conversations around the kitchen table. Take us back to one of those nights. What were you talking about when you both realized that this needs to become a book?

Anupriya:
[23:20] Debbie, this is very near and dear to my heart because a huge shift is happening in the industry around what we used to call the lower rungs of the career ladder. Typically, students would graduate from a bachelor's degree, for example, and they would join in these junior positions that would be doing a lot of data analytics, for example, or a lot of even some of this could even be termed busy work. But that is what gave those starters, students, fresh early career people, the first start in different careers, whether it was the legal field doing initial research. Whether it was in the medical field, assisting another doctor with research, et cetera, et cetera. So what we're finding out is that those early career rungs are changing, are going away, right? Because those are the ones that are getting replaced by those AI agents. My daughter and me were talking about how every industry out there is fundamentally going to change. So not only are those lower career runs going away, every industry that people and every job that people are targeting is going to look very different. In the case of my daughter, she aspires to be a lawyer someday. And we were like, OK, but the legal field is not going to look the same.

Anupriya:
[24:36] You might have a really hard time finding your first job because all of that legal research can now be done by some of the AI tooling that's emerging to do the legal research and even do a first draft of the cases. Right. There are definitely going to be lawyers, but maybe that you don't need so many junior lawyers to do the research. As we talked about that, then we realized the folks in college that are making their decisions, especially the earlier career folks, which want to decide which industry to go to, they need to have a picture of where these industries are going and how is AI going to change and what skills do they need to acquire to be successful in each one of those industries. So that's what prompted us to say, OK, let's pay it forward. We've got access to some experts. Let's go talk to them and then figure out what's changing in those industries. And we were really pleased that we became like an Amazon bestseller and career guidance because we really wanted this to be a career guidance book.

Debbie:
[25:27] I find it interesting because the book doesn't just bring two writers together. You and Avanti were bringing two generations into that same conversation about AI work and future. So for the book, you interviewed leaders across health care, law, finance, government, such a huge cybersecurity, education, arts, technology. After hearing all those different perspectives, what stood out to you most?

Debbie:
[25:55] And where do you think we still misunderstand what the future of work is going to look like?

Anupriya:
[26:00] There's a couple of big standouts there. And it's surprising that there was so many similarities across these different industries that you listed. And some of those commonalities and standouts with the fact that we are all learning that because of AI, things are going to change so fast that learning cannot be front loaded across any of the professions. Like the pace of change is going to be even more rapid, which means the people that are going to be more successful are the ones that are lifelong learners, right? So the way you do stuff is going to change. Some of the experts in our book gave us examples like the telephone operators, Debbie. Like in those days, they had a whole class of slew of people that used to be telephone operators and manually connect the calls and then electronic exchanges came and those vanished. There will be things like that, like there'll be entire disruptions where certain job classes would go away. But there will also be places where certain things will just morph and people have to keep on learning. Even for people in IT, like if you were to stick to just handwriting every piece of code, every line of code, you're not going to be as successful as the folks that are able to do the prompts and use wipe coding to generate the code. You just have to accept the fact that it is going to be more efficient to be a wipe coder. But you still have to understand the coding fundamentals, but you have to also learn the new technology around wipe coding, right? So that was one thing about the learning cannot be front loaded and people have to keep adapting. Yeah.

Anupriya:
[27:26] And I think another big takeaway was that, again, we were looking at this, as you pointed out, from an intergenerational lens, right? Like my daughter and me are 30 years apart.

Anupriya:
[27:36] I had been through a corporate career. She was coming in as a student trying to decide where she wants to go, what career she wants to pursue. So very different lenses. But I think the interesting angle there is that everybody pointed out, like, don't undervalue the human premium, right? Like we all get like really worried about like AI is taking over my job. Humans will have no value, but there is a human premium. And the easiest way to explain that is like as humans, there's always a trust factor in working with humans, right? Debbie, I think when we call a customer service and we get a robot answering us, we always want to find a button that will take us to the human, right? Whether it's a zero or a nine, we're always like, okay, what is the button that will get me to the human fastest, right? Because we value that human connection. And so I think some of our experts call it the human premium now. They actually say like AI will become like the lowest common denominator and the services that include the humans would be sold at a premium. So the human premium. So that was an interesting aspect. And that's going to be in every industry.

Debbie:
[28:39] Right. I have several, like, for example, when I get automated calls, it's like, oh, my God, bring me to a human. As you said, I want to talk to a human.

Anupriya:
[28:49] Exactly.

Debbie:
[28:50] The book also tackles some difficult questions around AI, like bias, governance, job disruption, and who benefits from these technologies. What was the hardest topic for you and Avanti to write about together in this book?

Anupriya:
[29:06] I think one of the toughest things is there is like two kind of forks. Emerging. Two schools of thought that are emerging. One is the utopian view, which says that AI is going to be fantastic, just like the industrial revolution made it better for humans, right? People had really terrible working conditions. And then after the industrial revolution, we had more mechanical automation. And so people had more free time. You had the Monday to Friday work week, you had weekends off. So it actually made life better, like more services, jobs, et cetera, right? So the utopian view is that AI is now going to remove, just like the industry, the machines, the industrial revolution took out some of the ratchety about labor. Similarly, AI is going to remove that ratchety and everybody's going to be in a better place. You're going to have more time to spend with human connection, your hobbies, et cetera. The dystopian view is that AI is going to go rogue, right? You had people talk about wars being fought with AI.

Anupriya:
[30:16] More lethal weapons that are made with the AI, lethal robots, lack of privacy with government spying on their people with AI equipment and name it, right? Like biased decisions with AI. So the dystopian view is we are going into chaos, but the machines will take over. We will have AI, AGI, superhuman intelligence, and then the bots will rule us. But when we wrote the book, we consciously said, we're going to lean towards the utopian side. We will recognize the risks. We will not downplay the risks, but we do not want to go towards the dystopian side. We debated it between ourselves, but we strongly believe that the future is in our hands as long as we put the right guardrails. And I think the regulation is lagging, Debbie, but it will get there, right? And I believe with the right guardrails, we can avoid the dystopian view.

Debbie:
[31:08] AI can help us be more productive as long as we have guardrails to safeguard the negative side of AI. Okay.

Debbie:
[31:18] You're also active, Anu, in communities, including Women in AI Networks, Lisa at Stanford GSB, and you've recently presented at Stanford Lead Me2We conference in 2026. Looking back, what kinds of support have made the biggest difference in your journey as a woman founder and leader in AI?

Anupriya:
[31:41] Debbie, I owe you a big thanks. You were one of the big organizers for Stanford Lead Me2We this year and made that possible. So thank you for all your efforts to pull it together and giving me that opportunity to speak as well. And as you pointed out, especially as a women founder, the statistic out there is that only 2% of women founders, all women teams, founding teams get funded, even in this day and age.

Anupriya:
[32:08] It's less than 2%. right so that's a big ouch right we are living yeah in this century to have a statistic that is so poor in terms of women founders getting funded so I think it's going to take some concerted efforts across so many different avenues to kind of change the needle and make it go positive and what I'm pleased to see is several organizations stepping up to support women founders There's an organization called Echo Her that is specifically focused on women founders, women in data, women in, there is how women invest. There's a couple of VC firms that are stepping up. There's one called Netri that they're saying we will invest in women founders. So I think this is very welcome because that statistic needs to change. And then at the other angle, just putting on my utopian AI hat on is that hopefully AI also helps us avoid that bias because many times VCs have a gut reaction to say, hey, I'm comfortable with just supporting one kind of founding teams, right? And now we can use AI to analyze it better and then maybe make a more informed decision and maybe that will benefit the women founders and we'll have less bias. That's my hope.

Debbie:
[33:27] Collectively, we have the power to change it.

Anupriya:
[33:30] Absolutely.

Debbie:
[33:32] And when we talk about changing the future, I think there's also a question about where AI education begins. It doesn't have to just start in the boardroom or the classroom. It can also start at home. Between Vaultzy and when AI robots knock, you're thinking about AI not just for enterprises, but for families and young people navigating their careers. So what does meaningful AI literacy actually look like at home? And what should parents and young people be talking about now?

Anupriya:
[34:07] I think it goes back to what we were talking about, right? The pace of change is so rapid, Debbie, that people have to be lifelong learners. And so acquiring these AI skills is so critical, right? AI literacy is so critical, right? And it's as basic as knowing prompt engineering, for example, because that becomes so fundamental to how you get so many things done, even coding, et cetera. So AI literacy, prompt engineering, knowing what's emerging in terms of AI tooling out there is also fundamental. And then also keeping a look out on the longer horizon, right? Especially as the younger people choose careers. This is what we were tempted to do in the book is just look out for how your different fields, different industries are morphing and then be ready for that change, right? Because there's going to be new opportunities as well, right? You're going to have chief AI officers that are going to be needed. You're going to need AI prompt engineers. You're going to need folks that do more vibe coding. So like AI is also going to create opportunities. And so I think being ready, getting that literacy and having those conversations as you pick your careers is so important.

Debbie:
[35:19] AI is moving so quickly that maybe a lot of people, even working in technology, can sometimes feel overwhelmed. For our listeners who want to become more informed and confident about AI over maybe the next six months, what are the three practical things you would encourage them to do? And as AI becomes a bigger part of our work, our lives, how can you also help them make smarter, safer choices about when and how to use it, both at work and at work?

Anupriya:
[35:52] I would say don't wait. I would make that the primary advice, Debbie. I think you asked me for three pieces of advice, but don't wait, right? Get started now. It is so important to experiment and learn and just keep going. I would say the most fundamental thing is get started right now. Don't wait. Go get those AI skills. Be more literate. Understand what's happening in those industries. That's the most fundamental thing. And like we talked about, you have to be lifelong learners and start it now. Number two is the fact that not only do you pick up those skills, you also have to know about the risks. Right. I mean, so many people take their most personal information and put it on a public LLM and that's just not kosher. Right. So that is something that they have to do. Be very conscious of understanding the risks. Just like if you're using social media, you have to understand the risks. If you're using AI, it's even more important you understand the risks. I think that number three, since you asked me for three things, is that always have a positive attitude around it. Like we talked about the utopian and the dystopian view, but it has never been a better time to be an entrepreneur, for example, because you can do so much with AI agents, right? Debbie, I think we were discussing some ideas before our call around. People can get started so easily because they don't need a big coding team. They don't need a big go-to-market team. So what are you waiting for? Go get it, right? So that would be the third thing I'll leave you with.

Debbie:
[37:19] Thank you. That was Anupriya Ramraj on Skin in The game. Anu, thank you so much. Not just for sharing your expertise today, but for sharing your personal experience and convictions behind the work that you're doing with Vaultzy and also when AI robots knock.

Anupriya:
[37:34] Thank you so much, Debbie, for having me in Skin in The Game podcast. And I am so grateful and I've just truly enjoyed this conversation with you. Thank you so much.

Debbie:
[37:44] So if this conversation resonated with you, share it with someone who's thinking about AI, leadership or the future of work. And until next time, I'm Debbie Go. Keep putting something real on the line for what matters.