Hosted by Christina Ruffini and Sir Richard Dearlove
Guest
Lauren Penneys
Lauren Penneys is Palantir's SVP.
Episode Summary
Is Palantir a sinister surveillance giant — or the gold standard in mission-critical software? In this episode of One Decision, hosts Christina Ruffini and ex-MI6 Chief Sir Richard Dearlove speak with Lauren Penneys, Palantir SVP , to separate fact from fiction. She discusses the firm’s rise from post-9/11 intelligence work to the front lines of Ukraine and Israel, Britain's National Health Service (NHS), and its controversial work with U.S. Customs and Immigration Enforcement (ICE). They also explore Palantir’s wider role in defense, intelligence, and healthcare, and whether artificial intelligence will magnify both the promise — and the risks — of its technology.
Episode produced by Situation Room Studios. Original music composed and produced by Leo Sidran.
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Transcript
COLD OPEN
Penny: No, we are not a data miner. We are not a data broker. We are not scraping the internet. We are not cross pollinating data across organizations. That's not accurate.
INTRODUCTION
Raffini: Hello, and welcome to One Decision. I'm Christina Raffini, joined, of course, by my cohost this week, Sir Richard Dearlove. And in today's episode, we're gonna be talking about Palantir. Yes, that Palantir, the Silicon Valley outlier, data mining behemoth, and conspiracy theorist favorite new boogeyman. So today's guest is Lauren Penny. She's the SVP for all things government, and boy, is that a lot of things. 1,900,000,000 in US contracts since 2008, including about a $30,000,000 deal with ICE that critics argue is helping create an Amazon Prime for deportations. But is that really fair or even accurate? From its deep cut Lord of the Rings inspired names to its newfound association with the Trump administration, we're gonna ask all the questions Reddit and Twitter have been throwing around for a year, plus some ones that, you know, actually took some research. Lauren, thank you so much for joining us. We both really appreciate you coming on today.
Penny: Yeah. I'm happy to be here, and thank you for having me.
INTERVIEW
Dearlove: I retired quite a long time ago in 2004, and the big problem that we faced in the British intelligence and security community was having lots and lots of separate legacy systems. And we thought we needed to get them talking to each other. There's no way that we could see how we were gonna do that. You know, should you dump the whole lot, create one big new system? Obviously, that wasn't practical. And, I mean, I was well aware. I can't remember exact date, but, I mean, I had retired by then that Peter Thiel and Palantir had the probable solution to this problem. And I think I would, you know, ask you whether my understanding is largely correct. What Palantir does brilliantly is you can stick it over the top of all these legacy systems and make them much more intelligent and get them to talk to each other. And, I mean, some of us think this is magic because it didn't think it was possible. And, of course, the worst thing that you want to do is to have a big bang change in the intelligence community and introduce a new system. So what Palantir did, in short, as far as I can see, was solve this extraordinary problem. Am I right?
Penny: I think you explained it quite beautifully, especially in terms of the history of the company. There was a reflection post 9/11. There was a lot of detailed analysis on what could we have learned from this experience, as you know very well. And one of those key issues was how do we make data available of any scale, type, size, while also respecting privacy and civil liberties. And I think to your point, there was, I think, an understanding at the time that that just wasn't possible. And thanks to our founders at that time, it's like, no, we want to take on a challenge of that scale. Right? I think it's also really important to understand how scary that must have been at that time, because there was this understanding that there was this block and it wasn't possible. The things I would maybe add on to what you said are we've evolved a fair amount since then. I think there are a couple of things that continue to serve us well. One is we started in the intelligence community. We started in the most exquisite of problem spaces, and that continues to bear fruit for us, not just in the government space, but across the world in terms of the private sector. I think the next thing that I'm excited to chat with you all about at some point is we've actually now made it such that the software and the ability to work in this kind of beautiful combination of securing your data while being able to operationalize it means that we can bring all of these next generation companies to the government, to some of these problem statements. So there's all sorts of technical ways we support other companies entering. And I think that's also just been the next generation of where we want to go, because as you know, there was a time where there was a major consolidation of government contractors, and I think that basically resulted in a lack of innovation, and we're trying to flip that. So in short, Sir Richard, you explained it beautifully. I would just add on a couple of those recent updates.
Dearlove: We were wandering around in the foothills when I was dealing with this problem, and it sounds to me that, you know, you're looking to scale some of the highest peaks now if you put it in a mountaineering context.
Penny: If it makes you feel any better, I still see green screens. We still see primitive tech. We still see PDFs. I mean, maybe you wouldn't be shocked, but there are still those places, right? Where, you know, there's resistance, but I think it's true that for places where we've been able to work at scale, we're able to just what you said, right? It doesn't mean you have to sunset 50 systems right away. We're able to basically apply that modern technology layer on top of some of these legacy data sets and legacy systems, kind of meet people where they are while not starving, you know, our most important workers, war fighters, public health professionals, etcetera, diplomats, are actually accessing this type of technologies.
Raffini: I do wanna get into the nitty gritty and talk about some specifics about what you've done and where the company's going. But for perspective, I wanna zoom out a little bit because Palantir was kind of a oddball tech company for a while. Until recently, it was, like, not cool in Silicon Valley to have much to do with the government, to wanna work with the government. But the opposite is now true when you're seeing all these tech leaders try really hard to ingratiate themselves to this administration. Tell us how long you've at the company and then kind of the evolution of the unsexy tech company to this kind of behemoth that now has its own conspiracy threads on Reddit, which is something you must just be so proud of.
Penny: Well, as a tired mom, I don't go deep in the Reddit threads. Have to admit. Yes, we were deeply uncool. We were contrarian and I think we still continue to be in our approach to the world, but it is incredible to see the success. I mean, you know, I've been at the company a bit over eleven years. So when I joined, first of all, no one could pronounce Palantir. No one had a clue what it meant. That was very common. When we started, there were, I think a few things that were not maybe widely held. There was no concept of defense tech as a big Silicon Valley thing. There are things that I think still hold true, I would highlight, are one, we've always, always been in support of the West. We've always been in support of The US and its allies, always. Day one, right? Started in the intelligence community. We then branched out into Department of War, federal law enforcement. This is where we actually learned. This is where we worked with users. It's the heart and soul, right? It's the heartbeat of our company, even as our commercial sector grows. I think the other thing that comes up a fair amount, and I would still say is very, very important today, is, you know, it's not an organization, nor is it a technology that shies away from complicated and complex environments, whether that's technical, right? Whether you're trying to collaborate cross network, cross country, cross organization, these are complicated technical problems all the way through just kind of like state of the world. I think the third thing, Shyam, our CTO, calls it an artist colony, and I think it's true. This is an artist colony that we operate with extreme urgency. Think to the extent we talk about some of the organizations we partner with and how we start working with them, it's often because they're in crisis, right? Something horrific has happened. An agent was killed. The pandemic hits. There's no room for error. And I think that kind of orientation of like, we're waking up in a fight. We're not here just to make money. That's just the spirit of how we operate. And I actually think it's almost like inextricably linked to how the software works. If that makes any sense. I still think all of that is true today. Of course, the scale with which we operate, the number of users who actually log into Palantir to do their job is many, many, many X'd over. Our voice, you know, carries a different weight. Right? All of that is true. But the approach to the world, I think, is still somewhat the same.
Dearlove: I don't think there's a company that I can think of in the West that's had a bigger and more positive impact on national security. Because, you know, what you've done is pull together the diversity and complexity of a modern democratic security structure and make it, let's say, fully adapt it to the world of data in a way that no one else has seemed to have had the conceptual approach. I mean, I'm not aware of any other company that's done this in the same space to the same extent. So you really changed the life of organizations like GCHQ, NSA, in particular, the big data collectors. But I mean, also the operational intelligence and security services. I'm not trying to flatter you, but it seems to me that, you know, the reputation you've earned, the sinister reputation is completely misplaced because people don't really understand what the achievements of Palantir are.
Penny: Thank you for sharing that perspective. There are a couple of reflections maybe I would say about your comment. I mean, one is, part of it is the nature of the work that we do can't be shared in detail. Right? I think the second element about this is it's hard unless you've operated in these environments to understand how difficult it is. We're deployed all over the world and we support the US government, every combatant command, military service, the State Department, diplomats, even think about public health has a global orientation. So, you know, our software is deployed around the world. Think, Sir Richard, one of the things too, that's really important is it's just speed to action, right? It's like, yes, we've continued to learn in the most complicated of spaces. So not to use space so many times, but think about things like space warfare, right? That's a very complicated technical problem. There are latency questions. There are security questions. There's hardware, software questions. I mean, are very, very complicated spaces that we operate in. If you think about recent operations in The Middle East, as an example, the software has to work. It can't go down. It can't stop working. It has to work in multiple networks. Thousands and thousands of people have to hit it. We, Palantir, have to be at the ready to support. All of that comes into play. I think one other kind of newer and important angle is actually how we're leveraging large language models and AI from this foundational layer that we've built. That's, I think, the next wave of us as a company and, you know, many, many parts of the missions we work on. So I think being able to actually take that secure infrastructure that we've created and apply best in class, diversified large language models, but actually bringing a security framework and a kind of human understanding of the data. We call it an ontology, which I'm happy to talk about, but that layer is what actually makes all of these next generation AI capabilities useful.
Raffini: I think the thing that's interesting, I mean, Sir Richard, if you come at it from like an intel perspective, Lauren, obviously it's your company. It is an incredibly useful tool. One of the big misconceptions seems to be that you are mining the data yourself. Is that accurate? Are you out like scrolling people's Facebooks?
Penny: It's funny, Christina, you had said data miner and I was waiting to correct you. So thank you for letting me correct the record. No, we are not a data miner. We are not a data broker. We are not scraping the internet. We are not cross pollinating data across organizations. That's not accurate. We're a commercial software company and organization that lets organizations essentially analyze, ingest, and leverage their data and the data that they have access to per their kind of data sharing agreements. So that's what the organization does.
Raffini: That's a myth that is that's just not accurate. But the interesting thing about the name, and I did check with my hyper nerd Lord of the Rings brother, who was on a train, but sent me several voice memos, several more than I really needed to know about Lord of the Rings. And now he's watching Lord of the Rings, but we'll move on from that. You know, the Palantir is this thing that you can look through, and it shows you what you need to see on the other side of the world or through time or all these other things. It's an incredibly useful tool. But like any incredibly useful tool, it can be used incorrectly. And even in the story, the Palantir is misused by one of the hobbits, and he looks into it and they get in trouble. And I think that is people's big concern is it is a tool, but it is also as evil or potentially good as the people or the governments using it. Right?
Penny: I mean, yes and no. Here's where I would kind of elaborate on what you said. Yes, that is the tale of Palantir, the Seeing Stones. I think it does speak to, we are operating in the world and that is a complicated space, right? Whether that's working with Department of Homeland Security, whether that's working with public health crises, whether that's, you know, kind of war fighter forward missions, right? These are not uncomplicated missions. We all acknowledge that. I think the thing that we do that's so important that I think Sir Richard hit on is actually the security kind of infrastructure and the privacy and civil liberties orientation that enables being able to audit everything that's happening. Being able to understand and trust the data that's coming in. Where is it coming from? How has it been altered or adjusted? Being able to govern who gets to see what, when, where, why. They're not just concepts. They exist in the thousands of users that are logging in every day and collaborating every day, cross nation, cross organization, per the agreements of the government. That creates a level of, I think, I mean, the crass way of saying it is, if I were a criminal, if I were doing something, why would I be passing something on a piece of paper versus, you know, the most exquisite software? Our software has actually codified all of the things you need in order to feel comfortable that we're, you know, adhering to rule of law and that you're adhering to the policy and doctrine of that place. That's what the software does. That's what we've spent billions of dollars building. And that doesn't mean there aren't bad actors in the world. That doesn't mean we're not operating complicated spaces, but I just think it's something that's lost in that argument, if that makes sense.
Dearlove: Well, I'm just intrigued by what you're saying about the legal framework and the legal context. Because of course, what, you know, the man in the street doesn't necessarily understand, certainly about The UK, and I'm reasonably familiar with The States, is the importance of the legal structures that surround the activities of, let's say, secret organizations operating in democracies in order to respect the rights of the individual. But there's no question what Palantir is doing. It's not doing it itself, but it's enhancing the horsepower of the organizations which are, as it were, working in a security context. And, I mean, I'm assuming you must have a phalanx of lawyers, a large legal counsel department who are making sure that, you know, you're on the right side of that Chinese wall.
Penny: Yes. There's another organization that we have that I think is quite unique. We have a privacy and civil liberties organization that's basically made up of not just legal minds, but academic minds and engineers. Because I think the distinction I would make is we operate in the substance of the thing, not the perception of the thing. And what's the substance of the thing? For us, that's data. That's users. That's what are they doing on an hourly basis, right? That's living, going from primitive tech, PDFs, imagery that a human clicks through, you know, all day. Can you imagine a place historically, right? When we were capturing satellite imagery, you had humans looking at the imagery every day, just thousands and thousands and thousands of images. I've done it. Yeah. That can't be the way we fight. Right? It just can't. And so yes, of course we have to be cognizant of privacy and civil liberties. I think it is worth noting, Sir Richard, I know you know this very, very well, but there are all sorts of legal agreements that essentially dictate what can be shared when, whether it's MOUs to data sharing agreements. We're very, very familiar with them. I think the thing that often folks ask is, you know, give me confidence that you can actually take that agreement and make it real when I unleash this technology to the entire organization. I think that stress testing is real and mission critical for us. I think as we bring in things like, you know, large language models, some of the same policies and questions come up.
Raffini: Do you have legal limits? Because I know you have international clients. I was actually reading about how your current CEO, Alex Karp, flew to Ukraine at the start of the war and offered this to Zelensky, and it's been helping with targeting and drones. And we've talked constantly on this podcast about how technology has helped Ukraine in that war. He also went to Israel and offered it to the Israelis. That kind of led me to two questions. Is there a policy for what clients, what foreign clients, what agencies you offer your systems to, or is it just kind of a gut check how leadership wants to go in that moment? And then is there anything that allows you to pull back those tools if you feel they are being misused by any of those clients?
Penny: We should start by saying I'm not a lawyer myself. So, you know, what I can say is that every single relationship we enter into is evaluated at the C suite level at the highest levels of our company. That's piece number one. I would say element number two is it's not even just about the customer, let's say, right? Just to reiterate, we really look at the data, the users, all of the specifics around that requirement. And I think that's really, really important. The final thing I would say, and, you know, again, not a lawyer, but at least in the federal space, of course, we have optionality to constantly reengage and reevaluate contractually. Of course, we do. That exists. And I think it's kind of a side pivot. One of the things I was reflecting on lately is I actually think in The US, this new drive towards efficiency and cost effectiveness has actually done the same on behalf of our government partners. In the past, it was, I think this concept of like, once you start working with the government, you know, you're never going to be fired. You're going to work there for fifty years, three generations later, that kind of a thing. The, you know, what's the saying, the road goes on forever and the party never ends. That kind of concept. There's been a major, major shakeup of late in terms of not just even at a substance level, like, are you delivering impact to the world? Have you hit your milestones? Why are you 50% over cost? Right? So I think it's been an interesting flip. Our government partners are actually now looking to us and looking to other companies and saying, you know, are you hitting the mark? I think that's refreshing and a good thing. But yes, we have all sorts of ways to both reinvestigate our scope of work and to, of course, exit relationships should that be, you know, the decision. Are there customers you've said no to? Are there agencies you've declined to work with? Oh, sure. A couple of places where we've either de-invested or kind of like aren't prioritizing at the moment. We have not prioritized investing at the state and local level. Those are very complicated places in terms of mission impact. It's also, you know, different scale. So that's been a place where we've worked in the past there and have, you know, said this isn't the place for us at the moment. Inside the federal space, there are moments where we say no. The flavor of that falls into a couple of categories. And one flavor of that is, especially as we've gotten bigger, a lot of people ask, how have we grown? Mostly it's through referral and people move around and say, you really need to look at this company that shows up day one. The other version is the version I shared, right? Crisis moments, aviation safety, the pandemic, major operations, agents being killed, you know, major crisis moments.
Raffini: And you guys really got a boost during the pandemic, right? Because that was data that you were able to sort through and sift through and kind of get faster than anybody else. That's the first time I really remember seeing your name and hearing about the company.
Penny: It's around the era when we went public, so that's also probably why. I just will make one adjustment to the language, which is the government or the users are the experts inside our customer base or our partner base. So in that instance, it's not Palantir, you know, hand jamming, doing the analysis. It's actually enabling all of the epidemiologists in that case or public health workers to do their job better. And I think that distinction is super important because that's actually one, how the software learns and gets how we learn, how we are constantly upgrading and adding capability. And two, that's why I think we've become the company we've become, because we're not sitting in a separate building doing the work for you like a consultant. So it just would make that change. I think the pandemic work is a really good example that we can speak to where it involves coordination across every state, local, tribal nation, cross government agencies, cross country. This is also obviously sensitive data. You're having to make all sorts of decisions, right? Where to move things around, hospital capacity, how to report at a very senior leader level, all the way down to the specific decisions, working with the private sector. So you can just imagine how complicated a problem like that is, and that's where we thrive in that kind of high use, high mission, multi party engagement, so to speak.
Dearlove: One of the areas I understand where you will have or are beginning to have a terrific impact in The UK is in the National Health Service because, you know, there, you have this massive disintegration of IT systems which have not been speaking to each other. And at the same time, I mean, what intrigues me, you know, with this opportunity, not only can you solve a lot of these problems, but on the other hand, I'd like to understand more about the empowerment that AI gives to Palantir. I mean, the two must be advancing on a parallel course, and it must be a bit like having rocket boosters on the back of your company, the speed at which AI is advancing. And I'm intrigued to know what your strategy is in relation to, as it were, pulling these two together. Because, I mean, for example, if that works as it should, let's take diagnosis of the National Health Service. AI has already proved it can do it a hell of a lot better than the human being in many, many cases, not every case. So take that and take you. You'll be able to aggregate using your technology, more health statistics from Britain's National Health Service. It will become a powerhouse of medical knowledge in my view or it could.
Penny: Yes. I agree with where you're going. I would add that just to maybe kind of make it a real world. What does that look like? There are a couple of things that are really important about when you leverage AI in that context. Like one of our biggest relationships is with the army, and we've helped the army really think about readiness. So let's just use examples, right? I need to know who's ready to deploy that speaks Korean, that has this set of expertise, and I need to know it now. And then I need to understand if there are gaps in readiness, why? Right? Is it because someone forgot to go to the dentist? That's easy to fix. Is it something more extreme? These are the kinds of questions you can imagine how hard they would be in a crisis if it was driven by PowerPoints and legacy systems. But now you get to a place where you can actually answer that. It's secure. And to the extent you want to leverage best in class AI capabilities, you can do that. The thing that's really important as the first order thing, let's say, what language do you speak or how many dependents do you have? In the past, that might actually be, go see row 17 and 3Q means two kids. No one can understand that, neither can AI. Our first step, the kind of secret sauce is this concept we call the ontology, but think about it as like providing meaning to all of that very hard to understand, but very important information. And then you can leverage large language models or other types of kind of exquisite AI tooling, that's super underappreciated.
Dearlove: Given, you know, the importance of this company and the way that it's positioned itself governmentally, one of the things that concerns me, and I mean, you may not want to say too much about this, but, for example, your intellectual property must be a massive interest to the Russians and the Chinese. So you almost need, you know, a sort of protective organization. I mean, in a way, you're rather like an intelligence and security organization where they have to spend an awful lot of time and energy and talent as it were protecting themselves against predation or penetration, to put it not too lightly. But I'm just assuming you have to conceptualize the company in this manner.
Penny: I think that's spot on. The way we think about operational security, information security, OPSEC, InfoSec, etcetera. You know, I would argue we have the best in the world in terms of constantly thinking about that. And I think Christina, to your point, we're also an organization that has, I think you've seen it, right? There have been protests. There have been people who are trying to learn about the company, misinformation, you know, that's a real thing for us, especially as we get larger and larger. I will say we have the most incredible team that thinks about how we secure facilities, how we think about our space, the data, our people. I can't get into the detail of it to your point, but I will say it's not lost on us.
Raffini: Well, that's reassuring. I do wanna ask you because you are the big honcho for US clients and some of these big contracts. You talked earlier about how you operate in the substance versus kind of the perception world, but you just talked about as the company's getting bigger, that is something you have to consider more and think about. And I'm wondering how that works and how that folds into your contracts with ICE. Obviously you've got this $30,000,000 contract. I think there's more than that's going into it over the long term. How do you approach that contract? Do you see any problems with how your programs are being used there? Do you plan to continue that partnership?
Penny: Yeah. I mean, a couple of things to highlight about the work with ICE, Immigration Customs Enforcement, which is a part of Department of Homeland Security that I think again are maybe buried in the media or not always raised, you know. So one is we started working with ICE under the Obama era. The software has been leveraged by agents, analysts, and employees there for some time. It's been focused on HSI. So HSI is obviously a subcomponent of ICE and their mission is transnational crime. So think like human trafficking, drug trafficking type work. We actually began our work with ICE because two agents were killed and there was an immediate need for an investigation at the largest scale. And again, in a moment like that, you don't want to be with Post-its and PDFs, right? You want to be able to understand your state of play and do it securely. We actually installed the software basically over the weekend and kind of were able to help support that again, kind of moment one. We've continued to support ICE since then. And I think again, this is about what does it mean to have an effective institution that isn't spending 80% of its time fat fingering or working off of poor data. This is about empowering those thousands of individuals to do their job in a better way, and we've continued to support them.
Raffini: But when you have like the ICE director coming out and saying things like, we want to create an Amazon Prime for deportation, and your company is so closely associated with that agency, does that sometimes create a problem? And how do you navigate things like that? If your argument is we're helping people do the best version of their job and the best version of their job maybe isn't happening, what do you do about that?
Penny: We're a company of thousands of people, right? So we don't shy away from debate and discussion inside the company. I think that's like really important to note because people have questions they want to understand. We need to debate the pros and cons of working generally, right? Not just with that part of the government, but in all sorts of contexts, right? Whether again, these could be kill chain contexts or public health contexts or immigration and securing the border context, right? Like we encourage debate internally to the company. We actually embed our privacy and civil liberties teams into the way we operate, into the account teams to make sure that we are adhering to the spirit of the contract, the way the software is set up, all of the principles I've already talked about, being able to audit the data, govern the data. We have three levels of access control. So who can see what, when, where, why? This is what the software does. We continue to work with DHS, as you know, that says something, right? I think, Sir Richard, you said it. We get tested in all sorts of environments. Right? Like, does the thing work?
Dearlove: Can I ask you a question of principle in relation to intelligence work? I mean, if you take, like, counterterrorism, it's very microcosmic. You can use massive resources just to chase down and neutralize, let's say, very, very small groups of people. But on the other hand, you have got these big national issues, let's say, war fighting where you're in an environment which is strategically massive. It seems to me that Palantir, rather extraordinarily, can do both. You can apply it efficiently to both situations. I mean, is it better at one than the other? For example, if you take the sort of 9/11 context and the follow-up to 9/11, which was, you know, personally, I experienced and was very microcosmic, very resource expensive because you're using massive resources to chase down, let's say, one person, Bin Laden.
Raffini: Wait. Did you kill Bin Laden, by the way?
Penny: Of course, I can't comment on that.
Raffini: Okay. Just checking. For our listeners who may not be familiar, there is a strong sense that Palantir was involved in helping find Bin Laden.
Penny: I will say again, it's the software, not the humans. Correct.
Dearlove: No. But I'm just saying, is it better at the really, really big stuff, or is it better at the microcosmic stuff? Because it's pretty extraordinary to have a software which spreads across this very interrelated but complex area of work.
Penny: I've never been asked a question like that. So part of what Palantir does really well or what it enables in a really interesting way. I'm sure you're familiar with something called suspicious activity reports. This is the reporting that happens across the financial services community on certain things, right? If somebody's going to bank to bank to submit $9,999 one might think that something is going on. So you think about these suspicious activity reports as an example, right? And we are producing a massive scale of that information, right? There's the needle in the haystack concept. There's the lead generation concept. Like, how do I take all of that and then understand, you know, what should I actually be paying attention to? And how do I incorporate human expertise into that? That's one of the things that I think the software is very well suited for. It's not just the, hey, I've got an individual point of interest or some sort of seed, and I want to work that way, but also the kind of top down of like, hey, I'm getting these kind of important streams and I need to be able to sift through them and find what's going to be important to whatever my job is. It really can handle both. Where we've learned is, for example, kind of like data that's coming in at such a scale, like kind of streaming data. Think about space as an area, right? The number of satellites, the proliferation of data there. What does that look like? How do you bring what a human can do when you have data at that scale and you have to make a decision that quickly? That's actually a new era for us, I would say. The time to make a decision is also a really important factor. You know, do I have to make a decision in a day? Do I have to make a decision in a moment? And how do you do that quickly? I mean, I'm excited by those types of problems because I think they're the extreme versions of challenge, right? You've got data scale, you have time to decision, you have security at scale. I think those places are really cool, so to speak.
Raffini: All right, Lauren, we really appreciate it. It was just absolutely fascinating.
Penny: Thank you, Christina.
Raffini: That's it for this week's episode of One Decision and another special thanks to our guest, Lauren Penny. One Decision is headed to Warsaw, Poland next week. We're an official media partner of the Warsaw Security Forum and we're gonna be talking to all kinds of world leaders. We're gonna have exclusive interviews, live streaming discussions, and all kinds of content. So please stay tuned to the feed and also follow our channels on social and our YouTube and stay tuned for special announcements. We'll see you there. I'm Christina Raffini. Thanks for listening.
