President Ahmed Al-Sharaa on Syria’s next chapter

And that is where I think the leadership challenge is, is creating enough agency that people can help shape transformation. (upbeat music) - Hey everybody, welcome to Catalyst, the launch by NCT Data Podcast. I'm your host, Tammy Soars. At launch we get to work with some of the most incredible companies and organizations to create digital products and experiences that improve lives, solve problems, and make a difference. But our show isn't about what we do, it's about people. The leaders who are making it happen and shaping the future. So each week I dig deep to find out what makes them tick, what drives and motivates them, and of course what they're most excited about right now in the world of technology. Joining me today is Deepesh Chandra, the senior vice president and chief digital and information officer Amanafiori Einstein, one of New York's most premier and mission-driven health systems. Deepesh has spent over 20 years in the healthcare and technology world, with stops at McKinsey, Mount Sinai, and Bonsa Core, Mercy Health. I've been really excited for this conversation because of the passion Deepesh has, when he talks about the work that he does, everything his team does is aimed at helping people at their most vulnerable moments and leveraging technology to improve healthcare for patients, consumers, and communities. So Deepesh, thank you so much for joining me on Catalyst today. How are you doing? - I'm doing quite well, Tammy. Thank you for having me here. - Absolutely, so let's start with your story. Tell us a little bit about who you are and how you got to where you are today. - I started my career believing that technology was primarily an engineering problem. But over time, I learned that the hardest problem are rarely technical in nature. They're often very organizational where incentives and cultures and decision making and how we spend money on technology matter more. And more so, people who are involved in that process matter the most. So this has been an incredible journey for me and healthcare from being focused on the most core engineering problem in terms of how technology drive day-to-day healthcare to now coming to a point where the job is not to run about technology, but it is to help the institution navigate the consequential changes that technology is bringing. And I am always very, very excited to help my team to help my organization in making the best out of technology. - Early on, you would say? You made that realization? - Yeah, very early on. In fact, my first job as an intern, I was placed at a cancer center hospital with a company that was deploying an electronic medical record. And I learned very first hand the human nature and adopting technology. As we were changing the system, it was going from an MS-DOS-based application to a more Windows-based application. And it involved using mouse in addition to a keyboard. And it was a brand new interface. The monitors were going from black and white to colored screen and all those kind of changes for an everyday user was a big leap. How they interacted with machine, how they interacted with software was a massive change management. So while there was an interesting engineering problem to solve to create these large electronic medical record, there was a human side of it. And working on that project taught me so much about change management in technology that I carry those lessons even today. - So your background is engineering. Was there anything that you did early on in an education perspective around the human and the human side of things? Or was that just developed over time as you rolled out more and more of these kinds of transformational applications and things? - So my education background was largely engineering-driven and computer science and engineering, how to build applications and systems that are more scalable in nature. And that was core of my study. But as my interest evolved and as I saw the interaction between the system and human and change management, I picked up a lot of learning both going back to the college, picking up some certificates, going into some training programs, or even just speaking to experts throughout my career as I have seen technology evolve and it's an option involved. And that has allowed me to understand the human center design part of it, how the interface needs to be built, but also how the system needs to build and how it needs to respond to how human wants the machine to work. So it has been a deep curiosity for me for several years and I continue to re-treat that as artificial intelligence is becoming a new reality for us. - How do you think about leadership? Because like I said, I think that, especially on the engineering or more technology side, sometimes it is a little bit more difficult to put the people front and center. So how do you think about that from a leadership perspective as your leading teams who maybe don't think about it the same way that you do? - Leadership to me belongs in, I would say two or three dimensions. One aspect is definitely helping the organization achieve its mission, achieve its goal. And if technology has to play a very big role in it, we have to make sure as a leader, we are setting the right strategy, we're giving them the right direction, especially when there is an advent of a very new technology that comes into our ecosystem. Because if you get it wrong, the damages are consequentially nature. The organization may get left behind from there here or they may completely bet on a wrong thing that may be quite expensive for them down the line to change. And so there is an element of leadership that is just associated to an organization and what do you do to help them. But then there is a very critical part of leading the team and the people to whom you are leader too. And for them, there is an extreme amount of clarity around what is our strategy where we would want to collectively go. And at the same time, where we should apply all our human workforce toward achieving the ambition of the organization, what are the right bets we need to make? And how do we need to take care of each other during that process? Because the best output that I believe are generated from high performing team and the high performing teams are the ones that have solved the aspect of how to work together and how to work with their leader to their advantage to achieving those ambitions together. - I would love to hear from you about high performing teams before AI and high performing teams after AI. I mean, I've certainly seen a change in the way that people collaborate, I've seen people use AI potentially to replace someone that's on their team that they used to work with before. So I'm just curious about how are you seeing how high performance teams are working through the current world and landscape that we're all living through? - I think the core tenets of a high performance team hasn't really changed just because we have a new technology in the mix. One of the biggest component of a high performance team that I have picked up has been around trust, the trust that people have in their leader and the leaders have in their people. And if that trust is not well established, it's not that well understood. I think the team cannot make one plus one equal to three. And a very big part of that challenge is if you're constantly judging, if someone is equally committed to your team, if you're constantly judging that if the individuals on your team are up to the mark or not, if you're constantly judging the work output of those individuals and you're not giving them a constructive feedback, those are all our elements that don't allow the multiplying effect of that team to come together. So to me, trust is the biggest part of it. I've seen teams with far less technical capabilities be able to move massive change management through an organization while I have seen high performance individuals with a very, very strong IQ but their EQs are not matching to each other and they just don't work. So to me, that is the core tenet of a high performance team. - What do you think shape that point of view? Is it experience? Is it just something that you and Aitli know? - It would be definitely an opportunity to work together through different scenarios. It is just one of those aspects of human experience that you cannot fast track. You cannot instantaneously trust someone on Devon. You do have to go to battles together. You do have to solve critical client problems together. You do have to be in the trenches when you had to stack hand and trust each other to get something done. I think those experiences do build over a period of time and this is one of those things that you just have to force yourself to work together to build that comfort. - I love that. I mean, I think that trust and building in psychological safety for people to work in an environment that allows them to bring their full selves. and create space to build that trust is really incredible. You know, when you look at Montefiori Einstein's mission to heal and teach, discover, and advance the health of the communities it serves, and it goes back more than I think 125 years. What does it mean to lead technology transformation inside an organization with that kind of history and community trust? The mission of the organization has stood decades if not over a century, and I don't think that any new wave of technology is going to change that mission. I think technology is a means to an end, and in the last 30, 40, 50 years, it has become a critical part of how do we deliver to that mission. And so like other services across our health system that are constantly working towards the same mission, technology is one of those. So I don't think of technology as a standout. I just see that as another force that you use to your benefit to deliver that mission. And to me, having that mission alignment is really important. My team has hundreds of people who have worked their entire career at Montefiori. They work in New York, they have choice to go work with any other health system. They are technologists, which means that their skills are equally applicable to finance and retail and media and every other industry that exists in New York. Their skills are transferable, yet they choose to work at Montefiori's time. And so to me, that is a grounding thing that there are people who simply just want to work for this organization and the foundation for which this organization stands for is the reason why they want to belong here. And so to me, that is just our not-stop. So very mission-driven people I would have to imagine. I mean, I think it makes work so much better when you believe the things that you're doing are making an impact or a change in someone's life. And I would have to imagine that healthcare is one of those places where it's a make or break for people. You're seeing people in their most vulnerable situations in their lives for themselves or for their families. So I could imagine how that can bleed through into the work culture and the environment that you're working in, which is really incredible. When you think about technology, you've said technology can't occur in silos that patients are key stakeholders. What does it look like when you involve patients and clinicians from day one? So those are the humans that you're building the technology for. One sort of receives the experience, one is using the experience to deliver. How do you do that? How do you bring them in? How do you make sure that they stay front and center? I think a core tenet of leading anything related to a human center technology doesn't mean that we preserve the work and the workflow as it is and just simply introduce technology in the middle of the current situation. Sometimes the most human centered thing is for us to think about how do we redesign the workflow entirely. One of the core tenets that we have seen and observe is we have to start with where the human constraint is and not where the technology capability is. Often people think that here's a technology. Here's what is capable of and let's force this technology on to people. We saw this with the internet where we saw this with mobile resolution, we saw this with social media and we are seeing that now with AI as well. We know what the potential is and we just want to begin to quote and quote sell them into our user base and that to me is always the challenge. If we flip the equation and we said that here's where our workflows are constrained, here's where our patients are finding friction with the system. Here's where the clinicians are getting burnt out by administrative burden and if we identify those choke points, those friction points, then we can reverse track what are the technology solutions that are available to us today in that current capability that can help solve those problems and that just changes how we approach technology, how do we bring them in and how do we bring the stakeholder in solving that problem together. Do you run into any issues or concerns in your past where you've brought that point of view and it's been met with resistance and you've had to overcome it? I think we would be surprised if there was no resistance to the idea that we brought to the table. I think resistance is a start to the conversation, to a collective problem solving together and arriving to a conclusion. To me, someone's opinion is not a resistance. It is that they have a point of view because they are living in day in day out and they may have a counterpoint to my one-dimensional thinking about a solution and as technologist as engineers, we often think about a solution in somewhat of a unique dimensional way. Sometimes we fail to understand that what the implication of this technology could be, what the implication could be to their change management, to their day-to-day job, to their own livelihood and other aspects. There are cross-gating impacts of bringing in this level of change in any situation. Hearing those opinions, those counterbalances, those counterpoints allows us an opportunity to sit down and find what would work and maybe there is an opportunity to create a version two, a version three, a version four of that solution and to me that is the right way to do it. I recently was working with a client who we were helping to reimagine an end-to-end vendor operating model and what I loved about the client was we didn't start with how can technology improve this operating model, how can it make things faster, what can we automate and it started with this is an old model, we need to create the model for the future and I bring it up because we did our normal design process of stakeholder interviews across all the touch points, what's the current process, what are the current friction points in the process and brought it all together for this group that was cross-functional from legal, HR procurement, finance, all the different parts of the IT organization and just watching humans behave on day one where they're defending the friction point they're responsible for potentially the policy they have or the tool they've put in place or the reporting mechanism and so this just speaks to your resistance idea right the very first day there's a little bit of defensiveness people are explaining why that exists, why we still have to have it and then as you continue to move towards what's possible that defensiveness goes down and then by the end of day two you've got the same person who was defending this piece very adamantly completely on the team that reimagined it and what's possible and so it is really incredible to see it's like natural what you just described as sort of natural human behavior of I'm coming at it from my point of view and if you create space for them to hear other points of views you can start building upon the ideas and then you created something it's gonna work for more than just the one user group or that's gonna work for more than just one department or function and it's just really incredible to see that happen and it's almost every time like you can pick whether it's a new digital product or are coming up with something completely different you just get people coming at it from their worldview and their mindset and then over time you can watch that shift. I recently heard on a podcast that how human beings are the most adaptable creatures on earth it is the reason why we are who we are is because we have adapted to all the changing conditions of the planet yet when we talk about change management and we talk about change being done in the moment we are the most resisting ones and so that that paradox of us just as a human being is just fascinating to hear but we do adopt with time it's just what's required there is time and sometimes that's what we need to keep in mind. There's an agency component as well if I think about the person who was resisting on day one if she hadn't been in the room for day one and day two and by the end of day two was part of the idea if that would have just been handed to her it would have been weeks or months of resistant no this isn't gonna work no it's not possible I'm not going to adopt it but I think by bringing her into the process it I think it sped up the change management piece it's the adoption piece because she was a part of making sure that this future solution met the previous needs and understood how it was arrived to was a part of it and we're publishing some research here pretty quick at our event that's coming up in November called nexus we've funded some proprietary research on the humans as we think about all the AI around them and one of the things that came out of it that was super interesting was that there's a direct correlation between the more agency someone has in defining what happens next what their role becomes what judgment they need to retain in their role where they want to keep creativity where their craft lies if they're a part of decision deciding that, then the adoption around that tool goes up dramatically. And it seems so obvious, but it's true. So I think there's a component of that as well. Are we handing someone a reimagined workflow that they've not been a part of or no one or their team's been a part of? Or have we brought them into the reimagination? Hi, Agria. I think your observation around when people generally resist transformation that is done to them far more than the transformation that has been designed with them. But at the same time, to your point about agency, transformation just cannot become consensus driven. It's just way too many voices. And that's where agency matters. I think this is where leadership still has to choose a direction. They still have to put their weight around. This is the direction we as an organization has to go. And that is where I think the leadership challenge is, is creating enough agency that people can help shape the transformation. While maintaining enough conviction that we are actually transforming and everyone's voices are being heard, but that is where your agency concept is so, so important, at least on large moves that we have to do as an organization. You just recently published on your sub-stack an article about human and the loop and human loop not being a control. I read it and it was just, it was really fascinating to me. So do you want to kind of describe it to the audience and then we can dig into it a little bit? Yes, I have been interviewing a lot of people to understand what is the role that the human plays when AI can begin to do very high speed transactions faster than human can do. And we have been hearing all the terms, autonomous agents can do this, can do that. And that is all great, but that is where the governance question comes in. And often we hear the term human in the loop. It is like if I'm driving an autonomous car that can sell drive, but I'm still a driver sitting on my seat holding the steering wheel and just watching so that the car doesn't make a mistake and I can take over in the moment. And there are a lot of research being published around these autonomous systems. They're having the human in the loop doesn't help the benefit of safety. And sometimes that safety is merely an illusion point being in an autonomous driving. If the driver who is sitting simply putting their hand on this steering wheel, if they cannot respond in the same moment as fast as AI can, they won't be able to save an accident. And there are more and more research coming in from autonomous vehicle and what VEMO has been doing versus Uber has done and other companies have done is to understand really putting human in the loop. What does it do? And so in my conversation with a lot of folks, that's where I have been trying to draw some conclusion is where does it make sense to keep human in the loop? And one of the drawing conclusions that I've been hearing more and more is the aspect of when the cost of being wrong is too high, human always has to remain in the loop. Use cases like healthcare and making care decision always, always has to have a human judgment involved. I don't think so. We as a society will in near term be ready when AI can make healthcare related decision by itself. However, there are use cases that are in banking and in retail and many others where we can allow to a good extent AI to make autonomous decision. And I quoted an example on credit card fraud where AI can detect and it can decline a transaction. And the cost of being wrong is fairly lower. It is inconvenience to the consumer. However, it is very easy to fix and recover from that. And so that becomes a very critical part of where that needs to be. The other research around all of this is as well is if simply placing a human in the loop involves someone to just constantly click an approved button almost without giving it a second thought, that doesn't help in so many ways. And so that has been putting some perspective together on where we are as technologists, as society. And as these systems are becoming more autonomous, does human in the loop really make sense for us in certain workflows versus the others? I was at a conference last week and we decided to start calling it human in control instead of human in the loop. I sort of have that vision and picture in my mind as well as the person who's just sitting there going, green, approve, approve, approve versus really being accountable and responsible and using human judgment around what's being needed. There's a risk component, like you said. I also think that there's a brand differentiation component. So you could choose to keep a human more involved at a critical moment because it's going to drive growth or it's an opportunity to increase customer satisfaction. So there's also a way to differentiate your brand in the future by keeping humans to engage with other humans in moments where that's going to drive a material impact either to your customer or to your organization around that growth metric. And I think we've spent a lot of time over the last couple of years talking about productivity and efficiency and automation. And I'm starting to see the conversation start to shift more towards growth and brand and differentiation and the other kinds of value that it can bring to an organization, which is exciting. And I think that is where the question about whether AI is delivering a value or not comes into the mix, whether it is truly working or not comes in question. - I'm frequently in conversations where people will talk about how important it is to retain human judgment and human creativity and empathy. But they have a very difficult time in saying how they're going to do that. And I think it's something you said in your article about how you're engineering mindset. You will ask how or an engineering mindset will ask how until there's a plan for how it's to be built. And I really love that because if you can't describe within your own industry, not you, but the audience as a whole, what the human judgment is that is critical in that moment and what does it drive? It's gonna be very difficult for you to design the technology that keeps humans in the loop delivering that bit of judgment. - It comes back to the question of trust. What AI has to do today to have you trust it? And the only way you can arrive to those is to understand some of those how question, how are you doing it? What is the governance? Walk me through it. What happens when something goes wrong? Where is the accountability? How we will recover from all these things? And that is all the core tenets of building a trust with a new system that is very nascent and scary and revolutionary in so many ways. So the gap that we have, which we always present that as a governance is actually a question of trust. And while it will take time for us to trust it, there are foundational questions in building that trust that is really important for us to ask and be given the evidence for. And again, one of the examples that I shared in my blog post was around Vemo. They made their entire evidence data opened and available to everyone. And of course, Vemo has gone in the direction of fully autonomous human less driving. And they have been publishing a lot of results around it for everyone to see their evidence. And are they making mistakes? Yes, but at the same time, it is also showing and building the trust that how these autonomous driving are far more safer than a human driver. Thinking about the trust, I mean, we're definitely moving from individual productivity where employees have been given these tools like the LLMs, whether it's quad or chat GPT or co-pilot. They get to decide what tasks they're gonna use it on and how they're gonna make themselves more efficient and what they're gonna do with that time that they get back. But as we move towards the agentic workflows and the autonomy that we're just talking about in the enterprise, that's when I think the trust needs to really be starting to be built. And you said it, it starts with the leadership, what are we going to be? Who are we going to become? What are the tenets of how we're gonna be using AI as a grounding point? Because I think that there is a lot more fear in this technology than any technology that I've seen before for a variety of reasons. And so I think that building that trust in that sort of environment is absolutely critical. And whether a company brings those folks in in order to design the future operating model and workflows that they'll contribute to or not, it's recognizing that that is the current environment. And I think we are seeing a lack of adoption and a lack of change because people are genuinely afraid. When you think about as individuals so much of your identity and who you are is about the experience the knowledge what you've contributed to your job, and so when that's threatened by anything, much less a technology, it is very difficult environment to create trust around. So I think that's a key to and I think of recognizing trust is required, but what is it going to take to build trust in that sort of environment? And I think the one part that I would add to what you just said, what makes this moment different from the previous technology revolution is the very fact of the speed of this technology. Internet and computers took three or four decades to become mainstream. It took mobile-based technologies almost two decades to become mainstream that every generation and across the world people could benefit from the advent of mobile technologies. It took us 20 plus years to get there. And I think what AI is showing is how fast it can get there in a matter of a few months. And that's the part that is scary. We have not been able to trust enough, and the evolution of it is just way too fast than anything that we have seen in our lifetime. And that is the part that is very, that is the part where people are not able to estimate what is going to be the outcome of this, how we will drive the right type of adoption, how we will prepare our society and our current generation and upcoming generation to live with this technology. Those questions are not yet answered. Policies way behind on these topics. So, combined all of that, the anxiety just around this is overly heightened just because of the speed of this change. How do you talk about this with your team? How do you inspire them to want to create with it, to want to imagine what's possible for patients, clinicians, and sort of leave the fear behind? I think the number one thing for us and everyone is to begin to understand this technology really well, not at the surface level, not at the level where we are using the consumer side of AI, which is mostly using it as a search engine that gives us one answer versus redoing a research. And I think understanding this to a few levels below is really important. It helps us really wrap our head around in terms of what's possible and what's not possible. It separates the high from the reality of the situation. And I think that's the number one thing is to truly understand investing time, becoming a practitioner yourself, whether at work, whether in your personal life is really important. See what can it really do? What is the hype about it in becoming a true personal assistant to what level that is true for us? And that is the number one thing. Number two is preparing ourselves and our organizations and our team around setting the guide rails. I think trust can be solved to an extent when we know where the guide rails are. What are the do's and don'ts? What is my safety infrastructure behind it? It's really really important to make sure that we are putting the right guide rail for us to establish our trust with the system. And lastly, I would say starting the change at the smallest level, pick up a workflow and make it AI assisted, whether it is your own workflow or your team's workflow and see what it does to you. Does it really bring the productivity that you are looking for? And from there, begin to scale it up. Take from trying to assist a workflow, to trying to change a given workflow, and then trying to see whether that can help change the operating model of a given work entirely or not. And that will take time. But to me, that is the progression that we all have to with that safety net underneath us. So let's talk about like how you've applied this. Tell me some exciting innovations that you've done a month fewer. One of the ways that we started on this journey was to take an enterprise version of chat GPT and open it up to a lot of leaders within our organization. And these are not the most senior level individuals. These are the folks who run big enough team across different departments across Montevere and think of these tools as much more of a co-pilot. Think of these tools as how you would use chat GPT and the guide rails around it was it is enterprise software and all our data is safe within a sandbox. So we ensured that everybody understood and we made sure that everyone also understand that even if it is safe, do not put any patient specific information in these environments, but still use it for your day-to-day work whether you're summarizing a document, you're trying to trigger a workflow, you're trying to create a PowerPoint or draft an email, begin to use it on a regular basis. And we saw a significant uptick in the practitioner side of AI. We immediately started having people who truly begin to understand what AI can do in their day-to-day life at work. And of course many of them carried those learnings into their personal life and into their personal chat parts and tried applying it everywhere they could. So over a period of time I heard great anecdotes coming in from these individuals to whom we have done this control release. We also gave chat GPT and education version on our college side where the students can interact with chat GPT and use it as a one-to-one tutoring for medical education. And some of these examples you will see it where chat GPT can present themselves as a patient with certain conditions to a first-year resident. And it allows the resident to train themselves while chat GPT is giving them the feedback that I was suffering with this and you could have asked me this question and that question just to dig into my condition a bit more. And it is amazing to see how we can bring something like a one-to-one tutoring capability at scale to all the students. And technology like that are really, really exciting for me. So these are just very crown-level, very basic cases that we have been beginning to do with. And of course there are several point solutions and other things where we have done some great work. But you know how individuals are changing their behavior with the technology, something that excites me the most. Was it voice or was it typing or both? Combination of both. Okay, you know we're seeing this. Where do people build their domain expertise and their knowledge if they're not apprentice in the same way that they were? And so there's this finding that the interns and the people that are coming into the workforce are using AI in the way that you described to apprentice themselves to look from because they can get access to it 24/7. Whereas if you use your boss or someone that you're apprenticing under, they're not available at the same time. It's really interesting to hear you're really leaning into that. The opportunity that is in front of us isn't to put AI everywhere, at least not in our industry. That's possible because the work we do is on bedside. But we are not going into this with an ambition that AI will be there everywhere. It is that we use AI wherever we are removing a constraint that is going to materially change the system. So to my earlier point around removing a constraint, removing a friction point into a workflow where we may have excessive administrative burden where we are not finding enough people or we are simply constraining the system in typing document or summarizing document where we can accelerate those aspects of the workflow. And the idea is to begin to again have right guidelines in the mix understand what that system could do, understand its full implication, bring the stakeholders into the conversation and then begin to call these win use cases that we go around and start building over and over again. How are you as an organization identifying those high value constraints or those high value use cases where if you fix it, it's going to have a material impact. Did you do that at the leadership level? I do it within your organization or so that is something that we are on a continuous journey to evolve. Where our current state is we do have cross functional teams that sit across technology team, our business operation, our clinical operation. And what we have started to do is to begin to catalog the ideas that people have. Either they have seen it at a peer organization, they have heard about it in a conference or they simply just have a great idea that what if AI could do this. And remember these are practitioners who are beginning to use co-pilot and chat GPT in our organization right. So they are beginning to extend the possibility of what these technologies can do. Further in the pipeline, we do start applying certain financial constraints around those ideas. As you can imagine, not everything is doable for us. We are always constrained by our ability to deploy capital or ability to invest behind those ideas. So there is always a make sure you're done. that we put together to truly understand, is it going to generate right kind of an ROI? And sometimes those ROI could be financial in nature, and some could be patient safety related, some could be great patient outcome, some could be just simply great employee experience, and reducing burnout, doesn't have to be a financial ROI. And we've taken to apply that matrix and begin to see, what is it that we can afford today, where the technology is already mature, and we can bring that technology to bear today. What says in some cases, we should just wait out a little bit more, because we don't feel confident that the technology is just there, or we haven't been able to establish the right level of safeguard in those areas, or we have been able to pull the stakeholders just in there yet. So those are, I would say, constraint that applies to qualifies certain ideas to go become a reality by my team. What are you personally most excited about? Is there like a use case you've used in your personal life, or is there something that you're thinking about that just gets you really excited about where things are going? I have been really trying to learn this technology myself, outside my work environment, and I have been playing a lot understanding from others, how they are using that technology, what kind of services they are bringing together. So I have been on this quest of creating a second brain for myself, which is a very common concept in the industry right now, and this is all about our ability to create a knowledge layer for everything that we know as an individual. So of course, I have so many things that I do on a personal basis. I read things, I have so many things on the family front, I put some ideas together, I have things on the financial journey, I have my travel thing, and so how do we create a knowledge layer that is a manifestation of our brain, and how do we organize that information? So I've been learning a lot of that from many of my peers, I've been trying to use the tools and services that are of label right now, and I've been tweaking some of those things as an engineer myself to Benta. All right, well, Deepesh, thank you so much for joining me today. I've absolutely loved our conversation. Thanks so much for having me. To our listeners, thank you so much for tuning in. We hope you enjoyed today's episode. We'll see you all back here next week, but until then, be bold, take risks, and shine bright.