Latest / TeqTalk with Jas / How to Build an AI Native Company in 2026

Transcript

How to Build an AI Native Company in 2026 · TeqTalk with Jas

• speaker-0: Thank so much Parul for being on the show, really appreciate and looking forward to this episode. speaker-1: I'm very excited to be here. Thank you for having me here and you look wonderful. So let's start with speaker-0: You made my day. Likewise, you look amazing. You look great, beautiful as a person. And I think I have known you for a little bit now, but love to know you more. What you do, what have you done so far? You have incredible journey of 20 years or so in this tech world. So today we are going to unpack all of that. speaker-1: Sounds good. All right. speaker-0: So let me start with one of the stats. So MIT CISR has surveyed more than hundreds of organizations. And what they have found is pretty interesting that there's a big gap on AI maturity level in these organizations. some organizations are too good in this maturity level and their growth and profit is way more than the average industry standard. While other organizations are still struggling, they do not have any idea on even how to get started. Right. And when I think about it, I come to a conclusion that AI models have really democratized now. So it's not the model differentiator. It is the differentiator that what actually you have built pre-model area. could be your data, architecture, your processes. all the operating system around the model. And sometimes we call it as harness. Right. So for my audience who want to learn more about harness, I have one episode explicitly for harness where I've defined nine layers of harness. Go ahead and check that episode. If you like it, subscribe. So coming back to Parallel. So I feel that is a differentiator what actually you have built before this Gen. AI explosion. And I know that you are in this tech world and GTM world from 20 plus years now. You have seen organizations coming and going, what are the best practices they are following? What are the things which, you know, they shouldn't do still they do it. So would love to know from you around your journey that what are the best practices some of these companies are really falling, which is making them AI native companies. speaker-1: Hmm. That's a very loaded question. So thank you for starting there. ⁓ you're right. I've had about twenty five plus experience in tech. speaker-0: Okay, correction, 25 years plus. speaker-1: Yeah, yes. And my background, I would say like I got lucky that I have a breadth of experience. So my background is a combination of infrastructure engineering, management consulting, product development, and then IT leadership. So I'm able to straddle a lot of worlds to then help my team build scalable products, right? Because IT solutions are more products. And I have had The fortune of working with small businesses over the last year. So I can give you a sense of what I'm noticing in enterprises, mid market, and also ⁓ small businesses. So let's start with enterprises. I think AI exposed the challenges that have existed in enterprises for a very long time. Yeah. Because when companies start, the desire is to do work manually because you don't have time to set up systems. And as I started my own business, I realized that's the tendency, right? You just want to get to the end point or end state as opposed to have to integrate systems or clean data. I have a lot of customers but I haven't uploaded all of my data in CRM because it's it's very, very frictionful. So wherever there is friction, people will tend to bypass systems, right? So and Technically, the systems haven't been designed with that type of user experience in mind. And then when they talk to each other, typically the language was not the same, which is why then all of these integration platforms were developed, which you very well know because you're you've been in this world for a very long time as well. So those problems with think taking a step back and thinking about what type of data you want in your platforms, what is the quality of data. What should be the primary source of data? And then what data elements or data fields should be used to make what decisions? All of that is done very ad hoc in enterprises. And as as you know very well, a lot of IT leaders and especially CIOs, their job primarily is to clean data so that we can make faster decisions and have better employee experience. And that's the TLDR of a CIO role. But in the back end there's so much that happens because we have to constantly figure out Who is responsible for making decisions in a certain area? What type of processes they have in place. Exactly. And then, like, what do you do and how do you automate some of these things? Which was the past. And now ⁓ you're applying sort of agentic layer on top of that. So if you don't have the foundations right, which is the data, which is the processes, which is the decision-making infrastructure, it exposes a lot of challenges. So the point that the coming to then the conclusion, where I've seen a lot of People move very fast is small businesses. Mm-hmm. You'll be surprised because they don't have all of these layers of enterprises. So I have actually spent a lot of time teaching small business owners how to use AI. And some of them have just gone and learnt it themselves. In fact, next week when I do my summit, one of the business owners is going to talk about how he changed his entire business to be AI native. He's running like 15 plus agents. And the individual is not technical at and that's the power of AI. If you have the desire to learn, you can learn, you can implement very, very quickly and then continue to iterate on it. So because they they have a handful of people in their team, five or ten or fifteen, max fifty, they're able to make decisions very, very quickly and iterate very, very quickly. And those are the people that are g able to get to a conclusion and good outcome very, very fast. speaker-0: happening to the enterprises now because if we see the enterprises the level of data they have is insane. Nobody has any clarity on the overall picture of the data and a lot of points, lot of areas where things are compensated. Everybody knows that this report is not going to work. Everybody knows that the processes, the workflows which are working are not correct. They are putting on human intervention and making it right. And now all of a sudden you see the AI boom and AI is going to take everything. What do you think? How they are going to go ahead and sort out this problem when the foundation itself is so blurred? speaker-1: Yeah. I think the the challenge is the expectations are so high to show a result right away. Yes. And because of that expectation, which is sometimes not practical as well, and I think everyone is trying to understand how to use AI. For most part we still don't know how the machine learning models I mean the models we know how wor how it works, but even like Dario said in his letter, there is They're still trying to understand how the LLM works and the output that it's generating, what is the rationale behind it, how is it coming to that outcome based on the data that's provided? There is a lot of unknown about these systems. There is a lot of unknown about using these systems. So while it's great for like personal use, when you're using in the context of enterprise, it's very challenging. And a lot of people are still trying to figure that out. In fact, some of my CIO friends. There can be different models that we've been playing with. ⁓ in my case, ⁓ at Uber, we IT sort of took on the responsibility of building things for our stakeholders. But at the same time giving them some tools where they can build their own agents with the right guardrails. So we did a combined sort of model and we used a combination of building agents and also buying some off the shelf tools, depending on which use case you're you're trying to build for. So that I can fast track innovation internally. Some of my CIO friends are trying to build harnesses but allow stakeholders to build ⁓ agents themselves. Some have not provided any harness and allowing stakeholders to build agents themselves. And the outcomes are very different. And I think what's gonna happen is we will figure out what's working, what's not working in the next 18 months, hopefully next 12 months. And We'll take a step back to then build the right infrastructure foundation on which we can build some of these things because i ⁓ identity, security, compliance, enterprises still have to report to the street. So you can't bypass some of these things that we absolutely need in enterprises, no matter how fast you want to work. So that's one thing I think we'll all have to take a step back and redo some of these things. The other thing I'm I'm seeing happen is true emergence of vibe coding in enterprises. Yeah. I was having some conversation. So vibe coding platforms, I'm not talking about Claud Code or Codecs. I'm truly talking about wibe coding platforms like Lovable or Replit. So far, they had no business being used in enterprises because as a CIO, it makes me very nervous. Would I allow somebody to just build and launch things in production? But these platforms are becoming very viable in enterprises because some of the engineering teams I've I've noticed are using it to build demo. Wherever they work with their customers, rather than code everything, they're using these vibe coding platforms to build demos so they can understand what the customer wants and then come back and build it in production. Yeah. So it's just so interesting. And the same vibe coding platform when I contrast the enterprise with small businesses, small businesses are building their entire businesses on these vibe coding platforms because and they can scale well for what they're trying to do. So it's just very interesting to see how technology is coexist. Does it speaker-0: a valid point, completely agree to it. And there was one interesting research and fact came from Gartner. It said that close to 67 % of B2B buyers, they're interested in buying products or services from the places where there is no sales rep. So basically buying is becoming more of self buying and agent tech. So when we are talking around these scale, just think about the infrastructure, think about the processes, think about the robustness, think about the compliance, guardrails, all have to be added in these systems to make systems more reliable and robust and trustworthy for the consumers. So if you talk about GTM, when somebody says that we are refining our go-to market, what are some of the portions which tech has to take care of, which other streams like sales, marketing and ⁓ Custom experience, finance do not even see. speaker-1: I think so in this context for go to market specifically, yeah. I t for us, the sellers, the marketers are customers, true customers of the platforms that we build and manage. So we have to think about these platforms as products that are serving our customers and their needs and their goals. So what they don't see, so from a salesperson's perspective, they are using Salesforce as a CRM. Yeah. They are thinking about their customers as bleeds or prospects or accounts. But then in the back end, we have to take care of all of the data fields. What comprises of an account? Right. What type of fields do we want to create in CRM? How do we standardize that across the different type of customers that you have? What are the different types of contracts that they're thinking about creating? What are the pass-through contracts versus some contracts that require escalations or exceptions? What are the level of approvals required? And how can I build that in my system in a manner that it's fast enough? But there is enough auditability for us to go back and look at the steps and who touched which which record. And then connecting those to downstream systems like contract lifecycle management systems. Essentially mapping the data model across the two systems, then connecting that with ERP and and thinking about the entire life cycle of lead to cash as opposed to just lead. Yes. Which is what the sellers are seeing or just campaigns, which is what marketers are seeing. So there is a lot of I I I ⁓ describe IT or the CIO role as the plumber of an organization, right? Essentially we are Fitting pipes, make sure your data, which is equivalent to water, flows effectively through the organization. Absolutely. And nobody is upset if the data is flowing well, just like water. But if a pipe is bursting or the quality of the water is bad, or something is broken, that's when they see the impact. So as long as it works well, it's invisible. But if there is a problem, we are the first ones to get to scene and have to fix it. Yeah. speaker-0: Tech is the one that is really connecting the dots of all these. Do you have any interesting story which you can tell us that something went well? speaker-1: Vertical. ⁓ yeah, th there are a few. Let me share one. ⁓ so the one challenge that salespeople always run into, actually let me take a step back. So whenever a new ⁓ product is launched or a GM has a goal for meeting a revenue target, their strategy is to sell more. Typically the way they want to sell more is to hire people to be able to sell. And now of course you can build agents to do that, but then you still need agents to do that work. But in the past, the strategy was to hire more people so you can access more accounts and target people and then figure out what those clients need and be able to sell to them effectively. That was the strategy. The challenge becomes when a salesperson has to navigate multiple different data sources to find the information about that customers in terms of what we are already selling to them. and then create the right pitch to go back to this customer. So one of my story is they these sort of poor sales people that we would onboard at my previous organization, they had a great sort of L and D platform, but there were so many data sources. Everyone had their own source of truth. Sales had their own product, had their own engineering team, had their own IT. We poor IT people were trying to figure out like who owns what type of data so we can ensure the CRM is high quality. And these folks, the salespeople, were spending hours just trying to get information on, based on their book of business, what customer is buying what from us, what can we upsell, where there is opportunity to cross-sell. And it would take hours for them to prepare for one client meeting. And then what we ended up doing was looked at that mess and then figured out how can we automate some of this and surface what they're trying to do in Salesforce directly. So they never have to leave their primary platform. And we'll just pull data in the back end. And that's the power of tech. Once we define the problem the right way, which is why my point was we really have to apply product thinking and not just adding more fields thinking. Not reactive, but truly think about how we create a scalable platform, we can do a lot for our customers like the sellers. I think that's one one thing that comes to mind. Great. speaker-0: and share with me some experiences you have in Uber, what exciting things you have done, you were leading the GTM end to end and share some experiences. speaker-1: Yeah, I think one of those things that we did early on was build these agents. One such example of this agent that we built for sellers, that was one to be able to connect the systems in a manner that we're cleansing data, creating our own sort of pub sub platform across different SaaS systems was another thing that we did. Uber scale is pretty big and it teaches you very quickly the importance of reliability. Yeah. So then my responsibility wasn't just GTM, but all of the systems and they kinda go hand in hand, right? We were able to we in IT, to your point, were able to make a connection between all of these different tech systems and surface the right insights for our stakeholders. Because then I was in a position to be able to do correlation between sales systems and finance systems and HR systems. So I could give them a three sixty view of their sales teams as an example, right? And that that is the power of if you do the connecting the dots the right way, as you mentioned earlier, we are able to impact the business directly. We being the IT team can impact the business directly. And the complexity at Uber was unparalleled because the different countries have different ways of selling, different compliance needs, different pricing structure, different currencies. And to be able to configure all of that in one system, it takes a lot of making the right architectural decisions. So the importance of architecture, the importance of right design, the importance of making sure the data converts and flows in a manner that we're not breaking downstream systems is is very, very high. And so again, going back to my point around the product thinking, which is why we really need to figure out truly what problem they're trying to solve. No matter what the s stakeholders are asking us to do, but what problem are we trying to solve? And how does us solving that problem create the downstream effects and rubble effects? And then think about those and proactively solve for all of these issues that will come up is one of those one of those learnings that we had. Now the second thing thing we learned was you can plan for the best, you can have the best design in the world, things will go wrong. Then how do you build your systems that are able to recover quickly from failures? And having the right high availability built into your systems. So a lot of that critical thinking goes into building systems at that scale. So speaker-0: What does it really take for a leader like yourself to make sure that there is absolutely no downtime? speaker-1: Yeah, I I think it goes back to the foundations of ⁓ engineering, right? And you as an engineer would have also seen that in your in your day. It is a combination of people, process and technology. Yeah. When we are thinking about making these change. So depending on the type of change, I would say the the first thing that we did and we did right was Uber is a very sort of engineering focused organization. So the foundational principles of How I used to tell my team, ⁓ a self-respecting engineer will design systems. We really need to think about that. Then having the right processes in place, which are the basics of do we have the right monitoring, do we have the right alerting in place? Do we have the right incident management process? Do we have the right escalation path? And truly kind of leading by example, because if you lead as a leader would not care about the downtime on the systems, the team wouldn't care. So for them to care, you have to show up as a leader and work with them when there is an issue and be there to support them. So that was one. So a lot of the those foundations were set up when I was there and my team did a fantastic job of being able to learn from the engineering teams, so product teams, engineering teams, and apply some of those learnings within IT. ⁓ then the other thing that we had to do was create a robust sort of BCP and DR plan because for SaaS systems, there's only so much you can do. You're not running that infrastructure. You're not responsible for the end-to-end system. It's not like it's running on-prem as we used to back in the day. And so we could create like clusters and have systems be highly available. And we were responsible for designing and building it, but that's not how it works in SaaS. So then creating the right ⁓ business continuity plan. So if Gmail is down What do people use? And if Slack is down, then what do people use for communicating with each other? If your SSO is down, how do you have a fallback SSO? Some of these systems we had to build. ⁓ and we used to do it in partnership with ⁓ identity team, which was ⁓ part of security team at the time. But we had to really design these systems because you couldn't have thirty thousand people not have access to Slack or email or you know, we had mm really big massive issues with SSO at the time. So all of that we had to do as part of our BCPDR plan and then create backup systems. So it really depends on what problem you're trying to solve. But I would tell you one thing that ⁓ solving that level of complexity, we always had to remind ourselves to keep the solutions simple because complex solutions are not necessarily the most sophisticated solutions. So that's the trade-off you'd have to make. So it really depends on what you're trying to solve. It's a combination of different things. Because technology lives in real world and real world is messy. So you just have to figure out how do you make the best of the situation you have to the best ⁓ best of your ability, figure out what things can go wrong and then create backup plans for that. speaker-0: It sounds simple, but it's not actually that simple. Okay, if I can ask you top three things that you have learned from your speaker-1: Uber days. You know, one thing I really appreciated about Uber was just No was never a thing, right? Like you would if there was something that needed to be done, no matter how impossible, we would figure it out. And I think this is Uber's speaker-0: culture, right? Because that is what I was hearing from one of my friends. She was at Uber as well. she was like, yeah, nobody says no to anything. Whenever there is any issue, everybody is there to help you jump right in there. speaker-1: Yes. Yes. I sometimes you have to say no to things, but that's it's an exception, not a rule. But the point is the innovation, the culture of innovation is just so amazing that we'll figure out how to get some things done. Some of these things were and not part of my peer view, my engineering counterparts had built systems that didn't exist externally. And in the early days of AI, some of those systems were used because ML has been part of Uber's platform from the very beginning. We were able to use some of those infrastructure hardness systems to be able to use LLMs effectively and protect against any kind of ⁓ data leakage, you know, that we hadn't planned for. So, yes, I mean the culture of innovation is amazing. ⁓ never saying no, just kind of figuring it out. And I I would say my impression of Uber was we had some of the brightest minds in the company, but also very humble, which is why like they were all ready to work together. And just learning from each other. I mean it was it was a fun, fun environment to be part of. What else did I learn? Yeah, scale and complexity. ⁓ I just didn't appreciate the scale and what it takes to run a platform with that level of complexity, with that scale. That was that was a really good learning. speaker-0: Great, great. And what made you, what was the motivation factor for you to start your own firm? And yeah, tell me the turning point, how it happened? What made you start? speaker-1: You venture. I would say I have the good fortune of having a lot of health challenges. ⁓ my God. And so I was going through one such pretty significant health challenge. ⁓ so as I took over the role of running IT at Uber, I was also diagnosed with ⁓ cancer one and a half months into taking the role. So and you know, I thought to myself, how hard can it be? We can go through chemo and have all those surgeries and everything else while I do my job. ⁓ my husband used to go to these doctors' appointments with me and he used to joke with my doctor. He's like, She loves her job more than she loves me, so figure out a path where she can go back to work faster than what they were planning to do. And that's how I kind of lived my life for the two and a half years I was there. And I decided I just needed to pick a lane which was taking care of my health. And then I decided to do that for a while. However, one of my Team members used to joke with me and I would tell Mohat often, I don't know why I'm so busy. And he would look at me, he goes, Perul, you're the kind of person you create work for yourself. And I did. So while I was taking time off for help last year, I I'm connected with the small business community in Oakland. A lot of my friends would come to me and be like, Hey, can you tell us how to use AI or what does this mean and how can we use it? I'm like, there seems to be an opportunity here. Let me just create A training program for all of these people, pull them in a room and teach them how to use AI. And that's how the AI Ally work started. This was an attempt to give back to community because I really think that small businesses have an unparalleled opportunity in using AI to really do well in their businesses. And while every vendor is trying to help them, I really feel somebody would figure out what they need and then teach them how to use AI as opposed to furthering their own agenda as in my system is better than somebody else's system. I think just just tell them what to do that is best for their their businesses and their needs. And that's what I wanted to do. Give back to community, empower them and furthering technical literacy with these people. speaker-0: First of all, Parul, thank you so much for sharing your health issues because this is so deeply personal. I really appreciate you sharing it. You're very strong and I hope you're doing well now. You're doing good, right? That's the first question I should ask you. speaker-1: Yes. Yes. I've been in remission for a few years, but you know, cancer is a complicated disease and I would say that I was a little crazy. So there were times when I would go go get my chemo treatment and then I'd be presenting, you know, at like company. ⁓ I was times. Yes. It was it was a two and a half year l long journey. So I was doing my role as the IT leader or head of IT at Uber while I was going through treatment. speaker-0: ⁓ that's massive. How did you do that? ⁓ speaker-1: that. I'm a very determined individual. ⁓ but at the same time my determination finally cracked where when when I had to take time off. So I would say, you know, kinda pick your own speaker-0: Do you think God is sending you a signal? power will slow down. I know you can do everything you can do wonders, but time to focus on your health. Something like. speaker-1: To slow down. That? Probably. But I wish the signal would have been sent either three years before or after. But you're I'll figure it out. But yes, I mean I finally had to to notice because it takes a while to recover. Mm-hmm. And you do need to give yourself space to recover in those circumstances. But yes, I am it has been the hardest time of my life, which is sitting at home and while I have my business, while I have my podcast, while I'm doing advising for a lot of companies, I'm still very bor bored. So yes, while it is Great. ⁓ speaker-0: to working like 20 hours. speaker-1: Yes, and I liked it. I still do that, but now for my health, but you know, it was something that I had to pay close attention to and choose health first. speaker-0: Of course, that is what matters, right? And a lot of times we ignore it and then we see the results and consequences. But I'm happy for you that you are doing good and really excited about your business coming up. Tell me more about it. Businesses, organizations, startups you are meeting and the innovations happening around it. Share something amazing around that. speaker-1: Yes. Yes. So I'll share three parts to it. The type of business. So I ⁓ partner with big enterprises. So PGE is one of our sponsors for our summit that's taking place next week. So the summits that I host, the last one I hosted in April, the next one is on the twenty-fourth of September. So I bring together my enterprise leader friends. So some of them are CIOs, some of them are CEOs, some AI native company CEOs. ⁓ enterprise architect. So I bring together my enterprise leader friends and then SMB owners that have used AI in their business so that the audience can learn from them. And then procurement officer. Because the the summit is primarily for small businesses so that they can learn how to use AI or see what trends or patterns are taking place at the enterprise level because a lot of these people sell to enterprises. So my goal was to create that bridge between this tech bubble that exists in Bay Area and then the rest of the world. ⁓ and then bring those two worlds together in a manner that we help each other out. Because at the end of the day, it is a community, right? And it takes a village to kind of get things right. And I thought AI was such a great opportunity for these two worlds to come together and I can act as a bridge between the two. So that's that's the summit that I do. And I also do working sessions or workshops in partnership with big enterprises, like you know, I just did one for Kaiser. So big enterprises typically have ⁓ a lot of investment in their suppliers. Yeah. They would host events for them, training sessions for them, and that's the opportunity where we partner with enterprises to help their suppliers become more AI relevant, pertinent, ready in whichever way that we can. So that's one. Second was your the type of people that I'm meeting. Amazing people. There is this story of Sandra. And ⁓ I also hosted the podcast The Courage Curb where I share the stories of women, amazing stories of women that have overcome some really difficult things in their life and built a great life for themselves. And one such story was Sandra James. So Sandra and you should go take a look at that. ⁓ you can tag Sandra, but Sandra's story is just so inspiring. And I have so many other ⁓ people that I want to shout out to. speaker-0: Sandra. speaker-1: But Sandra's story stuck with me. So she's a business owner. She runs a very, very successful business now. But in her early days, she was a drug addict. I think up to the age of 26, she was a drug addict and she was in and out of housing. At one point, she was homeless, dumpster diving. Then one day she just decided to get clean, started her business, and within three years, she made her first million dollars. Wow. And she's been clean ever since, and she's like this amazing beacon of. hope and she How do you meet people like this? At my summit. ⁓ okay. Yes. So that's how so these amazing business owners I meet at my in in this community. The second ⁓ person I'll give you an example of, her name is Jennifer ⁓ Harrington and she was a C level executive at multiple different health ⁓ companies or healthcare companies. And she started her own business and she has three master's degrees. Maybe a PhD, I forget at this point. And she's not technical at all. So I did wipe coding workshop with her once and I told her what was possible. She came back to me a couple of weeks later. She had completely reimagined how lead prospecting is done in her business by herself. And she would ping me and ask me like questions, really complex technical questions. I'm like, Who are you? How did you how did you even find out what to do? And so that's the story. Like sometimes you would speaker-0: just need direction, right? And that is the purpose of your community. speaker-1: I believe to provide rather than building an agent for them. Yeah. I want to teach them how to fish. Yeah. Because once I take away this helplessness away from them, wherein they are relying on somebody else to build technical tools for them, it's amazing what you can unleash. You just have to give them the right guardrails and then, you know, just don't put your sensitive data somewhere where it doesn't belong. Right. And it's it's common sense. If you can run a business, you're smart enough to be able to build. Yeah. Right? And that's what I'm trying to unlock for them. speaker-0: So good, so proud of you. And you know, what is the best thing I like about you? You have such a clear vision, the vision, the use cases, the interesting stories. That is what I always keep looking for. Is there anything we would want to talk to? speaker-1: Yes. How about we talk about the future of humanity? No pressure anymore I think so yeah, let's talk about the future of humanity. Now I'm just I'm just feeding your questions. Yes. Because I do think about that a lot. Yeah. I do think that with this new wave of AI, whether or not it's true, a lot of CEOs are saying that because of AI they don't need a lot of people and there is a lot of layoffs and speaker-0: important, I think. speaker-1: I feel like the toxicity in in corporate world has grown. Yeah. And that really hurts me personally. Because you know, when at least the in the culture that I grew up in, in in Indian culture, we grew up understanding the importance of oneness of life and environment. Wherein like you are not separate from your environment. Right. And I just feel like we've We've forgotten the basics. I feel like we've forgotten that how we treat people around you or how how you treat people around you, it is what you what you do to others will come back to you. Yeah. Because whether we believe in the concept of karma or not, but you know, negative energy and positive energy is a true thing. speaker-0: Give me an around you matter the most when you're working even the hardest thing you'll figure out if you have good people around you, good team around you. which is very less right everybody is just willing to promote themselves and kicking off others and that thing is going on a lot so what is the future of humanity? speaker-1: I d I don't I don't know, but you know, as a as a leader, I always put my team first. Not that I would not hold them to a high bar, but I would keep their interest at heart. And I think it's possible to and I would do that the same for my stakeholders and everyone around me. I tried to create an environment where everyone felt supported, taken care of, trusted and helped. Yeah. I used to get this advice a lot going, like you need to stop caring about others so much and you need to care about yourself. Kind of my example of, you know, when I was sick, I was even when I was sick, I would be working because I wanted to represent my teams the right way and and all that kind of good stuff. And I used to get a lot of this advice going, You should just, you know, prioritize yourself. Yes, sometimes it's okay, but as a leader you have a bigger responsibility. So the future of humanity. I do think that We really need to go back to the basics of oneness of life and environment. How you treat others will be reflected on what your life becomes. And this is the most important time where we should think about winning together, not instead of each other or instead. speaker-0: I think that is such a valuable thing which you have told all of us. But I think it was too harsh on you when you were still sick and you were still thinking about others, right? speaker-1: I think yeah, learning from experience. Yeah. ⁓ speaker-0: So that's why, mean, whatever advice you got that moment of time that slow down, look at your health first. speaker-1: I think it's important and I would say after having gone through that, I would I I say the same thing to my friends now who are pushing too hard because the other thing that I noticed was women just have so much on their plates right now. Not only are we the career people, sometimes we are the sole breadwinner. We also take care of kids, although I don't have any kids, so I don't have to worry about that. Also the the pressure to have the right society around you or friends around you, the structure around you. A lot of that just falls on women. We have to talk about now you have to come to my podcast. speaker-0: think this will take another hour. ⁓ We can talk about it and this is such a common thing which every woman feels. I really admire all your journey throughout from the beginning and it's such great pleasure to know you in person as well. And now for the last question, what do you think is going to happen with AI in next coming year? I wouldn't ask for three years because you never know. Three years is going to be, it's too far, right? The rate of innovation happening in every speaker-1: I I honestly don't know how to answer that question because there are engineers that are resigning saying open air anthropic are not training their models responsibility. Daria Dario had an essay out or a letter out saying we should slow down. How do you probably Yeah, so I I don't know. I don't know and some people are like we speaker-0: Everybody agreed as well. Open ear. speaker-1: You know, AI is going to kill us. Others are like AI going to be amazing because it's going to help us find cure for diseases that never existed before. In fact, Dario said that too. ⁓ so I don't I don't know what is going to happen, which is why I say, no matter what happens, if we band together as human beings and think of this as our collective effort and journey. And Enjoy no matter what happens next. That is going to be a lot more valuable than chasing whatever result we're trying to chase right now individually. Collectively if we try to do something, I think that is always more pa powerful. Recommend. ⁓ there is the one that I started reading because my last year was quite challenging. I'm not the kind of person who likes to sit and do nothing. And my health just would not get better. I'm like speaker-0: What are some of the books you would read? speaker-1: It's like not there's nothing I can I'm literally sitting at home and staring at a wall. How are you not better still? So I started reading this book. It's called Hope is a Decision. And because I had to make that decision for myself to have hope no matter what. And I was doing really well, like my business was doing really well and I was giving back to community. There was a big impact, but it just didn't feel like I was doing enough. So then I started reading that book and I had to just reset my expectations. Mm-hmm. And I realized that I have responsibility towards my own life as well, right? As much as I towards others. speaker-0: That is so so true. Thank you so much Parul for coming on to the show.