Why Human Judgment Still Beats AI at Scale: TCS's Sandeep Rachapudi on Judging Innovation and Enterprise AI | Sandeep Rachapudi

Russ Fordyce (00:00): Welcome back to the Winner Circle, everybody. I'm here today with Sandeep from TCS. He is one of our All-Star judges for 2025 and an expert in IT services and at the forefront of this massive AI innovation extravaganza that we're in. And he's helping all the enterprises become great at AI, but he's helping us judge all your nominations. So, Sandeep, welcome to the Winner Circle and congratulations on being an all-star last year. Sandeep Rachapudi (00:28): Thank you. Thank you for having me and it's always a pleasure to, you know, judge about some big innovation. I always get something to learn. Russ Fordyce (00:34): For yeah, for anybody that doesn't know, All-Stars are our top judges. These are the judges that are basically scoring the most programs, giving us the most honest and good feedback, which is so helpful for all the nominees. These are not AI feedbacks, we check for that. so these are real judges, real people like Sandeep judging your your nominations. And we're we're just thrilled to have you, you know, doing this and helping us and being part of this community. Sandeep Rachapudi (00:51): Ha ha ha. Russ Fordyce (01:03): But before we get into all of that, tell us a little bit about you and what you do at TCS. Sandeep Rachapudi (01:09): so you all know I'm Sandeep and I have been working with IT for well over two decades. And in the IT services companies, I predominantly have worked on fintech based projects and you know where digital transformation was the thing. Cloud technologies and you know cloud migrations was something that was going a lot in the last couple of years, and now we have definitely shifted into AI and Agentic. we was in generative AI, now we're in Agentic A, and yes, now we're implementing these AI-based solutions for all of our clients. yeah. Russ Fordyce (01:41): Yeah, and it's it's an it's a super interesting time, I think, to be where you guys are sitting. Because of all the we were talking about a little bit earlier, you know, we I've worked with the hyperscalers and and helping them launch networks, and you're helping these enterprises really kind of do the hard work of actually deploying AI. But before we get into that, take me back to the beginning. How did you first get involved as a big judge? And what was the kind of the theme of of your you know, your thinking about kind of getting into the innovation realm? Sandeep Rachapudi (02:12): Right. So IT services, it's a it's a very big domain and market, right? Like there are a lot of you know industry leading and in global giants in IT services companies. My own employer has over half a million employees spread across the globe. And then what we do, I mean, either with my current employer or my last employer who are global giants in IT services, we always work towards our customers and then make sure that you know there is value and innovation in everything that is being delivered for them. But in this process, you know, like in the last It's say two decades I've probably, you worked for a little more than 20 clients. That means I'm working on a new client every six months or every one year. And we constantly deliver in cycles. So the client would remember, you know, like of the value that we have given to them. But then it sometimes you know gets difficult for the employees to, you know, get themselves recognized. Yes, they definitely get recognized in their units within the org, but how do you get recognized even beyond the organization? Probably get it get recognized at an industry level. So that is where I was looking at, you know, how to you know like look for opportunities like these. I have even tried, in fact, got nominated and you know got selected to present my papers in some of the innovation-based seminars. and and I've been invited to you know like as a speaker to innovation seminar here in there in Bangalore, India, but by Moladin US by the time I was deputed over here. Which actually took over the opportunity of you know getting presenting my own paper and you know like probably you know getting selected you know for the specific award. So that pre pre-ultimate round You know, where my paper got selected only when I present, you know, it'll actually be considered as a valid nomination. that actually felt hard because in service companies or even in IT, moving across locations is pretty common. Within US in the last decade, I moved across four locations. In India, I have moved across several locations. When when there are these constraints about like being having to present paper physically in a seminar, stuff like that, you know, it might be good. It it is good to have those kind of things, but won't work in this dynamic world where people are always moving around. And that's where where I was thinking, you know, like what's actually happening in this world of getting recognized? Being within the team, within the unit, within the industry, across the industry, how do people do this? There are various avenues, but but not always as simple, straightforward, and transparent. And that is when, you know, like I was going through you know, as everybody does, you know, go or go online, check in like how people publish their papers and how do people become, you know, independent researchers when they become researchers, what are the ways that they try to Sandeep Rachapudi (04:39): Get them recognized and that's how you know I ended up finding about big innovation awards. And I had to yeah. Russ Fordyce (04:43): Yeah, well it it was interesting. Sorry, it's interesting because recognition's all about trust signals and kind of like what you're talking about is kind of layering on different trust signals, right? There's different types of awards. There's internal, you know, your employee of the year type of awards or pat on the back, hey, you're you did great this quarter type of stuff. Sales is always recognized for their great, you know, sales every year usually. so there's different layers inside and then w companies I've seen that do it well do kind of bring in that external sources and that third party validation like us and others that really help you get that third party perspective. And then that's where you kind of have to look under the covers a little bit and kind of go, you know, who are these guys and how are they judging things? We were talking about that earlier, right? There's lots of different ways that these award programs are judged. Sandeep Rachapudi (05:24): Mm. Mm. Right, right, yeah. Yeah. Sandeep Rachapudi (05:33): Yes, yes, yes, yes. many many our programmers do, you know, like expect, you know, to come to a specific location, you know, like be it you know be it sometimes it's a hotel and sometimes it's a restaurant where they actually request us to come over there, present the award. And yes, there are sometimes entry fees in order to get into these kind of awards or you know, like a you know, like ceremonies that they conduct. I do I I many of them are legit. I I think many of them are legit and some are like I'm not sure like why they're asking me to come over there, et cetera. But the the matter of the fact is that we have now we have grown up into this place where everything could be done online. We can actually have this human interaction by actually talking to people, you know. I think the winner circle podcast, you know, where we are able to see the people who actually won and what they have delivered, etc. That actually adds a lot of legitimacy to what has going around and and the entire process is fully transparent. I just in in my case, my own example, I just requ I just put my application to Russ saying, Hey, this is my profile, this is what I have done and have done so much of research work. In fact, I shared some of my research papers to Russ when I initially reached out to him saying that you know this what I do. And if you think I'm good enough to, you know, to be part of your entire this big awards judging panel, I'm more than happy to join. And I've seen a lot of the judges, like they're from everywhere, you know, all fan companies are there. Yeah. Russ Fordyce (06:46): They're from everywhere. It's and it's all walks of life. So that's been the the most humbling part of this job is watching all these people volunteer to do this. And like you yourself, you I think last year in 2025, you judged six programs: AI Excellence, Stratus, Big Innovation, the new one, the Evan Kirstel We Love Tech Awards, Customer Service, and Sales and Marketing, the SAMI. That's a real commitment to, you know, to when you have a demanding IT services job, what keeps you kind of coming back? Sandeep Rachapudi (07:20): So i I would actually call it the full cycle. You know, one thing is because of my experience of working with so many clients across so many employers. I definitely know like what what each client is looking for and how they try to, you know, sell their product. Because I'm a services company that I'm selling our product to our clients and probably sometimes developing their own products through our employers. So so I always because it was natural for us to like show value and innovation, it actually became you know like my second nature to look for value in a particular project on a particular delivery because I've been doing it naturally in my work to identify what is the best project and like a problem like a give a presentation internally to the team. So I thought no why can't I use this similar knowledge to judge what is happening in the industry. I'll bring my experience of you know like how to look for you know the best you know like among the pack. And at the same time I'm very impressed to see how people are trying to you know like a showcase their innovation, even the smallest company, you know, it's so funny to Say that's one of my scenarios in the past has actually actually you know applied not for my current employer. I'm trying to be very clear, from my earlier employer has actually come over here to big awards to showcase what he has done for the company. And it was so great to think about my CNV president after a long time and like how they are coming back over here to showcase their value. All that gave me a lot of confidence about you know this big innovation awards and kept me driving. Okay, now I have to go and read more of these nominations, understand what everybody else is doing. in the industry, not only my past boss, but my past employees and everybody else in the market. So it was a learning. form it is learning by reviewing everything and also bringing my expertise you know, of in tech working with so many clients. Russ Fordyce (08:55): Well, I I think it's it's it's like watching a little bit, it's like watching a Shark Tank episode. You know, you c you get, you know, t kind of ten pitches of these really cool, kind of innovative companies like you said, where you get this like unique take on something and it's usually something very specific. You know, they're solving a problem that somebody hasn't solved for decades or hundreds of years or ever, and they've narrowed in on a very, you know, small subset segment of something, and they're really going after a niche kind of that's Russ Fordyce (09:25): That's some that's something to an industry. And it's really cool to see this come together. And and to be able to kind of go through ten of those really quick, it must be really kind of fun. So wal walk me through what it's actually like to kind of evaluate an entry and kind of go through the whole program. Sandeep Rachapudi (09:40): Yeah. Firstly, I want to say I always love the entries which have got links to their external material. Many people, you know, submit their, you know, like a nomination just with a lot of text, which is good. But then always, you know, having that links to their portal or, you know, like an external link or a media post that has happened would actually add a little bit more confidence and feel-good factor for the judge. I'm reading so I always go through definitely the entire content. I always look at what has been the outcome. Sometimes they It's like a real big complicated, you know, like solution that have implemented some security stuff here or there, et cetera, which is good. But at the end of the day, how did it actually help the customer? What is the benefit that they have got of implementing this complex technology or probably this innovative process? I look at the value that has been delivered to the customer at the end of the day. I mean, the the nomination has been by an ex company, and how did their customers get benefited? Who got the value addition out of it, et cetera? So I look at the value of it. And of course, definitely the technology implementation of it, how feasible it is, how complex it is, is is another thing that I always look at. And the the company portals. Many people add YouTube video links, you know, to explain about their particular nomination. I really love to go through those, you know, all those YouTube links, and I definitely browse through all their company portals. I actually do a little bit of Google about the company to see what were the latest feedbacks that you know people have been giving about the company and their products. Many of them are in startups, which are pretty new. I sometimes don't find anything when they search about those companies, but then I rely on the material that what they provide and the video links that they provide and then come to my judgment. And and yes, yeah, being in services for so long have working with different clients has been my nature and now working with different nominations also become my second nature. Russ Fordyce (11:22): Well, it it it I find it gives you so many good ideas of your own too. Like it it sparks ideas when I when I when I hear about this stuff. And I I was telling you earlier, like I we had a one we had a customer who was or a winner who was who was doing AI in hospital cafeterials to make sure that the food going to the patient's room was the correct food. In a hospital setting, that's pretty important. Right. And and so it's Russ Fordyce (11:47): It's very, very interesting to to start thinking about these little problem these these issues that are going on. Now you've eva evaluated hundreds of submissions across all these programs. if you could kind of pinpoint something that separates the ones that genuinely stood out to you from kind of the bad ones or papers or whatever, what would what would you kind of tell people? What would you what are you looking for? Sandeep Rachapudi (12:06): Yeah. Right. I don't remember the name of the company, but I'll tell you what. but I still remember the concept that you know, like they have used. They were talking about you know like reducing the greenhose emission and actually making the world more greener with IT. I was like, my god. Okay, how are you doing this? And so they that specific company spoke about implementing the efficiency of the battery systems or the machines that they are using in Agricultural sector. They have implemented some small models. They have done some data analytics to see how these particular battery systems are being utilized over a period of time. And then they have come to this conclusion that they can actually reduce the amount of power consumption. If they can, you know, like irrigate the system for a specific amount of time, etc. And that's a process what they have implemented. And finally, they have said because of this, we have reduced greenhouse emission gases for. So long, and this is the process what we have implemented. We have used so many monitoring tools. So they have used IT. I mean, they have used computer monitoring systems across their farms in order to make sure that the greenhouse emission gases are reduced because they are trying to use less electricity and less battery power and get the value out. There's no direct customer over there, the customer over there is the nature. You know, I mean to say who benefit over this over there, you know, like with the reduced greenhouse emissions. And you like a save saving of selectity, etc., was also good good value. And somebody and there are companies who actually spoke about how repeated rejection of their product has been, you know, like has been a has been a problem. And they've implemented CIA solutions and chatbots obviously for the customers to interact with them and identify patterns and they understand okay, this specific set of product, when it is delivered with a delay, is probably causing them to lose interest. So they have and identify the pattern that you know. All the products that actually get delayed due to so and so reasons would actually get probably get rejected, they do they lose interest, etc. And hence they have to improve the process of their supply chain management. And then they have seen that you know customers have started buying their products more and they have seen value. So these are the kind of they're all smart, I would say tiny little things, but then still they're adding value. Somebody's actually trying to add value in terms of know, like having better electricity management, somebody's creating value in terms of making their customers use these products even more better. Sandeep Rachapudi (14:27): etc. So, yeah, there have been nominations about a complex identity access management in AWS Cloud. I felt you know that was a pretty good way of implementing and the amount of you know reduction in the number of security incidents. They have shown a pretty good graph and a data of you know how that has helped them to strengthen the confidence of the customers after they implemented this you know identity access management in AWS Cloud. And that also was good because of the fact that. Identity access management cloud is a pretty standard process. I mean, everybody knows it, but they're able to articulate that implementation and first identifying the problem that security was the issue, and putting the proper guardrails or you know, like security stuff into it, and then showing the value that also caught my attention. Yeah. So I always look for value. Russ Fordyce (15:17): Yeah, well I mean I I I think I that was my always my my kind of advice to employees was always make sure you're providing value every day. Sandeep Rachapudi (15:28): Exactly. Yeah. Like, yeah, implement such a complex thing and but then at the end of the day they're unable to articulate what has happened because of this implement is complex process or technology. Okay, I AA bot. Yes, which is good. this is becoming even more easier to generate and create AA bots or chatbots. But what is the outcome of it? because I think a lot of people are creating you know, AA based tools, but I think what stands out is the one that is giving better value. And I think I would I would always look at simple so I think simple solutions are the best solutions at times. They give the maximum ROI. That's my personal opinion. Doesn't mean that I'm judging only for simple solutions, but that tends to catch my attention. How simply this person was able to identify and bring value. Like the, like you know, unable to sell that product because always getting delayed. They found the pattern that is the delayed product that always gets rejected, that's the return. That's that's a key point. I in that's a bunch of data. How do you identify what is causing the problem? The pattern was good. And they probably they also implemented this AI chatboard, customers started interacting with it and they collected all the data, found the pattern and they're able to show some value. That is yeah. Good. Russ Fordyce (16:34): N now you work you work in these kind of complicated, very regulated environments, especially in fintech, and you get ex now you're getting exposed to kind of this more retail world of AI and innovation where we've got God, we've got law firms and car companies and chemical companies. And it's like it's across the board you see this kind of innovation across all these different sectors. Does that change how you show up for work at TCS and how does it make you a better practitioner? Sandeep Rachapudi (17:06): so the knowledge what I gain over here is you know something that I try to you know like use as innovation. right. So they are my points of innovation. I'm I'm learning from my from my industry. I self-learn a lot. I even I'm right now as I'm speaking, actually I'm registering myself into a an agent DKI, you know, like course, you know, to understand better and how to integrate all the tools together and you know, like a build more a agents on my own. So a part of this knowledge that I get. I'm actually trying to actually implement my my own AI agents based off you know what people are developing here and nominating themselves to big innovation awards. so it is it is adding value to myself also and these ideas, yes, when I when I give when I give you like a general weekly say AI gatherings that happen within the company, I do talk about various ideas that I get both from my experience as and as for as well as judging these awards to you know like a share different perspectives. So right now it is adding value in terms of you know adding creating more perspectives in a place where I work and also adding value to myself because I'm trying to build my own agents and actually, you know, like in in in the middle of learning courses, you know, where I can build L to end lifecycles with in implementing guardrails, including evals, and building end-to-end AI systems. Russ Fordyce (18:30): It's it's an interesting time because we went into this, as you as you mentioned, you know, when you talked about your your journey here, is we went through this process of digital transformation, which was hysterical. I I hated the term because it was so generic. It was it was it it it meant that dentists, you know, put their files, you know, online, you know, at the very kind of low end of it, which was very complex, by the way, with all the healthcare rules. Russ Fordyce (18:59): in the early days. and then and so that was like digital transformation. And then, you know, or it meant your phone system moved to an IP phone system. And that was a digital transformation. And I just hated the term because it what was it? It was really just companies kind of evolving into this new technology realm that kind of I think they had the third realm or whatever that online realm. It was, it was really an online transformation. It was a digital like we most of the stuff was already digital. Russ Fordyce (19:28): We had computers for, you know, forty years at that point. so so it's it's really interesting now to to see this transformation and being where you guys are, what what's kind of what's surprised you the most as as you kind of go into these projects to help these companies kind of move? You know, they've mostly everybody's in the cloud these days. I'm sure there are some Russ Fordyce (19:52): some some legacy projects out there. I know there's lots of COBOL systems out there that still need updating and a lot of companies working on that. But you know, you everybody gets the cloud and the value and we've, you know, we've figured that out when it's good on, you know, on-prem versus the cloud. And that's always debated these days, but but but you're now taking that company and going, let's transform your entire organization or pieces of it. What ha what's surprised you the most in the last 12 months? Sandeep Rachapudi (20:23): What surprised me in the last twelve months, yep, as you mentioned, digital transformation is one is generic, but where I was at least in my context it was about cloud migrations, which is kind of old now, everybody's onto cloud. I agree that. But that's a that's how it was sold in IT services, digital transformation. Right? But mostly this cloud transformation in Russ Fordyce (20:39): no, I I remember. It just didn't describe it. It was just so you know, we should go back and find out who coined that phrase and have them flogged somewhere. Sandeep Rachapudi (20:51): Right. So the cloud transformations are all done, you know, most of the cloud migrations are done. And now, yes, almost every project. I'm talking both from my work perspective and my general, because as I mentioned, I'm an independent researcher, so I do actually read a lot and contribute a lot into research forums. So I'll talk from both in in general perspective. What I've seen is now everybody wants to implement AI, but we know that agentic AI are kind of non-deterministic systems in the sense there is a little bit of probability in it, right? So People should know where they're trying to implement AI. It's not that everybody would want to do AI everywhere and then you know, like suddenly they'll realize the token cost is too high. And if you see there are a lot of memes, either in LinkedIn or you know, like on Facebook, anywhere, you know, like how people are, you know, losing all their money just to this you know, token cost because they ask some silly questions to and you know, solve some very basic problems using lots of tokens. I think what's changing over in the last 12 months is that people are realizing the cost associated. With using Agentic AI because tokens don't come free. People have this concept that I'm using Chat GPT, I'm using Cloud, and everything is free. So probably like everything comes probably in lower cost, if not free, when it goes to enterprises. But looking at the clo token cost is number one. Knowing that you know, like AI is Agentic AI is non-deterministic with a little bit of a probability in it, and hence we have to pick what we are supposed to do. In the example dress what that you just gave. In in a hospital environment, using AI actually to see what food is going inside is definitely okay. But probably asking A to probably do something in the room, like switch on, switch off, put the ventilator on, ventilator off, something like that, you know, when the nurse is not there is not. He's not, right? I mean, so so that's a very crude example. But then there are many ways, you know, like even if you take into fintech, the transaction processing, like the visa, the master card, you know, the transaction processing. And the settlements happening globally is a well-engined oil. It has been running perfectly for decades. If I am put as a person to take care of you know implement agenda, I would not go and touch the core, you know, like a transaction management system because they're really doing good. Where would I put it? I'll put it into fraud prevention, I would probably put it into pattern recognization, I'll put it into data analytics around it. So, because with with for fraud prevention is a pattern. Sandeep Rachapudi (23:16): And data lentics also looks for patterns. And with these patterns, we want to improve security of the system. And but but with transaction processing and all they're they're very deterministic. I am giving you $100 issue to you, $100 settlement is this, there's 2% commission, whatever it should happen. That's all those numbers are always there. And over there, I would not want to touch their system for AI or AND TK, but around it, you know, for fraud prevention and pattern recognization. You know, in or data analytics to actually improve the business. How do we actually make more sales? How do you do more transactions? How do we actually increase my commission or decrease my commission? Those kind of things. For or there, you know, AA would play a very good role. And even for what do you call that? refunds, maybe you can use AI over there too, you know, agent KI in if at all there is a pattern, the customer is always asking for you know refunds or returns because he thinks a fraud has happened on his transaction when he went abroad or to some vacation place and he gives all the details, he puts all the bills. And then you're then a agent DKI system can take an independent decision, an autonomous decision, based on the past patterns and information what this fellow is giving. Yes, I think I should be in a position to initiate a refund. So identifying where to put a Gent DKI is most important. It's not that we have put it everywhere. Russ Fordyce (24:27): Yeah, I I have I I was I I went through a a project where we basic we moved customer service to a to a consultant to an outsourcer. And in that process we learned so much about our own business because we didn't have anything documented. And I feel like we're kind of in that same realm with AI right now of Russ Fordyce (24:51): People know that the value's there and they see the value every day in their personal lives and everything else. And they struggle to kind of have that foundational kind of project to figure out what they need to even start, you know, really tackling, you know, how do I A run the business better and B, how do I accelerate my business to, you know, to beat all the other competitors that are doing the same thing? And so it's it is that twofold I think. Russ Fordyce (25:21): that twofold benefit of make my current operation better, faster, leaner, richer for my existing customer base too, right? If you can improve your product, go for it, right? It make and it's easier than ever to do that. and, you know, and then and then how can I better attack markets, go after stuff? It really is this, you know, it's it's so enabling. It must be really transformative for you guys to see that on the front end. Sandeep Rachapudi (25:48): Yes, yes, yes, definitely, definitely yours. I I I do see that in and out. Yeah. While I cannot take you know specific details about the products, but have seen, you know, even some of some products are so nice, you know. you know, very we're even automating the kitchen systems, you know, because most of the IT companies have got even kitchen systems. And you know, like some of the IT companies have got thousands of employees, and then you know, there are there are there are you know projects that actually generally talk about. How to maintain the kitchen inventory, like create a shopping list for the chef, you know, know what is the best selling food item. you know, all that, you know, nobody is gonna sit and watch and see who likes what and what is my best item. You know, like every day a lot of food items are coming, and then and then you know, like the chef is probably always thinking, What should I do next? And you know, like what should be my next, you know, like a recipe of the week, etc. Then he wants to look at what is the trend that has been going in recently and then agents can actually you know actually propose hey this should be an item based upon what the last trend is and the agents are also in a position to reduce waste they're able to create automated you know like a chef shopping list saying that you know you have to you know probably take less amount of oil this time because people are going onto healthier options and the consumption has been so and so based on this it'll give you proper reasoning also with some of the transactions and say that hey and then you know you could actually reduce the amount of things that you Spring, like this inventory tells me that you need less oil. You know, as simple as that. So it it is everywhere. it is everywhere. But yes, the the one question I think port people should ask is if my A agent fails, what is the impact of it? I think that first question should be answered. In the hospital example, if the A agent fails, you know, if the the patient is going to have some serious trouble, yes, that is not a place where you need to go. But in a kitchen system or in a customer system where Probably I'm impacting one customer. There'll be one bad one customer who will give a bad review because they've given a wrong return. Or probably I'm picking a wrong dish as my recipe of the week. Yeah, they're acceptable risks. It is okay. We can probably like definitely play around and you know be confident to imprint a systems, but not to transaction settlements and not to healthcare analytics and pattern patterns is fine. I mean, there is a lot of drug discovery happening in AI. That is fine because you're discovering it and you're trying to test it on. Sandeep Rachapudi (28:14): probably in the lab and only when it is approved then it'll go into the market. That is fine. But not in live healthcare systems. So that the judgment has to be there. Where can we have probability where we should not have probability. Russ Fordyce (28:28): That that human in the loop, you know, has to t i is that last risk mitigator. and I I, you know, I I I I f I'm finding that even with my own AIs, you know, it's a learning process. You kind of have to build on the process. If you want it to solve a pro a very complex problem, you know, break it into ten problems and solve them individually, because it's you run into so many little intricate details. Russ Fordyce (28:56): you know, just solving some of these, you know, connection issues or whatever. but it's it's it is you can really get some amazing work done now, which is really fun fun to see. For for someone that listens to this episode, what's the one thing you want them to walk away about judging and recognition and about Sandeep Rachapudi (29:16): Yeah. So I think for for for any person, you know, like in Iterate anywhere, when we do some work, what do you want as an outcome of it? one is yes, you will learn and you will gain knowledge. And at the same time, the best recognition is about, you know, getting noticed, you know, like getting recognized. It's always not about perks and you know, like a bonuses and all. Yes, they're always there, they're all numbers, but then they are they are kind of expected that happen naturally, but then What we should have is a way to get recognized. Recognition could come in a very smaller fashion, as I mentioned, it could be within the team, within the unit, you know, within the organization. But then actually going above and beyond and trying to see where somebody fits in the industry, you know, that those are the places where platforms like Big Innovation Awards would definitely help a lot because people want to get recognized. That gives you lots of self-satisfaction about the work that you're doing. Other parks like like salary numbers, yes, they're always there. but then what gives, you know, more satisfaction to anybody is being recognized. And I think you know, platforms like Big Innovation Awards with lot of transparency play a great role in it and I'm happy and thankful to be part of this ecosystem. Russ Fordyce (30:30): Well, and I think you hit the nail on the head, which is, you know, we are moving in such a fast way into this agent world that you know, you you almost don't know what's real these days, right? We don't know if the commercial was shot with AI, you know, or produced with AI, not even shot with AI. yeah, you know, you you see something blowing up on Twitter, you're you you're instantly skeptical. and I I think programs like this that are human. Russ Fordyce (30:58): and that are transparent really kinda you know, kinda counter that. It's like I think I you know, I I'm I'm hoping that, you know, it there's a even a harder sway more towards the more human things like, you know, recognition. Sandeep Rachapudi (31:11): Mm-hmm. Right, right. Definitely. Definitely rest. I know, I know. I remember, you know, in in every nomination that comes, you clearly write no AI based suggestions, no A base strategics. You know, I used to like that, you know, that reminder is every time. you know, like but but I but I love the fact that you try to make it no, it's not trying to make it. You are making it only human-centric and there shouldn't be any Russ Fordyce (31:15): And we don't need to recognize the AIs, they they're doing just fine. Sandeep Rachapudi (31:36): AI intervention in judging and all and constantly being reminded about it. It's always good. Reminders are always nice. Russ Fordyce (31:42): Well, you know, th third party perspectives are always good if you're building a product. And, you know, whether it be a customer or a vendor or somebody outside of your organization, somebody they're patting you back or patting you on the back or going, you know, you know, you could do something a little bit better. It's always helpful. It's it's it makes you feel good, it keeps you motivated. So Sandeep, thank you for taking the time to do all of this work for us and to and to, you know, be part of this community. I really appreciate it. Sandeep Rachapudi (32:05): Thank you. Thank you, Ross. Thanks for actually having me. I really love talking to you.