Navigating Global Customers: Sudi Navile on Customer Success and AI Innovation

Welcome to the Customer Success Pivot Your Career podcast. I'm Alex White. My co-host is David Locheats. Our podcast is focused on people looking to get into customer success profession or move up in customer success if you're already in the field. How are you doing, David? Alex, I'm doing great. Having a wonderful week after a nice long weekend up in Mariposa and Yosemite. So I'm really relaxed and looking forward to our conversation. Awesome. How are you doing? David, I'm doing great. The weather's starting to turn. I'm starting to plant my garden. Things are looking well. Uh, what's on your mind today? Well, now that you mention it, gardening would be, so that's another topic for another day and something I really enjoy as well. I've had a lot of conversations over the last month or so. With some colleagues and folks that I coach who are actually out there looking for jobs. They're running into some serious roadblocks or challenges in how to find jobs. What are the right jobs? How many people are applying? So I've got a lot of brainpower wrapped around that. So that's what's gone into a lot of my thinking. What about you? As you know, I'm looking for a job currently. The more and more I hear about AI and everything, Customer success is going the AI route if you like it or not. It's just such an ideal profession to be able to take all survey data or customer data and be able to analyze it quickly to have better insights and see patterns that you can't see normally. So what I've been doing is I've been leaning heavily into AI. I've taken classes. I got a certification, AI for Customer Success. I'm using Gemini and Claude and ChatGPT. I'm developing these projects to actually go out and take all my background. I give it my resume. I give it the background of what I'm looking for, the types of jobs I'm feeding in, past jobs I've applied to that I liked to give it a kind of a sense of what I like to do. And I save that. And now I've actually taught it to give me the next 5 jobs and it'll go out and it knows only jobs posted in the last 7 days. It knows which ones. I've already told it to eliminate, ones I've applied to, and it makes it real efficient for me. So not only am I making my process of finding a role efficient, I'm actually learning AI and I have a story to tell when I get interviewed because I can't imagine customer success interviews aren't going to turn to AI heavily focused. And since I'm not working currently, I'm doing the best I can to do that and make it efficient on all kinds of levels. I'm having a blast. It's actually every day I wake up and say, what What can I do with AI today? Which is a lot of fun. What a cool way to think of how do I have my own personal tiger team that's focused on nothing but me? And I think it's great. I think more folks, as they get more comfortable with it, as they find out how to leverage multiple types of tools, how to control it and how to help with messaging or how to direct the agents, more and more folks are going to begin doing what you're doing or continue doing what you're doing. And I hope it would begin to streamline and become a little bit more efficient for the recruiters and more effective for candidates and companies. So way cool. I'm really impressed. One day you'll have to kind of set up a session for us on the side to show me what you're doing. Anyhow. Yeah, I'm actually sitting down with my wife because she wants to use it for some stuff in a business that she's going to be starting and trying to get my kids who are much younger, just starting out and trying to reinforce just how important AI is going to be going forward and to embrace it. So that's my wisdom I want to pass on to all the people listening, like just grab onto— I've learned stuff, like I got really frustrated. I'm using Claude Cowork to actually do a bunch of things for me and set up my day for me and look at my tasks that I completed and all this stuff. And it kept messing it up., and now I have the experience of figuring out what did I do wrong? And these instructions are very standard, so it knows to repeat it. Like it started dropping things. I'm like, why do you keep dropping this stuff? So it's one of those things that's just get in there and start learning, do something that you're not going to hurt anything and just start to iterate and learn the tools better. That's a great experience. We'll call you Professor. Yeah. All right. So we ready to jump into it? Let's do it. All right. Our guest today is Sudi Naveiling, Chief Customer Officer with Syd Global Solutions. He has led global business and technology teams from startup to Fortune 500 in high-growth and mature markets by being at the forefront of the digital transformation. Sudi is the executive owner for customer outcomes, revenue growth, retention, and expansion across the enterprise and AI-enabled platform customers. Welcome to the podcast, Sudhi. Thank you, David. Glad to be here and looking forward to this conversation. To get us started, Sudhi, why don't you expand on your career and how customer success is at the forefront of your role? Yeah, so I think I want to go back to my first job. I think it's important, not because of this role, the customer success is at the forefront. I was very fortunate to join a company in India that was a multinational company that was selling mining equipment, and I was in sales. And one thing I found out really early on, I was very fortunate, is there are two tenets that really made it for customers to want to do business with you again and again. One is to solve their problem, 2, by virtue of solving their problem, create value for them. You could solve their problem, but if you did not create value, they would not come back to you. So you got to do both. And pretty quickly you learn fast that those are the two things that stayed with me throughout in, in whether I've done commercial insurance, inside technology, consulting work, that particular tenet, the two pieces has stayed with me. And that is the thing that I believe has been a driver for me to work alongside the customer successfully. I've had the fortune of working with 7 different verticals after coming to US. I've done enterprise technology from inside application development, infrastructure, global infrastructure, digital online marketing technology, and then consulting. So it's spanned quite a few things, and then that has also helped me understand from a customer perspective and cross-pollinate things to stitch together solutions that would help create value for them. Sudi, it's great to have you on the show, so welcome. We had talked about the Growth Department book by Alex Raymond, and one of the things that he talks about is solving for the bigger problems. And Syd Global being a worldwide consulting organization, very pertinent to this. Raymond talks about your customer brings you surface requests. Your job is to find the bigger issue underneath. Larger problems mean larger budgets and longer partnerships. And I think that's very, very telling and very true. But can you expand on how you approach these conversations with your clients? And this is actually, this paradigm is something that you face on a daily basis. Most people will come to you with a solution You got to take a step back and say, why do you need that? A lot of times people are just implementing. You can't be somebody that takes a request from the customer and just implements it. The idea is to stop and say, okay, what are you trying to solve? So it usually— it's funny because when I was in IT, I remember people would come and tell me, Forget external customers. Internal customers come and tell me, "I need this done." We're like, "Wait, what are you trying to do?" Then you go 2 steps down and you realize they don't need a space shuttle. They just need a car to go for 10 miles, but they're asking for the space shuttle. This is a very common pattern, but I think the idea for people is to stop, ask questions. Be curious. And this is harder in today's world because somebody comes in and says, I need it done by tomorrow. And I use a sharpen the axe analogy. So you can basically spend 10 minutes and solve the problem, or, and then do the rework later, or you spend the 10 minutes to understand the problem and do it right the first time. When you do that, it could start out with a small opportunity, but it can grow bigger because now the customer understands and you've built that trust and willingness to understand their perspective from their vantage point. So that's been the core in terms of the approach, and that stays consistent independent of the size and the type of customer that you work with. Yeah. And I think it's probably people getting confused on when they say the customer's always right. It's not that the customer's wrong, but they don't really understand what they're trying to solve a lot of times. They've made a bunch of assumptions and a bunch of things, and I want this. But even myself, I've done this. I've gone to companies that I bring in and I'm like, "Oh, we're going to do these things in order," and they don't challenge me. I'm like, I take a step back. I'm like, maybe I didn't do that. They're the experts in this. I told them what to do, and they just started doing it. And that customer is always right is another thing that kind of is important to add a nuance to that. Yes, the customer is always right in terms of where they want to go, but they may not always be right about how they want to get there. I think if we can understand that nuance, I think it's helpful to keep their perspective and say, you're right, we'll get you there. But to understand that you need to get there is the challenge that most people face today. When these challenges come up and you're brought in and they bring you, hey, here's what we're thinking, what we want to do here, let's move forward and let's do this, and you pump the brakes, you hit pause, how do you approach, getting them on the right rails to ascertain or figure out what the true feature or the true value they're targeting for? And is it different internationally with companies that may have a basis outside of the US versus here in the US? I think the first— let's talk about what is common. What is common is the human psychology is the same. Everybody wants to be successful. And that's why they're doing it. But culturally, there could be nuances that you may need to think about. So that's what probably is different. How you ask questions to listen, how do you engage with them to have an opposing point of view. In some cultures, you can be very direct. In some cultures, you have to figure out a way to get them to that point. By working with them in certain types of conversations. So those are some small examples, but you can understand that two things. One is it's not just what you're trying to communicate, it's also how you listen. It's important that, you know, when you're listening to somebody in the US, I am trained to react emotionally a certain way. I could be as rational as I want to be as an individual, but in the micro reactions, I am reacting emotionally. How you do that when you go to Japan versus when you go to Germany is going to be very different. You have to train yourself prior to the meeting. I always tell people that if you have a 2-hour meeting, it's probably good to have a 2-hour prep. To make that 2-hour meeting effective. And that includes anticipating some of these things from a cultural nuance perspective as well. I would actually argue in the US, working in the Northeast versus me out here in California— I grew up on the East Coast and working out here in California— there's cultural differences there as well. So it's definitely— absolutely. Yeah, so agree with you on that. In fact, yeah. Yeah. I think it's interesting when you talk about these differences for our audience, this is about getting into customer success or moving up. Well, some of the questions you'll get is around, how have you worked with international teams or something like that? And people have to be careful not to be too specific on it because I think the answer they're looking for— not being a recruiter, but this is what I think they're looking for— is really Talking about the differences in cultures and maybe have an example or two to show that you've been there or have done that before and that you're at least conscious of the differences in it. I remember when I was in New York, I mean, this was an insurance company and they had just outsourced and we had a team, an international team that had just landed and they were going to continue to work from here. But here is the thing. Culturally, they would basically have a nice engaging conversation with the customer, and then suddenly something comes up and is fairly complex. And then I see silence, and then the teams go off in the room talking in their own language. Now, it may seem rude, But if you are facilitating something like that, in the larger scheme of things, sometimes that may be necessary to solve a problem because their ability to synthesize that information quickly solve that. It's not that they're trying to exclude the person. It's your tendency to solve the problem in your native tongue may be you do it faster, and then you're coming back and saying, okay, this is how we do it. Now, you could look at that and say, how rude of them to do that. Or you could say, maybe it's actually helping synthesize a complex situation and come back and solve a problem. So I feel that one of the things that I, I've seen is people are quick to judge, in my view. But at the end of the day, I think everybody has to think about, are we solving the problem? And is— over time, if we continue to work and we are well-versed in that, and that complexity gets into the engagement, in the level of engagement and the communication, maybe those teams will get better. But initially, when you brought those two teams together, you will see those differences. And it's OK. It's not end of the world. So I think having tolerance to those nuances is extremely important. That's one example. We could also think about other things, but in my view, taking that extra effort to understand and tolerate what they're doing and understand while you're in the meeting and learn along the way in terms of that culture. You can read as much as you want to, But when you experience this, it'll be different. I think when you talk about some of the challenges in working across international borders, cultural differences is absolutely at the forefront of it. And I think your article that you wrote on Threads and Perspectives, your mother tongue, the new programming language, I thought was dead on where you talked about fluency versus literacy and stepping back and understanding what they're trying to accomplish and how it is about the learning and access to this— what did you call it? Access to intelligence, I think it was. Yeah. So this was written in the context of AI. And what I was originally trying to showcase was that if you think about it, things like when BASIC, the language BASIC, was introduced, Because people realize that not everybody is going to be doing things in the assembler, right? So you needed some kind of a skill set. What AI is bringing to the forefront is when we're solving technology problems today, we have to talk that technical language. There needs to be that depth. Oh, you're trying to solve this platform issue. You're trying to solve this infrastructure issue. You're trying to solve this application performance issue. I think what AI has done is brought everybody to a level playing field where they could use their native tongue to communicate. Now, one thing that I believe is this— If you're working as a team and if AI agent is in the middle of it, I don't have to worry about too much of a nuance because AI can help with that nuance. So it's making it easier for people with differences in the native tongue or the cultural way of expressing to come together without any challenges. So I see, to me, this is an enabler from an AI perspective. While that was a challenge without the AI where people would have to put in the extra effort, now AI has made it easy for you to say, so you don't even have to say that. You can configure your agent to say, while you're listening, make sure you listen to the emotions and then articulate that in that sense for me. So those kinds of things would become easier And it's in that context that there's one problem, but there's another solution that's coming together from an AI perspective. So that's interesting. So in AI and where we are today, how advanced is it to understand all the different languages and nuances and all those type of things? I know you can train it, and if you're writing an article, here's a bunch of things I've written before, do that. But As far as speaking in your native language, and I don't know how many languages are, probably thousands, how advanced are they in being able to cover all those different languages and being able to make it appropriate for that, what's in that culture? So I think, so there's two parts to this. From an adoption perspective, it may not have solved all of the problems, right? But from a capability perspective, there are companies If you've heard of ElevenLabs, they do extremely well. So we talk about Google Translate, you talk about ElevenLabs. Now there is a company that I'm aware of who actually is providing voice solutions for outbound calls. One of the things they solved was to figure out how to get rid of the background noise really well. And the reason is, and this is a company in India, so when they call, people are out on the busy streets. And when you're asking for help for something, or they call in and they're asking for help, you need to get rid of a lot of background noise. Your ability to solve that, because the algorithms are capable of learning and doing that. So there are different pockets of innovation that are happening. How much of that has been applied to a scale that becomes your second nature, right, from an implementation perspective, it's available. That is the one that I think is lagging. But from a capability perspective, I think it's way ahead of what people really know of today in general context. Sudhi, I find that AI, those competencies as they're growing, as you mentioned, are just absolutely amazing to me. And it's coming faster and faster. And you talk about reducing the noise. That sort of brings me to the next challenge or opportunity that I think of, or what I've read about as challenges working internationally, and that's purely around logistics and operational hurdles. I wanted to put that on the table and see what some of the conflicts or challenges you've had in those kinds of areas. So multiple things. First of all, I think time zone is the number one thing. And even though people say it's 24/7, When you have teams, it gets harder to collaborate with overlapping time zones. And when we do that, it's typically people are doing it from their homes, sometimes they're out. So there's a lot of that, and it seems like it's happening in a chaotic sense. So I think getting that part of the equation resolved is important. Typically, if you have a good program structure, then you could have different cadences organized and make sure different types of meeting have certain corement, and you could drive some of those, I would say, standards from how you execute. And then you have to learn that depending on which, if you go to Singapore and you have, you're trying to figure out a way to collaborate with some entity in Singapore. Or east of Singapore, if you go to other parts like Vietnam, Manila, and you want to collaborate with them, they're 10, 12, 13 hours out from where we are. Could be more depending on which part of the coast you are in the US. So I think it's important to have that perspective and figure out. I still see people struggling with collaborating in that sense. One of the things that I learned from Apigee, one of the companies, was that asynchronous collaboration actually helped. But asynchronous collaboration with AI is superpower because asynchronous collaboration without AI could be based on a perception that you create based on your own understanding. Now, when you have AI to augment, so that'll help you. That's one aspect of it. The second part of the equation is you need a team. Are you going to hire locally? How quickly can you hire? Do you understand what it takes to hire them? Do you understand some of the internal workings of that locality or even within— let's take Europe. You can't just say Europe is all one. If you go to Italy, The way you're going to hire a resource would be different than how you do it in Romania versus how you do it in Poland versus Germany. Same thing in India. So same kind of differences exist. Then from a customer perspective, you have to understand what's their motivation. If I talk to a bank in India, a lot of the times they're coming at it from two perspectives. There's a national infrastructure that's being built for digital., and there is compliance from the central bank. They're worried about those two things because they want to make sure that you understand that context. They may not say that, but it's implied. So that's the other thing that you have to put aside time to prepare. The reason I'm putting it on the logistics is a lot of the preparation work to me is also important part of the logistics, right? And that's basically what I'm driving at. I really appreciate and like the comment about async and async with AI as being more powerful. The one thing I wanted to add to what you're talking about is what I've observed over the last 5, 6 years since we had the lockdown is individuals are becoming a little bit more aware and/or compassionate as to adaptation. We're becoming more comfortable with people from working at home and having the proverbial conference call in our pajamas with kids crying and dogs barking in the background. It's become more of the norm and just purely accepted as part of doing business. And I think as we continue to grow, being able to adapt and use AI in an asynchronous manner, I think becomes easier for us. And as individuals across the planet adapt more. They're going to find it easier and easier to communicate. I think time zones are always going to be a challenge, but we kind of shrink that down a little bit. That's what I observed. I agree with that assessment. I think people have, I think, seen or experienced some of these background scenarios. In the past, you'd be like, hey, there's too much noise. It would bother you. But as you see more of these humans in that situation. I think you're building that muscle for tolerance. Agree with you. I think that has definitely helped people see the real human and the real scenario from the human perspective. I've also noticed one more thing on this topic, and then I know, Alex, you got something, but I've noticed more and more companies are demanding folks come into an office again. Okay. And I think There's some reasons for that, but I think it also inhibits individuals' ability to be flexible. So if I'm working with a team in the Philippines, there's a large gap. If I need to meet with them at the beginning of their day, I may end up getting online late at night, but I'm able to flex. And then after I wake up, get on a call and see how they did in their day, it becomes a little bit more flexible. I can adapt to work in these kind of scenarios. If I'm having to commute or be in an office, standard 8 to 5 kind of thing, that kind of takes away from the 6:00 AM to 8:00 AM call and the 6:00 PM to 8:00 PM call. Now, there's a quality of life we want people to have, but I think we have to continue to evolve the way we think, the way we structure our working schedule to accommodate this. And with that said, it comes with a heavy dose of accountability. On the individuals that are going to be doing that. Yeah, so it's actually interesting because I remember having a conversation in this regard, and the point that we were having is you would have both these formats that are gonna continue to grow. So a company like WordPress, it basically has everybody remote, but if you look at the structure of that, everybody is what I call as a high IC. A high individual contributor. When your company is made up of a lot of high ICs, then remote work is actually very effective. However, when you look at a consulting company or even some of the large enterprises, they're more pyramids. So what happened, and this was firsthand experience for me, is the bottom of the pyramid suffered a lot. The amount of learning— so I could see the people who joined during the COVID timeframe, 2 years later, their performance when I compared to a benchmark for somebody else that joined and was in the office that was being mentored and they worked together was different. Now, can we figure out how to navigate that and work? Yes. But I don't think that is really understood that globally to solve that problem. The back to office can be done where it's a rigid rule versus the back to office, the keyword that you talked about, David, was flexibility. So if there are ways to, and it's possible to do that, we did that before. It's not like somehow from the copasco, we kind of pivoted into this thing and there is this notion that back-to-office culture is all about being rigid. And my view is that, you know what, yes, some things are good from an office perspective, some things can be done remote. Sometimes you need that flexibility. Sometimes the employees need the flexibility. Sometimes the employers need the flexibility for people to come in. So I think we're still learning as a group to figure out that balance, in my view. Yeah, and I've seen companies, either departments or the whole company, pick the days of the week so there's consistency, so you don't always miss each other. Make sure that the teams are coordinating and doing the things where in-person makes sense. One of the things I think has always been complicated, especially with the laws that came down with Europe, is around data protection when you start to get into international teams. And if you have teams spread over 3 or 4 different countries with different things, and especially with the cloud, So now you have the cloud infrastructure, where does that data reside and everything? What are your thoughts on that data protection and how you handle that with customers when you have international teams? So two parts. From a customer perspective, it's extremely important to make sure that you start to build some level of knowledge from a requirement of data privacy. For a specific location. It's important to understand that. A lot of the times, people fully don't understand. I think it's a culture where you have to manage to risk. You don't want to stop the business, in my view, because there is no value from that perspective in going so much overboard. At the same time, how do you de-risk that? That conversation is what typically helps early in the cycle. I think when it— I'll come to the team's part of the view. I think to me, from a customer perspective, you have to bring it right from the design stage, right from the requirements and the design stage to think about it in terms of what are the constraints that you're going to operate under. You don't want to put constraints that become friction, but the constraints have to be just the guardrails without friction. So that's difficult to do, but it's also sometimes you have to bring the experts. So a lot of the times people penny pinch on this is they pay at a later point instead, figure out a way to bring that person in early. So that you have the foundations understood prior to you getting value to the customer or solutions to the customer. So I, I see people typically trying to catch up and they think, hey, we can do it all. That sometimes you gotta bring the right experts in. That's from a customer perspective. So I look at it that way. From a team perspective, it depends on the enterprise. It's gotten easier today to have a small company that has people in 6 different countries. Let's say you're a 10-people company and they're in 6 different countries. There are platforms that help you do that. But I would say 5 years ago, if you wanted to do something like that, you're doing it at a lot of risk. But I also believe this. So one of my pet peeves is that You're going to land into problems when you have a lot of success with these situations of data privacy. When you're small, when you're not that successful, you're under the radar. I'm not saying don't prioritize that, but typically you're flying under the radar. So you have time to figure out how to do that, right? You have to be practical as an entrepreneur doing it. But as a larger business, if you're doing it as an enterprise, then it's a very different mindset, right? So how— then you need to start to have very specific solutions depending on the team size and where they are and make sure those processes are part of your operating procedure so that you execute it the right way. Think about the problems that people are going to face. If somebody is going to build an agent for a company that is small today and they don't have these ground rules done, what do you think is going to happen? The agent's going to do the same crappy thing that you're trying to automate. This is like the old adage where automation of bad things will only give you bad outcomes faster. Same thing is going to happen with the agent. There's no different in my view, except the velocity here is unbelievably You know, uh, vague. Okay. So Sudi, along the line of some of the challenges, what we've seen and what, as I mentioned earlier, what I've read, there's challenges all over the place as to consistency in the value proposition, how organizations see pricing, how they see what deliverables are. Wanted to get your spin on that. And there's now this new push for outcome-based pricing too. Yeah. So before we get to the outcome-based pricing, the value proposition is very much, I would say, not just from a customer perspective, it also has to resonate from an ecosystem perspective. So if you are doing something like an Uber and you go to India, if you look at the local cities, they have different modes of transport. So you have taxis, you have the competition for them, and you have these three-wheelers, what they call as the autos. They have their own stuff. So how are you going to provide— like, if I'm doing like 2 kilometers, which is very crowded, auto is the best way for me to do that. So what kind of messaging are you kind of providing in that context. That to me, the use case itself is very different in this scenario. So understanding that as you go down this path, it's not going to be a cookie cutter for every city, depending on the location, it could be different. And same is true of many products. When you sell, let's say you're a B2B and you do some kind of a last mile service. Your last mile service in US is very different from a last mile service in Asia. Amazon's taken most of the stuff. They're doing Dropboxes. They're doing some of these other solutions. But how they go about doing that locally in some of these Asian countries are very different. So just from that contrast alone, even from a health perspective, let's talk about the drugs. You can't advertise drugs other than a few countries in the world. So knowing that kind of difference is equally important. What can you do? What can you not do from a positioning perspective is also equally important in terms of regulatory aspect. It gives you two different, like, spectrums, but there's a lot in the middle in terms of there are what the feasibilities are, but gives you an idea of making sure you understand the regulations, making sure you understand the ecosystem and the impact, making sure What type of value and how is it different in that particular ecosystem? And the context is how you want to think about the messaging. And that actually blends into the pricing as well, because the positioning and the value that you're talking about is how— or it's going to help you determine the pricing in, in terms of about your product and how you're going to sell. Yeah, I have a funny story about that last mile on Amazon. So, across the street, I saw this Amazon truck pull up, and I saw a car pull up, and they started putting boxes and packages in the car. I'm like, "Oh, my God, they're like stealing all these packages out of this Amazon car." And I realized they hire independent people to go then take those packages in our town and distribute them out as independent workers outside. I guess they're like kind of gig workers outside of Amazon. Yeah. I thought it was pretty interesting when I saw that. I'm like, okay, it's nothing I have to report to the police. So going to the pricing conversation, so maybe wrapping that ball up in like a conversation to just close out the episode and give another sense of how AI is changing the world. That'd be great. Yeah. So I think if you think at the core, the two things that are important from a pricing perspective are trust and value. But that perception of that value that you're gonna provide is gonna continue to change with AI coming into the picture. What would take a content writer 2 days to give me a content today? And if they tell me, hey, it's gonna cost you 16 hours of consulting to do this, I can know that, hey, that's not the value you're providing cuz I can do that in 2 hours. So I think that's changing. And that's gonna have an impact on a lot of these working white-collar work that people are doing, whether it is the legal, the accounting, some of the business services, all these things will have a significant impact. And in this context, if you are a small business and you wanna start to consume, or a medium-sized business, unless people start to think about it differently, that, hey, if instead of you paying me for 10 hours being a delivery driver, I can figure out some creative ways to deliver that. I'll pay you per piece. I'm using that physical world as an example, but I think in the AI world, that is, there is a lot more of that possible scenarios in terms of how to solve that problem. So if you call a customer service today, I still think there's a spectrum of solutions when it comes to voice. There is voice solutions where you get frustrated and you basically want a human and you figure out a way to do that. And somebody was very ingenious in doing this for some company where they basically ordered 18,000 cups and then the human had to come in because it did not allow for that number. So the point is that, okay, so if I bring an AI agent to an ordering solution, how successfully did you complete n number of orders? And you get paid for that, not for the platform. So if you had 100 orders and 90 of them were successful and they had no complaints and they had a high rating, then you get paid for that. For the 10, that, you know, had some challenges, you don't get paid. Now, hey, that happened in less than 2 hours, but you can figure out some model saying that, hey, you know what? You either do a revenue share or you do a base plus some kind of a comp for every successful order. So it's going to come. And I think one of the companies that I've been following, Sierra.ai, has done this really well in terms of outcome-based pricing. And they really go down that path. But if you take the larger companies, they have a different problem. They have to buy. If they're buying LLMs and they're buying like, okay, I need to buy these two models and that costs me a million dollars a year for the tokens. But the problem with that is the token rates are going down significantly over time. So are you going to sign a contract for a million dollars? Because in 3 months, the rate of that would be much different. So maybe there is an opportunity for somebody to do a token cost index and use a peg and then say, basically, have that rate and say, hey, my price will be slightly above that rate. So if the token cost of per million tokens goes down in 3 months, the index goes down, and you get charged only so much. So I think the number of tokens people are going to use is going to exponentially increase as well, based on the use cases. So it is inevitable that there has to be some innovation in that pricing model on the input side. Outcome part is the easier one because you can basically have, based on a revenue or based on a margin that you're going to influence, let me get something, a cut of it. So it's easier conversation, but the input for the larger enterprise is something that needs to evolve as we go through this. But at the end of the day, do they trust you? And are you providing value? Those two things are going to drive what they're willing to pay. And you have to come up with these creative mechanisms to keep that trust high in the world of AI. Well, this was a great conversation, Sudhi. We appreciate you coming on and sharing your experience and knowledge with us. We always have one question that we ask our guests. I guess, at the end, which I think I'm going to try to modify it slightly here because our question is about a lot of people go out to LinkedIn to either look for jobs, they put their profile information, post things. Do you have any pet peeves about LinkedIn as far as what people do on that, either on their profile or writing or not on that? Do you— are you starting to use Substack? Is now the big thing, and I see a lot of people are starting to abandon posting on LinkedIn. Do you have an opinion around on that and also any recommendations for people looking for a job? Yeah. One of my pet peeves is how real is the content on LinkedIn, right? Which is fine. I mean, you basically— and the LinkedIn algorithm actually skews a lot of it. So I don't really have a very specific view there, but I do see people have to be genuine in my view on LinkedIn if they want to be. Now, I, I like the fact that obviously the Medium, the Substack, and Reddit is such a big thing for certain group of people. So they don't even come to LinkedIn, they're on Reddit. So what is it that you're trying to achieve? And I think if you really did some demographic assessment, depending on what group you belong to, you may do certain things on LinkedIn. You may do certain things on Substack, right? Some people do multiple. They do both LinkedIn and Substack because they know they have audiences on both. But I think at the end of the day, I believe you have to know your audience. Do you have your audience on LinkedIn? There's nothing wrong in staying within the LinkedIn bounds. If you wanna reach people who may not be on LinkedIn, And they're the people who typically do the Reddits or the Substacks of the world. Then you have to figure out how to do your stuff out there. So I think that's my view. The details of how you get some of the things done is kind of very similar if you want to get people engaged. And in today's world, one other thing that I don't like, which I wrote about And I think you've seen this headline, the 95% of the projects fail from MIT. And my first follow-up question for most people who commented on that was, did you actually read that report? And when you read that report, there are nuggets of data inside of that's very different in what you take out of it. So that's the struggle more than people producing the content. People consuming the content is where I feel need to go in. And in fact, I wrote a, you know, this TL— you see the TL;DR culture. So I actually put a thing called Read the Whole Damn Thing article, and especially with AI, it helps you do it faster as well. So those are some of the things on the producer and the consumer side that I— on platform— that I feel about LinkedIn or any of the other platforms. Hopefully that helps. Oh, it does. It helps put some stuff into context and And it's thought-provoking because there's value in Substack, there's value in Reddit, and there's value in LinkedIn. But it's really like you said, know your audience. And right now, too many people are living in the small snippet world as opposed to really diving in deep into an article. And it gets taken out of context. Well, Sudi, we really appreciate your time. It was a great conversation we had with you. Thank you very much., and we look forward to staying in touch. In doing this, how can our listeners get in touch with you or contact you? What's the best approach? So LinkedIn is the best place for people to get hold of me. And through LinkedIn, they have access to my newsletter on the top. So that is on Medium under the brand FourthCircle.ai. That's basically what I'm going to use to publish. Trying to get a book out as well at some point. You don't have to put that out there, but just I'm telling you. So I think they can reach me on that. And they can also, you know, I do have Twitter, but I'm not very active on Twitter, but LinkedIn is the best place. Medium is the other one that I think would help. So if you want to stay close to what I do. Yeah. And when they find you on LinkedIn, they'll find you on Medium as well, correct? Yes, that's right. Yeah. Well, thank you. We appreciate your time. Thank you. Thank you. Thanks, Sudhi. Bye. Well, David, that was a great conversation with Sudie. What stood out to you? Yeah, Alex, I thought the discussion was great. Every time I meet and talk to Sudie, it's always a fun conversation, well thought through. The one thing that just popped for me or jumped out was the conversation we had about cultural differences with the international market. And I really enjoyed the conversation about how AI is beginning to help bridge the gap in understanding culture and languages. We've always, not always, but at least for the last couple decades, every time we've had these large projects that are international, you and I have worked on, we've always worked at understanding the logistics, the timelines or the time zones everybody's living in. We've talked about how to honor that. We respect it. And I think Overall, culturally, we've really, really worked on bridging the gap of culture, but there's always still been, there still is that issue around language and certain cultural things. And listening to Sudi talk about how AI is now being used and can be or should be used in the future, I thought was very thought-provoking and quite interesting. So It's something I'm going to take away and think about a little bit more. Very much like how you're using AI in the job search. Now I have another thing to think about. How am I going to apply AI or how can I leverage AI? Because everything we're doing now is international. So quite interesting. Yeah, I think having an episode focused on international, we hit a lot of different checkmarks. Talked about consulting in general and trying to find the larger problem versus just the task at hand. We got into the AI, like you mentioned, and even the challenges of data protection, other things that consulting companies have to work with when they get international. So if you have international customers, even international companies internally where you have to work across teams, hopefully people got a little bit of a nugget here and there to help them be successful and think about how that impacts it. So all good. Well, that does it for this episode of the CS Pivot Your Career podcast. We thank Sudi for his time. We encourage people to subscribe and rate our podcast along with leaving comments wherever you get your podcasts or on our LinkedIn post for this episode. Until next time, we hope everyone has a great day and we'll talk to you next month.